Spatial Distribution of the Population at Risk of Cholangiocarcinoma in Chum Phaung District, Nakhon Ratchasima Province of Thailand.

PubMed

Kaewpitoon, Soraya J; Rujirakul, Ratana; Loyd, Ryan A; Matrakool, Likit; Sangkudloa, Amnat; Kaewthani, Sarochinee; Khemplila, Kritsakorn; Eaksanti, Thawatchai; Phatisena, Tanida; Kujapun, Jirawoot; Norkaew, Jun; Joosiri, Apinya; Kaewpitoon, Natthawut

2016-01-01

Cholangiocarcinoma (CCA) is a serious health problem in Thailand, particularly in northeastern and northern regions, but epidemiological studies are scarce and the spatial distribution of CCA remains to be determined. A database for the population at risk is required for monitoring, surveillance and organization of home health care. This study aim was to geo-visually display the distribution of CCA in northeast Thailand, using a geographic information system and Google Earth. A cross-sectional survey was carried out in 9 sub-districts and 133 villages in Chum Phuang district, Nakhon Ratchasima province during June and October 2015. Data on demography, and the population at risk for CCA were combined with the points of villages, sub-district boundaries, district boundaries, and points of hospitals in districts, then fed into a geographical information system. After the conversion, all of the data were imported into Google Earth for geo-visualization. A total of 11,960 from 83,096 population were included in this study. Females and male were 52.5%, and 47.8%, the age group 41-50 years old 33.3%. Individual risk for CCA was identifed and classified by using the Korat CCA verbal screening test as low (92.8%), followed by high risk (6.74%), and no (0.49%), respectively. Gender (X2-test=1143.63, p-value= 0.001), age group (X2-test==211.36, p-value=0.0001), and sub-district (X2-test=1471.858, p-value=0.0001) were significantly associated with CCA risk. Spatial distribution of the population at risk for CCA in Chum Phuang district was viewed with Google Earth. Geo-visual display followed Layer 1: District, Layer 2: Sub-district, Layer 3: Number of low risk in village, Layer 4: Number of high risk in village, and Layer 5: Hospital in Chum Phuang District and their related catchment areas. We present the first risk geo-visual display of CCA in this rural community, which is important for spatial targeting of control efforts. Risk appears to be strongly associated with gender, age group, and sub-district. Therefor, spatial distribution is suitable for the use in the further monitoring, surveillance, and home health care for CCA.

A Predictive Risk Model for A(H7N9) Human Infections Based on Spatial-Temporal Autocorrelation and Risk Factors: China, 2013–2014

PubMed Central

Dong, Wen; Yang, Kun; Xu, Quan-Li; Yang, Yu-Lian

2015-01-01

This study investigated the spatial distribution, spatial autocorrelation, temporal cluster, spatial-temporal autocorrelation and probable risk factors of H7N9 outbreaks in humans from March 2013 to December 2014 in China. The results showed that the epidemic spread with significant spatial-temporal autocorrelation. In order to describe the spatial-temporal autocorrelation of H7N9, an improved model was developed by introducing a spatial-temporal factor in this paper. Logistic regression analyses were utilized to investigate the risk factors associated with their distribution, and nine risk factors were significantly associated with the occurrence of A(H7N9) human infections: the spatial-temporal factor φ (OR = 2546669.382, p < 0.001), migration route (OR = 0.993, p < 0.01), river (OR = 0.861, p < 0.001), lake(OR = 0.992, p < 0.001), road (OR = 0.906, p < 0.001), railway (OR = 0.980, p < 0.001), temperature (OR = 1.170, p < 0.01), precipitation (OR = 0.615, p < 0.001) and relative humidity (OR = 1.337, p < 0.001). The improved model obtained a better prediction performance and a higher fitting accuracy than the traditional model: in the improved model 90.1% (91/101) of the cases during February 2014 occurred in the high risk areas (the predictive risk > 0.70) of the predictive risk map, whereas 44.6% (45/101) of which overlaid on the high risk areas (the predictive risk > 0.70) for the traditional model, and the fitting accuracy of the improved model was 91.6% which was superior to the traditional model (86.1%). The predictive risk map generated based on the improved model revealed that the east and southeast of China were the high risk areas of A(H7N9) human infections in February 2014. These results provided baseline data for the control and prevention of future human infections. PMID:26633446

Spatial distribution of Echinococcus multilocularis, Svalbard, Norway.

PubMed

Fuglei, Eva; Stien, Audun; Yoccoz, Nigel G; Ims, Rolf A; Eide, Nina E; Prestrud, Pål; Deplazes, Peter; Oksanen, Antti

2008-01-01

In Svalbard, Norway, the only intermediate host for Echinococcus multilocularis, the sibling vole, has restricted spatial distribution. A survey of feces from the main host, the arctic fox, showed that only the area occupied by the intermediate host is associated with increased risk for human infection.

Using spatial information about recurrence risk for robust optimization of dose-painting prescription functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bender, Edward T.

Purpose: To develop a robust method for deriving dose-painting prescription functions using spatial information about the risk for disease recurrence. Methods: Spatial distributions of radiobiological model parameters are derived from distributions of recurrence risk after uniform irradiation. These model parameters are then used to derive optimal dose-painting prescription functions given a constant mean biologically effective dose. Results: An estimate for the optimal dose distribution can be derived based on spatial information about recurrence risk. Dose painting based on imaging markers that are moderately or poorly correlated with recurrence risk are predicted to potentially result in inferior disease control when comparedmore » the same mean biologically effective dose delivered uniformly. A robust optimization approach may partially mitigate this issue. Conclusions: The methods described here can be used to derive an estimate for a robust, patient-specific prescription function for use in dose painting. Two approximate scaling relationships were observed: First, the optimal choice for the maximum dose differential when using either a linear or two-compartment prescription function is proportional to R, where R is the Pearson correlation coefficient between a given imaging marker and recurrence risk after uniform irradiation. Second, the predicted maximum possible gain in tumor control probability for any robust optimization technique is nearly proportional to the square of R.« less

Pollution Characteristics and Health Risk Assessment of Airborne Heavy Metals Collected from Beijing Bus Stations

PubMed Central

Zheng, Xiaoxia; Zhao, Wenji; Yan, Xing; Shu, Tongtong; Xiong, Qiulin; Chen, Fantao

2015-01-01

Airborne dust, which contains high levels of toxic metals, is recognized as one of the most harmful environment component. The purpose of this study was to evaluate heavy metals pollution in dustfall from bus stations in Beijing, and to perform a risk assessment analysis for adult passengers. The concentrations of Cd, Co, Cr, Cu, Mo, Ni, Pb, V and Zn were determined by inductively coupled plasma mass spectroscopy (ICP-MS). The spatial distribution, pollution level and potential health risk of heavy metals were analyzed by Geographic Information System (GIS) mapping technology, geo-accumulation index and health risk assessment model, respectively. The results indicate that dust samples have elevated metal concentrations, especially for Cd, Cu, Pb and Zn. The nine metals can be divided into two categories in terms of spatial distribution and pollution level. Cd, Cr, Cu, Mo, Pb and Zn reach contaminated level and have similar spatial patterns with hotspots distributed within the Fifth Ring Road. While the hot spot areas of Co and V are always out of the Fifth Ring Road. Health risk assessment shows that both carcinogenic and non-carcinogenic risks of selected metals were within the safe range. PMID:26287229

Pollution Characteristics and Health Risk Assessment of Airborne Heavy Metals Collected from Beijing Bus Stations.

PubMed

Zheng, Xiaoxia; Zhao, Wenji; Yan, Xing; Shu, Tongtong; Xiong, Qiulin; Chen, Fantao

2015-08-17

Airborne dust, which contains high levels of toxic metals, is recognized as one of the most harmful environment component. The purpose of this study was to evaluate heavy metals pollution in dustfall from bus stations in Beijing, and to perform a risk assessment analysis for adult passengers. The concentrations of Cd, Co, Cr, Cu, Mo, Ni, Pb, V and Zn were determined by inductively coupled plasma mass spectroscopy (ICP-MS). The spatial distribution, pollution level and potential health risk of heavy metals were analyzed by Geographic Information System (GIS) mapping technology, geo-accumulation index and health risk assessment model, respectively. The results indicate that dust samples have elevated metal concentrations, especially for Cd, Cu, Pb and Zn. The nine metals can be divided into two categories in terms of spatial distribution and pollution level. Cd, Cr, Cu, Mo, Pb and Zn reach contaminated level and have similar spatial patterns with hotspots distributed within the Fifth Ring Road. While the hot spot areas of Co and V are always out of the Fifth Ring Road. Health risk assessment shows that both carcinogenic and non-carcinogenic risks of selected metals were within the safe range.

Transit time distributions to assess present and future contamination risk of karst aquifers over Europe and the Mediterranean

NASA Astrophysics Data System (ADS)

Hartmann, Andreas; Gleeson, Tom; Wada, Yoshihide; Wagener, Thorsten

2016-04-01

Karst develops through the dissolution of carbonate rock. Karst groundwater in Europe is a major source of fresh water contributing up to half of the total drinking water supply in some countries. Climate model projections suggest that in the next 100 years, karst regions will experience a strong increase in temperature and a serious decrease of precipitation - especially in the Mediterranean region. Previous work showed that the karstic preferential recharge processes result in enhanced recharge rates and future climate sensitivity. But as there is fast water flow form the surface to the aquifer, there is also an enhanced risk of groundwater contamination. In this study we will assess the contamination risk of karst aquifers over Europe and the Mediterranean using simulated transit time distributions. Using a new type of semi-distributed model that considers the spatial heterogeneity of the karst system by distribution functions we simulated a range of spatially variable pathways of karstic groundwater recharge. The model is driven by the bias-corrected 5 GCMs of the ISI-MIP project (RCP8.5). Transit time distributions are calculated by virtual tracer experiments. These are repeated several times in the present (1991-2010) and the future (2080-2099). We can show that regions with larger fractions of preferential recharge show higher risks of contamination and that spatial patterns of contamination risk change towards the future.

Bisphenol analogues in surface water and sediment from the shallow Chinese freshwater lakes: Occurrence, distribution, source apportionment, and ecological and human health risk.

PubMed

Yan, Zhengyu; Liu, Yanhua; Yan, Kun; Wu, Shengmin; Han, Zhihua; Guo, Ruixin; Chen, Meihong; Yang, Qiulian; Zhang, Shenghu; Chen, Jianqiu

2017-10-01

Compared to Bisphenol A (BPA), current knowledge on the spatial distribution, potential sources and environmental risk assessment of other bisphenol analogues (BPs) remains limited. The occurrence, distribution and sources of seven BPs were investigated in the surface water and sediment from Taihu Lake and Luoma Lake, which are the Chinese shallow freshwater lakes. Because there are many industries and living areas around Taihu Lake, the total concentrations of ∑BPs were much higher than that in Luoma Lake, which is away from the industry-intensive areas. For the two lakes, BPA was still the dominant BPs in both surface water and sediment, followed by BPF and BPS. The spatial distribution and principal component analysis showed that BPs in Luoma Lake was relatively homogeneous and the potential sources were relatively simple than that in Taihu Lake. The spatial distribution of BPs in sediment of Taihu Lake indicated that ∑BPs positively correlated with the TOC content. For both Taihu Lake and Luoma Lake, the risk assessment at the sampling sites showed that no high risk in surface water and sediment (RQ t  < 1.0, and EEQ t  < 1.0 ng E 2 /L). Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial pattern of risk of common raven predation on desert tortoises

USGS Publications Warehouse

Kristan, W. B.; Boarman, W.I.

2003-01-01

Common Ravens (Corvus corax) in the Mojave Desert of California, USA are subsidized by anthropogenic resources. Large numbers of nonbreeding ravens are attracted to human developments and thus are spatially restricted, whereas breeding ravens are distributed more evenly throughout the area. We investigated whether the spatial distribution of risk of predation by ravens to juveniles of the threatened desert tortoise (Gopherus agassizii) was determined by the spatial distribution of (1) nonbreeding ravens at human developments (leading to "spillover" predation) or (2) breeding individuals throughout developed and undeveloped areas (leading to " hyperpredation"). Predation risk, measured using styrofoam models of juvenile desert tortoises, was high near places attracting large numbers of nonbreeding ravens, near successful nests, and far from successful nests when large numbers of nonbreeding ravens were present. Patterns consistent with both "spillover" predation and "hyperpredation" were thus observed, attributed to the nonbreeding and breeding segments of the population, respectively. Furthermore, because locations of successful nests changed almost annually, consistent low-predation refugia for juvenile desert tortoises were nearly nonexistent. Consequently, anthropogenic resources for ravens could indirectly lead to the suppression, decline, or even extinction of desert tortoise populations.

Determinants of the geographic distribution of Puumala virus and Lyme borreliosis infections in Belgium

PubMed Central

Linard, Catherine; Lamarque, Pénélope; Heyman, Paul; Ducoffre, Geneviève; Luyasu, Victor; Tersago, Katrien; Vanwambeke, Sophie O; Lambin, Eric F

2007-01-01

Background Vector-borne and zoonotic diseases generally display clear spatial patterns due to different space-dependent factors. Land cover and land use influence disease transmission by controlling both the spatial distribution of vectors or hosts, and the probability of contact with susceptible human populations. The objective of this study was to combine environmental and socio-economic factors to explain the spatial distribution of two emerging human diseases in Belgium, Puumala virus (PUUV) and Lyme borreliosis. Municipalities were taken as units of analysis. Results Negative binomial regressions including a correction for spatial endogeneity show that the spatial distribution of PUUV and Lyme borreliosis infections are associated with a combination of factors linked to the vector and host populations, to human behaviours, and to landscape attributes. Both diseases are associated with the presence of forests, which are the preferred habitat for vector or host populations. The PUUV infection risk is higher in remote forest areas, where the level of urbanisation is low, and among low-income populations. The Lyme borreliosis transmission risk is higher in mixed landscapes with forests and spatially dispersed houses, mostly in wealthy peri-urban areas. The spatial dependence resulting from a combination of endogenous and exogenous processes could be accounted for in the model on PUUV but not for Lyme borreliosis. Conclusion A large part of the spatial variation in disease risk can be explained by environmental and socio-economic factors. The two diseases not only are most prevalent in different regions but also affect different groups of people. Combining these two criteria may increase the efficiency of information campaigns through appropriate targeting. PMID:17474974

Fine-Scale Mapping by Spatial Risk Distribution Modeling for Regional Malaria Endemicity and Its Implications under the Low-to-Moderate Transmission Setting in Western Cambodia

PubMed Central

Okami, Suguru; Kohtake, Naohiko

2016-01-01

The disease burden of malaria has decreased as malaria elimination efforts progress. The mapping approach that uses spatial risk distribution modeling needs some adjustment and reinvestigation in accordance with situational changes. Here we applied a mathematical modeling approach for standardized morbidity ratio (SMR) calculated by annual parasite incidence using routinely aggregated surveillance reports, environmental data such as remote sensing data, and non-environmental anthropogenic data to create fine-scale spatial risk distribution maps of western Cambodia. Furthermore, we incorporated a combination of containment status indicators into the model to demonstrate spatial heterogeneities of the relationship between containment status and risks. The explanatory model was fitted to estimate the SMR of each area (adjusted Pearson correlation coefficient R2 = 0.774; Akaike information criterion AIC = 149.423). A Bayesian modeling framework was applied to estimate the uncertainty of the model and cross-scale predictions. Fine-scale maps were created by the spatial interpolation of estimated SMRs at each village. Compared with geocoded case data, corresponding predicted values showed conformity [Spearman’s rank correlation r = 0.662 in the inverse distance weighed interpolation and 0.645 in ordinal kriging (95% confidence intervals of 0.414–0.827 and 0.368–0.813, respectively), Welch’s t-test; Not significant]. The proposed approach successfully explained regional malaria risks and fine-scale risk maps were created under low-to-moderate malaria transmission settings where reinvestigations of existing risk modeling approaches were needed. Moreover, different representations of simulated outcomes of containment status indicators for respective areas provided useful insights for tailored interventional planning, considering regional malaria endemicity. PMID:27415623

Fine-Scale Spatial Heterogeneity in the Distribution of Waterborne Protozoa in a Drinking Water Reservoir

PubMed Central

Burnet, Jean-Baptiste; Ogorzaly, Leslie; Penny, Christian; Cauchie, Henry-Michel

2015-01-01

Background: The occurrence of faecal pathogens in drinking water resources constitutes a threat to the supply of safe drinking water, even in industrialized nations. To efficiently assess and monitor the risk posed by these pathogens, sampling deserves careful design, based on preliminary knowledge on their distribution dynamics in water. For the protozoan pathogens Cryptosporidium and Giardia, only little is known about their spatial distribution within drinking water supplies, especially at fine scale. Methods: Two-dimensional distribution maps were generated by sampling cross-sections at meter resolution in two different zones of a drinking water reservoir. Samples were analysed for protozoan pathogens as well as for E. coli, turbidity and physico-chemical parameters. Results: Parasites displayed heterogeneous distribution patterns, as reflected by significant (oo)cyst density gradients along reservoir depth. Spatial correlations between parasites and E. coli were observed near the reservoir inlet but were absent in the downstream lacustrine zone. Measurements of surface and subsurface flow velocities suggest a role of local hydrodynamics on these spatial patterns. Conclusion: This fine-scale spatial study emphasizes the importance of sampling design (site, depth and position on the reservoir) for the acquisition of representative parasite data and for optimization of microbial risk assessment and monitoring. Such spatial information should prove useful to the modelling of pathogen transport dynamics in drinking water supplies. PMID:26404350

Spatial ecology of refuge selection by an herbivore under risk of predation

USGS Publications Warehouse

Wilson, Tammy L.; Rayburn, Andrew P.; Edwards, Thomas C.

2012-01-01

Prey species use structures such as burrows to minimize predation risk. The spatial arrangement of these resources can have important implications for individual and population fitness. For example, there is evidence that clustered resources can benefit individuals by reducing predation risk and increasing foraging opportunity concurrently, which leads to higher population density. However, the scale of clustering that is important in these processes has been ignored during theoretical and empirical development of resource models. Ecological understanding of refuge exploitation by prey can be improved by spatial analysis of refuge use and availability that incorporates the effect of scale. We measured the spatial distribution of pygmy rabbit (Brachylagus idahoensis) refugia (burrows) through censuses in four 6-ha sites. Point pattern analyses were used to evaluate burrow selection by comparing the spatial distribution of used and available burrows. The presence of food resources and additional overstory cover resources was further examined using logistic regression. Burrows were spatially clustered at scales up to approximately 25 m, and then regularly spaced at distances beyond ~40 m. Pygmy rabbit exploitation of burrows did not match availability. Burrows used by pygmy rabbits were likely to be located in areas with high overall burrow density (resource clusters) and high overstory cover, which together minimized predation risk. However, in some cases we observed an interaction between either overstory cover (safety) or understory cover (forage) and burrow density. The interactions show that pygmy rabbits will use burrows in areas with low relative burrow density (high relative predation risk) if understory food resources are high. This points to a potential trade-off whereby rabbits must sacrifice some safety afforded by additional nearby burrows to obtain ample forage resources. Observed patterns of clustered burrows and non-random burrow use improve understanding of the importance of spatial distribution of refugia for burrowing herbivores. The analyses used allowed for the estimation of the spatial scale where subtle trade-offs between predation avoidance and foraging opportunity are likely to occur in a natural system.

ASSESSING THE RISK ASSOCIATED WITH MERCURY: USING REVA'S WEBTOOL TO COMPARE DATA, ASSUMPTIONS, AND MODELS

EPA Science Inventory

The problem of assessing risk from mercury across the nation is extremely complex involving integration of I) our understanding of the methylation process in ecosystems, 2) the identification and spatial distribution of sensitive populations, and 3) the spatial pattern of mercury...

Limited spatial response to direct predation risk by African herbivores following predator reintroduction.

PubMed

Davies, Andrew B; Tambling, Craig J; Kerley, Graham I H; Asner, Gregory P

2016-08-01

Predators affect ecosystems not only through direct mortality of prey, but also through risk effects on prey behavior, which can exert strong influences on ecosystem function and prey fitness. However, how functionally different prey species respond to predation risk and how prey strategies vary across ecosystems and in response to predator reintroduction are poorly understood. We investigated the spatial distributions of six African herbivores varying in foraging strategy and body size in response to environmental factors and direct predation risk by recently reintroduced lions in the thicket biome of the Addo Elephant National Park, South Africa, using camera trap surveys, GPS telemetry, kill site locations and Light Detection and Ranging. Spatial distributions of all species, apart from buffalo, were driven primarily by environmental factors, with limited responses to direct predation risk. Responses to predation risk were instead indirect, with species distributions driven by environmental factors, and diel patterns being particularly pronounced. Grazers were more responsive to the measured variables than browsers, with more observations in open areas. Terrain ruggedness was a stronger predictor of browser distributions than was vegetation density. Buffalo was the only species to respond to predator encounter risk, avoiding areas with higher lion utilization. Buffalo therefore behaved in similar ways to when lions were absent from the study area. Our results suggest that direct predation risk effects are relatively weak when predator densities are low and the time since reintroduction is short and emphasize the need for robust, long-term monitoring of predator reintroductions to place such events in the broader context of predation risk effects.

Polycyclic aromatic hydrocarbons in soils from urban to rural areas in Nanjing: Concentration, source, spatial distribution, and potential human health risk.

PubMed

Wang, Chunhui; Wu, Shaohua; Zhou, Sheng Lu; Wang, Hui; Li, Baojie; Chen, Hao; Yu, Yanna; Shi, Yaxing

2015-09-15

Polycyclic aromatic hydrocarbons (PAHs) have become a major type of pollutant in urban areas and their degree of pollution and characteristics of spatial distribution differ between various regions. We conducted a comprehensive study about the concentration, source, spatial distribution, and health risk of 16 PAHs from urban to rural soils in Nanjing. The mean total concentrations of 16 PAHs (∑16PAHs) were 3330 ng g(-1) for urban soils, 1680 ng g(-1) for suburban soils, and 1060 ng g(-1) for rural soils. Five sources in urban, suburban, and rural areas of Nanjing were identified by positive matrix factorization. Their relative contributions of sources to the total soil PAH burden in descending order was coal combustion, vehicle emissions, biomass burning, coke tar, and oil in urban areas; in suburban areas the main sources of soil PAHs were gasoline engine and diesel engine, whereas in rural areas the main sources were creosote and biomass burning. The spatial distribution of soil PAH concentrations shows that old urban districts and commercial centers were the most contaminated of all areas in Nanjing. The distribution pattern of heavier PAHs was in accordance with ∑16PAHs, whereas lighter PAHs show some special characteristics. Health risk assessment based on toxic equivalency factors of benzo[a]pyrene indicated a low concentration of PAHs in most areas in Nanjing, but some sensitive sites should draw considerable attention. We conclude that urbanization has accelerated the accumulation of soil PAHs and increased the environmental risk for urban residents. Copyright © 2015. Published by Elsevier B.V.

Differential adult survival at close seabird colonies: The importance of spatial foraging segregation and bycatch risk during the breeding season.

PubMed

Genovart, Meritxell; Bécares, Juan; Igual, José-Manuel; Martínez-Abraín, Alejandro; Escandell, Raul; Sánchez, Antonio; Rodríguez, Beneharo; Arcos, José M; Oro, Daniel

2018-03-01

Marine megafauna, including seabirds, are critically affected by fisheries bycatch. However, bycatch risk may differ on temporal and spatial scales due to the uneven distribution and effort of fleets operating different fishing gear, and to focal species distribution and foraging behavior. Scopoli's shearwater Calonectris diomedea is a long-lived seabird that experiences high bycatch rates in longline fisheries and strong population-level impacts due to this type of anthropogenic mortality. Analyzing a long-term dataset on individual monitoring, we compared adult survival (by means of multi-event capture-recapture models) among three close predator-free Mediterranean colonies of the species. Unexpectedly for a long-lived organism, adult survival varied among colonies. We explored potential causes of this differential survival by (1) measuring egg volume as a proxy of food availability and parental condition; (2) building a specific longline bycatch risk map for the species; and (3) assessing the distribution patterns of breeding birds from the three study colonies via GPS tracking. Egg volume was very similar between colonies over time, suggesting that environmental variability related to habitat foraging suitability was not the main cause of differential survival. On the other hand, differences in foraging movements among individuals from the three colonies expose them to differential mortality risk, which likely influenced the observed differences in adult survival. The overlap of information obtained by the generation of specific bycatch risk maps, the quantification of population demographic parameters, and the foraging spatial analysis should inform managers about differential sensitivity to the anthropogenic impact at mesoscale level and guide decisions depending on the spatial configuration of local populations. The approach would apply and should be considered in any species where foraging distribution is colony-specific and mortality risk varies spatially. © 2017 John Wiley & Sons Ltd.

Into the environment of mosquito-borne disease: A spatial analysis of vector distribution using traditional and remotely sensed methods

NASA Astrophysics Data System (ADS)

Brown, Heidi E.

Spatially explicit information is increasingly available for infectious disease modeling. However, such information is reluctantly or inappropriately incorporated. My dissertation research uses spatially explicit data to assess relationships between landscape and mosquito species distribution and discusses challenges regarding accurate predictive risk modeling. The goal of my research is to use remotely sensed environmental information and spatial statistical methods to better understand mosquito-borne disease epidemiology for improvement of public health responses. In addition to reviewing the progress of spatial infectious disease modeling, I present four research projects. I begin by evaluating the biases in surveillance data and build up to predictive modeling of mosquito species presence. In the first study I explore how mosquito surveillance trap types influence estimations of mosquito populations. Then. I use county-based human surveillance data and landscape variables to identify risk factors for West Nile virus disease. The third study uses satellite-based vegetation indices to identify spatial variation among West Nile virus vectors in an urban area and relates the variability to virus transmission dynamics. Finally, I explore how information from three satellite sensors of differing spatial and spectral resolution can be used to identify and distinguish mosquito habitat across central Connecticut wetlands. Analyses presented here constitute improvements to the prediction of mosquito distribution and therefore identification of disease risk factors. Current methods for mosquito surveillance data collection are labor intensive and provide an extremely limited, incomplete picture of the species composition and abundance. Human surveillance data offers additional challenges with respect to reporting bias and resolution, but is nonetheless informative in identifying environmental risk factors and disease transmission dynamics. Remotely sensed imagery supports mosquito and human disease surveillance data by providing spatially explicit, line resolution information about environmental factors relevant to vector-borne disease processes. Together, surveillance and remotely sensed environmental data facilitate improved description and modeling of disease transmission. Remote sensing can be used to develop predictive maps of mosquito distribution in relation to disease risk. This has implications for increased accuracy of mosquito control efforts. The projects presented in this dissertation enhance current public health capacities by examining the applications of spatial modeling with respect to mosquito-borne disease.

The Potential for Spatial Distribution Indices to Signal Thresholds in Marine Fish Biomass

PubMed Central

Reuchlin-Hugenholtz, Emilie

2015-01-01

The frequently observed positive relationship between fish population abundance and spatial distribution suggests that changes in distribution can be indicative of trends in abundance. If contractions in spatial distribution precede declines in spawning stock biomass (SSB), spatial distribution reference points could complement the SSB reference points that are commonly used in marine conservation biology and fisheries management. When relevant spatial distribution information is integrated into fisheries management and recovery plans, risks and uncertainties associated with a plan based solely on the SSB criterion would be reduced. To assess the added value of spatial distribution data, we examine the relationship between SSB and four metrics of spatial distribution intended to reflect changes in population range, concentration, and density for 10 demersal populations (9 species) inhabiting the Scotian Shelf, Northwest Atlantic. Our primary purpose is to assess their potential to serve as indices of SSB, using fisheries independent survey data. We find that metrics of density offer the best correlate of spawner biomass. A decline in the frequency of encountering high density areas is associated with, and in a few cases preceded by, rapid declines in SSB in 6 of 10 populations. Density-based indices have considerable potential to serve both as an indicator of SSB and as spatially based reference points in fisheries management. PMID:25789624

Spatial heterogeneity of type I error for local cluster detection tests

PubMed Central

2014-01-01

Background Just as power, type I error of cluster detection tests (CDTs) should be spatially assessed. Indeed, CDTs’ type I error and power have both a spatial component as CDTs both detect and locate clusters. In the case of type I error, the spatial distribution of wrongly detected clusters (WDCs) can be particularly affected by edge effect. This simulation study aims to describe the spatial distribution of WDCs and to confirm and quantify the presence of edge effect. Methods A simulation of 40 000 datasets has been performed under the null hypothesis of risk homogeneity. The simulation design used realistic parameters from survey data on birth defects, and in particular, two baseline risks. The simulated datasets were analyzed using the Kulldorff’s spatial scan as a commonly used test whose behavior is otherwise well known. To describe the spatial distribution of type I error, we defined the participation rate for each spatial unit of the region. We used this indicator in a new statistical test proposed to confirm, as well as quantify, the edge effect. Results The predefined type I error of 5% was respected for both baseline risks. Results showed strong edge effect in participation rates, with a descending gradient from center to edge, and WDCs more often centrally situated. Conclusions In routine analysis of real data, clusters on the edge of the region should be carefully considered as they rarely occur when there is no cluster. Further work is needed to combine results from power studies with this work in order to optimize CDTs performance. PMID:24885343

QMRA for Drinking Water: 2. The Effect of Pathogen Clustering in Single-Hit Dose-Response Models.

PubMed

Nilsen, Vegard; Wyller, John

2016-01-01

Spatial and/or temporal clustering of pathogens will invalidate the commonly used assumption of Poisson-distributed pathogen counts (doses) in quantitative microbial risk assessment. In this work, the theoretically predicted effect of spatial clustering in conventional "single-hit" dose-response models is investigated by employing the stuttering Poisson distribution, a very general family of count distributions that naturally models pathogen clustering and contains the Poisson and negative binomial distributions as special cases. The analysis is facilitated by formulating the dose-response models in terms of probability generating functions. It is shown formally that the theoretical single-hit risk obtained with a stuttering Poisson distribution is lower than that obtained with a Poisson distribution, assuming identical mean doses. A similar result holds for mixed Poisson distributions. Numerical examples indicate that the theoretical single-hit risk is fairly insensitive to moderate clustering, though the effect tends to be more pronounced for low mean doses. Furthermore, using Jensen's inequality, an upper bound on risk is derived that tends to better approximate the exact theoretical single-hit risk for highly overdispersed dose distributions. The bound holds with any dose distribution (characterized by its mean and zero inflation index) and any conditional dose-response model that is concave in the dose variable. Its application is exemplified with published data from Norovirus feeding trials, for which some of the administered doses were prepared from an inoculum of aggregated viruses. The potential implications of clustering for dose-response assessment as well as practical risk characterization are discussed. © 2016 Society for Risk Analysis.

Contribution of industrial density and socioeconomic status to the spatial distribution of thyroid cancer risk in Hangzhou, China.

PubMed

Fei, Xufeng; Lou, Zhaohan; Christakos, George; Liu, Qingmin; Ren, Yanjun; Wu, Jiaping

2018-02-01

The thyroid cancer (TC) incidence in China has increased dramatically during the last three decades. Typical in this respect is the case of Hangzhou city (China), where 7147 new TC cases were diagnosed during the period 2008-2012. Hence, the assessment of the TC incidence risk increase due to environmental exposure is an important public health matter. Correlation analysis, Analysis of Variance (ANOVA) and Poisson regression were first used to evaluate the statistical association between TC and key risk factors (industrial density and socioeconomic status). Then, the Bayesian maximum entropy (BME) theory and the integrative disease predictability (IDP) criterion were combined to quantitatively assess both the overall and the spatially distributed strength of the "exposure-disease" association. Overall, higher socioeconomic status was positively correlated with higher TC risk (Pearson correlation coefficient=0.687, P<0.01). Compared to people of low socioeconomic status, people of median and high socioeconomic status showed higher TC risk: the Relative Risk (RR) and associated 95% confidence interval (CI) were found to be, respectively, RR=2.29 with 95% CI=1.99 to 2.63, and RR=3.67 with 95% CI=3.22 to 4.19. The "industrial density-TC incidence" correlation, however, was non-significant. Spatially, the "socioeconomic status-TC" association measured by the corresponding IDP coefficient was significant throughout the study area: the mean IDP value was -0.12 and the spatial IDP values were consistently negative at the township level. It was found that stronger associations were distributed among residents mainly on a stripe of land from northeast to southwest (consisting mainly of sub-district areas). The "industrial density-TC" association measured by its IDP coefficient was spatially non-consistent. Socioeconomic status is an important indicator of TC risk factor in Hangzhou (China) whose effect varies across space. Hence, socioeconomic status shows the highest TC risk effect in sub-district areas. Copyright © 2017. Published by Elsevier B.V.

Development of an Asset Value Map for Disaster Risk Assessment in China by Spatial Disaggregation Using Ancillary Remote Sensing Data.

PubMed

Wu, Jidong; Li, Ying; Li, Ning; Shi, Peijun

2018-01-01

The extent of economic losses due to a natural hazard and disaster depends largely on the spatial distribution of asset values in relation to the hazard intensity distribution within the affected area. Given that statistical data on asset value are collected by administrative units in China, generating spatially explicit asset exposure maps remains a key challenge for rapid postdisaster economic loss assessment. The goal of this study is to introduce a top-down (or downscaling) approach to disaggregate administrative-unit level asset value to grid-cell level. To do so, finding the highly correlated "surrogate" indicators is the key. A combination of three data sets-nighttime light grid, LandScan population grid, and road density grid, is used as ancillary asset density distribution information for spatializing the asset value. As a result, a high spatial resolution asset value map of China for 2015 is generated. The spatial data set contains aggregated economic value at risk at 30 arc-second spatial resolution. Accuracy of the spatial disaggregation reflects redistribution errors introduced by the disaggregation process as well as errors from the original ancillary data sets. The overall accuracy of the results proves to be promising. The example of using the developed disaggregated asset value map in exposure assessment of watersheds demonstrates that the data set offers immense analytical flexibility for overlay analysis according to the hazard extent. This product will help current efforts to analyze spatial characteristics of exposure and to uncover the contributions of both physical and social drivers of natural hazard and disaster across space and time. © 2017 Society for Risk Analysis.

USE OF HABITAT-CONTAMINATION SPATIAL CORRELATION TO DETERMINE WHEN TO PERFORM A SPATIALLY EXPLICIT ECOLOGICAL RISK ASSESSMENT

EPA Science Inventory

Anthropogenic contamination is typically distributed heterogeneously through space. This spatial structure can have different effects on the cumulative doses of individuals exposed to contamination within the environment. These effects are accentuated when individuals pursue di...

Geographical Environment Factors and Risk Assessment of Tick-Borne Encephalitis in Hulunbuir, Northeastern China.

PubMed

Li, Yifan; Wang, Juanle; Gao, Mengxu; Fang, Liqun; Liu, Changhua; Lyu, Xin; Bai, Yongqing; Zhao, Qiang; Li, Hairong; Yu, Hongjie; Cao, Wuchun; Feng, Liqiang; Wang, Yanjun; Zhang, Bin

2017-05-26

Tick-borne encephalitis (TBE) is one of natural foci diseases transmitted by ticks. Its distribution and transmission are closely related to geographic and environmental factors. Identification of environmental determinates of TBE is of great importance to understanding the general distribution of existing and potential TBE natural foci. Hulunbuir, one of the most severe endemic areas of the disease, is selected as the study area. Statistical analysis, global and local spatial autocorrelation analysis, and regression methods were applied to detect the spatiotemporal characteristics, compare the impact degree of associated factors, and model the risk distribution using the heterogeneity. The statistical analysis of gridded geographic and environmental factors and TBE incidence show that the TBE patients mainly occurred during spring and summer and that there is a significant positive spatial autocorrelation between the distribution of TBE cases and environmental characteristics. The impact degree of these factors on TBE risks has the following descending order: temperature, relative humidity, vegetation coverage, precipitation and topography. A high-risk area with a triangle shape was determined in the central part of Hulunbuir; the low-risk area is located in the two belts next to the outside edge of the central triangle. The TBE risk distribution revealed that the impact of the geographic factors changed depending on the heterogeneity.

A Rapid Monitoring and Evaluation Method of Schistosomiasis Based on Spatial Information Technology.

PubMed

Wang, Yong; Zhuang, Dafang

2015-12-12

Thanks to Spatial Information Technologies (SITs) such as Remote Sensing (RS) and Geographical Information System (GIS) that are being quickly developed and updated, SITs are being used more widely in the public health field. The use of SITs to study the characteristics of the temporal and spatial distribution of Schistosoma japonicum and to assess the risk of infection provides methods for the control and prevention of schistosomiasis japonica has gradually become a hot topic in the field. The purpose of the present paper was to use RS and GIS technology to develop an efficient method of prediction and assessment of the risk of schistosomiasis japonica. We choose the Yueyang region, close to the east DongTing Lake (Hunan Province, China), as the study area, where a recent serious outbreak of schistosomiasis japonica took place. We monitored and evaluated the transmission risk of schistosomiasis japonica in the region using SITs. Water distribution data were extracted from RS images. The ground temperature, ground humidity and vegetation index were calculated based on RS images. Additionally, the density of oncomelania snails, which are the Schistosoma japonicum intermediate host, was calculated on the base of RS data and field measurements. The spatial distribution of oncomelania snails was explored using SITs in order to estimate the area surrounding the residents with transmission risk of schistosomiasis japonica. Our research result demonstrated: (1) the risk factors for the transmission of schistosomiasis japonica were closely related to the living environment of oncomelania snails. Key factors such as water distribution, ground temperature, ground humidity and vegetation index can be quickly obtained and calculated from RS images; (2) using GIS technology and a RS deduction technique along with statistical regression models, the density distribution model of oncomelania snails could be quickly built; (3) using SITs and analysis with overlaying population distribution data, the range of transmission risk of schistosomiasis japonica of the study area can be quickly monitored and evaluated. This method will help support the decision making for the control and prevention of schistosomiasis and form a valuable application using SITs for the schistosomiasis research.

Multi-Scale Clustering of Lyme Disease Risk at the Expanding Leading Edge of the Range of Ixodes scapularis in Canada.

PubMed

Ripoche, Marion; Lindsay, Leslie Robbin; Ludwig, Antoinette; Ogden, Nicholas H; Thivierge, Karine; Leighton, Patrick A

2018-03-27

Since its detection in Canada in the early 1990s, Ixodes scapularis , the primary tick vector of Lyme disease in eastern North America, has continued to expand northward. Estimates of the tick's broad-scale distribution are useful for tracking the extent of the Lyme disease risk zone; however, tick distribution may vary widely within this zone. Here, we investigated I. scapularis nymph distribution at three spatial scales across the Lyme disease emergence zone in southern Quebec, Canada. We collected ticks and compared the nymph densities among different woodlands and different plots and transects within the same woodland. Hot spot analysis highlighted significant nymph clustering at each spatial scale. In regression models, nymph abundance was associated with litter depth, humidity, and elevation, which contribute to a suitable habitat for ticks, but also with the distance from the trail and the type of trail, which could be linked to host distribution and human disturbance. Accounting for this heterogeneous nymph distribution at a fine spatial scale could help improve Lyme disease management strategies but also help people to understand the risk variation around them and to adopt appropriate behaviors, such as staying on the trail in infested parks to limit their exposure to the vector and associated pathogens.

Multi-Scale Clustering of Lyme Disease Risk at the Expanding Leading Edge of the Range of Ixodes scapularis in Canada

PubMed Central

Lindsay, Leslie Robbin; Ludwig, Antoinette; Ogden, Nicholas H.; Thivierge, Karine; Leighton, Patrick A.

2018-01-01

Since its detection in Canada in the early 1990s, Ixodes scapularis, the primary tick vector of Lyme disease in eastern North America, has continued to expand northward. Estimates of the tick’s broad-scale distribution are useful for tracking the extent of the Lyme disease risk zone; however, tick distribution may vary widely within this zone. Here, we investigated I. scapularis nymph distribution at three spatial scales across the Lyme disease emergence zone in southern Quebec, Canada. We collected ticks and compared the nymph densities among different woodlands and different plots and transects within the same woodland. Hot spot analysis highlighted significant nymph clustering at each spatial scale. In regression models, nymph abundance was associated with litter depth, humidity, and elevation, which contribute to a suitable habitat for ticks, but also with the distance from the trail and the type of trail, which could be linked to host distribution and human disturbance. Accounting for this heterogeneous nymph distribution at a fine spatial scale could help improve Lyme disease management strategies but also help people to understand the risk variation around them and to adopt appropriate behaviors, such as staying on the trail in infested parks to limit their exposure to the vector and associated pathogens. PMID:29584627

Development of a module for Cost-Benefit analysis of risk reduction measures for natural hazards for the CHANGES-SDSS platform

NASA Astrophysics Data System (ADS)

Berlin, Julian; Bogaard, Thom; Van Westen, Cees; Bakker, Wim; Mostert, Eric; Dopheide, Emile

2014-05-01

Cost benefit analysis (CBA) is a well know method used widely for the assessment of investments either in the private and public sector. In the context of risk mitigation and the evaluation of risk reduction alternatives for natural hazards its use is very important to evaluate the effectiveness of such efforts in terms of avoided monetary losses. However the current method has some disadvantages related to the spatial distribution of the costs and benefits, the geographical distribution of the avoided damage and losses, the variation in areas that are benefited in terms of invested money and avoided monetary risk. Decision-makers are often interested in how the costs and benefits are distributed among different administrative units of a large area or region, so they will be able to compare and analyse the cost and benefits per administrative unit as a result of the implementation of the risk reduction projects. In this work we first examined the Cost benefit procedure for natural hazards, how the costs are assessed for several structural and non-structural risk reduction alternatives, we also examined the current problems of the method such as the inclusion of cultural and social considerations that are complex to monetize , the problem of discounting future values using a defined interest rate and the spatial distribution of cost and benefits. We also examined the additional benefits and the indirect costs associated with the implementation of the risk reduction alternatives such as the cost of having a ugly landscape (also called negative benefits). In the last part we examined the current tools and software used in natural hazards assessment with support to conduct CBA and we propose design considerations for the implementation of the CBA module for the CHANGES-SDSS Platform an initiative of the ongoing 7th Framework Programme "CHANGES of the European commission. Keywords: Risk management, Economics of risk mitigation, EU Flood Directive, resilience, prevention, cost benefit analysis, spatial distribution of costs and benefits

Spatial analysis of health risk assessment with arsenic intake of drinking water in the LanYang plain

NASA Astrophysics Data System (ADS)

Chen, C. F.; Liang, C. P.; Jang, C. S.; Chen, J. S.

2016-12-01

Groundwater is one of the most component water resources in Lanyang plain. The groundwater of the Lanyang Plain contains arsenic levels that exceed the current Taiwan Environmental Protection Administration (Taiwan EPA) limit of 10 μg/L. The arsenic of groundwater in some areas of the Lanyang Plain pose great menace for the safe use of groundwater resources. Therefore, poor water quality can adversely impact drinking water uses, leading to human health risks. This study analyzed the potential health risk associated with the ingestion of arsenic-affected groundwater in the arseniasis-endemic Lanyang plain. Geostatistical approach is widely used in spatial variability analysis and distributions of field data with uncertainty. The estimation of spatial distribution of the arsenic contaminant in groundwater is very important in the health risk assessment. This study used indicator kriging (IK) and ordinary kriging (OK) methods to explore the spatial variability of arsenic-polluted parameters. The estimated difference between IK and OK estimates was compared. The extent of arsenic pollution was spatially determined and the Target cancer risk (TR) and dose response were explored when the ingestion of arsenic in groundwater. Thus, a zonal management plan based on safe groundwater use is formulated. The research findings can provide a plan reference of regional water resources supplies for local government administrators and developing groundwater resources in the Lanyang Plain.

Spatial heterogeneity and risk factors for stunting among children under age five in Ethiopia: A Bayesian geo-statistical model.

PubMed

Hagos, Seifu; Hailemariam, Damen; WoldeHanna, Tasew; Lindtjørn, Bernt

2017-01-01

Understanding the spatial distribution of stunting and underlying factors operating at meso-scale is of paramount importance for intervention designing and implementations. Yet, little is known about the spatial distribution of stunting and some discrepancies are documented on the relative importance of reported risk factors. Therefore, the present study aims at exploring the spatial distribution of stunting at meso- (district) scale, and evaluates the effect of spatial dependency on the identification of risk factors and their relative contribution to the occurrence of stunting and severe stunting in a rural area of Ethiopia. A community based cross sectional study was conducted to measure the occurrence of stunting and severe stunting among children aged 0-59 months. Additionally, we collected relevant information on anthropometric measures, dietary habits, parent and child-related demographic and socio-economic status. Latitude and longitude of surveyed households were also recorded. Local Anselin Moran's I was calculated to investigate the spatial variation of stunting prevalence and identify potential local pockets (hotspots) of high prevalence. Finally, we employed a Bayesian geo-statistical model, which accounted for spatial dependency structure in the data, to identify potential risk factors for stunting in the study area. Overall, the prevalence of stunting and severe stunting in the district was 43.7% [95%CI: 40.9, 46.4] and 21.3% [95%CI: 19.5, 23.3] respectively. We identified statistically significant clusters of high prevalence of stunting (hotspots) in the eastern part of the district and clusters of low prevalence (cold spots) in the western. We found out that the inclusion of spatial structure of the data into the Bayesian model has shown to improve the fit for stunting model. The Bayesian geo-statistical model indicated that the risk of stunting increased as the child's age increased (OR 4.74; 95% Bayesian credible interval [BCI]:3.35-6.58) and among boys (OR 1.28; 95%BCI; 1.12-1.45). However, maternal education and household food security were found to be protective against stunting and severe stunting. Stunting prevalence may vary across space at different scale. For this, it's important that nutrition studies and, more importantly, control interventions take into account this spatial heterogeneity in the distribution of nutritional deficits and their underlying associated factors. The findings of this study also indicated that interventions integrating household food insecurity in nutrition programs in the district might help to avert the burden of stunting.

PREDICTING RELATIVE RISK OF INVASION BY SALTCEDAR AND MUD SNAILS IN RIVER NETWORKS UNDER DIFFERENT SCENARIOS OF CLIMATE CHANGE AND DAM OPERATIONS IN THE WESTERN UNITED STATES

EPA Science Inventory

This synthetic, multi-scale approach will generate a sequence of spatially explicit maps that will provide science guidance to support strategic decision-making regarding the spatially-distributed risk of, and possible adaptation to, the spread of invasive species at local to ...

The spatial distribution of threats to plant species with extremely small populations

NASA Astrophysics Data System (ADS)

Wang, Chunjing; Zhang, Jing; Wan, Jizhong; Qu, Hong; Mu, Xianyun; Zhang, Zhixiang

2017-03-01

Many biological conservationists take actions to conserve plant species with extremely small populations (PSESP) in China; however, there have been few studies on the spatial distribution of threats to PSESP. Hence, we selected distribution data of PSESP and made a map of the spatial distribution of threats to PSESP in China. First, we used the weight assignment method to evaluate the threat risk to PSESP at both country and county scales. Second, we used a geographic information system to map the spatial distribution of threats to PSESP, and explored the threat factors based on linear regression analysis. Finally, we suggested some effective conservation options. We found that the PSESP with high values of protection, such as the plants with high scientific research values and ornamental plants, were threatened by over-exploitation and utilization, habitat fragmentation, and a small sized wild population in broad-leaved forests and bush fallows. We also identified some risk hotspots for PSESP in China. Regions with low elevation should be given priority for ex- and in-situ conservation. Moreover, climate change should be considered for conservation of PSESP. To avoid intensive over-exploitation or utilization and habitat fragmentation, in-situ conservation should be practiced in regions with high temperatures and low temperature seasonality, particularly in the high risk hotspots for PSESP that we proposed. Ex-situ conservation should be applied in these same regions, and over-exploitation and utilization of natural resources should be prevented. It is our goal to apply the concept of PSESP to the global scale in the future.

Mapping populations at risk: improving spatial demographic data for infectious disease modeling and metric derivation

PubMed Central

2012-01-01

The use of Global Positioning Systems (GPS) and Geographical Information Systems (GIS) in disease surveys and reporting is becoming increasingly routine, enabling a better understanding of spatial epidemiology and the improvement of surveillance and control strategies. In turn, the greater availability of spatially referenced epidemiological data is driving the rapid expansion of disease mapping and spatial modeling methods, which are becoming increasingly detailed and sophisticated, with rigorous handling of uncertainties. This expansion has, however, not been matched by advancements in the development of spatial datasets of human population distribution that accompany disease maps or spatial models. Where risks are heterogeneous across population groups or space or dependent on transmission between individuals, spatial data on human population distributions and demographic structures are required to estimate infectious disease risks, burdens, and dynamics. The disease impact in terms of morbidity, mortality, and speed of spread varies substantially with demographic profiles, so that identifying the most exposed or affected populations becomes a key aspect of planning and targeting interventions. Subnational breakdowns of population counts by age and sex are routinely collected during national censuses and maintained in finer detail within microcensus data. Moreover, demographic and health surveys continue to collect representative and contemporary samples from clusters of communities in low-income countries where census data may be less detailed and not collected regularly. Together, these freely available datasets form a rich resource for quantifying and understanding the spatial variations in the sizes and distributions of those most at risk of disease in low income regions, yet at present, they remain unconnected data scattered across national statistical offices and websites. In this paper we discuss the deficiencies of existing spatial population datasets and their limitations on epidemiological analyses. We review sources of detailed, contemporary, freely available and relevant spatial demographic data focusing on low income regions where such data are often sparse and highlight the value of incorporating these through a set of examples of their application in disease studies. Moreover, the importance of acknowledging, measuring, and accounting for uncertainty in spatial demographic datasets is outlined. Finally, a strategy for building an open-access database of spatial demographic data that is tailored to epidemiological applications is put forward. PMID:22591595

Role of Environmental Factors in Shaping Spatial Distribution of Salmonella enterica Serovar Typhi, Fiji.

PubMed

de Alwis, Ruklanthi; Watson, Conall; Nikolay, Birgit; Lowry, John H; Thieu, Nga Tran Vu; Van, Tan Trinh; Ngoc, Dung Tran Thi; Rawalai, Kitione; Taufa, Mere; Coriakula, Jerimaia; Lau, Colleen L; Nilles, Eric J; Edmunds, W John; Kama, Mike; Baker, Stephen; Cano, Jorge

2018-02-01

Fiji recently experienced a sharp increase in reported typhoid fever cases. To investigate geographic distribution and environmental risk factors associated with Salmonella enterica serovar Typhi infection, we conducted a cross-sectional cluster survey with associated serologic testing for Vi capsular antigen-specific antibodies (a marker for exposure to Salmonella Typhi in Fiji in 2013. Hotspots with high seroprevalence of Vi-specific antibodies were identified in northeastern mainland Fiji. Risk for Vi seropositivity increased with increased annual rainfall (odds ratio [OR] 1.26/quintile increase, 95% CI 1.12-1.42), and decreased with increased distance from major rivers and creeks (OR 0.89/km increase, 95% CI 0.80-0.99) and distance to modeled flood-risk areas (OR 0.80/quintile increase, 95% CI 0.69-0.92) after being adjusted for age, typhoid fever vaccination, and home toilet type. Risk for exposure to Salmonella Typhi and its spatial distribution in Fiji are driven by environmental factors. Our findings can directly affect typhoid fever control efforts in Fiji.

An analysis of spatial and socio-economic determinants of tuberculosis in Hermosillo, Mexico, 2000-2006.

PubMed

Alvarez-Hernández, G; Lara-Valencia, F; Reyes-Castro, P A; Rascón-Pacheco, R A

2010-06-01

The city of Hermosillo, in Northwest Mexico, has a higher incidence of tuberculosis (TB) than the national average. However, the intra-urban TB distribution, which could limit the effectiveness of preventive strategies and control, is unknown. Using geographic information systems (GIS) and spatial analysis, we characterized the geographical distribution of TB by basic geostatistical area (BGA), and compared it with a social deprivation index. Univariate and bivariate techniques were used to detect risk areas. Globally, TB in the city of Hermosillo is not spatially auto-correlated, but local clusters with high incidence and mortality rates were identified in the northwest, central-east and southwest sections of the city. BGAs with high social deprivation had an excess risk of TB. GIS and spatial analysis are useful tools to detect high TB risk areas in the city of Hermosillo. Such areas may be vulnerable due to low socio-economic status. The study of small geographical areas in urban settings similar to Hermosillo could indicate the best course of action to be taken for TB prevention and control.

Opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks

NASA Astrophysics Data System (ADS)

Gaitan, S.; ten Veldhuis, J. A. E.

2015-06-01

Cities worldwide are challenged by increasing urban flood risks. Precise and realistic measures are required to reduce flooding impacts. However, currently implemented sewer and topographic models do not provide realistic predictions of local flooding occurrence during heavy rain events. Assessing other factors such as spatially distributed rainfall, socioeconomic characteristics, and social sensing, may help to explain probability and impacts of urban flooding. Several spatial datasets have been recently made available in the Netherlands, including rainfall-related incident reports made by citizens, spatially distributed rain depths, semidistributed socioeconomic information, and buildings age. Inspecting the potential of this data to explain the occurrence of rainfall related incidents has not been done yet. Multivariate analysis tools for describing communities and environmental patterns have been previously developed and used in the field of study of ecology. The objective of this paper is to outline opportunities for these tools to explore urban flooding risks patterns in the mentioned datasets. To that end, a cluster analysis is performed. Results indicate that incidence of rainfall-related impacts is higher in areas characterized by older infrastructure and higher population density.

Essays on the Impacts of Geography and Institutions on Access to Energy and Public Infrastructure Services

NASA Astrophysics Data System (ADS)

Archibong, Belinda

While previous literature has emphasized the importance of energy and public infrastructure services for economic development, questions surrounding the implications of unequal spatial distribution in access to these resources remain, particularly in the developing country context. This dissertation provides evidence on the nature, origins and implications of this distribution uniting three strands of research from the development and political economy, regional science and energy economics fields. The dissertation unites three papers on the nature of spatial inequality of access to energy and infrastructure with further implications for conflict risk , the historical institutional and biogeographical determinants of current distribution of access to energy and public infrastructure services and the response of households to fuel price changes over time. Chapter 2 uses a novel survey dataset to provide evidence for spatial clustering of public infrastructure non-functionality at schools by geopolitical zone in Nigeria with further implications for armed conflict risk in the region. Chapter 3 investigates the drivers of the results in chapter 2, exploiting variation in the spatial distribution of precolonial institutions and geography in the region, to provide evidence for the long-term impacts of these factors on current heterogeneity of access to public services. Chapter 4 addresses the policy implications of energy access, providing the first multi-year evidence on firewood demand elasticities in India, using the spatial variation in prices for estimation.

REVIEW OF SIMULATION METHODS FOR SPATIALLY-EXPLICIT POPULATION-LEVEL RISK ASSESSMENT

EPA Science Inventory

Factors that significantly impact population dynamics, such as resource availability and exposure to stressors, frequently vary over space and thereby determine the heterogeneous spatial distributions of organisms. Considering this fact, the US Environmental Protection Agency's ...

Spatial analysis for the identification of risk areas for schistosomiasis mansoni in the State of Sergipe, Brazil, 2005-2014.

PubMed

Santos, Allan Dantas Dos; Lima, Ana Caroline Rodrigues; Santos, Márcio Bezerra; Alves, José Antônio Barreto; Góes, Marco Aurélio de Oliveira; Nunes, Marco Antônio Prado; Sá, Sidney Lourdes César Souza; Araújo, Karina Conceição Gomes Machado de

2016-01-01

Schistosomiasis is a parasitic infectious disease with a worldwide prevalence. The objective of this work is to identify risk areas for schistosomiasis mansoni transmission in the State of Sergipe, Brazil, during the period from 2005 to 2014. We conducted an epidemiological study with secondary data from the Information System Control Program of Schistosomiasis [Sistema de Informação do Programa de Controle da Esquistossomose (SISPCE)]. Temporal trends were analyzed to obtain the annual percentage change (APC) in the rates of annual prevalence. In addition to the description of general indicators of the disease, the spatial analysis was descriptive, by means of the estimator of intensity kernel, and showed spatial dependence by indicators of global Moran (I) and Local Index of Spatial Association (LISA). Thematic maps of spatial distribution were made, identifying priority intervention areas in need of healthcare. There were 78,663 cases of schistosomiasis, with an average of 8.7% positivity recorded; 79.8% of the cases were treated, and Sergipe showed a decreasing positive trend (APC: -2.78). There was the presence of spatial autocorrelation and a significant global Moran index (I = 0.19; p-value = 0.03). We identified clusters of high-risk areas, mainly located in the northeast and southcentral of the state, which each had equally high infection rates. There was a decreasing positive trend of schistosomiasis in Sergipe. Spatial analysis identified the geographic distribution of risk and allowed the definition of priority areas for the maintenance and intensification of control interventions.

Spatial analysis of dengue fever in Guangdong Province, China, 2001-2006.

PubMed

Liu, Chunxiao; Liu, Qiyong; Lin, Hualiang; Xin, Benqiang; Nie, Jun

2014-01-01

Guangdong Province is the area most seriously affected by dengue fever in China. In this study, we describe the spatial distribution of dengue fever in Guangdong Province from 2001 to 2006 with the objective of informing priority areas for public health planning and resource allocation. Annualized incidence at a county level was calculated and mapped to show crude incidence, excess hazard, and spatial smoothed incidence. Geographic information system-based spatial scan statistics was conducted to detect the spatial distribution pattern of dengue fever incidence at the county level. Spatial scan cluster analyses suggested that counties around Guangzhou City and Chaoshan Region were at increased risk for dengue fever (P < .01). Some spatial clusters of dengue fever were found in Guangdong Province, which allowed intervention measures to be targeted for maximum effect.

Spatial Distribution, Sources Apportionment and Health Risk of Metals in Topsoil in Beijing, China.

PubMed

Sun, Chunyuan; Zhao, Wenji; Zhang, Qianzhong; Yu, Xue; Zheng, Xiaoxia; Zhao, Jiayin; Lv, Ming

2016-07-20

In order to acquire the pollution feature and regularities of distribution of metals in the topsoil within the sixth ring road in Beijing, a total of 46 soil samples were collected, and the concentrations of twelve elements (Nickel, Ni, Lithium, Li, Vanadium, V, Cobalt, Co, Barium, Ba, Strontium, Sr, Chrome, Cr, Molybdenum, Mo, Copper, Cu, Cadmium, Cd, Zinc, Zn, Lead, Pb) were analyzed. Geostatistics and multivariate statistics were conducted to identify spatial distribution characteristics and sources. In addition, the health risk of the analyzed heavy metals to humans (adult) was evaluated by an U.S. Environmental Protection Agency health risk assessment model. The results indicate that these metals have notable variation in spatial scale. The concentration of Cr was high in the west and low in the east, while that of Mo was high in the north and low in the south. High concentrations of Cu, Cd, Zn, and Pb were found in the central part of the city. The average enrichment degree of Cd is 5.94, reaching the standard of significant enrichment. The accumulation of Cr, Mo, Cu, Cd, Zn, and Pb is influenced by anthropogenic activity, including vehicle exhaustion, coal burning, and industrial processes. Health risk assessment shows that both non-carcinogenic and carcinogenic risks of selected heavy metals are within the safety standard and the rank of the carcinogenic risk of the four heavy metals is Cr > Co > Ni > Cd.

Spatial Distribution, Sources Apportionment and Health Risk of Metals in Topsoil in Beijing, China

PubMed Central

Sun, Chunyuan; Zhao, Wenji; Zhang, Qianzhong; Yu, Xue; Zheng, Xiaoxia; Zhao, Jiayin; Lv, Ming

2016-01-01

In order to acquire the pollution feature and regularities of distribution of metals in the topsoil within the sixth ring road in Beijing, a total of 46 soil samples were collected, and the concentrations of twelve elements (Nickel, Ni, Lithium, Li, Vanadium, V, Cobalt, Co, Barium, Ba, Strontium, Sr, Chrome, Cr, Molybdenum, Mo, Copper, Cu, Cadmium, Cd, Zinc, Zn, Lead, Pb) were analyzed. Geostatistics and multivariate statistics were conducted to identify spatial distribution characteristics and sources. In addition, the health risk of the analyzed heavy metals to humans (adult) was evaluated by an U.S. Environmental Protection Agency health risk assessment model. The results indicate that these metals have notable variation in spatial scale. The concentration of Cr was high in the west and low in the east, while that of Mo was high in the north and low in the south. High concentrations of Cu, Cd, Zn, and Pb were found in the central part of the city. The average enrichment degree of Cd is 5.94, reaching the standard of significant enrichment. The accumulation of Cr, Mo, Cu, Cd, Zn, and Pb is influenced by anthropogenic activity, including vehicle exhaustion, coal burning, and industrial processes. Health risk assessment shows that both non-carcinogenic and carcinogenic risks of selected heavy metals are within the safety standard and the rank of the carcinogenic risk of the four heavy metals is Cr > Co > Ni > Cd. PMID:27447657

Spatiotemporal analysis of the agricultural drought risk in Heilongjiang Province, China

NASA Astrophysics Data System (ADS)

Pei, Wei; Fu, Qiang; Liu, Dong; Li, Tian-xiao; Cheng, Kun; Cui, Song

2017-06-01

Droughts are natural disasters that pose significant threats to agricultural production as well as living conditions, and a spatial-temporal difference analysis of agricultural drought risk can help determine the spatial distribution and temporal variation of the drought risk within a region. Moreover, this type of analysis can provide a theoretical basis for the identification, prevention, and mitigation of drought disasters. In this study, the overall dispersion and local aggregation of projection points were based on research by Friedman and Tukey (IEEE Trans on Computer 23:881-890, 1974). In this work, high-dimensional samples were clustered by cluster analysis. The clustering results were represented by the clustering matrix, which determined the local density in the projection index. This method avoids the problem of determining a cutoff radius. An improved projection pursuit model is proposed that combines cluster analysis and the projection pursuit model, which offer advantages for classification and assessment, respectively. The improved model was applied to analyze the agricultural drought risk of 13 cities in Heilongjiang Province over 6 years (2004, 2006, 2008, 2010, 2012, and 2014). The risk of an agricultural drought disaster was characterized by 14 indicators and the following four aspects: hazard, exposure, sensitivity, and resistance capacity. The spatial distribution and temporal variation characteristics of the agricultural drought risk in Heilongjiang Province were analyzed. The spatial distribution results indicated that Suihua, Qigihar, Daqing, Harbin, and Jiamusi are located in high-risk areas, Daxing'anling and Yichun are located in low-risk areas, and the differences among the regions were primarily caused by the aspects exposure and resistance capacity. The temporal variation results indicated that the risk of agricultural drought in most areas presented an initially increasing and then decreasing trend. A higher value for the exposure aspect increased the risk of drought, whereas a higher value for the resistance capacity aspect reduced the risk of drought. Over the long term, the exposure level of the region presented limited increases, whereas the resistance capacity presented considerable increases. Therefore, the risk of agricultural drought in Heilongjiang Province will continue to exhibit a decreasing trend.

Spatiotemporal Risk of Bacillary Dysentery and Sensitivity to Meteorological Factors in Hunan Province, China.

PubMed

Xu, Chengdong; Xiao, Gexin; Wang, Jinfeng; Zhang, Xiangxue; Liang, Jinjun

2017-12-29

Bacillary dysentery remains a public health concern in the world. Hunan Province is one of the provinces having the highest risk of bacillary dysentery in China, however, the spatial-temporal distribution, variation of bacillary dysentery and sensitivity to meteorological factors in there are unclear. In this paper, a Bayesian space-time hierarchical model (BSTHM) was used to detect space-time variation, and effects of meteorological factors between 2010 and 2015. The risk of bacillary dysentery showed apparent spatial-temporal heterogeneity. The highest risk occurred in the summer season. Economically undeveloped mountainous areas in the west and south of the province had the highest incidence rates. Twenty three (18.9%) and 20 (16.4%) counties were identified as hot and cold spots, respectively. Among the hotspots, 11 counties (47.8%) exhibited a rapidly decreasing trend, suggesting they may become low-risk areas in the future. Of the cold spot counties, six (30%) showed a slowly decreasing trend, and may have a higher risk in the future. Among meteorological factors, air temperature, relative humidity, and wind speed all played a significant role in the spatial-temporal distribution of bacillary dysentery risk. These findings can contribute to the implementation of an early warning system for controlling and preventing bacillary dysentery.

Spatiotemporal Risk of Bacillary Dysentery and Sensitivity to Meteorological Factors in Hunan Province, China

PubMed Central

Xu, Chengdong; Xiao, Gexin; Wang, Jinfeng; Zhang, Xiangxue; Liang, Jinjun

2017-01-01

Bacillary dysentery remains a public health concern in the world. Hunan Province is one of the provinces having the highest risk of bacillary dysentery in China, however, the spatial-temporal distribution, variation of bacillary dysentery and sensitivity to meteorological factors in there are unclear. In this paper, a Bayesian space-time hierarchical model (BSTHM) was used to detect space-time variation, and effects of meteorological factors between 2010 and 2015. The risk of bacillary dysentery showed apparent spatial-temporal heterogeneity. The highest risk occurred in the summer season. Economically undeveloped mountainous areas in the west and south of the province had the highest incidence rates. Twenty three (18.9%) and 20 (16.4%) counties were identified as hot and cold spots, respectively. Among the hotspots, 11 counties (47.8%) exhibited a rapidly decreasing trend, suggesting they may become low-risk areas in the future. Of the cold spot counties, six (30%) showed a slowly decreasing trend, and may have a higher risk in the future. Among meteorological factors, air temperature, relative humidity, and wind speed all played a significant role in the spatial-temporal distribution of bacillary dysentery risk. These findings can contribute to the implementation of an early warning system for controlling and preventing bacillary dysentery. PMID:29286297

Associations between residence at birth and mental health disorders: a spatial analysis of retrospective cohort data.

PubMed

Hoffman, Kate; Aschengrau, Ann; Webster, Thomas F; Bartell, Scott M; Vieira, Verónica M

2015-07-21

Mental health disorders impact approximately one in four US adults. While their causes are likely multifactorial, prior research has linked the risk of certain mental health disorders to prenatal and early childhood environmental exposures, motivating a spatial analysis to determine whether risk varies by birth location. We investigated the spatial associations between residence at birth and odds of depression, bipolar disorder, and post-traumatic stress disorder (PTSD) in a retrospective cohort (Cape Cod, Massachusetts, 1969-1983) using generalized additive models to simultaneously smooth location and adjust for confounders. Birth location served as a surrogate for prenatal exposure to the combination of social and environmental factors related to the development of mental illness. We predicted crude and adjusted odds ratios (aOR) for each outcome across the study area. The results were mapped to identify areas of increased risk. We observed spatial variation in the crude odds ratios of depression that was still present even after accounting for spatial confounding due to geographic differences in the distribution of known risk factors (aOR range: 0.61-3.07, P = 0.03). Similar geographic patterns were seen for the crude odds of PTSD; however, these patterns were no longer present in the adjusted analysis (aOR range: 0.49-1.36, P = 0.79), with family history of mental illness most notably influencing the geographic patterns. Analyses of the odds of bipolar disorder did not show any meaningful spatial variation (aOR range: 0.58-1.17, P = 0.82). Spatial associations exist between residence at birth and odds of PTSD and depression, but much of this variation can be explained by the geographic distributions of available risk factors. However, these risk factors did not account for all the variation observed with depression, suggesting that other social and environmental factors within our study area need further investigation.

Using spatial mark-recapture for conservation monitoring of grizzly bear populations in Alberta.

PubMed

Boulanger, John; Nielsen, Scott E; Stenhouse, Gordon B

2018-03-26

One of the challenges in conservation is determining patterns and responses in population density and distribution as it relates to habitat and changes in anthropogenic activities. We applied spatially explicit capture recapture (SECR) methods, combined with density surface modelling from five grizzly bear (Ursus arctos) management areas (BMAs) in Alberta, Canada, to assess SECR methods and to explore factors influencing bear distribution. Here we used models of grizzly bear habitat and mortality risk to test local density associations using density surface modelling. Results demonstrated BMA-specific factors influenced density, as well as the effects of habitat and topography on detections and movements of bears. Estimates from SECR were similar to those from closed population models and telemetry data, but with similar or higher levels of precision. Habitat was most associated with areas of higher bear density in the north, whereas mortality risk was most associated (negatively) with density of bears in the south. Comparisons of the distribution of mortality risk and habitat revealed differences by BMA that in turn influenced local abundance of bears. Combining SECR methods with density surface modelling increases the resolution of mark-recapture methods by directly inferring the effect of spatial factors on regulating local densities of animals.

Spatial analysis to identify hotspots of prevalence of schizophrenia.

PubMed

Moreno, Berta; García-Alonso, Carlos R; Negrín Hernández, Miguel A; Torres-González, Francisco; Salvador-Carulla, Luis

2008-10-01

The geographical distribution of mental health disorders is useful information for epidemiological research and health services planning. To determine the existence of geographical hotspots with a high prevalence of schizophrenia in a mental health area in Spain. The study included 774 patients with schizophrenia who were users of the community mental health care service in the area of South Granada. Spatial analysis (Kernel estimation) and Bayesian relative risks were used to locate potential hotspots. Availability and accessibility were both rated in each zone and spatial algebra was applied to identify hotspots in a particular zone. The age-corrected prevalence rate of schizophrenia was 2.86 per 1,000 population in the South Granada area. Bayesian analysis showed a relative risk varying from 0.43 to 2.33. The area analysed had a non-uniform spatial distribution of schizophrenia, with one main hotspot (zone S2). This zone had poor accessibility to and availability of mental health services. A municipality-based variation exists in the prevalence of schizophrenia and related disorders in the study area. Spatial analysis techniques are useful tools to analyse the heterogeneous distribution of a variable and to explain genetic/environmental factors in hotspots related with a lack of easy availability of and accessibility to adequate health care services.

Elevation and cholera: an epidemiological spatial analysis of the cholera epidemic in Harare, Zimbabwe, 2008-2009

PubMed Central

2012-01-01

Background In highly populated African urban areas where access to clean water is a challenge, water source contamination is one of the most cited risk factors in a cholera epidemic. During the rainy season, where there is either no sewage disposal or working sewer system, runoff of rains follows the slopes and gets into the lower parts of towns where shallow wells could easily become contaminated by excretes. In cholera endemic areas, spatial information about topographical elevation could help to guide preventive interventions. This study aims to analyze the association between topographic elevation and the distribution of cholera cases in Harare during the cholera epidemic in 2008 and 2009. Methods We developed an ecological study using secondary data. First, we described attack rates by suburb and then calculated rate ratios using whole Harare as reference. We illustrated the average elevation and cholera cases by suburbs using geographical information. Finally, we estimated a generalized linear mixed model (under the assumption of a Poisson distribution) with an Empirical Bayesian approach to model the relation between the risk of cholera and the elevation in meters in Harare. We used a random intercept to allow for spatial correlation of neighboring suburbs. Results This study identifies a spatial pattern of the distribution of cholera cases in the Harare epidemic, characterized by a lower cholera risk in the highest elevation suburbs of Harare. The generalized linear mixed model showed that for each 100 meters of increase in the topographical elevation, the cholera risk was 30% lower with a rate ratio of 0.70 (95% confidence interval=0.66-0.76). Sensitivity analysis confirmed the risk reduction with an overall estimate of the rate ratio between 20% and 40%. Conclusion This study highlights the importance of considering topographical elevation as a geographical and environmental risk factor in order to plan cholera preventive activities linked with water and sanitation in endemic areas. Furthermore, elevation information, among other risk factors, could help to spatially orientate cholera control interventions during an epidemic. PMID:22708576

SPATIAL EXPLICIT POPULATION MODELS FOR RISK ASSESSMENT: COMMON LOONS AND MERCURY AS A CASE STUDY

EPA Science Inventory

Factors that significantly impact population dynamics, such as resource availability and exposure to stressors, frequently vary over space and thereby determine the heterogeneous spatial distributions of organisms. Considering this fact, the US Environmental Protection Agency's ...

Accounting for rate instability and spatial patterns in the boundary analysis of cancer mortality maps

PubMed Central

Goovaerts, Pierre

2006-01-01

Boundary analysis of cancer maps may highlight areas where causative exposures change through geographic space, the presence of local populations with distinct cancer incidences, or the impact of different cancer control methods. Too often, such analysis ignores the spatial pattern of incidence or mortality rates and overlooks the fact that rates computed from sparsely populated geographic entities can be very unreliable. This paper proposes a new methodology that accounts for the uncertainty and spatial correlation of rate data in the detection of significant edges between adjacent entities or polygons. Poisson kriging is first used to estimate the risk value and the associated standard error within each polygon, accounting for the population size and the risk semivariogram computed from raw rates. The boundary statistic is then defined as half the absolute difference between kriged risks. Its reference distribution, under the null hypothesis of no boundary, is derived through the generation of multiple realizations of the spatial distribution of cancer risk values. This paper presents three types of neutral models generated using methods of increasing complexity: the common random shuffle of estimated risk values, a spatial re-ordering of these risks, or p-field simulation that accounts for the population size within each polygon. The approach is illustrated using age-adjusted pancreatic cancer mortality rates for white females in 295 US counties of the Northeast (1970–1994). Simulation studies demonstrate that Poisson kriging yields more accurate estimates of the cancer risk and how its value changes between polygons (i.e. boundary statistic), relatively to the use of raw rates or local empirical Bayes smoother. When used in conjunction with spatial neutral models generated by p-field simulation, the boundary analysis based on Poisson kriging estimates minimizes the proportion of type I errors (i.e. edges wrongly declared significant) while the frequency of these errors is predicted well by the p-value of the statistical test. PMID:19023455

Population at risk: using areal interpolation and Twitter messages to create population models for burglaries and robberies

PubMed Central

2018-01-01

ABSTRACT Population at risk of crime varies due to the characteristics of a population as well as the crime generator and attractor places where crime is located. This establishes different crime opportunities for different crimes. However, there are very few efforts of modeling structures that derive spatiotemporal population models to allow accurate assessment of population exposure to crime. This study develops population models to depict the spatial distribution of people who have a heightened crime risk for burglaries and robberies. The data used in the study include: Census data as source data for the existing population, Twitter geo-located data, and locations of schools as ancillary data to redistribute the source data more accurately in the space, and finally gridded population and crime data to evaluate the derived population models. To create the models, a density-weighted areal interpolation technique was used that disaggregates the source data in smaller spatial units considering the spatial distribution of the ancillary data. The models were evaluated with validation data that assess the interpolation error and spatial statistics that examine their relationship with the crime types. Our approach derived population models of a finer resolution that can assist in more precise spatial crime analyses and also provide accurate information about crime rates to the public. PMID:29887766

Use of portable X-ray fluorescence spectroscopy and geostatistics for health risk assessment.

PubMed

Yang, Meng; Wang, Cheng; Yang, Zhao-Ping; Yan, Nan; Li, Feng-Ying; Diao, Yi-Wei; Chen, Min-Dong; Li, Hui-Ming; Wang, Jin-Hua; Qian, Xin

2018-05-30

Laboratory analysis of trace metals using inductively coupled plasma (ICP) spectroscopy is not cost effective, and the complex spatial distribution of soil trace metals makes their spatial analysis and prediction problematic. Thus, for the health risk assessment of exposure to trace metals in soils, portable X-ray fluorescence (PXRF) spectroscopy was used to replace ICP spectroscopy for metal analysis, and robust geostatistical methods were used to identify spatial outliers in trace metal concentrations and to map trace metal distributions. A case study was carried out around an industrial area in Nanjing, China. The results showed that PXRF spectroscopy provided results for trace metal (Cu, Ni, Pb and Zn) levels comparable to ICP spectroscopy. The results of the health risk assessment showed that Ni posed a higher non-carcinogenic risk than Cu, Pb and Zn, indicating a higher priority of concern than the other elements. Sampling locations associated with adverse health effects were identified as 'hotspots', and high-risk areas were delineated from risk maps. These 'hotspots' and high-risk areas were in close proximity to and downwind from petrochemical plants, indicating the dominant role of industrial activities as the major sources of trace metals in soils. The approach used in this study could be adopted as a cost-effective methodology for screening 'hotspots' and priority areas of concern for cost-efficient health risk management. Copyright © 2018 Elsevier Inc. All rights reserved.

Spatial exposure-hazard and landscape models for assessing the impact of GM crops on non-target organisms.

PubMed

Leclerc, Melen; Walker, Emily; Messéan, Antoine; Soubeyrand, Samuel

2018-05-15

The cultivation of Genetically Modified (GM) crops may have substantial impacts on populations of non-target organisms (NTOs) in agroecosystems. These impacts should be assessed at larger spatial scales than the cultivated field, and, as landscape-scale experiments are difficult, if not impossible, modelling approaches are needed to address landscape risk management. We present an original stochastic and spatially explicit modelling framework for assessing the risk at the landscape level. We use techniques from spatial statistics for simulating simplified landscapes made up of (aggregated or non-aggregated) GM fields, neutral fields and NTO's habitat areas. The dispersal of toxic pollen grains is obtained by convolving the emission of GM plants and validated dispersal kernel functions while the locations of exposed individuals are drawn from a point process. By taking into account the adherence of the ambient pollen on plants, the loss of pollen due to climatic events, and, an experimentally-validated mortality-dose function we predict risk maps and provide a distribution giving how the risk varies within exposed individuals in the landscape. Then, we consider the impact of the Bt maize on Inachis io in worst-case scenarii where exposed individuals are located in the vicinity of GM fields and pollen shedding overlaps with larval emergence. We perform a Global Sensitivity Analysis (GSA) to explore numerically how our input parameters influence the risk. Our results confirm the important effects of pollen emission and loss. Most interestingly they highlight that the optimal spatial distribution of GM fields that mitigates the risk depends on our knowledge of the habitats of NTOs, and finally, moderate the influence of the dispersal kernel function. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial distribution and risk assessment of radionuclides in soils around a coal-fired power plant: A case study from the city of Baoji, China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai Lijun; Wei Haiyan; Wang Lingqing

2007-06-15

Coal burning may enhance human exposure to the natural radionuclides that occur around coal-fired power plants (CFPP). In this study, the spatial distribution and hazard assessment of radionuclides found in soils around a CFPP were investigated using statistics, geostatistics, and geographic information system (GIS) techniques. The concentrations of {sup 226}Ra, {sup 232}Th, and {sup 40}K in soils range from 12.54 to 40.18, 38.02 to 72.55, and 498.02 to 1126.98 Bq kg{sup -1}, respectively. Ordinary kriging was carried out to map the spatial patterns of radionuclides, and disjunctive kriging was used to quantify the probability of radium equivalent activity (Ra{sub eq})more » higher than the threshold. The maps show that the spatial variability of the natural radionuclide concentrations in soils was apparent. The results of this study could provide valuable information for risk assessment of environmental pollution and decision support.« less

Spatial distribution and risk assessment of radionuclides in soils around a coal-fired power plant: A case study from the city of Baoji, China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, L.J.; Wei, H.Y.; Wang, L.Q.

2007-06-15

Coal burning may enhance human exposure to the natural radionuclides that occur around coal-fired power plants (CFPP). In this study, the spatial distribution and hazard assessment of radionuclides found in soils around a CFPP were investigated using statistics, geostatistics, and geographic information system (GIS) techniques. The concentrations of Ra-226, Th-232, and K-40 in soils range from 12.54 to 40.18, 38.02 to 72.55, and 498.02 to 1126.98 Bq kg{sup -1}, respectively. Ordinary kriging was carried out to map the spatial patterns of radionuclides, and disjunctive kriging was used to quantify the probability of radium equivalent activity (Ra{sub eq}) higher than themore » threshold. The maps show that the spatial variability of the natural radionuclide concentrations in soils was apparent. The results of this study could provide valuable information for risk assessment of environmental pollution and decision support.« less

Understanding high magnitude flood risk: evidence from the past

NASA Astrophysics Data System (ADS)

MacDonald, N.

2009-04-01

The average length of gauged river flow records in the UK is ~25 years, which presents a problem in determining flood risk for high-magnitude flood events. Severe floods have been recorded in many UK catchments during the past 10 years, increasing the uncertainty in conventional flood risk estimates based on river flow records. Current uncertainty in flood risk has implications for society (insurance costs), individuals (personal vulnerability) and water resource managers (flood/drought risk). An alternative approach is required which can improve current understanding of the flood frequency/magnitude relationship. Historical documentary accounts are now recognised as a valuable resource when considering the flood frequency/magnitude relationship, but little consideration has been given to the temporal and spatial distribution of these records. Building on previous research based on British rivers (urban centre): Ouse (York), Trent (Nottingham), Tay (Perth), Severn (Shrewsbury), Dee (Chester), Great Ouse (Cambridge), Sussex Ouse (Lewes), Thames (Oxford), Tweed (Kelso) and Tyne (Hexham), this work considers the spatial and temporal distribution of historical flooding. The selected sites provide a network covering many of the largest river catchments in Britain, based on urban centres with long detailed documentary flood histories. The chronologies offer an opportunity to assess long-term patterns of flooding, indirectly determining periods of climatic variability and potentially increased geomorphic activity. This research represents the first coherent large scale analysis undertaken of historical multi-catchment flood chronologies, providing an unparalleled network of sites, permitting analysis of the spatial and temporal distribution of historical flood patterns on a national scale.

Evaluating efficiency-equality tradeoffs for mobile source control strategies in an urban area

PubMed Central

Levy, Jonathan I.; Greco, Susan L.; Melly, Steven J.; Mukhi, Neha

2013-01-01

In environmental risk management, there are often interests in maximizing public health benefits (efficiency) and addressing inequality in the distribution of health outcomes. However, both dimensions are not generally considered within a single analytical framework. In this study, we estimate both total population health benefits and changes in quantitative indicators of health inequality for a number of alternative spatial distributions of diesel particulate filter retrofits across half of an urban bus fleet in Boston, Massachusetts. We focus on the impact of emissions controls on primary fine particulate matter (PM2.5) emissions, modeling the effect on PM2.5 concentrations and premature mortality. Given spatial heterogeneity in baseline mortality rates, we apply the Atkinson index and other inequality indicators to quantify changes in the distribution of mortality risk. Across the different spatial distributions of control strategies, the public health benefits varied by more than a factor of two, related to factors such as mileage driven per day, population density near roadways, and baseline mortality rates in exposed populations. Changes in health inequality indicators varied across control strategies, with the subset of optimal strategies considering both efficiency and equality generally robust across different parametric assumptions and inequality indicators. Our analysis demonstrates the viability of formal analytical approaches to jointly address both efficiency and equality in risk assessment, providing a tool for decision-makers who wish to consider both issues. PMID:18793281

Risk avoidance in sympatric large carnivores: reactive or predictive?

PubMed

Broekhuis, Femke; Cozzi, Gabriele; Valeix, Marion; McNutt, John W; Macdonald, David W

2013-09-01

1. Risks of predation or interference competition are major factors shaping the distribution of species. An animal's response to risk can either be reactive, to an immediate risk, or predictive, based on preceding risk or past experiences. The manner in which animals respond to risk is key in understanding avoidance, and hence coexistence, between interacting species. 2. We investigated whether cheetahs (Acinonyx jubatus), known to be affected by predation and competition by lions (Panthera leo) and spotted hyaenas (Crocuta crocuta), respond reactively or predictively to the risks posed by these larger carnivores. 3. We used simultaneous spatial data from Global Positioning System (GPS) radiocollars deployed on all known social groups of cheetahs, lions and spotted hyaenas within a 2700 km(2) study area on the periphery of the Okavango Delta in northern Botswana. The response to risk of encountering lions and spotted hyaenas was explored on three levels: short-term or immediate risk, calculated as the distance to the nearest (contemporaneous) lion or spotted hyaena, long-term risk, calculated as the likelihood of encountering lions and spotted hyaenas based on their cumulative distributions over a 6-month period and habitat-associated risk, quantified by the habitat used by each of the three species. 4. We showed that space and habitat use by cheetahs was similar to that of lions and, to a lesser extent, spotted hyaenas. However, cheetahs avoided immediate risks by positioning themselves further from lions and spotted hyaenas than predicted by a random distribution. 5. Our results suggest that cheetah spatial distribution is a hierarchical process, first driven by resource acquisition and thereafter fine-tuned by predator avoidance; thus suggesting a reactive, rather than a predictive, response to risk. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

Assessment of spatial distribution of soil loss over the upper basin of Miyun reservoir in China based on RS and GIS techniques.

PubMed

Chen, Tao; Niu, Rui-qing; Wang, Yi; Li, Ping-xiang; Zhang, Liang-pei; Du, Bo

2011-08-01

Soil conservation planning often requires estimates of the spatial distribution of soil erosion at a catchment or regional scale. This paper applied the Revised Universal Soil Loss Equation (RUSLE) to investigate the spatial distribution of annual soil loss over the upper basin of Miyun reservoir in China. Among the soil erosion factors, which are rainfall erosivity (R), soil erodibility (K), slope length (L), slope steepness (S), vegetation cover (C), and support practice factor (P), the vegetative cover or C factor, which represents the effects of vegetation canopy and ground covers in reducing soil loss, has been one of the most difficult to estimate over broad geographic areas. In this paper, the C factor was estimated based on back propagation neural network and the results were compared with the values measured in the field. The correlation coefficient (r) obtained was 0.929. Then the C factor and the other factors were used as the input to RUSLE model. By integrating the six factor maps in geographical information system (GIS) through pixel-based computing, the spatial distribution of soil loss over the upper basin of Miyun reservoir was obtained. The results showed that the annual average soil loss for the upper basin of Miyun reservoir was 9.86 t ha(-1) ya(-1) in 2005, and the area of 46.61 km(2) (0.3%) experiences extremely severe erosion risk, which needs suitable conservation measures to be adopted on a priority basis. The spatial distribution of erosion risk classes was 66.9% very low, 21.89% low, 6.18% moderate, 2.89% severe, and 1.84% very severe. Thus, by using RUSLE in a GIS environment, the spatial distribution of water erosion can be obtained and the regions which susceptible to water erosion and need immediate soil conservation planning and application over the upper watershed of Miyun reservoir in China can be identified.

Role of Environmental Factors in Shaping Spatial Distribution of Salmonella enterica Serovar Typhi, Fiji

PubMed Central

Watson, Conall; Nikolay, Birgit; Lowry, John H.; Thieu, Nga Tran Vu; Van, Tan Trinh; Ngoc, Dung Tran Thi; Rawalai, Kitione; Taufa, Mere; Coriakula, Jerimaia; Lau, Colleen L.; Nilles, Eric J.; Edmunds, W. John; Kama, Mike; Baker, Stephen; Cano, Jorge

2018-01-01

Fiji recently experienced a sharp increase in reported typhoid fever cases. To investigate geographic distribution and environmental risk factors associated with Salmonella enterica serovar Typhi infection, we conducted a cross-sectional cluster survey with associated serologic testing for Vi capsular antigen–specific antibodies (a marker for exposure to Salmonella Typhi in Fiji in 2013. Hotspots with high seroprevalence of Vi-specific antibodies were identified in northeastern mainland Fiji. Risk for Vi seropositivity increased with increased annual rainfall (odds ratio [OR] 1.26/quintile increase, 95% CI 1.12–1.42), and decreased with increased distance from major rivers and creeks (OR 0.89/km increase, 95% CI 0.80–0.99) and distance to modeled flood-risk areas (OR 0.80/quintile increase, 95% CI 0.69–0.92) after being adjusted for age, typhoid fever vaccination, and home toilet type. Risk for exposure to Salmonella Typhi and its spatial distribution in Fiji are driven by environmental factors. Our findings can directly affect typhoid fever control efforts in Fiji. PMID:29350150

The spatial optimism model research for the regional land use based on the ecological constraint

NASA Astrophysics Data System (ADS)

XU, K.; Lu, J.; Chi, Y.

2013-12-01

The study focuses on the Yunnan-Guizhou (i.e. Yunnan province and Guizhou province) Plateau in China. Since the Yunnan-Guizhou region consists of closed basins, the land resources suiting for development are in a shortage, and the ecological problems in the area are quite complicated. In such circumstance, in order to get the applicable basins area and distribution, certain spatial optimism model is needed. In this research, Digital Elevation Model (DEM) and land use data are used to get the boundary rules of the basins distribution. Furthermore, natural risks, ecological risks and human-made ecological risks are integrated to be analyzed. Finally, the spatial overlay analysis method is used to model the developable basins area and distribution for industries and urbanization. The study process can be divided into six steps. First, basins and their distribution need to be recognized. In this way, the DEM data is used to extract the geomorphology characteristics. The plaque regions with gradient under eight degrees are selected. Among these regions, the total area of the plaque with the area above 8 km2 is 54,000 km2, 10% of the total area. These regions are selected to the potential application of industries and urbanization. In the later five steps, analyses are aimed at these regions. Secondly, the natural risks are analyzed. The conditions of the earthquake, debris flow and rainstorm and flood are combined to classify the natural risks. Thirdly, the ecological risks are analyzed containing the ecological sensibility and ecosystem service function importance. According to the regional ecologic features, the sensibility containing the soil erosion, acid rain, stony desertification and survive condition factors is derived and classified according to the medium value to get the ecological sensibility partition. The ecosystem service function importance is classified and divided considering the biology variation protection and water conservation factors. The fourth step is the man-made ecological risks analysis. The mineral resources exploitation, forest resources developing, farming, tourism, industrialization and urbanization are integrated to derive the potential ecological risks made by human activities. The risks weight are given using the expert marking method, Then the man-made ecological risks are classified and divided among the regions. In the fifth step, the comprehensive ecological controlling divisions are obtained based on the above factors classification. At last, the applicable regions and distribution are derived using the spatial overlay analysis removing the higher ecological risks area and considering the land use status. In conclusion, based on the above comprehensive analyses, the applicable basins area are 2,575 km2 and 1,011 km2 respectively for the Yunnan province and Guizhou province. The amount is less than 1% of the perspective province total area focusing on the central part of the two provinces.

Relations between Spatial Distribution, Social Affiliations and Dominance Hierarchy in a Semi-Free Mandrill Population

PubMed Central

Naud, Alexandre; Chailleux, Eloise; Kestens, Yan; Bret, Céline; Desjardins, Dominic; Petit, Odile; Ngoubangoye, Barthélémy; Sueur, Cédric

2016-01-01

Although there exist advantages to group-living in comparison to a solitary lifestyle, costs and gains of group-living may be unequally distributed among group members. Predation risk, vigilance levels and food intake may be unevenly distributed across group spatial geometry and certain within-group spatial positions may be more or less advantageous depending on the spatial distribution of these factors. In species characterized with dominance hierarchy, high-ranking individuals are commonly observed in advantageous spatial position. However, in complex social systems, individuals can develop affiliative relationships that may balance the effect of dominance relationships in individual's spatial distribution. The objective of the present study is to investigate how the group spatial distribution of a semi-free ranging colony of Mandrills relates to its social organization. Using spatial observations in an area surrounding the feeding zone, we tested the three following hypothesis: (1) does dominance hierarchy explain being observed in proximity or far from a food patch? (2) Do affiliative associations also explain being observed in proximity or far from a food patch? (3) Do the differences in rank in the group hierarchy explain being co-observed in proximity of a food patch? Our results showed that high-ranking individuals were more observed in proximity of the feeding zone while low-ranking individuals were more observed at the boundaries of the observation area. Furthermore, we observed that affiliative relationships were also associated with individual spatial distributions and explain more of the total variance of the spatial distribution in comparison with dominance hierarchy. Finally, we found that individuals observed at a same moment in proximity of the feeding zone were more likely to be distant in the hierarchy while controlling for maternal kinship, age and sex similarity. This study brings some elements about how affiliative networks and dominance hierarchy are related to spatial positions in primates. PMID:27199845

Relations between Spatial Distribution, Social Affiliations and Dominance Hierarchy in a Semi-Free Mandrill Population.

PubMed

Naud, Alexandre; Chailleux, Eloise; Kestens, Yan; Bret, Céline; Desjardins, Dominic; Petit, Odile; Ngoubangoye, Barthélémy; Sueur, Cédric

2016-01-01

Although there exist advantages to group-living in comparison to a solitary lifestyle, costs and gains of group-living may be unequally distributed among group members. Predation risk, vigilance levels and food intake may be unevenly distributed across group spatial geometry and certain within-group spatial positions may be more or less advantageous depending on the spatial distribution of these factors. In species characterized with dominance hierarchy, high-ranking individuals are commonly observed in advantageous spatial position. However, in complex social systems, individuals can develop affiliative relationships that may balance the effect of dominance relationships in individual's spatial distribution. The objective of the present study is to investigate how the group spatial distribution of a semi-free ranging colony of Mandrills relates to its social organization. Using spatial observations in an area surrounding the feeding zone, we tested the three following hypothesis: (1) does dominance hierarchy explain being observed in proximity or far from a food patch? (2) Do affiliative associations also explain being observed in proximity or far from a food patch? (3) Do the differences in rank in the group hierarchy explain being co-observed in proximity of a food patch? Our results showed that high-ranking individuals were more observed in proximity of the feeding zone while low-ranking individuals were more observed at the boundaries of the observation area. Furthermore, we observed that affiliative relationships were also associated with individual spatial distributions and explain more of the total variance of the spatial distribution in comparison with dominance hierarchy. Finally, we found that individuals observed at a same moment in proximity of the feeding zone were more likely to be distant in the hierarchy while controlling for maternal kinship, age and sex similarity. This study brings some elements about how affiliative networks and dominance hierarchy are related to spatial positions in primates.

Spatial Patterns and Impacts of Environmental and Climatic Factors on Canine Sinonasal Aspergillosis in Northern California

PubMed Central

Magro, Monise; Sykes, Jane; Vishkautsan, Polina; Martínez-López, Beatriz

2017-01-01

Sinonasal aspergillosis (SNA) causes chronic nasal discharge in dogs and has a worldwide distribution, although most reports of SNA in North America originate from the western USA. SNA is mainly caused by Aspergillus fumigatus, a ubiquitous saprophytic filamentous fungus. Infection is thought to follow inhalation of spores. SNA is a disease of the nasal cavity and/or sinuses with variable degrees of local invasion and destruction. While some host factors appear to predispose to SNA (such as belonging to a dolichocephalic breed), environmental risk factors have been scarcely studied. Because A. fumigatus is also the main cause of invasive aspergillosis in humans, unraveling the distribution and the environmental and climatic risk factors for this agent in dogs would be of great benefit for public health studies, advancing understanding of both distribution and risk factors in humans. In this study, we reviewed electronic medical records of 250 dogs diagnosed with SNA between 1990 and 2014 at the University of California Davis Veterinary Medical Teaching Hospital (VMTH). A 145-mile radius catchment area around the VMTH was selected. Data were aggregated by zip code and incorporated into a multivariate logistic regression model. The logistic regression model was compared to an autologistic regression model to evaluate the effect of spatial autocorrelation. Traffic density, active composting sites, and environmental and climatic factors related with wind and temperature were significantly associated with increase in disease occurrence in dogs. Results provide valuable information about the risk factors and spatial distribution of SNA in dogs in Northern California. Our ultimate goal is to utilize the results to investigate risk-based interventions, promote awareness, and serve as a model for further studies of aspergillosis in humans. PMID:28717638

Spatial Patterns and Impacts of Environmental and Climatic Factors on Canine Sinonasal Aspergillosis in Northern California.

PubMed

Magro, Monise; Sykes, Jane; Vishkautsan, Polina; Martínez-López, Beatriz

2017-01-01

Sinonasal aspergillosis (SNA) causes chronic nasal discharge in dogs and has a worldwide distribution, although most reports of SNA in North America originate from the western USA. SNA is mainly caused by Aspergillus fumigatus , a ubiquitous saprophytic filamentous fungus. Infection is thought to follow inhalation of spores. SNA is a disease of the nasal cavity and/or sinuses with variable degrees of local invasion and destruction. While some host factors appear to predispose to SNA (such as belonging to a dolichocephalic breed), environmental risk factors have been scarcely studied. Because A. fumigatus is also the main cause of invasive aspergillosis in humans, unraveling the distribution and the environmental and climatic risk factors for this agent in dogs would be of great benefit for public health studies, advancing understanding of both distribution and risk factors in humans. In this study, we reviewed electronic medical records of 250 dogs diagnosed with SNA between 1990 and 2014 at the University of California Davis Veterinary Medical Teaching Hospital (VMTH). A 145-mile radius catchment area around the VMTH was selected. Data were aggregated by zip code and incorporated into a multivariate logistic regression model. The logistic regression model was compared to an autologistic regression model to evaluate the effect of spatial autocorrelation. Traffic density, active composting sites, and environmental and climatic factors related with wind and temperature were significantly associated with increase in disease occurrence in dogs. Results provide valuable information about the risk factors and spatial distribution of SNA in dogs in Northern California. Our ultimate goal is to utilize the results to investigate risk-based interventions, promote awareness, and serve as a model for further studies of aspergillosis in humans.

Long-term impact of the World Bank Loan Project for schistosomiasis control: a comparison of the spatial distribution of schistosomiasis risk in China.

PubMed

Zhang, Zhijie; Zhu, Rong; Ward, Michael P; Xu, Wanghong; Zhang, Lijuan; Guo, Jiagang; Zhao, Fei; Jiang, Qingwu

2012-01-01

The World Bank Loan Project (WBLP) for controlling schistosomiasis in China was implemented during 1992-2001. Its short-term impact has been assessed from non-spatial perspective, but its long-term impact remains unclear and a spatial evaluation has not previously been conducted. Here we compared the spatial distribution of schistosomiasis risk using national datasets in the lake and marshland regions from 1999-2001 and 2007-2008 to evaluate the long-term impact of WBLP strategy on China's schistosomiasis burden. A hierarchical Poisson regression model was developed in a Bayesian framework with spatially correlated and uncorrelated heterogeneities at the county-level, modeled using a conditional autoregressive prior structure and a spatially unstructured Gaussian distribution, respectively. There were two important findings from this study. The WBLP strategy was found to have a good short-term impact on schistosomiasis control, but its long-term impact was not ideal. It has successfully reduced the morbidity of schistosomiasis to a low level, but can not contribute further to China's schistosomiasis control because of the current low endemic level. A second finding is that the WBLP strategy could not effectively compress the spatial distribution of schistosomiasis risk. To achieve further reductions in schistosomiasis-affected areas, and for sustainable control, focusing on the intermediate host snail should become the next step to interrupt schistosomiasis transmission within the two most affected regions surrounding the Dongting and Poyang Lakes. Furthermore, in the lower reaches of the Yangtze River, the WBLP's morbidity control strategy may need to continue for some time until snails in the upriver provinces have been well controlled. It is difficult to further reduce morbidity due to schistosomiasis using a chemotherapy-based control strategy in the lake and marshland regions of China because of the current low endemic levels of infection. The future control strategy for schistosomiasis should instead focus on a snail-based integrated control strategy to maintain the program achievements and sustainably reduce the burden of schistosomiasis in China.

The effects of spatial population dataset choice on estimates of population at risk of disease

PubMed Central

2011-01-01

Background The spatial modeling of infectious disease distributions and dynamics is increasingly being undertaken for health services planning and disease control monitoring, implementation, and evaluation. Where risks are heterogeneous in space or dependent on person-to-person transmission, spatial data on human population distributions are required to estimate infectious disease risks, burdens, and dynamics. Several different modeled human population distribution datasets are available and widely used, but the disparities among them and the implications for enumerating disease burdens and populations at risk have not been considered systematically. Here, we quantify some of these effects using global estimates of populations at risk (PAR) of P. falciparum malaria as an example. Methods The recent construction of a global map of P. falciparum malaria endemicity enabled the testing of different gridded population datasets for providing estimates of PAR by endemicity class. The estimated population numbers within each class were calculated for each country using four different global gridded human population datasets: GRUMP (~1 km spatial resolution), LandScan (~1 km), UNEP Global Population Databases (~5 km), and GPW3 (~5 km). More detailed assessments of PAR variation and accuracy were conducted for three African countries where census data were available at a higher administrative-unit level than used by any of the four gridded population datasets. Results The estimates of PAR based on the datasets varied by more than 10 million people for some countries, even accounting for the fact that estimates of population totals made by different agencies are used to correct national totals in these datasets and can vary by more than 5% for many low-income countries. In many cases, these variations in PAR estimates comprised more than 10% of the total national population. The detailed country-level assessments suggested that none of the datasets was consistently more accurate than the others in estimating PAR. The sizes of such differences among modeled human populations were related to variations in the methods, input resolution, and date of the census data underlying each dataset. Data quality varied from country to country within the spatial population datasets. Conclusions Detailed, highly spatially resolved human population data are an essential resource for planning health service delivery for disease control, for the spatial modeling of epidemics, and for decision-making processes related to public health. However, our results highlight that for the low-income regions of the world where disease burden is greatest, existing datasets display substantial variations in estimated population distributions, resulting in uncertainty in disease assessments that utilize them. Increased efforts are required to gather contemporary and spatially detailed demographic data to reduce this uncertainty, particularly in Africa, and to develop population distribution modeling methods that match the rigor, sophistication, and ability to handle uncertainty of contemporary disease mapping and spread modeling. In the meantime, studies that utilize a particular spatial population dataset need to acknowledge the uncertainties inherent within them and consider how the methods and data that comprise each will affect conclusions. PMID:21299885

Integrated drought risk assessment of multi-hazard-affected bodies based on copulas in the Taoerhe Basin, China

NASA Astrophysics Data System (ADS)

Wang, Rui; Zhang, Jiquan; Guo, Enliang; Alu, Si; Li, Danjun; Ha, Si; Dong, Zhenhua

2018-02-01

Along with global warming, drought disasters are occurring more frequently and are seriously affecting normal life and food security in China. Drought risk assessments are necessary to provide support for local governments. This study aimed to establish an integrated drought risk model based on the relation curve of drought joint probabilities and drought losses of multi-hazard-affected bodies. First, drought characteristics, including duration and severity, were classified using the 1953-2010 precipitation anomaly in the Taoerhe Basin based on run theory, and their marginal distributions were identified by exponential and Gamma distributions, respectively. Then, drought duration and severity were related to construct a joint probability distribution based on the copula function. We used the EPIC (Environmental Policy Integrated Climate) model to simulate maize yield and historical data to calculate the loss rates of agriculture, industry, and animal husbandry in the study area. Next, we constructed vulnerability curves. Finally, the spatial distributions of drought risk for 10-, 20-, and 50-year return periods were expressed using inverse distance weighting. Our results indicate that the spatial distributions of the three return periods are consistent. The highest drought risk is in Ulanhot, and the duration and severity there were both highest. This means that higher drought risk corresponds to longer drought duration and larger drought severity, thus providing useful information for drought and water resource management. For 10-, 20-, and 50-year return periods, the drought risk values ranged from 0.41 to 0.53, 0.45 to 0.59, and 0.50 to 0.67, respectively. Therefore, when the return period increases, the drought risk increases.

Comparison of the geographical distribution of feline immunodeficiency virus and feline leukemia virus infections in the United States of America (2000-2011).

PubMed

Chhetri, Bimal K; Berke, Olaf; Pearl, David L; Bienzle, Dorothee

2013-01-05

Although feline immunodeficiency virus (FIV) and feline leukemia virus (FeLV) have similar risk factors and control measures, infection rates have been speculated to vary in geographic distribution over North America. Since both infections are endemic in North America, it was assumed as a working hypothesis that their geographic distributions were similar. Hence, the purpose of this exploratory analysis was to investigate the comparative geographical distribution of both viral infections. Counts of FIV (n=17,108) and FeLV (n=30,017) positive serology results (FIV antibody and FeLV ELISA) were obtained for 48 contiguous states and District of Columbia of the United States of America (US) from the IDEXX Laboratories website. The proportional morbidity ratio of FIV to FeLV infection was estimated for each administrative region and its geographic distribution pattern was visualized by a choropleth map. Statistical evidence of an excess in the proportional morbidity ratio from unity was assessed using the spatial scan test under the normal probability model. This study revealed distinct spatial distribution patterns in the proportional morbidity ratio suggesting the presence of one or more relevant and geographically varying risk factors. The disease map indicates that there is a higher prevalence of FIV infections in the southern and eastern US compared to FeLV. In contrast, FeLV infections were observed to be more frequent in the western US compared to FIV. The respective excess in proportional morbidity ratio was significant with respect to the spatial scan test (p < 0.05). The observed variability in the geographical distribution of the proportional morbidity ratio of FIV to FeLV may be related to the presence of an additional or unique, but yet unknown, spatial risk factor. Putative factors may be geographic variations in specific virus strains and rate of vaccination. Knowledge of these factors and the geographical distributions of these infections can inform recommendations for testing, management and prevention. However, further studies are required to investigate the potential association of these factors with FIV and FeLV.

Landscape genetics and the spatial distribution of chronic wasting disease

USGS Publications Warehouse

Blanchong, Julie A.; Samuel, M.D.; Scribner, K.T.; Weckworth, B.V.; Langenberg, J.A.; Filcek, K.B.

2008-01-01

Predicting the spread of wildlife disease is critical for identifying populations at risk, targeting surveillance and designing proactive management programmes. We used a landscape genetics approach to identify landscape features that influenced gene flow and the distribution of chronic wasting disease (CWD) in Wisconsin white-tailed deer. CWD prevalence was negatively correlated with genetic differentiation of study area deer from deer in the area of disease origin (core-area). Genetic differentiation was greatest, and CWD prevalence lowest, in areas separated from the core-area by the Wisconsin River, indicating that this river reduced deer gene flow and probably disease spread. Features of the landscape that influence host dispersal and spatial patterns of disease can be identified based on host spatial genetic structure. Landscape genetics may be used to predict high-risk populations based on their genetic connection to infected populations and to target disease surveillance, control and preventative activities. ?? 2007 The Royal Society.

Cross-scale assessment of potential habitat shifts in a rapidly changing climate

USGS Publications Warehouse

Jarnevich, Catherine S.; Holcombe, Tracy R.; Bella, Elizabeth S.; Carlson, Matthew L.; Graziano, Gino; Lamb, Melinda; Seefeldt, Steven S.; Morisette, Jeffrey T.

2014-01-01

We assessed the ability of climatic, environmental, and anthropogenic variables to predict areas of high-risk for plant invasion and consider the relative importance and contribution of these predictor variables by considering two spatial scales in a region of rapidly changing climate. We created predictive distribution models, using Maxent, for three highly invasive plant species (Canada thistle, white sweetclover, and reed canarygrass) in Alaska at both a regional scale and a local scale. Regional scale models encompassed southern coastal Alaska and were developed from topographic and climatic data at a 2 km (1.2 mi) spatial resolution. Models were applied to future climate (2030). Local scale models were spatially nested within the regional area; these models incorporated physiographic and anthropogenic variables at a 30 m (98.4 ft) resolution. Regional and local models performed well (AUC values > 0.7), with the exception of one species at each spatial scale. Regional models predict an increase in area of suitable habitat for all species by 2030 with a general shift to higher elevation areas; however, the distribution of each species was driven by different climate and topographical variables. In contrast local models indicate that distance to right-of-ways and elevation are associated with habitat suitability for all three species at this spatial level. Combining results from regional models, capturing long-term distribution, and local models, capturing near-term establishment and distribution, offers a new and effective tool for highlighting at-risk areas and provides insight on how variables acting at different scales contribute to suitability predictions. The combinations also provides easy comparison, highlighting agreement between the two scales, where long-term distribution factors predict suitability while near-term do not and vice versa.

SPATIAL PATTERN OF WATER POLLUTION RISK IN MARYLAND, USA

EPA Science Inventory

Numerous field studies show that nitrogen (and phosphorous)export coefficients are significantly different acroos forest, agriculture, and urban land-cover types. We treated these export coefficients as a distribution, and used simulations to estimate the risk of increased nitro...

USE OF REVA'S WEB-BASED ENVIRONMENTAL DECISION TOOLKIT (EDT) TO ASSESS VULNERABILITY TO MERCURY ACROSS THE UNITED STATES

EPA Science Inventory

The problem of assessing risk from mercury across the nation is extremely complex involving integration of 1) our understanding of the methylation process in ecosystems, 2) the identification and spatial distribution of sensitive populations, and 3) the spatial pattern of mercury...

Quantifying the efficiency and equity implications of power plant air pollution control strategies in the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levy, J.I.; Wilson, A.M.; Zwack, L.M.

2007-05-15

We modeled the public health benefits and the change in the spatial inequality of health risk for a number of hypothetical control scenarios for power plants in the United States to determine optimal control strategies. We simulated various ways by which emission reductions of sulfur dioxide (SO{sub 2}), nitrogen oxides, and fine particulate matter (PM2.5) could be distributed to reach national emissions caps. We applied a source-receptor matrix to determine the PM2.5 concentration changes associated with each control scenario and estimated the mortality reductions. We estimated changes in the spatial inequality of health risk using the Atkinson index and othermore » indicators, following previously derived axioms for measuring health risk inequality. In our baseline model, benefits ranged from 17,000-21,000 fewer premature deaths per year across control scenarios. Scenarios with greater health benefits also tended to have greater reductions in the spatial inequality of health risk, as many sources with high health benefits per unit emissions of SO{sub 2} were in areas with high background PM2.5 concentrations. Sensitivity analyses indicated that conclusions were generally robust to the choice of indicator and other model specifications. Our analysis demonstrates an approach for formally quantifying both the magnitude and spatial distribution of health benefits of pollution control strategies, allowing for joint consideration of efficiency and equity.« less

[Spatial analysis of mortality from cardiovascular diseases in Madrid City, Spain].

PubMed

Gómez-Barroso, Diana; Prieto-Flores, María-Eugenia; Mellado San Gabino, Ana; Moreno Jiménez, Antonio

2015-01-01

Cardiovascular disease is the leading cause of death worldwide, but its spatial distribution is not homogeneous. The objective of this study is to analyze the spatial pattern of mortality from these diseases for men and women, in the populated urban area (AUP) of the municipality of Madrid, and to identify spatial aggregations. An ecological study was carried out by census tract, for men and women in 2010. Standardized Mortality Ratio (SMR), Relative Risk Smoothing (RRS) and Posterior Probability (PP) were calculated to consider the spatial pattern of the disease. To identify spatial clusters the Moran index (Moran I) and the Local Index of Spatial Autocorrelation (LISA) were used. The results were mapped. SMR higher than 1.1 was observed mainly in central areas among men and in peripheral areas among women. The PP that RRS was higher than 1 surpassed 0.8 in the center and in the periphery, in both men and women. Moran's I was 0.04 for men and 0.03 for women (p <0.05 in both cases). Sex differences were observed in the spatial distribution of mortality cases. RME RRS and PP maps showed a heterogeneous pattern in men, whereas in women a clearer pattern was detected, with a relatively higher risk in peripheral areas of the AUP. The LISA method showed similar patterns to those previously observed.

Spatial analysis and health risk assessment of heavy metals concentration in drinking water resources.

PubMed

Fallahzadeh, Reza Ali; Ghaneian, Mohammad Taghi; Miri, Mohammad; Dashti, Mohamad Mehdi

2017-11-01

The heavy metals available in drinking water can be considered as a threat to human health. Oncogenic risk of such metals is proven in several studies. Present study aimed to investigate concentration of the heavy metals including As, Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn in 39 water supply wells and 5 water reservoirs within the cities Ardakan, Meibod, Abarkouh, Bafgh, and Bahabad. The spatial distribution of the concentration was carried out by the software ArcGIS. Such simulations as non-carcinogenic hazard and lifetime cancer risk were conducted for lead and nickel using Monte Carlo technique. The sensitivity analysis was carried out to find the most important and effective parameters on risk assessment. The results indicated that concentration of all metals in 39 wells (except iron in 3 cases) reached the levels mentioned in EPA, World Health Organization, and Pollution Control Department standards. Based on the spatial distribution results at all studied regions, the highest concentrations of metals were derived, respectively, for iron and zinc. Calculated HQ values for non-carcinogenic hazard indicated a reasonable risk. Average lifetime cancer risks for the lead in Ardakan and nickel in Meibod and Bahabad were shown to be 1.09 × 10 -3 , 1.67 × 10 -1 , and 2 × 10 -1 , respectively, demonstrating high carcinogenic risk compared to similar standards and studies. The sensitivity analysis suggests high impact of concentration and BW in carcinogenic risk.

Hyperspectral imaging spectro radiometer improves radiometric accuracy

NASA Astrophysics Data System (ADS)

Prel, Florent; Moreau, Louis; Bouchard, Robert; Bullis, Ritchie D.; Roy, Claude; Vallières, Christian; Levesque, Luc

2013-06-01

Reliable and accurate infrared characterization is necessary to measure the specific spectral signatures of aircrafts and associated infrared counter-measures protections (i.e. flares). Infrared characterization is essential to improve counter measures efficiency, improve friend-foe identification and reduce the risk of friendly fire. Typical infrared characterization measurement setups include a variety of panchromatic cameras and spectroradiometers. Each instrument brings essential information; cameras measure the spatial distribution of targets and spectroradiometers provide the spectral distribution of the emitted energy. However, the combination of separate instruments brings out possible radiometric errors and uncertainties that can be reduced with Hyperspectral imagers. These instruments combine both spectral and spatial information into the same data. These instruments measure both the spectral and spatial distribution of the energy at the same time ensuring the temporal and spatial cohesion of collected information. This paper presents a quantitative analysis of the main contributors of radiometric uncertainties and shows how a hyperspectral imager can reduce these uncertainties.

GIS-supported investigation of human EHEC and cattle VTEC O157 infections in Sweden: geographical distribution, spatial variation and possible risk factors.

PubMed Central

Kistemann, Thomas; Zimmer, Sonja; Vågsholm, Ivar; Andersson, Yvonne

2004-01-01

This article describes the spatial and temporal distribution of verotoxin-producing Escherichia coli among humans (EHEC) and cattle (VTEC) in Sweden, in order to evaluate relationships between the incidence of EHEC in humans, prevalence of VTEC O157 in livestock and agricultural structure by an ecological study. The spatial patterns of the distribution of human infections were described and compared with spatial patterns of occurrence in cattle, using a Geographic Information System (GIS). The findings implicate a concentration of human infection and cattle prevalence in the southwest of Sweden. The use of probability mapping confirmed unusual patterns of infection rates. The comparison of human and cattle infection indicated a spatial and statistical association. The correlation between variables of the agricultural structure and human EHEC incidence was high, indicating a significant statistical association of cattle and farm density with human infection. The explained variation of a multiple linear regression model was 0.56. PMID:15188718

Spatial epidemiological techniques in cholera mapping and analysis towards a local scale predictive modelling

NASA Astrophysics Data System (ADS)

Rasam, A. R. A.; Ghazali, R.; Noor, A. M. M.; Mohd, W. M. N. W.; Hamid, J. R. A.; Bazlan, M. J.; Ahmad, N.

2014-02-01

Cholera spatial epidemiology is the study of the spread and control of the disease spatial pattern and epidemics. Previous studies have shown that multi-factorial causation such as human behaviour, ecology and other infectious risk factors influence the disease outbreaks. Thus, understanding spatial pattern and possible interrelationship factors of the outbreaks are crucial to be explored an in-depth study. This study focuses on the integration of geographical information system (GIS) and epidemiological techniques in exploratory analyzing the cholera spatial pattern and distribution in the selected district of Sabah. Spatial Statistic and Pattern tools in ArcGIS and Microsoft Excel software were utilized to map and analyze the reported cholera cases and other data used. Meanwhile, cohort study in epidemiological technique was applied to investigate multiple outcomes of the disease exposure. The general spatial pattern of cholera was highly clustered showed the disease spread easily at a place or person to others especially 1500 meters from the infected person and locations. Although the cholera outbreaks in the districts are not critical, it could be endemic at the crowded areas, unhygienic environment, and close to contaminated water. It was also strongly believed that the coastal water of the study areas has possible relationship with the cholera transmission and phytoplankton bloom since the areas recorded higher cases. GIS demonstrates a vital spatial epidemiological technique in determining the distribution pattern and elucidating the hypotheses generating of the disease. The next research would be applying some advanced geo-analysis methods and other disease risk factors for producing a significant a local scale predictive risk model of the disease in Malaysia.

Short- and medium-chain chlorinated paraffins in sediments from the middle reaches of the Yangtze River: Spatial distributions, source apportionment and risk assessment.

PubMed

Qiao, Lin; Gao, Lirong; Xia, Dan; Huang, Huiting; Zheng, Minghui

2017-01-01

Chlorinated paraffins (CPs) are easily adsorbed into sediments where they pose potential risks to the ecosystem and human health. Few studies have investigated short- and medium-chain CPs (SCCPs and MCCPs) in sediments. The aim of the present study was to comprehensively investigate contamination levels, spatial distributions, sources and risks posed by CPs in sediments from the middle reaches of the Yangtze River. The sediment samples were analyzed by two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS). The concentrations of SCCPs and MCCPs ranged from 4.19 to 41.6ng/g dry weight (dw) and not detected to 14.6ng/g dw, respectively. No significant correlation was found between the total organic carbon contents and CP concentrations (P>0.05). The spatial distributions showed that CP contamination levels in the sediments were related to local human activities. The dominant congener groups were C 10-11 Cl 6-7 for SCCPs, and C 14 Cl 7-8 for MCCPs. Correspondence analysis revealed that likely sources of SCCPs were the production and use of CP-42 and CP-52. Principal component analysis indicated that SCCPs and MCCPs in the sediments may come from different sources. Moreover, CPs with nine carbon atoms were quantitated for the first time in sediment samples, and the results indicated they should not be neglected in future analyses. Risk assessments indicated that CPs in the sediments did not pose a great ecological risk currently. Copyright © 2016 Elsevier B.V. All rights reserved.

The ecological risk, source identification, and pollution assessment of heavy metals in road dust: a case study in Rafsanjan, SE Iran.

PubMed

Mirzaei Aminiyan, Milad; Baalousha, Mohammed; Mousavi, Rouhollah; Mirzaei Aminiyan, Farzad; Hosseini, Hamideh; Heydariyan, Amin

2018-05-01

Heavy metal (HM) contamination in road dust is a potential environmental and human health threat. The sources, concentrations, spatial distribution, and ecological risk of As, Cd, Cu, Cr, Ni, Pb, and Zn in road dust in Rafsanjan City, Iran, were investigated. Pollution was assessed using the enrichment factor (EF). The potentially harmful effects of HMs were evaluated by calculating the potential ecological risk factor of individual metals (E r ) and of multiple metals (RI) using the Hakanson method. Correlation and principal component analyses (PCA) were applied to identify HM pollution sources. The concentrations of HMs in road dust were higher (ca. 5-10 folds) than their natural background values. The EF and E r increased according to the following order Cu > Pb > As > Zn > Cd > Cr > Ni and Cu > Cd > Pb > As > Ni > Zn > Cr, respectively. Thus, Cu is regarded as the pollutant of highest concern. Based on potential ecological risk index (RI) spatial distribution, all parts of Rafsanjan are characterized by significantly high potential ecological risk. HM concentration heat maps, PCA, and correlation analysis suggest that Cu, Pb, As, Cd, and Zn may have originated from the same source and follow the same spatial distribution pattern. These metals originated mainly from anthropogenic sources like copper mining and smelting plants, industrial and chemical activities, inordinate application of chemical fertilizers and pesticides in farmlands, and heavy traffic. Ni and Cr are likely to origniate from the industrial activities and traffic load in Rafsanjan City.

Risk maps for targeting exotic plant pest detection programs in the United States

Treesearch

R.D. Magarey; D.M. Borchert; J.S. Engle; M Garcia-Colunga; Frank H. Koch; et al

2011-01-01

In the United States, pest risk maps are used by the Cooperative Agricultural Pest Survey for spatial and temporal targeting of exotic plant pest detection programs. Methods are described to create standardized host distribution, climate and pathway risk maps for the top nationally ranked exotic pest targets. Two examples are provided to illustrate the risk mapping...

Predicting spatial distribution of postfire debris flows and potential consequences for native trout in headwater streams

USGS Publications Warehouse

Sedell, Edwin R; Gresswell, Bob; McMahon, Thomas E.

2015-01-01

Habitat fragmentation and degradation and invasion of nonnative species have restricted the distribution of native trout. Many trout populations are limited to headwater streams where negative effects of predicted climate change, including reduced stream flow and increased risk of catastrophic fires, may further jeopardize their persistence. Headwater streams in steep terrain are especially susceptible to disturbance associated with postfire debris flows, which have led to local extirpation of trout populations in some systems. We conducted a reach-scale spatial analysis of debris-flow risk among 11 high-elevation watersheds of the Colorado Rocky Mountains occupied by isolated populations of Colorado River Cutthroat Trout (Oncorhynchus clarkii pleuriticus). Stream reaches at high risk of disturbance by postfire debris flow were identified with the aid of a qualitative model based on 4 primary initiating and transport factors (hillslope gradient, flow accumulation pathways, channel gradient, and valley confinement). This model was coupled with a spatially continuous survey of trout distributions in these stream networks to assess the predicted extent of trout population disturbances related to debris flows. In the study systems, debris-flow potential was highest in the lower and middle reaches of most watersheds. Colorado River Cutthroat Trout occurred in areas of high postfire debris-flow risk, but they were never restricted to those areas. Postfire debris flows could extirpate trout from local reaches in these watersheds, but trout populations occupy refugia that should allow recolonization of interconnected, downstream reaches. Specific results of our study may not be universally applicable, but our risk assessment approach can be applied to assess postfire debris-flow risk for stream reaches in other watersheds.

Visualization of risk of radiogenic second cancer in the organs and tissues of the human body.

PubMed

Zhang, Rui; Mirkovic, Dragan; Newhauser, Wayne D

2015-04-28

Radiogenic second cancer is a common late effect in long term cancer survivors. Currently there are few methods or tools available to visually evaluate the spatial distribution of risks of radiogenic late effects in the human body. We developed a risk visualization method and demonstrated it for radiogenic second cancers in tissues and organs of one patient treated with photon volumetric modulated arc therapy and one patient treated with proton craniospinal irradiation. Treatment plans were generated using radiotherapy treatment planning systems (TPS) and dose information was obtained from TPS. Linear non-threshold risk coefficients for organs at risk of second cancer incidence were taken from the Biological Effects of Ionization Radiation VII report. Alternative risk models including linear exponential model and linear plateau model were also examined. The predicted absolute lifetime risk distributions were visualized together with images of the patient anatomy. The risk distributions of second cancer for the two patients were visually presented. The risk distributions varied with tissue, dose, dose-risk model used, and the risk distribution could be similar to or very different from the dose distribution. Our method provides a convenient way to directly visualize and evaluate the risks of radiogenic second cancer in organs and tissues of the human body. In the future, visual assessment of risk distribution could be an influential determinant for treatment plan scoring.

Spatial assessment of the potential risk of avian influenza A virus infection in three raptor species in Japan

PubMed Central

MORIGUCHI, Sachiko; ONUMA, Manabu; GOKA, Koichi

2016-01-01

Avian influenza A, a highly pathogenic avian influenza, is a lethal infection in certain species of wild birds, including some endangered species. Raptors are susceptible to avian influenza, and spatial risk assessment of such species may be valuable for conservation planning. We used the maximum entropy approach to generate potential distribution models of three raptor species from presence-only data for the mountain hawk-eagle Nisaetus nipalensis, northern goshawk Accipiter gentilis and peregrine falcon Falco peregrinus, surveyed during the winter from 1996 to 2001. These potential distribution maps for raptors were superimposed on avian influenza A risk maps of Japan, created from data on incidence of the virus in wild birds throughout Japan from October 2010 to March 2011. The avian influenza A risk map for the mountain hawk-eagle showed that most regions of Japan had a low risk for avian influenza A. In contrast, the maps for the northern goshawk and peregrine falcon showed that their high-risk areas were distributed on the plains along the Sea of Japan and Pacific coast. We recommend enhanced surveillance for each raptor species in high-risk areas and immediate establishment of inspection systems. At the same time, ecological risk assessments that determine factors, such as the composition of prey species, and differential sensitivity of avian influenza A virus between bird species should provide multifaceted insights into the total risk assessment of endangered species. PMID:26972333

Bovine spongiform encephalopathy and spatial analysis of the feed industry.

PubMed

Paul, Mathilde; Abrial, David; Jarrige, Nathalie; Rican, Stéphane; Garrido, Myriam; Calavas, Didier; Ducrot, Christian

2007-06-01

In France, despite the ban of meat-and-bone meal (MBM) in cattle feed, bovine spongiform encephalopathy (BSE) was detected in hundreds of cattle born after the ban. To study the role of MBM, animal fat, and dicalcium phosphate on the risk for BSE after the feed ban, we conducted a spatial analysis of the feed industry. We used data from 629 BSE cases as well as data on use of each byproduct and market area of the feed factories. We mapped risk for BSE in 951 areas supplied by the same factories and connection with use of byproducts. A disease map of BSE with covariates was built with the hierarchical Bayesian modeling methods, based on Poisson distribution with spatial smoothing. Only use of MBM was spatially linked to risk for BSE, which highlights cross-contamination as the most probable source of infection after the feed ban.

Spatial analysis of infection by the human immunodeficiency virus among pregnant women1

PubMed Central

de Holanda, Eliane Rolim; Galvão, Marli Teresinha Gimeniz; Pedrosa, Nathália Lima; Paiva, Simone de Sousa; de Almeida, Rosa Lívia Freitas

2015-01-01

OBJECTIVES: to analyze the spatial distribution of reported cases of pregnant women infected by the human immunodeficiency virus and to identify the urban areas with greater social vulnerability to the infection among pregnant women. METHOD: ecological study, developed by means of spatial analysis techniques of area data. Secondary data were used from the Brazilian National Disease Notification System for the city of Recife, Pernambuco. Birth data were obtained from the Brazilian Information System on Live Births and socioeconomic data from the 2010 Demographic Census. RESULTS: the presence of spatial self-correlation was verified. Moran's Index was significant for the distribution. Clusters were identified, considered as high-risk areas, located in grouped neighborhoods, with equally high infection rates among pregnant women. A neighborhood located in the Northwest of the city was distinguished, considered in an epidemiological transition phase. CONCLUSION: precarious living conditions, as evidenced by the indicators illiteracy, absence of prenatal care and poverty, were relevant for the risk of vertical HIV transmission, converging to the grouping of cases among disadvantaged regions. PMID:26155005

Heavy Metal Contamination Assessment and Partition for Industrial and Mining Gathering Areas

PubMed Central

Guan, Yang; Shao, Chaofeng; Ju, Meiting

2014-01-01

Industrial and mining activities have been recognized as the major sources of soil heavy metal contamination. This study introduced an improved Nemerow index method based on the Nemerow and geo-accumulation index. Taking a typical industrial and mining gathering area in Tianjin (China) as example, this study then analyzed the contamination sources as well as the ecological and integrated risks. The spatial distribution of the contamination level and ecological risk were determined using Geographic Information Systems. The results are as follows: (1) Zinc showed the highest contaminant level in the study area; the contamination levels of the other seven heavy metals assessed were relatively lower. (2) The combustion of fossil fuels and emissions from industrial and mining activities were the main sources of contamination in the study area. (3) The overall contamination level of heavy metals in the study area ranged from heavily contaminated to extremely contaminated and showed an uneven distribution. (4) The potential ecological risk showed an uneven distribution, and the overall ecological risk level ranged from low to moderate. This study also emphasized the importance of partition in industrial and mining areas, the extensive application of spatial analysis methods, and the consideration of human health risks in future studies. PMID:25032743

Spatial pattern evolution of Aedes aegypti breeding sites in an Argentinean city without a dengue vector control programme.

PubMed

Espinosa, Manuel O; Polop, Francisco; Rotela, Camilo H; Abril, Marcelo; Scavuzzo, Carlos M

2016-11-21

The main objective of this study was to obtain and analyse the space-time dynamics of Aedes aegypti breeding sites in Clorinda City, Formosa Province, Argentina coupled with landscape analysis using the maximum entropy approach in order to generate a dengue vector niche model. In urban areas, without vector control activities, 12 entomologic (larval) samplings were performed during three years (October 2011 to October 2014). The entomologic surveillance area represented 16,511 houses. Predictive models for Aedes distribution were developed using vector breeding abundance data, density analysis, clustering and geoprocessing techniques coupled with Earth observation satellite data. The spatial analysis showed a vector spatial distribution pattern with clusters of high density in the central region of Clorinda with a well-defined high-risk area in the western part of the city. It also showed a differential temporal behaviour among different areas, which could have implications for risk models and control strategies at the urban scale. The niche model obtained for Ae. aegypti, based on only one year of field data, showed that 85.8% of the distribution of breeding sites is explained by the percentage of water supply (48.2%), urban distribution (33.2%), and the percentage of urban coverage (4.4%). The consequences for the development of control strategies are discussed with reference to the results obtained using distribution maps based on environmental variables.

Spatial distribution of Giardia lamblia infection among general population in Mazandaran Province, north of Iran.

PubMed

Siyadatpanah, Abolghasem; Sharif, Mehdi; Daryani, Ahmad; Sarvi, Shahabeddin; Kohansal, Mohammad Hasan; Barzegari, Saeed; Pagheh, Abdol Sattar; Gholami, Shirzad

2018-06-01

Giardia lamblia is the most prevalent intestinal parasites of humans in Iran and other in the world although information on geographical distribution of giardiasis plays significant role in identifying communities at high risk, little attention has been paid to study human giardiasis using geographical information system. Therefore, the aim of the current study was to determine temporal and spatial patterns of human giardiasis distribution to identify possible high risk areas and seasons in northern Iran. A total of 4788 people referred to health centers in the Mazandaran Province of northern Iran were surveyed January to December 2015. From each person stool sample and questionnaire with socio-demographic data were collected. Giardia infection was diagnosed using direct wet mount, formalin ether concentration and trichrome staining. The results were analyzed using Moran Local Indicators of spatial association and geographically weighted regression. The overall prevalence of Giardia infection was 4.6% (222/4788), and was significantly higher among those aged 5-9 years compared to their older peers ( P  < 0.0001). Our data showed a significant dependency between the prevalence of G. lamblia and age, job, residence, season and height from the sea ( P  < 0.0001). The results of this study provided a precise and specific spatial and temporal pattern of human giardiasis distribution in the Mazandaran Province, Iran. These evidences should be considered for proper control of disease decisions and strategies.

Mapping malaria risk among children in Côte d'Ivoire using Bayesian geo-statistical models.

PubMed

Raso, Giovanna; Schur, Nadine; Utzinger, Jürg; Koudou, Benjamin G; Tchicaya, Emile S; Rohner, Fabian; N'goran, Eliézer K; Silué, Kigbafori D; Matthys, Barbara; Assi, Serge; Tanner, Marcel; Vounatsou, Penelope

2012-05-09

In Côte d'Ivoire, an estimated 767,000 disability-adjusted life years are due to malaria, placing the country at position number 14 with regard to the global burden of malaria. Risk maps are important to guide control interventions, and hence, the aim of this study was to predict the geographical distribution of malaria infection risk in children aged <16 years in Côte d'Ivoire at high spatial resolution. Using different data sources, a systematic review was carried out to compile and geo-reference survey data on Plasmodium spp. infection prevalence in Côte d'Ivoire, focusing on children aged <16 years. The period from 1988 to 2007 was covered. A suite of Bayesian geo-statistical logistic regression models was fitted to analyse malaria risk. Non-spatial models with and without exchangeable random effect parameters were compared to stationary and non-stationary spatial models. Non-stationarity was modelled assuming that the underlying spatial process is a mixture of separate stationary processes in each ecological zone. The best fitting model based on the deviance information criterion was used to predict Plasmodium spp. infection risk for entire Côte d'Ivoire, including uncertainty. Overall, 235 data points at 170 unique survey locations with malaria prevalence data for individuals aged <16 years were extracted. Most data points (n = 182, 77.4%) were collected between 2000 and 2007. A Bayesian non-stationary regression model showed the best fit with annualized rainfall and maximum land surface temperature identified as significant environmental covariates. This model was used to predict malaria infection risk at non-sampled locations. High-risk areas were mainly found in the north-central and western area, while relatively low-risk areas were located in the north at the country border, in the north-east, in the south-east around Abidjan, and in the central-west between two high prevalence areas. The malaria risk map at high spatial resolution gives an important overview of the geographical distribution of the disease in Côte d'Ivoire. It is a useful tool for the national malaria control programme and can be utilized for spatial targeting of control interventions and rational resource allocation.

Mapping malaria risk among children in Côte d’Ivoire using Bayesian geo-statistical models

PubMed Central

2012-01-01

Background In Côte d’Ivoire, an estimated 767,000 disability-adjusted life years are due to malaria, placing the country at position number 14 with regard to the global burden of malaria. Risk maps are important to guide control interventions, and hence, the aim of this study was to predict the geographical distribution of malaria infection risk in children aged <16 years in Côte d’Ivoire at high spatial resolution. Methods Using different data sources, a systematic review was carried out to compile and geo-reference survey data on Plasmodium spp. infection prevalence in Côte d’Ivoire, focusing on children aged <16 years. The period from 1988 to 2007 was covered. A suite of Bayesian geo-statistical logistic regression models was fitted to analyse malaria risk. Non-spatial models with and without exchangeable random effect parameters were compared to stationary and non-stationary spatial models. Non-stationarity was modelled assuming that the underlying spatial process is a mixture of separate stationary processes in each ecological zone. The best fitting model based on the deviance information criterion was used to predict Plasmodium spp. infection risk for entire Côte d’Ivoire, including uncertainty. Results Overall, 235 data points at 170 unique survey locations with malaria prevalence data for individuals aged <16 years were extracted. Most data points (n = 182, 77.4%) were collected between 2000 and 2007. A Bayesian non-stationary regression model showed the best fit with annualized rainfall and maximum land surface temperature identified as significant environmental covariates. This model was used to predict malaria infection risk at non-sampled locations. High-risk areas were mainly found in the north-central and western area, while relatively low-risk areas were located in the north at the country border, in the north-east, in the south-east around Abidjan, and in the central-west between two high prevalence areas. Conclusion The malaria risk map at high spatial resolution gives an important overview of the geographical distribution of the disease in Côte d’Ivoire. It is a useful tool for the national malaria control programme and can be utilized for spatial targeting of control interventions and rational resource allocation. PMID:22571469

Spatial autocorrelation analysis of health care hotspots in Taiwan in 2006

PubMed Central

2009-01-01

Background Spatial analytical techniques and models are often used in epidemiology to identify spatial anomalies (hotspots) in disease regions. These analytical approaches can be used to not only identify the location of such hotspots, but also their spatial patterns. Methods In this study, we utilize spatial autocorrelation methodologies, including Global Moran's I and Local Getis-Ord statistics, to describe and map spatial clusters, and areas in which these are situated, for the 20 leading causes of death in Taiwan. In addition, we use the fit to a logistic regression model to test the characteristics of similarity and dissimilarity by gender. Results Gender is compared in efforts to formulate the common spatial risk. The mean found by local spatial autocorrelation analysis is utilized to identify spatial cluster patterns. There is naturally great interest in discovering the relationship between the leading causes of death and well-documented spatial risk factors. For example, in Taiwan, we found the geographical distribution of clusters where there is a prevalence of tuberculosis to closely correspond to the location of aboriginal townships. Conclusions Cluster mapping helps to clarify issues such as the spatial aspects of both internal and external correlations for leading health care events. This is of great aid in assessing spatial risk factors, which in turn facilitates the planning of the most advantageous types of health care policies and implementation of effective health care services. PMID:20003460

AN APPROACH FOR CHARACTERIZING TROPOSPHERIC OZONE RISK TO FOREST

EPA Science Inventory

The risk tropospheric ozone poses to forests in the United States is dependent on the variation in ozone exposure across the distribution of the forests in question and the various environmental and climate factors predominant in the region. All these factors have a spatial natur...

Modeling the spatial distribution of Chagas disease vectors using environmental variables and people´s knowledge.

PubMed

Hernández, Jaime; Núñez, Ignacia; Bacigalupo, Antonella; Cattan, Pedro E

2013-05-31

Chagas disease is caused by the protozoan Trypanosoma cruzi, which is transmitted to mammal hosts by triatomine insect vectors. The goal of this study was to model the spatial distribution of triatomine species in an endemic area. Vector's locations were obtained with a rural householders' survey. This information was combined with environmental data obtained from remote sensors, land use maps and topographic SRTM data, using the machine learning algorithm Random Forests to model species distribution. We analysed the combination of variables on three scales: 10 km, 5 km and 2.5 km cell size grids. The best estimation, explaining 46.2% of the triatomines spatial distribution, was obtained for 5 km of spatial resolution. Presence probability distribution increases from central Chile towards the north, tending to cover the central-coastal region and avoiding areas of the Andes range. The methodology presented here was useful to model the distribution of triatomines in an endemic area; it is best explained using 5 km of spatial resolution, and their presence increases in the northern part of the study area. This study's methodology can be replicated in other countries with Chagas disease or other vectorial transmitted diseases, and be used to locate high risk areas and to optimize resource allocation, for prevention and control of vectorial diseases.

Modeling the spatial distribution of Chagas disease vectors using environmental variables and people´s knowledge

PubMed Central

2013-01-01

Background Chagas disease is caused by the protozoan Trypanosoma cruzi, which is transmitted to mammal hosts by triatomine insect vectors. The goal of this study was to model the spatial distribution of triatomine species in an endemic area. Methods Vector’s locations were obtained with a rural householders’ survey. This information was combined with environmental data obtained from remote sensors, land use maps and topographic SRTM data, using the machine learning algorithm Random Forests to model species distribution. We analysed the combination of variables on three scales: 10 km, 5 km and 2.5 km cell size grids. Results The best estimation, explaining 46.2% of the triatomines spatial distribution, was obtained for 5 km of spatial resolution. Presence probability distribution increases from central Chile towards the north, tending to cover the central-coastal region and avoiding areas of the Andes range. Conclusions The methodology presented here was useful to model the distribution of triatomines in an endemic area; it is best explained using 5 km of spatial resolution, and their presence increases in the northern part of the study area. This study’s methodology can be replicated in other countries with Chagas disease or other vectorial transmitted diseases, and be used to locate high risk areas and to optimize resource allocation, for prevention and control of vectorial diseases. PMID:23724993

Modeling runoff and erosion risk in a~small steep cultivated watershed using different data sources: from on-site measurements to farmers' perceptions

NASA Astrophysics Data System (ADS)

Auvet, B.; Lidon, B.; Kartiwa, B.; Le Bissonnais, Y.; Poussin, J.-C.

2015-09-01

This paper presents an approach to model runoff and erosion risk in a context of data scarcity, whereas the majority of available models require large quantities of physical data that are frequently not accessible. To overcome this problem, our approach uses different sources of data, particularly on agricultural practices (tillage and land cover) and farmers' perceptions of runoff and erosion. The model was developed on a small (5 ha) cultivated watershed characterized by extreme conditions (slopes of up to 55 %, extreme rainfall events) on the Merapi volcano in Indonesia. Runoff was modelled using two versions of STREAM. First, a lumped version was used to determine the global parameters of the watershed. Second, a distributed version used three parameters for the production of runoff (slope, land cover and roughness), a precise DEM, and the position of waterways for runoff distribution. This information was derived from field observations and interviews with farmers. Both surface runoff models accurately reproduced runoff at the outlet. However, the distributed model (Nash-Sutcliffe = 0.94) was more accurate than the adjusted lumped model (N-S = 0.85), especially for the smallest and biggest runoff events, and produced accurate spatial distribution of runoff production and concentration. Different types of erosion processes (landslides, linear inter-ridge erosion, linear erosion in main waterways) were modelled as a combination of a hazard map (the spatial distribution of runoff/infiltration volume provided by the distributed model), and a susceptibility map combining slope, land cover and tillage, derived from in situ observations and interviews with farmers. Each erosion risk map gives a spatial representation of the different erosion processes including risk intensities and frequencies that were validated by the farmers and by in situ observations. Maps of erosion risk confirmed the impact of the concentration of runoff, the high susceptibility of long steep slopes, and revealed the critical role of tillage direction. Calibrating and validating models using in situ measurements, observations and farmers' perceptions made it possible to represent runoff and erosion risk despite the initial scarcity of hydrological data. Even if the models mainly provided orders of magnitude and qualitative information, they significantly improved our understanding of the watershed dynamics. In addition, the information produced by such models is easy for farmers to use to manage runoff and erosion by using appropriate agricultural practices.

Spatiotemporal Determinants of Urban Leptospirosis Transmission: Four-Year Prospective Cohort Study of Slum Residents in Brazil.

PubMed

Hagan, José E; Moraga, Paula; Costa, Federico; Capian, Nicolas; Ribeiro, Guilherme S; Wunder, Elsio A; Felzemburgh, Ridalva D M; Reis, Renato B; Nery, Nivison; Santana, Francisco S; Fraga, Deborah; Dos Santos, Balbino L; Santos, Andréia C; Queiroz, Adriano; Tassinari, Wagner; Carvalho, Marilia S; Reis, Mitermayer G; Diggle, Peter J; Ko, Albert I

2016-01-01

Rat-borne leptospirosis is an emerging zoonotic disease in urban slum settlements for which there are no adequate control measures. The challenge in elucidating risk factors and informing approaches for prevention is the complex and heterogeneous environment within slums, which vary at fine spatial scales and influence transmission of the bacterial agent. We performed a prospective study of 2,003 slum residents in the city of Salvador, Brazil during a four-year period (2003-2007) and used a spatiotemporal modelling approach to delineate the dynamics of leptospiral transmission. Household interviews and Geographical Information System surveys were performed annually to evaluate risk exposures and environmental transmission sources. We completed annual serosurveys to ascertain leptospiral infection based on serological evidence. Among the 1,730 (86%) individuals who completed at least one year of follow-up, the infection rate was 35.4 (95% CI, 30.7-40.6) per 1,000 annual follow-up events. Male gender, illiteracy, and age were independently associated with infection risk. Environmental risk factors included rat infestation (OR 1.46, 95% CI, 1.00-2.16), contact with mud (OR 1.57, 95% CI 1.17-2.17) and lower household elevation (OR 0.92 per 10m increase in elevation, 95% CI 0.82-1.04). The spatial distribution of infection risk was highly heterogeneous and varied across small scales. Fixed effects in the spatiotemporal model accounted for the majority of the spatial variation in risk, but there was a significant residual component that was best explained by the spatial random effect. Although infection risk varied between years, the spatial distribution of risk associated with fixed and random effects did not vary temporally. Specific "hot-spots" consistently had higher transmission risk during study years. The risk for leptospiral infection in urban slums is determined in large part by structural features, both social and environmental. Our findings indicate that topographic factors such as household elevation and inadequate drainage increase risk by promoting contact with mud and suggest that the soil-water interface serves as the environmental reservoir for spillover transmission. The use of a spatiotemporal approach allowed the identification of geographic outliers with unexplained risk patterns. This approach, in addition to guiding targeted community-based interventions and identifying new hypotheses, may have general applicability towards addressing environmentally-transmitted diseases that have emerged in complex urban slum settings.

Modeling waterfowl habitat selection in the Central Valley of California to better understand the spatial relationship between commercial poultry and waterfowl

USGS Publications Warehouse

Matchett, Elliott L.; Casazza, Michael L.; Fleskes, Joseph; Kelman, T.; Cadena, M.; Pitesky, M.

2017-01-01

Wildlife researchers frequently study resource and habitat selection of wildlife to understand their potential habitat requirements and to conserve their populations. Understanding wildlife spatial-temporal distributions related to habitat have other applications such as to model interfaces between wildlife and domestic food animals in order to mitigate disease transmission to food animals. The highly pathogenic avian influenza (HPAI) virus represents a significant risk to the poultry industry. The Central Valley of California offers a unique geographical confluence of commercial poultry and wild waterfowl, which are thought to be a key reservoir of avian influenza (AI). Therefore, understanding spatio-temporal distributions of waterfowl could improve our understanding of potential risk of HPAI exposure from a commercial poultry perspective. Using existing radio-telemetry data on waterfowl (U.S. Geological Survey) in combination with habitat and vegetation data based on Geographic Information Systems (GIS), we are developing GIS-based statistical models that predict the probability of waterfowl presence (Habitat Suitability Mapping). Near-real-time application can be developed using recent habitat data derived from Landsat imagery (acquired by satellites and publically available through the U.S. Geological Survey) to predict temporally- and spatially-varying distributions of waterfowl in the Central Valley. These results could be used to provide decision support for the poultry industry in addressing potential risk of HPAI exposure related to waterfowl proximity.

Spatial interpolation and radiological mapping of ambient gamma dose rate by using artificial neural networks and fuzzy logic methods.

PubMed

Yeşilkanat, Cafer Mert; Kobya, Yaşar; Taşkın, Halim; Çevik, Uğur

2017-09-01

The aim of this study was to determine spatial risk dispersion of ambient gamma dose rate (AGDR) by using both artificial neural network (ANN) and fuzzy logic (FL) methods, compare the performances of methods, make dose estimations for intermediate stations with no previous measurements and create dose rate risk maps of the study area. In order to determine the dose distribution by using artificial neural networks, two main networks and five different network structures were used; feed forward ANN; Multi-layer perceptron (MLP), Radial basis functional neural network (RBFNN), Quantile regression neural network (QRNN) and recurrent ANN; Jordan networks (JN), Elman networks (EN). In the evaluation of estimation performance obtained for the test data, all models appear to give similar results. According to the cross-validation results obtained for explaining AGDR distribution, Pearson's r coefficients were calculated as 0.94, 0.91, 0.89, 0.91, 0.91 and 0.92 and RMSE values were calculated as 34.78, 43.28, 63.92, 44.86, 46.77 and 37.92 for MLP, RBFNN, QRNN, JN, EN and FL, respectively. In addition, spatial risk maps showing distributions of AGDR of the study area were created by all models and results were compared with geological, topological and soil structure. Copyright © 2017 Elsevier Ltd. All rights reserved.

Freight transportation and the potential for invasions of exotic insects in urban and periurban forests of the United States.

PubMed

Colunga-Garcia, Manuel; Haack, Robert A; Adelaja, Adesoji O

2009-02-01

Freight transportation is an important pathway for the introduction and dissemination of exotic forest insects (EFI). Identifying the final destination of imports is critical in determining the likelihood of EFI establishment. We analyzed the use of regional freight transport information to characterize risk of urban and periurban areas to EFI introductions. Specific objectives were to 1) approximate the final distribution of selected imports among urban areas of the United States, 2) characterize the final distribution of imports in terms of their spatial aggregation and dominant world region of origin, and 3) assess the effect of the final distribution of imports on the level of risk to urban and periurban forests from EFI. Freight pattern analyses were conducted for three categories of imports whose products or packaging materials are associated with EFI: wood products, nonmetallic mineral products, and machinery. The final distribution of wood products was the most evenly distributed of the three selected imports, whereas machinery was most spatially concentrated. We found that the type of import and the world region of origin greatly influence the final distribution of imported products. Risk assessment models were built based on the amount of forestland and imports for each urban area The model indicated that 84-88% of the imported tonnage went to only 4-6% of the urban areas in the contiguous United States. We concluded that freight movement information is critical for proper risk assessment of EFI. Implications of our findings and future research needs are discussed.

Temporal and spatial distribution characteristics in the natural plague foci of Chinese Mongolian gerbils based on spatial autocorrelation.

PubMed

Du, Hai-Wen; Wang, Yong; Zhuang, Da-Fang; Jiang, Xiao-San

2017-08-07

The nest flea index of Meriones unguiculatus is a critical indicator for the prevention and control of plague, which can be used not only to detect the spatial and temporal distributions of Meriones unguiculatus, but also to reveal its cluster rule. This research detected the temporal and spatial distribution characteristics of the plague natural foci of Mongolian gerbils by body flea index from 2005 to 2014, in order to predict plague outbreaks. Global spatial autocorrelation was used to describe the entire spatial distribution pattern of the body flea index in the natural plague foci of typical Chinese Mongolian gerbils. Cluster and outlier analysis and hot spot analysis were also used to detect the intensity of clusters based on geographic information system methods. The quantity of M. unguiculatus nest fleas in the sentinel surveillance sites from 2005 to 2014 and host density data of the study area from 2005 to 2010 used in this study were provided by Chinese Center for Disease Control and Prevention. The epidemic focus regions of the Mongolian gerbils remain the same as the hot spot regions relating to the body flea index. High clustering areas possess a similar pattern as the distribution pattern of the body flea index indicating that the transmission risk of plague is relatively high. In terms of time series, the area of the epidemic focus gradually increased from 2005 to 2007, declined rapidly in 2008 and 2009, and then decreased slowly and began trending towards stability from 2009 to 2014. For the spatial change, the epidemic focus regions began moving northward from the southwest epidemic focus of the Mongolian gerbils from 2005 to 2007, and then moved from north to south in 2007 and 2008. The body flea index of Chinese gerbil foci reveals significant spatial and temporal aggregation characteristics through the employing of spatial autocorrelation. The diversity of temporary and spatial distribution is mainly affected by seasonal variation, the human activity and natural factors.

[Spatial analysis of autumn-winter type scrub typhus in Shandong province, 2006-2014].

PubMed

Yang, H; Bi, Z W; Kou, Z Q; Zheng, L; Zhao, Z T

2016-05-01

To discuss the spatial-temporal distribution and epidemic trends of autumn-winter type scrub typhus in Shandong province, and provide scientific evidence for further study for the prevention and control of the disease. The scrub typhus surveillance data during 2006-2014 were collected from Shandong Disease Reporting Information System. The data was analyzed by using software ArcGIS 9.3(ESRI Inc., Redlands, CA, USA), GeoDa 0.9.5-i and SatScan 9.1.1. The Moran' s I, log-likelihood ratio(LLR), relative risk(RR)were calculated and the incidence choropleth maps, local indicators of spatial autocorrelation cluster maps and space scaning cluster maps were drawn. A total of 4 453 scrub typhus cases were reported during 2006-2014, and the annual incidence increased with year. Among the 17 prefectures(municipality)in Shandong, 13 were affected by scrub typhus. The global Moran's I index was 0.501 5(P<0.01). The differences in local Moran' s I index among 16 prefectures were significant(P<0.01). The " high-high" clustering areas were mainly Wulian county, Lanshan district and Juxian county of Rizhao, Xintai county of Tai' an, Gangcheng and Laicheng districts of Laiwu, Yiyuan county of Zibo and Mengyin county of Linyi. Spatial scan analysis showed that an eastward moving trend of high-risk clusters and two new high-risk clusters were found in Zaozhuang in 2014. The centers of the most likely clusters were in the south central mountainous areas during 2006-2010 and in 2012, eastern hilly areas in 2011, 2013 and 2014, and the size of the clusters expanded in 2008, 2011, 2013 and 2014. One spatial-temporal cluster was detected from October 1, 2014 to November 30, 2014, the center of the cluster was in Rizhao and the radius was 222.34 kilometers. A positive spatial correlation and spatial agglomerations were found in the distribution of autumn-winter type scrub typhus in Shandong. Since 2006, the epidemic area of the disease has expanded and the number of high-risk areas has increased. Moreover, the eastward moving and periodically expanding trends of high-risk clusters were detected.

Prostate cancer and industrial pollution Risk around putative focus in a multi-source scenario.

PubMed

Ramis, Rebeca; Diggle, Peter; Cambra, Koldo; López-Abente, Gonzalo

2011-04-01

Prostate cancer is the second most common type of cancer among men but its aetiology is still largely unknown. Different studies have proposed several risk factors such as ethnic origin, age, genetic factors, hormonal factors, diet and insulin-like growth factor, but the spatial distribution of the disease suggests that other environmental factors are involved. This paper studies the spatial distribution of prostate cancer mortality in an industrialized area using distances from each of a number of industrial facilities as indirect measures of exposure to industrial pollution. We studied the Gran Bilbao area (Spain) with a population of 791,519 inhabitants distributed in 657 census tracts. There were 20 industrial facilities within the area, 8 of them in the central axis of the region. We analysed prostate cancer mortality during the period 1996-2003. There were 883 deaths giving a crude rate of 14 per 100,000 inhabitants. We extended the standard Poisson regression model by the inclusion of a multiplicative non-linear function to model the effect of distance from an industrial facility. The function's shape combined an elevated risk close to the source with a neutral effect at large distance. We also included socio-demographic covariates in the model to control potential confounding. We aggregated the industrial facilities by sector: metal, mineral, chemical and other activities. Results relating to metal industries showed a significantly elevated risk by a factor of approximately 1.4 in the immediate vicinity, decaying with distance to a value of 1.08 at 12km. The remaining sectors did not show a statistically significant excess of risk at the source. Notwithstanding the limitations of this kind of study, we found evidence of association between the spatial distribution of prostate cancer mortality aggregated by census tracts and proximity to metal industrial facilities located within the area, after adjusting for socio-demographic characteristics at municipality level. Copyright © 2010 Elsevier Ltd. All rights reserved.

[Spatial distribution of mercury in soils of a typical small agricultural watershed in the Three Gorges Reservoir region].

PubMed

Wang, Ya; Zhao, Zheng; Mu, Zhi-jian; Wang, Dlng-yong; Yu, Ya-wei

2015-01-01

To understand the mercury (Hg) pollution level and the corresponding ecological risk in agricultural watershed of the Three Gorges Reservoir region, a typical watershed, Wangjiagou, located in Fuling, where is in interior zones of the Three Gorges Reservoir region, was selected as the study object. Meanwhile, ArcGIS geo-statistics module was conducted for investigation of the Hg contents and distribution characteristics in soils of different land use types including dry land, farmland, woodland and settlements. Also the corresponding Hg pollution level and ecological risk were assessed. The results suggested that soil Hg contents in this watershed ranged from 9.47 to 94.57 microg x kg(-1), and the mean value was (34.23 +/- 16.23) microg x kg(-1). Higher Hg contents in surfaces of soils were observed in woodland, followed by farmland and settlement. The lowest was found in dry land. Surfaces of soils significantly showed Hg accumulation, and an obvious inverse correlation between soil Hg contents and soil depths was also observed in this study. Additionally, geo-statistics analysis showed a weak spatial correlation of soil Hg contents in this watershed, indicating the spatial distribution of soil Hg in this watershed was mainly influenced by several natural factors such as atmospheric wet-dry deposit, vegetation coverage and topography, instead of anthropogenic interference. Overall confirmative soil Hg pollution was not found in this watershed, which showed a very low pollution index (-0.08), but a moderate potential ecological risk still existed (the ecological risk index was 57), of which woodland had the highest potential risk. The total capacity of Hg in this watershed was 25.39 kg, among which dry land accounted for 69%.

Missing in space: an evaluation of imputation methods for missing data in spatial analysis of risk factors for type II diabetes.

PubMed

Baker, Jannah; White, Nicole; Mengersen, Kerrie

2014-11-20

Spatial analysis is increasingly important for identifying modifiable geographic risk factors for disease. However, spatial health data from surveys are often incomplete, ranging from missing data for only a few variables, to missing data for many variables. For spatial analyses of health outcomes, selection of an appropriate imputation method is critical in order to produce the most accurate inferences. We present a cross-validation approach to select between three imputation methods for health survey data with correlated lifestyle covariates, using as a case study, type II diabetes mellitus (DM II) risk across 71 Queensland Local Government Areas (LGAs). We compare the accuracy of mean imputation to imputation using multivariate normal and conditional autoregressive prior distributions. Choice of imputation method depends upon the application and is not necessarily the most complex method. Mean imputation was selected as the most accurate method in this application. Selecting an appropriate imputation method for health survey data, after accounting for spatial correlation and correlation between covariates, allows more complete analysis of geographic risk factors for disease with more confidence in the results to inform public policy decision-making.

Threshold exceedance risk assessment in complex space-time systems

NASA Astrophysics Data System (ADS)

Angulo, José M.; Madrid, Ana E.; Romero, José L.

2015-04-01

Environmental and health impact risk assessment studies most often involve analysis and characterization of complex spatio-temporal dynamics. Recent developments in this context are addressed, among other objectives, to proper representation of structural heterogeneities, heavy-tailed processes, long-range dependence, intermittency, scaling behavior, etc. Extremal behaviour related to spatial threshold exceedances can be described in terms of geometrical characteristics and distribution patterns of excursion sets, which are the basis for construction of risk-related quantities, such as in the case of evolutionary study of 'hotspots' and long-term indicators of occurrence of extremal episodes. Derivation of flexible techniques, suitable for both the application under general conditions and the interpretation on singularities, is important for practice. Modern risk theory, a developing discipline motivated by the need to establish solid general mathematical-probabilistic foundations for rigorous definition and characterization of risk measures, has led to the introduction of a variety of classes and families, ranging from some conceptually inspired by specific fields of applications, to some intended to provide generality and flexibility to risk analysts under parametric specifications, etc. Quantile-based risk measures, such as Value-at-Risk (VaR), Average Value-at-Risk (AVaR), and generalization to spectral measures, are of particular interest for assessment under very general conditions. In this work, we study the application of quantile-based risk measures in the spatio-temporal context in relation to certain geometrical characteristics of spatial threshold exceedance sets. In particular, we establish a closed-form relationship between VaR, AVaR, and the expected value of threshold exceedance areas and excess volumes. Conditional simulation allows us, by means of empirical global and local spatial cumulative distributions, the derivation of various statistics of practical interest, and subsequent construction of dynamic risk maps. Further, we study the implementation of static and dynamic spatial deformation under this setup, meaningful, among other aspects, for incorporation of heterogeneities and/or covariate effects, or consideration of external factors for risk measurement. We illustrate this approach though Environment and Health applications. This work is partially supported by grant MTM2012-32666 of the Spanish Ministry of Economy and Competitiveness (co-financed by FEDER).

Including the third dimension: a spatial analysis of TB cases in Houston Harris County.

PubMed

Feske, Marsha L; Teeter, Larry D; Musser, James M; Graviss, Edward A

2011-12-01

To reach the tuberculosis (TB) elimination goals established by the Institute of Medicine (IOM) and the Centers for Disease Control and Prevention (CDC), measures must be taken to speed the currently stagnant TB elimination rate and curtail a future peak in TB incidence. Increases in TB incidence have historically coincided with immigration, poverty, and joblessness; all situations that are currently occurring worldwide. Effective TB elimination strategies will require the geographical elucidation of areas within the U.S. that have endemic TB, and systematic surveillance of the locations and location-based risk factors associated with TB transmission. Surveillance data was used to assess the spatial distribution of cases, the yearly TB incidence by census tract, and the statistical significance of case clustering. The analysis revealed that there are neighborhoods within Houston/Harris County that had a heavy TB burden. The maximum yearly incidence varied from 245/100,000-754/100,000 and was not exclusively dependent of the number of cases reported. Geographically weighted regression identified risk factors associated with the spatial distribution of cases such as: poverty, age, Black race, and foreign birth. Public transportation was also associated with the spatial distribution of cases and census tracts identified as high incidence were found to be irregularly clustered within communities of varied SES. Copyright © 2011 Elsevier Ltd. All rights reserved.

Mapping the Distribution of Anthrax in Mainland China, 2005-2013.

PubMed

Chen, Wan-Jun; Lai, Sheng-Jie; Yang, Yang; Liu, Kun; Li, Xin-Lou; Yao, Hong-Wu; Li, Yu; Zhou, Hang; Wang, Li-Ping; Mu, Di; Yin, Wen-Wu; Fang, Li-Qun; Yu, Hong-Jie; Cao, Wu-Chun

2016-04-01

Anthrax, a global re-emerging zoonotic disease in recent years is enzootic in mainland China. Despite its significance to the public health, spatiotemporal distributions of the disease in human and livestock and its potential driving factors remain poorly understood. Using the national surveillance data of human and livestock anthrax from 2005 to 2013, we conducted a retrospective epidemiological study and risk assessment of anthrax in mainland China. The potential determinants for the temporal and spatial distributions of human anthrax were also explored. We found that the majority of human anthrax cases were located in six provinces in western and northeastern China, and five clustering areas with higher incidences were identified. The disease mostly peaked in July or August, and males aged 30-49 years had higher incidence than other subgroups. Monthly incidence of human anthrax was positively correlated with monthly average temperature, relative humidity and monthly accumulative rainfall with lags of 0-2 months. A boosted regression trees (BRT) model at the county level reveals that densities of cattle, sheep and human, coverage of meadow, coverage of typical grassland, elevation, coverage of topsoil with pH > 6.1, concentration of organic carbon in topsoil, and the meteorological factors have contributed substantially to the spatial distribution of the disease. The model-predicted probability of occurrence of human cases in mainland China was mapped at the county level. Anthrax in China was characterized by significant seasonality and spatial clustering. The spatial distribution of human anthrax was largely driven by livestock husbandry, human density, land cover, elevation, topsoil features and climate. Enhanced surveillance and intervention for livestock and human anthrax in the high-risk regions, particularly on the Qinghai-Tibetan Plateau, is the key to the prevention of human infections.

Mapping the Distribution of Anthrax in Mainland China, 2005–2013

PubMed Central

Yang, Yang; Liu, Kun; Li, Xin-Lou; Yao, Hong-Wu; Li, Yu; Zhou, Hang; Wang, Li-Ping; Mu, Di; Yin, Wen-Wu; Fang, Li-Qun; Yu, Hong-Jie; Cao, Wu-Chun

2016-01-01

Background Anthrax, a global re-emerging zoonotic disease in recent years is enzootic in mainland China. Despite its significance to the public health, spatiotemporal distributions of the disease in human and livestock and its potential driving factors remain poorly understood. Methodology/Principal Findings Using the national surveillance data of human and livestock anthrax from 2005 to 2013, we conducted a retrospective epidemiological study and risk assessment of anthrax in mainland China. The potential determinants for the temporal and spatial distributions of human anthrax were also explored. We found that the majority of human anthrax cases were located in six provinces in western and northeastern China, and five clustering areas with higher incidences were identified. The disease mostly peaked in July or August, and males aged 30–49 years had higher incidence than other subgroups. Monthly incidence of human anthrax was positively correlated with monthly average temperature, relative humidity and monthly accumulative rainfall with lags of 0–2 months. A boosted regression trees (BRT) model at the county level reveals that densities of cattle, sheep and human, coverage of meadow, coverage of typical grassland, elevation, coverage of topsoil with pH > 6.1, concentration of organic carbon in topsoil, and the meteorological factors have contributed substantially to the spatial distribution of the disease. The model-predicted probability of occurrence of human cases in mainland China was mapped at the county level. Conclusions/Significance Anthrax in China was characterized by significant seasonality and spatial clustering. The spatial distribution of human anthrax was largely driven by livestock husbandry, human density, land cover, elevation, topsoil features and climate. Enhanced surveillance and intervention for livestock and human anthrax in the high-risk regions, particularly on the Qinghai-Tibetan Plateau, is the key to the prevention of human infections. PMID:27097318

The Source, Spatial Distribution and Risk Assessment of Heavy Metals in Soil from the Pearl River Delta Based on the National Multi-Purpose Regional Geochemical Survey.

PubMed

Zhang, Lingyan; Guo, Shuhai; Wu, Bo

2015-01-01

The data on the heavy metal content at different soil depths derived from a multi-purpose regional geochemical survey in the Pearl River Delta (PRD) were analyzed using ArcGIS 10.0. By comparing their spatial distributions and areas, the sources of heavy metals (Cd, Hg, As and Pb) were quantitatively identified and explored. Netted measuring points at 25 ×25 km were set over the entire PRD according to the geochemical maps. Based on the calculation data obtained from different soil depths, the concentrations of As and Cd in a large area of the PRD exceeded the National Second-class Standard. The spatial disparity of the geometric centers in the surface soil and deep soil showed that As in the surface soil mainly came from parent materials, while Cd had high consistency in different soil profiles because of deposition in the soil forming process. The migration of Cd also resulted in a considerable ecological risk to the Beijiang and Xijiang River watershed. The potential ecological risk index followed the order Cd ≥ Hg > Pb > As. According to the sources, the distribution trends and the characteristics of heavy metals in the soil from the perspective of the whole area, the Cd pollution should be repaired, especially in the upper reaches of the Xijiang and Beijiang watershed to prevent risk explosion while the pollution of Hg and Pb should be controlled in areas with intense human activity, and supervision during production should be strengthened to maintain the ecological balance of As.

The Source, Spatial Distribution and Risk Assessment of Heavy Metals in Soil from the Pearl River Delta Based on the National Multi-Purpose Regional Geochemical Survey

PubMed Central

Zhang, Lingyan; Guo, Shuhai; Wu, Bo

2015-01-01

The data on the heavy metal content at different soil depths derived from a multi-purpose regional geochemical survey in the Pearl River Delta (PRD) were analyzed using ArcGIS 10.0. By comparing their spatial distributions and areas, the sources of heavy metals (Cd, Hg, As and Pb) were quantitatively identified and explored. Netted measuring points at 25 ×25 km were set over the entire PRD according to the geochemical maps. Based on the calculation data obtained from different soil depths, the concentrations of As and Cd in a large area of the PRD exceeded the National Second-class Standard. The spatial disparity of the geometric centers in the surface soil and deep soil showed that As in the surface soil mainly came from parent materials, while Cd had high consistency in different soil profiles because of deposition in the soil forming process. The migration of Cd also resulted in a considerable ecological risk to the Beijiang and Xijiang River watershed. The potential ecological risk index followed the order Cd ≥ Hg > Pb > As. According to the sources, the distribution trends and the characteristics of heavy metals in the soil from the perspective of the whole area, the Cd pollution should be repaired, especially in the upper reaches of the Xijiang and Beijiang watershed to prevent risk explosion while the pollution of Hg and Pb should be controlled in areas with intense human activity, and supervision during production should be strengthened to maintain the ecological balance of As. PMID:26230506

A method for mapping fire hazard and risk across multiple scales and its application in fire management

Treesearch

Robert E. Keane; Stacy A. Drury; Eva C. Karau; Paul F. Hessburg; Keith M. Reynolds

2010-01-01

This paper presents modeling methods for mapping fire hazard and fire risk using a research model called FIREHARM (FIRE Hazard and Risk Model) that computes common measures of fire behavior, fire danger, and fire effects to spatially portray fire hazard over space. FIREHARM can compute a measure of risk associated with the distribution of these measures over time using...

[Using sequential indicator simulation method to define risk areas of soil heavy metals in farmland.

PubMed

Yang, Hao; Song, Ying Qiang; Hu, Yue Ming; Chen, Fei Xiang; Zhang, Rui

2018-05-01

The heavy metals in soil have serious impacts on safety, ecological environment and human health due to their toxicity and accumulation. It is necessary to efficiently identify the risk area of heavy metals in farmland soil, which is of important significance for environment protection, pollution warning and farmland risk control. We collected 204 samples and analyzed the contents of seven kinds of heavy metals (Cu, Zn, Pb, Cd, Cr, As, Hg) in Zengcheng District of Guangzhou, China. In order to overcame the problems of the data, including the limitation of abnormal values and skewness distribution and the smooth effect with the traditional kriging methods, we used sequential indicator simulation method (SISIM) to define the spatial distribution of heavy metals, and combined Hakanson index method to identify potential ecological risk area of heavy metals in farmland. The results showed that: (1) Based on the similar accuracy of spatial prediction of soil heavy metals, the SISIM had a better expression of detail rebuild than ordinary kriging in small scale area. Compared to indicator kriging, the SISIM had less error rate (4.9%-17.1%) in uncertainty evaluation of heavy-metal risk identification. The SISIM had less smooth effect and was more applicable to simulate the spatial uncertainty assessment of soil heavy metals and risk identification. (2) There was no pollution in Zengcheng's farmland. Moderate potential ecological risk was found in the southern part of study area due to enterprise production, human activities, and river sediments. This study combined the sequential indicator simulation with Hakanson risk index method, and effectively overcame the outlier information loss and smooth effect of traditional kriging method. It provided a new way to identify the soil heavy metal risk area of farmland in uneven sampling.

Wild Fire Risk Map in the Eastern Steppe of Mongolia Using Spatial Multi-Criteria Analysis

NASA Astrophysics Data System (ADS)

Nasanbat, Elbegjargal; Lkhamjav, Ochirkhuyag

2016-06-01

Grassland fire is a cause of major disturbance to ecosystems and economies throughout the world. This paper investigated to identify risk zone of wildfire distributions on the Eastern Steppe of Mongolia. The study selected variables for wildfire risk assessment using a combination of data collection, including Social Economic, Climate, Geographic Information Systems, Remotely sensed imagery, and statistical yearbook information. Moreover, an evaluation of the result is used field validation data and assessment. The data evaluation resulted divided by main three group factors Environmental, Social Economic factor, Climate factor and Fire information factor into eleven input variables, which were classified into five categories by risk levels important criteria and ranks. All of the explanatory variables were integrated into spatial a model and used to estimate the wildfire risk index. Within the index, five categories were created, based on spatial statistics, to adequately assess respective fire risk: very high risk, high risk, moderate risk, low and very low. Approximately more than half, 68 percent of the study area was predicted accuracy to good within the very high, high risk and moderate risk zones. The percentages of actual fires in each fire risk zone were as follows: very high risk, 42 percent; high risk, 26 percent; moderate risk, 13 percent; low risk, 8 percent; and very low risk, 11 percent. The main overall accuracy to correct prediction from the model was 62 percent. The model and results could be support in spatial decision making support system processes and in preventative wildfire management strategies. Also it could be help to improve ecological and biodiversity conservation management.

Spatial and temporal patterns of chronic wasting disease: Fine-scale mapping of a wildlife epidemic in Wisconsin

USGS Publications Warehouse

Osnas, E.E.; Heisey, D.M.; Rolley, R.E.; Samuel, M.D.

2009-01-01

Emerging infectious diseases threaten wildlife populations and human health. Understanding the spatial distributions of these new diseases is important for disease management and policy makers; however, the data are complicated by heterogeneities across host classes, sampling variance, sampling biases, and the space-time epidemic process. Ignoring these issues can lead to false conclusions or obscure important patterns in the data, such as spatial variation in disease prevalence. Here, we applied hierarchical Bayesian disease mapping methods to account for risk factors and to estimate spatial and temporal patterns of infection by chronic wasting disease (CWD) in white-tailed deer (Odocoileus virginianus) of Wisconsin, USA. We found significant heterogeneities for infection due to age, sex, and spatial location. Infection probability increased with age for all young deer, increased with age faster for young males, and then declined for some older animals, as expected from disease-associated mortality and age-related changes in infection risk. We found that disease prevalence was clustered in a central location, as expected under a simple spatial epidemic process where disease prevalence should increase with time and expand spatially. However, we could not detect any consistent temporal or spatiotemporal trends in CWD prevalence. Estimates of the temporal trend indicated that prevalence may have decreased or increased with nearly equal posterior probability, and the model without temporal or spatiotemporal effects was nearly equivalent to models with these effects based on deviance information criteria. For maximum interpretability of the role of location as a disease risk factor, we used the technique of direct standardization for prevalence mapping, which we develop and describe. These mapping results allow disease management actions to be employed with reference to the estimated spatial distribution of the disease and to those host classes most at risk. Future wildlife epidemiology studies should employ hierarchical Bayesian methods to smooth estimated quantities across space and time, account for heterogeneities, and then report disease rates based on an appropriate standardization. ?? 2009 by the Ecological Society of America.

The spatial distribution of gender differences in obesity prevalence differs from overall obesity prevalence among US adults

PubMed Central

Gartner, Danielle R.; Taber, Daniel R.; Hirsch, Jana A.; Robinson, Whitney R.

2016-01-01

Purpose While obesity disparities between racial and socioeconomic groups have been well characterized, those based on gender and geography have not been as thoroughly documented. This study describes obesity prevalence by state, gender, and race/ethnicity to (1) characterize obesity gender inequality, (2) determine if the geographic distribution of inequality is spatially clustered and (3) contrast the spatial clustering patterns of obesity gender inequality with overall obesity prevalence. Methods Data from the Centers for Disease Control and Prevention’s 2013 Behavioral Risk Factor Surveillance System (BRFSS) were used to calculate state-specific obesity prevalence and gender inequality measures. Global and Local Moran’s Indices were calculated to determine spatial autocorrelation. Results Age-adjusted, state-specific obesity prevalence difference and ratio measures show spatial autocorrelation (z-score=4.89, p-value <0.001). Local Moran’s Indices indicate the spatial distributions of obesity prevalence and obesity gender inequalities are not the same. High and low values of obesity prevalence and gender inequalities cluster in different areas of the U.S. Conclusion Clustering of gender inequality suggests that spatial processes operating at the state level, such as occupational or physical activity policies or social norms, are involved in the etiology of the inequality and necessitate further attention to the determinates of obesity gender inequality. PMID:27039046

Relative importance of management, meteorological and environmental factors in the spatial distribution of Fasciola hepatica in dairy cattle in a temperate climate zone.

PubMed

Bennema, S C; Ducheyne, E; Vercruysse, J; Claerebout, E; Hendrickx, G; Charlier, J

2011-02-01

Fasciola hepatica, a trematode parasite with a worldwide distribution, is the cause of important production losses in the dairy industry. Diagnosis is hampered by the fact that the infection is mostly subclinical. To increase awareness and develop regionally adapted control methods, knowledge on the spatial distribution of economically important infection levels is needed. Previous studies modelling the spatial distribution of F. hepatica are mostly based on single cross-sectional samplings and have focussed on climatic and environmental factors, often ignoring management factors. This study investigated the associations between management, climatic and environmental factors affecting the spatial distribution of infection with F. hepatica in dairy herds in a temperate climate zone (Flanders, Belgium) over three consecutive years. A bulk-tank milk antibody ELISA was used to measure F. hepatica infection levels in a random sample of 1762 dairy herds in the autumns of 2006, 2007 and 2008. The infection levels were included in a Geographic Information System together with meteorological, environmental and management parameters. Logistic regression models were used to determine associations between possible risk factors and infection levels. The prevalence and spatial distribution of F. hepatica was relatively stable, with small interannual differences in prevalence and location of clusters. The logistic regression model based on both management and climatic/environmental factors included the factors: annual rainfall, mowing of pastures, proportion of grazed grass in the diet and length of grazing season as significant predictors and described the spatial distribution of F. hepatica better than the model based on climatic/environmental factors only (annual rainfall, elevation and slope, soil type), with an Area Under the Curve of the Receiver Operating Characteristic of 0.68 compared with 0.62. The results indicate that in temperate climate zones without large climatic and environmental variation, management factors affect the spatial distribution of F. hepatica, and should be included in future spatial distribution models. Copyright © 2010 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

GIS-based spatial statistical analysis of risk areas for liver flukes in Surin Province of Thailand.

PubMed

Rujirakul, Ratana; Ueng-arporn, Naporn; Kaewpitoon, Soraya; Loyd, Ryan J; Kaewthani, Sarochinee; Kaewpitoon, Natthawut

2015-01-01

It is urgently necessary to be aware of the distribution and risk areas of liver fluke, Opisthorchis viverrini, for proper allocation of prevention and control measures. This study aimed to investigate the human behavior, and environmental factors influencing the distribution in Surin Province of Thailand, and to build a model using stepwise multiple regression analysis with a geographic information system (GIS) on environment and climate data. The relationship between the human behavior, attitudes (<50%; X111), environmental factors like population density (148-169 pop/km2; X73), and land use as wetland (X64), were correlated with the liver fluke disease distribution at 0.000, 0.034, and 0.006 levels, respectively. Multiple regression analysis, by equations OV=-0.599+0.005(population density (148-169 pop/km2); X73)+0.040 (human attitude (<50%); X111)+0.022 (land used (wetland; X64), was used to predict the distribution of liver fluke. OV is the patients of liver fluke infection, R Square=0.878, and, Adjust R Square=0.849. By GIS analysis, we found Si Narong, Sangkha, Phanom Dong Rak, Mueang Surin, Non Narai, Samrong Thap, Chumphon Buri, and Rattanaburi to have the highest distributions in Surin province. In conclusion, the combination of GIS and statistical analysis can help simulate the spatial distribution and risk areas of liver fluke, and thus may be an important tool for future planning of prevention and control measures.

[Study on the risk assessment method of regional groundwater pollution].

PubMed

Yang, Yan; Yu, Yun-Jiang; Wang, Zong-Qing; Li, Ding-Long; Sun, Hong-Wei

2013-02-01

Based on the boundary elements of system risk assessment, the regional groundwater pollution risk assessment index system was preliminarily established, which included: regional groundwater specific vulnerability assessment, the regional pollution sources characteristics assessment and the health risk assessment of regional featured pollutants. The three sub-evaluation systems were coupled with the multi-index comprehensive method, the risk was characterized with the Spatial Analysis of ArcMap, and a new method to evaluate regional groundwater pollution risk that suitable for different parts of natural conditions, different types of pollution was established. Take Changzhou as an example, the risk of shallow groundwater pollution was studied with the new method, and found that the vulnerability index of groundwater in Changzhou is high and distributes unevenly; The distribution of pollution sources is concentrated and has a great impact on groundwater pollution risks; Influenced by the pollutants and pollution sources, the values of health risks are high in the urban area of Changzhou. The pollution risk of shallow groundwater is high and distributes unevenly, and distributes in the north of the line of Anjia-Xuejia-Zhenglu, the center of the city and the southeast, where the human activities are more intense and the pollution sources are intensive.

Spatio-temporal assessment of food safety risks in Canadian food distribution systems using GIS.

PubMed

Hashemi Beni, Leila; Villeneuve, Sébastien; LeBlanc, Denyse I; Côté, Kevin; Fazil, Aamir; Otten, Ainsley; McKellar, Robin; Delaquis, Pascal

2012-09-01

While the value of geographic information systems (GIS) is widely applied in public health there have been comparatively few examples of applications that extend to the assessment of risks in food distribution systems. GIS can provide decision makers with strong computing platforms for spatial data management, integration, analysis, querying and visualization. The present report addresses some spatio-analyses in a complex food distribution system and defines influence areas as travel time zones generated through road network analysis on a national scale rather than on a community scale. In addition, a dynamic risk index is defined to translate a contamination event into a public health risk as time progresses. More specifically, in this research, GIS is used to map the Canadian produce distribution system, analyze accessibility to contaminated product by consumers, and estimate the level of risk associated with a contamination event over time, as illustrated in a scenario. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

Spatial distribution and socioeconomic context of tuberculosis in Rio de Janeiro, Brazil

PubMed Central

Pereira, Alessandra Gonçalves Lisbôa; Medronho, Roberto de Andrade; Escosteguy, Claudia Caminha; Valencia, Luis Iván Ortiz; Magalhães, Mônica de Avelar Figueiredo Mafra

2015-01-01

OBJECTIVE To analyze the spatial distribution of risk for tuberculosis and its socioeconomic determinants in the city of Rio de Janeiro, Brazil. METHODS An ecological study on the association between the mean incidence rate of tuberculosis from 2004 to 2006 and socioeconomic indicators of the Censo Demográfico (Demographic Census) of 2000. The unit of analysis was the home district registered in the Sistema de Informação de Agravos de Notificação (Notifiable Diseases Information System) of Rio de Janeiro, Southeastern Brazil. The rates were standardized by sex and age group, and smoothed by the empirical Bayes method. Spatial autocorrelation was evaluated by Moran’s I. Multiple linear regression models were studied and the appropriateness of incorporating the spatial component in modeling was evaluated. RESULTS We observed a higher risk of the disease in some neighborhoods of the port and north regions, as well as a high incidence in the slums of Rocinha and Vidigal, in the south region, and Cidade de Deus, in the west. The final model identified a positive association for the variables: percentage of permanent private households in which the head of the house earns three to five minimum wages; percentage of individual residents in the neighborhood; and percentage of people living in homes with more than two people per bedroom. CONCLUSIONS The spatial analysis identified areas of risk of tuberculosis incidence in the neighborhoods of the city of Rio de Janeiro and also found spatial dependence for the incidence of tuberculosis and some socioeconomic variables. However, the inclusion of the space component in the final model was not required during the modeling process. PMID:26270014

Spatial distribution and socioeconomic context of tuberculosis in Rio de Janeiro, Brazil.

PubMed

Pereira, Alessandra Gonçalves Lisbôa; Medronho, Roberto de Andrade; Escosteguy, Claudia Caminha; Valencia, Luis Iván Ortiz; Magalhães, Mônica de Avelar Figueiredo Mafra

2015-01-01

OBJECTIVE To analyze the spatial distribution of risk for tuberculosis and its socioeconomic determinants in the city of Rio de Janeiro, Brazil. METHODS An ecological study on the association between the mean incidence rate of tuberculosis from 2004 to 2006 and socioeconomic indicators of the Censo Demográfico (Demographic Census) of 2000. The unit of analysis was the home district registered in the Sistema de Informação de Agravos de Notificação (Notifiable Diseases Information System) of Rio de Janeiro, Southeastern Brazil. The rates were standardized by sex and age group, and smoothed by the empirical Bayes method. Spatial autocorrelation was evaluated by Moran's I. Multiple linear regression models were studied and the appropriateness of incorporating the spatial component in modeling was evaluated. RESULTS We observed a higher risk of the disease in some neighborhoods of the port and north regions, as well as a high incidence in the slums of Rocinha and Vidigal, in the south region, and Cidade de Deus, in the west. The final model identified a positive association for the variables: percentage of permanent private households in which the head of the house earns three to five minimum wages; percentage of individual residents in the neighborhood; and percentage of people living in homes with more than two people per bedroom. CONCLUSIONS The spatial analysis identified areas of risk of tuberculosis incidence in the neighborhoods of the city of Rio de Janeiro and also found spatial dependence for the incidence of tuberculosis and some socioeconomic variables. However, the inclusion of the space component in the final model was not required during the modeling process.

Using biogeographic distributions and natural history to predict marine/estuarine species at risk to climate change

EPA Science Inventory

Effects of climate change on marine and estuarine species will vary with attributes of the species and the spatial patterns of environmental change at the habitat and global scales. To better predict which species are at greatest risk, we are developing a knowledge base of specie...

Spatial distribution and historical trends of heavy metals in the sediments of petroleum producing regions of the Beibu Gulf, China.

PubMed

Yang, Jichao; Wang, Weiguo; Zhao, Mengwei; Chen, Bin; Dada, Olusegun A; Chu, Zhihui

2015-02-15

The concentrations of As, Sb, Hg, Pb, Cd, and Ba in the surface and core sediments of the oil and gas producing region of the Beibu Gulf were measured by Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES), Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and Atomic Fluorescence Spectrometry (AFS), and the spatial distribution and historical trends of these elements are discussed. The results show that the concentrations of these elements are highest near the platforms. The results of Enrichment Factor (EF) and Potential Ecological Risk Index (PERI) also reveal significantly higher enrichment around the platforms, which imply that the offshore petroleum production was the cause of the unusual distribution and severe enrichment of these elements in the study area. The environment around the platforms was highly laden with toxic elements, thereby representing a very high ecological risk to the environment of the study area. Copyright © 2014 Elsevier Ltd. All rights reserved.

The landscape of fear as an emergent property of heterogeneity: Contrasting patterns of predation risk in grassland ecosystems.

PubMed

Atuo, Fidelis Akunke; O'Connell, Timothy John

2017-07-01

The likelihood of encountering a predator influences prey behavior and spatial distribution such that non-consumptive effects can outweigh the influence of direct predation. Prey species are thought to filter information on perceived predator encounter rates in physical landscapes into a landscape of fear defined by spatially explicit heterogeneity in predation risk. The presence of multiple predators using different hunting strategies further complicates navigation through a landscape of fear and potentially exposes prey to greater risk of predation. The juxtaposition of land cover types likely influences overlap in occurrence of different predators, suggesting that attributes of a landscape of fear result from complexity in the physical landscape. Woody encroachment in grasslands furnishes an example of increasing complexity with the potential to influence predator distributions. We examined the role of vegetation structure on the distribution of two avian predators, Red-tailed Hawk ( Buteo jamaicensis ) and Northern Harrier ( Circus cyaneus ), and the vulnerability of a frequent prey species of those predators, Northern Bobwhite ( Colinus virginianus ). We mapped occurrences of the raptors and kill locations of Northern Bobwhite to examine spatial vulnerability patterns in relation to landscape complexity. We use an offset model to examine spatially explicit habitat use patterns of these predators in the Southern Great Plains of the United States, and monitored vulnerability patterns of their prey species based on kill locations collected during radio telemetry monitoring. Both predator density and predation-specific mortality of Northern Bobwhite increased with vegetation complexity generated by fine-scale interspersion of grassland and woodland. Predation pressure was lower in more homogeneous landscapes where overlap of the two predators was less frequent. Predator overlap created areas of high risk for Northern Bobwhite amounting to 32% of the land area where landscape complexity was high and 7% where complexity was lower. Our study emphasizes the need to evaluate the role of landscape structure on predation dynamics and reveals another threat from woody encroachment in grasslands.

Harmful algal bloom characterization at ultra-high spatial and temporal resolution using small unmanned aircraft systems.

PubMed

Van der Merwe, Deon; Price, Kevin P

2015-03-27

Harmful algal blooms (HABs) degrade water quality and produce toxins. The spatial distribution of HAbs may change rapidly due to variations wind, water currents, and population dynamics. Risk assessments, based on traditional sampling methods, are hampered by the sparseness of water sample data points, and delays between sampling and the availability of results. There is a need for local risk assessment and risk management at the spatial and temporal resolution relevant to local human and animal interactions at specific sites and times. Small, unmanned aircraft systems can gather color-infrared reflectance data at appropriate spatial and temporal resolutions, with full control over data collection timing, and short intervals between data gathering and result availability. Data can be interpreted qualitatively, or by generating a blue normalized difference vegetation index (BNDVI) that is correlated with cyanobacterial biomass densities at the water surface, as estimated using a buoyant packed cell volume (BPCV). Correlations between BNDVI and BPCV follow a logarithmic model, with r(2)-values under field conditions from 0.77 to 0.87. These methods provide valuable information that is complimentary to risk assessment data derived from traditional risk assessment methods, and could help to improve risk management at the local level.

Harmful Algal Bloom Characterization at Ultra-High Spatial and Temporal Resolution Using Small Unmanned Aircraft Systems

PubMed Central

Van der Merwe, Deon; Price, Kevin P.

2015-01-01

Harmful algal blooms (HABs) degrade water quality and produce toxins. The spatial distribution of HAbs may change rapidly due to variations wind, water currents, and population dynamics. Risk assessments, based on traditional sampling methods, are hampered by the sparseness of water sample data points, and delays between sampling and the availability of results. There is a need for local risk assessment and risk management at the spatial and temporal resolution relevant to local human and animal interactions at specific sites and times. Small, unmanned aircraft systems can gather color-infrared reflectance data at appropriate spatial and temporal resolutions, with full control over data collection timing, and short intervals between data gathering and result availability. Data can be interpreted qualitatively, or by generating a blue normalized difference vegetation index (BNDVI) that is correlated with cyanobacterial biomass densities at the water surface, as estimated using a buoyant packed cell volume (BPCV). Correlations between BNDVI and BPCV follow a logarithmic model, with r2-values under field conditions from 0.77 to 0.87. These methods provide valuable information that is complimentary to risk assessment data derived from traditional risk assessment methods, and could help to improve risk management at the local level. PMID:25826055

[Distribution of polycyclic aromatic hydrocarbons in water and sediment from Zhoushan coastal area, China].

PubMed

Jiang, Min; Tuan, Le Huy; Mei, Wei-Ping; Ruan, Hui-Hui; Wu, Hao

2014-07-01

The spatial and temporal distribution of 16 polycyclic aromatic hydrocarbons (PAHs) has been investigated in water and sediments of Zhoushan coastal area every two months in 2012. The concentrations of total PAHs ranged from 382.3 to 816.9 ng x L(-1), with the mean value of 552.5 ng x L(-1) in water; whereas it ranged from 1017.9 to 3047.1 ng x g(-1), with the mean value of 2 022.4 ng x g(-1) in sediment. Spatial distribution showed that Yangshan and Yanwoshan offshore area had the maximum and minimum of total PAHs contents in water, while the maximum and minimum occurred at Yangshan and Zhujiajian Nansha offshore area in sediment. Temporal distribution revealed that total PAHs contents in water reached the maximum and minimum values in October and June, however in sediments these values were found in August and June, respectively. The PAHs pollution was affected by oil emission, charcoal and coal combustion. Using the biological threshold and exceeded coefficient method to assess the ecological risk of PAHs in Zhoushan coastal area, the result showed that sigma PAHs had a lower probability of potential risk, while there was a higher probability of potential risk for acenaphthylene monomer, and there might be ecological risk for acenaphthene and fluorene. Distribution of PAHs between sediment and water showed that Zhoushan coastal sediment enriched a lot of PAHs, meanwhile the enrichment coefficient (K(d) value) of sediment in Daishan island was larger than that in Zhoushan main island.

Antibiotics in the coastal environment of the Hailing Bay region, South China Sea: Spatial distribution, source analysis and ecological risks.

PubMed

Chen, Hui; Liu, Shan; Xu, Xiang-Rong; Zhou, Guang-Jie; Liu, Shuang-Shuang; Yue, Wei-Zhong; Sun, Kai-Feng; Ying, Guang-Guo

2015-06-15

In this study, the occurrence and spatial distribution of 38 antibiotics in surface water and sediment samples of the Hailing Bay region, South China Sea, were investigated. Twenty-one, 16 and 15 of 38 antibiotics were detected with the concentrations ranging from <0.08 (clarithromycin) to 15,163ng/L (oxytetracycline), 2.12 (methacycline) to 1318ng/L (erythromycin-H2O), <1.95 (ciprofloxacin) to 184ng/g (chlortetracycline) in the seawater, discharged effluent and sediment samples, respectively. The concentrations of antibiotics in the water phase were correlated positively with chemical oxygen demand and nitrate. The source analysis indicated that untreated domestic sewage was the primary source of antibiotics in the study region. Fluoroquinolones showed strong sorption capacity onto sediments due to their high pseudo-partitioning coefficients. Risk assessment indicated that oxytetracycline, norfloxacin and erythromycin-H2O posed high risks to aquatic organisms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Adaptive web sampling.

PubMed

Thompson, Steven K

2006-12-01

A flexible class of adaptive sampling designs is introduced for sampling in network and spatial settings. In the designs, selections are made sequentially with a mixture distribution based on an active set that changes as the sampling progresses, using network or spatial relationships as well as sample values. The new designs have certain advantages compared with previously existing adaptive and link-tracing designs, including control over sample sizes and of the proportion of effort allocated to adaptive selections. Efficient inference involves averaging over sample paths consistent with the minimal sufficient statistic. A Markov chain resampling method makes the inference computationally feasible. The designs are evaluated in network and spatial settings using two empirical populations: a hidden human population at high risk for HIV/AIDS and an unevenly distributed bird population.

New method for generating breast models featuring glandular tissue spatial distribution

NASA Astrophysics Data System (ADS)

Paixão, L.; Oliveira, B. B.; Oliveira, M. A.; Teixeira, M. H. A.; Fonseca, T. C. F.; Nogueira, M. S.

2016-02-01

Mammography is the main radiographic technique used for breast imaging. A major concern with mammographic imaging is the risk of radiation-induced breast cancer due to the high sensitivity of breast tissue. The mean glandular dose (DG) is the dosimetric quantity widely accepted to characterize the risk of radiation induced cancer. Previous studies have concluded that DG depends not only on the breast glandular content but also on the spatial distribution of glandular tissue within the breast. In this work, a new method for generating computational breast models featuring skin composition and glandular tissue distribution from patients undergoing digital mammography is proposed. Such models allow a more accurate way of calculating individualized breast glandular doses taking into consideration the glandular tissue fraction. Sixteen breast models of four patients with different glandularity breasts were simulated and the results were compared with those obtained from recommended DG conversion factors. The results show that the internationally recommended conversion factors may be overestimating the mean glandular dose to less dense breasts and underestimating the mean glandular dose for denser breasts. The methodology described in this work constitutes a powerful tool for breast dosimetry, especially for risk studies.

A spatio-temporal analysis of BSE cases born before and after the reinforced feed ban in France.

PubMed

Ducrot, Christian; Abrial, David; Calavas, Didier; Carpenter, Tim

2005-01-01

A spatio-temporal analysis was carried out to see how the risk distribution of bovine spongiform encephalopathy (BSE) in France changed depending on the period of birth. The data concerned the 539 BSE cases born in France after the ban (BAB) of meat and bone meal (MBM) in 1990 and detected between July 1, 2001 and December 31, 2003, when the surveillance of BSE was comprehensive. Seventy-two of these cases were born after the reinforced (second) ban (BASB) in 1996, which involved the removal of BSE-risk materials and cadavers from the processing of MBM. The Ederer-Myers-Mantel (EMM) time and space cluster test was applied, after classifying the cases by trimester and region of birth, BAB or BASB status, and dairy or beef status. Then disease mapping was performed for four successive birth periods, three for the BAB cases (January 1991 through June 1994, July 1994 through June 1995, July 1995 through June 1996), and one for the BASB (July 1996 through October 1998). It was elaborated with the Bayesian graphical modelling methods and based on a Poisson distribution with spatial smoothing. The parameters were estimated by a Markov Chain Monte Carlo (MCMC) simulation method. The main finding was that the areas with the highest risk of BSE changed largely from one birth period to another; from the west, it reached the east of France for birth cohort 1994-1995 and the southwest for birth cohort 1995-1996. The EMM test identified a peak risk in this region both for dairy and beef cattle in the fall 1995. The spatial distribution of the risk for the BASB cases matched the spatial pattern of risk for the preceding BAB birth cohort quite well; this was in favour of a common origin of the infection of the BAB and BASB cases, despite the complementary control measures.

Confronting the Paradox of Enrichment to the Metacommunity Perspective

PubMed Central

Hauzy, Céline; Nadin, Grégoire; Canard, Elsa; Gounand, Isabelle; Mouquet, Nicolas; Ebenman, Bo

2013-01-01

Resource enrichment can potentially destabilize predator-prey dynamics. This phenomenon historically referred as the "paradox of enrichment" has mostly been explored in spatially homogenous environments. However, many predator-prey communities exchange organisms within spatially heterogeneous networks called metacommunities. This heterogeneity can result from uneven distribution of resources among communities and thus can lead to the spreading of local enrichment within metacommunities. Here, we adapted the original Rosenzweig-MacArthur predator-prey model, built to study the paradox of enrichment, to investigate the effect of regional enrichment and of its spatial distribution on predator-prey dynamics in metacommunities. We found that the potential for destabilization was depending on the connectivity among communities and the spatial distribution of enrichment. In one hand, we found that at low dispersal regional enrichment led to the destabilization of predator-prey dynamics. This destabilizing effect was more pronounced when the enrichment was uneven among communities. In the other hand, we found that high dispersal could stabilize the predator-prey dynamics when the enrichment was spatially heterogeneous. Our results illustrate that the destabilizing effect of enrichment can be dampened when the spatial scale of resource enrichment is lower than that of organismss movements (heterogeneous enrichment). From a conservation perspective, our results illustrate that spatial heterogeneity could decrease the regional extinction risk of species involved in specialized trophic interactions. From the perspective of biological control, our results show that the heterogeneous distribution of pest resource could favor or dampen outbreaks of pests and of their natural enemies, depending on the spatial scale of heterogeneity. PMID:24358242

Multilevel Analysis of Trachomatous Trichiasis and Corneal Opacity in Nigeria: The Role of Environmental and Climatic Risk Factors on the Distribution of Disease.

PubMed

Smith, Jennifer L; Sivasubramaniam, Selvaraj; Rabiu, Mansur M; Kyari, Fatima; Solomon, Anthony W; Gilbert, Clare

2015-01-01

The distribution of trachoma in Nigeria is spatially heterogeneous, with large-scale trends observed across the country and more local variation within areas. Relative contributions of individual and cluster-level risk factors to the geographic distribution of disease remain largely unknown. The primary aim of this analysis is to assess the relationship between climatic factors and trachomatous trichiasis (TT) and/or corneal opacity (CO) due to trachoma in Nigeria, while accounting for the effects of individual risk factors and spatial correlation. In addition, we explore the relative importance of variation in the risk of trichiasis and/or corneal opacity (TT/CO) at different levels. Data from the 2007 National Blindness and Visual Impairment Survey were used for this analysis, which included a nationally representative sample of adults aged 40 years and above. Complete data were available from 304 clusters selected using a multi-stage stratified cluster-random sampling strategy. All participants (13,543 individuals) were interviewed and examined by an ophthalmologist for the presence or absence of TT and CO. In addition to field-collected data, remotely sensed climatic data were extracted for each cluster and used to fit Bayesian hierarchical logistic models to disease outcome. The risk of TT/CO was associated with factors at both the individual and cluster levels, with approximately 14% of the total variation attributed to the cluster level. Beyond established individual risk factors (age, gender and occupation), there was strong evidence that environmental/climatic factors at the cluster-level (lower precipitation, higher land surface temperature, higher mean annual temperature and rural classification) were also associated with a greater risk of TT/CO. This study establishes the importance of large-scale risk factors in the geographical distribution of TT/CO in Nigeria, supporting anecdotal evidence that environmental conditions are associated with increased risk in this context and highlighting their potential use in improving estimates of disease burden at large scales.

Schistosomiasis mansoni incidence data in Rwanda can improve prevalence assessments, by providing high-resolution hotspot and risk factors identification.

PubMed

Nyandwi, E; Veldkamp, A; Amer, S; Karema, C; Umulisa, I

2017-10-25

Schistosomiasis mansoni constitutes a significant public health problem in Rwanda. The nationwide prevalence mapping conducted in 2007-2008 revealed that prevalence per district ranges from 0 to 69.5% among school children. In response, mass drug administration campaigns were initiated. However, a few years later some additional small-scale studies revealed the existence of areas of high transmission in districts formerly classified as low endemic suggesting the need for a more accurate methodology for identification of hotspots. This study investigated if confirmed cases of schistosomiasis recorded at health facility level can be used to, next to existing prevalence data, detect geographically more accurate hotspots of the disease and its associated risk factors. A GIS-based spatial and statistical analysis was carried out. Confirmed cases, recorded at primary health facilities level, were combined with demographic data to calculate incidence rates for each of 367 health facility service area. Empirical Bayesian smoothing was used to deal with rate instability. Incidence rates were compared with prevalence data to identify their level of agreement. Spatial autocorrelation of the incidence rates was analyzed using Moran's Index, to check if spatial clustering occurs. Finally, the spatial relationship between schistosomiasis distribution and potential risk factors was assessed using multiple regression. Incidence rates for 2007-2008 were highly correlated with prevalence values (R 2  = 0.79), indicating that in the case of Rwanda incidence data can be used as a proxy for prevalence data. We observed a focal distribution of schistosomiasis with a significant spatial autocorrelation (Moran's I > 0: 0,05-0.20 and p ≤ 0,05), indicating the occurrence of hotspots. Regarding risk factors, it was identified that the spatial pattern of schistosomiasis is significantly associated with wetland conditions and rice cultivation. In Rwanda the high density of health facilities and the standardized microscopic laboratory diagnostic allow the derived data to be used to complement prevalence studies to identify hotspots of schistosomiasis and its associated risk factors. This type of information, in turn, can support disease control interventions and monitoring.

Evaluation of agricultural nonpoint source pollution potential risk over China with a Transformed-Agricultural Nonpoint Pollution Potential Index method.

PubMed

Yang, Fei; Xu, Zhencheng; Zhu, Yunqiang; He, Chansheng; Wu, Genyi; Qiu, Jin Rong; Fu, Qiang; Liu, Qingsong

2013-01-01

Agricultural nonpoint source (NPS) pollution has been the most important threat to water environment quality. Understanding the spatial distribution of NPS pollution potential risk is important for taking effective measures to control and reduce NPS pollution. A Transformed-Agricultural Nonpoint Pollution Potential Index (T-APPI) model was constructed for evaluating the national NPS pollution potential risk in this study; it was also combined with remote sensing and geographic information system techniques for evaluation on the large scale and at 1 km2 spatial resolution. This model considers many factors contributing to the NPS pollution as the original APPI model, summarized as four indicators of the runoff, sediment production, chemical use and the people and animal load. These four indicators were analysed in detail at 1 km2 spatial resolution throughout China. The T-APPI model distinguished the four indicators into pollution source factors and transport process factors; it also took their relationship into consideration. The studied results showed that T-APPI is a credible and convenient method for NPS pollution potential risk evaluation. The results also indicated that the highest NPS pollution potential risk is distributed in the middle-southern Jiangsu province. Several other regions, including the North China Plain, Chengdu Basin Plain, Jianghan Plain, cultivated lands in Guangdong and Guangxi provinces, also showed serious NPS pollution potential. This study can provide a scientific reference for predicting the future NPS pollution risk throughout China and may be helpful for taking reasonable and effective measures for preventing and controlling NPS pollution.

Mapping snow depth return levels: smooth spatial modeling versus station interpolation

NASA Astrophysics Data System (ADS)

Blanchet, J.; Lehning, M.

2010-12-01

For adequate risk management in mountainous countries, hazard maps for extreme snow events are needed. This requires the computation of spatial estimates of return levels. In this article we use recent developments in extreme value theory and compare two main approaches for mapping snow depth return levels from in situ measurements. The first one is based on the spatial interpolation of pointwise extremal distributions (the so-called Generalized Extreme Value distribution, GEV henceforth) computed at station locations. The second one is new and based on the direct estimation of a spatially smooth GEV distribution with the joint use of all stations. We compare and validate the different approaches for modeling annual maximum snow depth measured at 100 sites in Switzerland during winters 1965-1966 to 2007-2008. The results show a better performance of the smooth GEV distribution fitting, in particular where the station network is sparser. Smooth return level maps can be computed from the fitted model without any further interpolation. Their regional variability can be revealed by removing the altitudinal dependent covariates in the model. We show how return levels and their regional variability are linked to the main climatological patterns of Switzerland.

Spatial distribution of malaria in Peninsular Malaysia from 2000 to 2009.

PubMed

Alias, Haridah; Surin, Johari; Mahmud, Rohela; Shafie, Aziz; Mohd Zin, Junaidden; Mohamad Nor, Mahadzir; Ibrahim, Ahmad Shah; Rundi, Christina

2014-04-15

Malaria is still an endemic disease of public health importance in Malaysia. Populations at risk of contracting malaria includes indigenous people, traditional villagers, mobile ethnic groups and land scheme settlers, immigrants from malaria endemic countries as well as jungle workers and loggers. The predominant species are Plasmodium falciparum and P. vivax. An increasing number of P. knowlesi infections have also been encountered. The principal vectors in Peninsular Malaysia are Anopheles maculatus and An. cracens. This study aims to determine the changes in spatial distribution of malaria in Peninsular Malaysia from year 2000-2009. Data for the study was collected from Ministry of Health, Malaysia and was analysed using Geographic Information System (GIS). Changes for a period of 10 years of malaria spatial distribution in 12 states of Peninsular Malaysia were documented and discussed. This is illustrated by digital mapping according to five variables; incidence rate (IR), fatality rate (FR), annual blood examination rate (ABER), annual parasite index (API) and slide positivity rate (SPR). There is a profound change in the spatial distribution of malaria within a 10-year period. This is evident from the digital mapping of the infection in Peninsular Malaysia.

Spatial clustering of mental disorders and associated characteristics of the neighbourhood context in Malmö, Sweden, in 2001

PubMed Central

Chaix, Basile; Leyland, Alastair H; Sabel, Clive E; Chauvin, Pierre; Råstam, Lennart; Kristersson, Håkan; Merlo, Juan

2006-01-01

Study objective Previous research provides preliminary evidence of spatial variations of mental disorders and associations between neighbourhood social context and mental health. This study expands past literature by (1) using spatial techniques, rather than multilevel models, to compare the spatial distributions of two groups of mental disorders (that is, disorders due to psychoactive substance use, and neurotic, stress related, and somatoform disorders); and (2) investigating the independent impact of contextual deprivation and neighbourhood social disorganisation on mental health, while assessing both the magnitude and the spatial scale of these effects. Design Using different spatial techniques, the study investigated mental disorders due to psychoactive substance use, and neurotic disorders. Participants All 89 285 persons aged 40–69 years residing in Malmö, Sweden, in 2001, geolocated to their place of residence. Main results The spatial scan statistic identified a large cluster of increased prevalence in a similar location for the two mental disorders in the northern part of Malmö. However, hierarchical geostatistical models showed that the two groups of disorders exhibited a different spatial distribution, in terms of both magnitude and spatial scale. Mental disorders due to substance consumption showed larger neighbourhood variations, and varied in space on a larger scale, than neurotic disorders. After adjustment for individual factors, the risk of substance related disorders increased with neighbourhood deprivation and neighbourhood social disorganisation. The risk of neurotic disorders only increased with contextual deprivation. Measuring contextual factors across continuous space, it was found that these associations operated on a local scale. Conclusions Taking space into account in the analyses permitted deeper insight into the contextual determinants of mental disorders. PMID:16614334

Spatiotemporal Determinants of Urban Leptospirosis Transmission: Four-Year Prospective Cohort Study of Slum Residents in Brazil

PubMed Central

Hagan, José E.; Moraga, Paula; Costa, Federico; Capian, Nicolas; Ribeiro, Guilherme S.; Wunder, Elsio A.; Felzemburgh, Ridalva D. M.; Reis, Renato B.; Nery, Nivison; Santana, Francisco S.; Fraga, Deborah; dos Santos, Balbino L.; Santos, Andréia C.; Queiroz, Adriano; Tassinari, Wagner; Carvalho, Marilia S.; Reis, Mitermayer G.; Diggle, Peter J.; Ko, Albert I.

2016-01-01

Background Rat-borne leptospirosis is an emerging zoonotic disease in urban slum settlements for which there are no adequate control measures. The challenge in elucidating risk factors and informing approaches for prevention is the complex and heterogeneous environment within slums, which vary at fine spatial scales and influence transmission of the bacterial agent. Methodology/Principal Findings We performed a prospective study of 2,003 slum residents in the city of Salvador, Brazil during a four-year period (2003–2007) and used a spatiotemporal modelling approach to delineate the dynamics of leptospiral transmission. Household interviews and Geographical Information System surveys were performed annually to evaluate risk exposures and environmental transmission sources. We completed annual serosurveys to ascertain leptospiral infection based on serological evidence. Among the 1,730 (86%) individuals who completed at least one year of follow-up, the infection rate was 35.4 (95% CI, 30.7–40.6) per 1,000 annual follow-up events. Male gender, illiteracy, and age were independently associated with infection risk. Environmental risk factors included rat infestation (OR 1.46, 95% CI, 1.00–2.16), contact with mud (OR 1.57, 95% CI 1.17–2.17) and lower household elevation (OR 0.92 per 10m increase in elevation, 95% CI 0.82–1.04). The spatial distribution of infection risk was highly heterogeneous and varied across small scales. Fixed effects in the spatiotemporal model accounted for the majority of the spatial variation in risk, but there was a significant residual component that was best explained by the spatial random effect. Although infection risk varied between years, the spatial distribution of risk associated with fixed and random effects did not vary temporally. Specific “hot-spots” consistently had higher transmission risk during study years. Conclusions/Significance The risk for leptospiral infection in urban slums is determined in large part by structural features, both social and environmental. Our findings indicate that topographic factors such as household elevation and inadequate drainage increase risk by promoting contact with mud and suggest that the soil-water interface serves as the environmental reservoir for spillover transmission. The use of a spatiotemporal approach allowed the identification of geographic outliers with unexplained risk patterns. This approach, in addition to guiding targeted community-based interventions and identifying new hypotheses, may have general applicability towards addressing environmentally-transmitted diseases that have emerged in complex urban slum settings. PMID:26771379

Modelling Soil Erosion in the Densu River Basin Using RUSLE and GIS Tools.

PubMed

Ashiagbori, G; Forkuo, E K; Laari, P; Aabeyir, R

2014-07-01

Soil erosion involves detachment and transport of soil particles from top soil layers, degrading soil quality and reducing the productivity of affected lands. Soil eroded from the upland catchment causes depletion of fertile agricultural land and the resulting sediment deposited at the river networks creates river morphological change and reservoir sedimentation problems. However, land managers and policy makers are more interested in the spatial distribution of soil erosion risk than in absolute values of soil erosion loss. The aim of this paper is to model the spatial distribution of soil erosion in Densu River Basin of Ghana using RUSLE and GIS tools and to use the model to explore the relationship between erosion susceptibility, slope and land use/land cover (LULC) in the Basin. The rainfall map, digital elevation model, soil type map, and land cover map, were input data in the soil erosion model developed. This model was then categorized into four different erosion risk classes. The developed soil erosion map was then overlaid with the slope and LULC maps of the study area to explore their effects on erosion susceptibility of the soil in the Densu River Basin. The Model, predicted 88% of the basin as low erosion risk and 6% as moderate erosion risk, 3% as high erosion risk and 3% as severe risk. The high and severe erosion areas were distributed mainly within the areas of high slope gradient and also sections of the moderate forest LULC class. Also, the areas within the moderate forest LULC class found to have high erosion risk, had an intersecting high erodibility soil group.

Spatial distribution estimation of malaria in northern China and its scenarios in 2020, 2030, 2040 and 2050.

PubMed

Song, Yongze; Ge, Yong; Wang, Jinfeng; Ren, Zhoupeng; Liao, Yilan; Peng, Junhuan

2016-07-07

Malaria is one of the most severe parasitic diseases in the world. Spatial distribution estimation of malaria and its future scenarios are important issues for malaria control and elimination. Furthermore, sophisticated nonlinear relationships for prediction between malaria incidence and potential variables have not been well constructed in previous research. This study aims to estimate these nonlinear relationships and predict future malaria scenarios in northern China. Nonlinear relationships between malaria incidence and predictor variables were constructed using a genetic programming (GP) method, to predict the spatial distributions of malaria under climate change scenarios. For this, the examples of monthly average malaria incidence were used in each county of northern China from 2004 to 2010. Among the five variables at county level, precipitation rate and temperature are used for projections, while elevation, water density index, and gross domestic product are held at their present-day values. Average malaria incidence was 0.107 ‰ per annum in northern China, with incidence characteristics in significant spatial clustering. A GP-based model fit the relationships with average relative error (ARE) = 8.127 % for training data (R(2) = 0.825) and 17.102 % for test data (R(2) = 0.532). The fitness of GP results are significantly improved compared with those by generalized additive models (GAM) and linear regressions. With the future precipitation rate and temperature conditions in Special Report on Emission Scenarios (SRES) family B1, A1B and A2 scenarios, spatial distributions and changes in malaria incidences in 2020, 2030, 2040 and 2050 were predicted and mapped. The GP method increases the precision of predicting the spatial distribution of malaria incidence. With the assumption of varied precipitation rate and temperature, and other variables controlled, the relationships between incidence and the varied variables appear sophisticated nonlinearity and spatially differentiation. Using the future fluctuated precipitation and the increased temperature, median malaria incidence in 2020, 2030, 2040 and 2050 would significantly increase that it might increase 19 to 29 % in 2020, but currently China is in the malaria elimination phase, indicating that the effective strategies and actions had been taken. While the mean incidences will not increase even reduce due to the incidence reduction in high-risk regions but the simultaneous expansion of the high-risk areas.

Influenza A H5N1 and H7N9 in China: A spatial risk analysis

PubMed Central

Gardner, Lauren; MacIntyre, Raina; Sarkar, Sahotra

2017-01-01

Background Zoonotic avian influenza poses a major risk to China, and other parts of the world. H5N1 has remained endemic in China and globally for nearly two decades, and in 2013, a novel zoonotic influenza A subtype H7N9 emerged in China. This study aimed to improve upon our current understanding of the spreading mechanisms of H7N9 and H5N1 by generating spatial risk profiles for each of the two virus subtypes across mainland China. Methods and findings In this study, we (i) developed a refined data set of H5N1 and H7N9 locations with consideration of animal/animal environment case data, as well as spatial accuracy and precision; (ii) used this data set along with environmental variables to build species distribution models (SDMs) for each virus subtype in high resolution spatial units of 1km2 cells using Maxent; (iii) developed a risk modelling framework which integrated the results from the SDMs with human and chicken population variables, which was done to quantify the risk of zoonotic transmission; and (iv) identified areas at high risk of H5N1 and H7N9 transmission. We produced high performing SDMs (6 of 8 models with AUC > 0.9) for both H5N1 and H7N9. In all our SDMs, H7N9 consistently showed higher AUC results compared to H5N1, suggesting H7N9 suitability could be better explained by environmental variables. For both subtypes, high risk areas were primarily located in south-eastern China, with H5N1 distributions found to be more diffuse and extending more inland compared to H7N9. Conclusions We provide projections of our risk models to public health policy makers so that specific high risk areas can be targeted for control measures. We recommend comparing H5N1 and H7N9 prevalence rates and survivability in the natural environment to better understand the role of animal and environmental transmission in human infections. PMID:28376125

Impacts of road network expansion on landscape ecological risk in a megacity, China: A case study of Beijing.

PubMed

Mo, Wenbo; Wang, Yong; Zhang, Yingxue; Zhuang, Dafang

2017-01-01

Road networks affect the spatial structure of urban landscapes, and with continuous expansion, it will also exert more widespread influences on the regional ecological environment. With the support of geographic information system (GIS) technology, based on the application of various spatial analysis methods, this study analyzed the spatiotemporal changes of road networks and landscape ecological risk in the research area of Beijing to explore the impacts of road network expansion on ecological risk in the urban landscape. The results showed the following: 1) In the dynamic processes of change in the overall landscape pattern, the changing differences in landscape indices of various landscape types were obvious and were primarily related to land-use type. 2) For the changes in a time series, the expansion of the road kernel area was consistent with the extension of the sub-low-risk area in the urban center, but some differences were observed during different stages of development. 3) For the spatial position, the expanding changes in the road kernel area were consistent with the grade changes of the urban central ecological risk, primarily because both had a certain spatial correlation with the expressways. 4) The influence of road network expansion on the ecological risk in the study area had obvious spatial differences, which may be closely associated with the distribution of ecosystem types. Copyright © 2016 Office national des forêts. Published by Elsevier B.V. All rights reserved.

Targeting hunter distribution based on host resource selection and kill sites to manage disease risk.

PubMed

Dugal, Cherie J; van Beest, Floris M; Vander Wal, Eric; Brook, Ryan K

2013-10-01

Endemic and emerging diseases are rarely uniform in their spatial distribution or prevalence among cohorts of wildlife. Spatial models that quantify risk-driven differences in resource selection and hunter mortality of animals at fine spatial scales can assist disease management by identifying high-risk areas and individuals. We used resource selection functions (RSFs) and selection ratios (SRs) to quantify sex- and age-specific resource selection patterns of collared (n = 67) and hunter-killed (n = 796) nonmigratory elk (Cervus canadensis manitobensis) during the hunting season between 2002 and 2012, in southwestern Manitoba, Canada. Distance to protected area was the most important covariate influencing resource selection and hunter-kill sites of elk (AICw = 1.00). Collared adult males (which are most likely to be infected with bovine tuberculosis (Mycobacterium bovis) and chronic wasting disease) rarely selected for sites outside of parks during the hunting season in contrast to adult females and juvenile males. The RSFs showed selection by adult females and juvenile males to be negatively associated with landscape-level forest cover, high road density, and water cover, whereas hunter-kill sites of these cohorts were positively associated with landscape-level forest cover and increasing distance to streams and negatively associated with high road density. Local-level forest was positively associated with collared animal locations and hunter-kill sites; however, selection was stronger for collared juvenile males and hunter-killed adult females. In instances where disease infects a metapopulation and eradication is infeasible, a principle goal of management is to limit the spread of disease among infected animals. We map high-risk areas that are regularly used by potentially infectious hosts but currently underrepresented in the distribution of kill sites. We present a novel application of widely available data to target hunter distribution based on host resource selection and kill sites as a promising tool for applying selective hunting to the management of transmissible diseases in a game species.

Crop connectivity under climate change: future environmental and geographic risks of potato late blight in Scotland.

PubMed

Skelsey, Peter; Cooke, David E L; Lynott, James S; Lees, Alison K

2016-11-01

The impact of climate change on dispersal processes is largely ignored in risk assessments for crop diseases, as inoculum is generally assumed to be ubiquitous and nonlimiting. We suggest that consideration of the impact of climate change on the connectivity of crops for inoculum transmission may provide additional explanatory and predictive power in disease risk assessments, leading to improved recommendations for agricultural adaptation to climate change. In this study, a crop-growth model was combined with aerobiological models and a newly developed infection risk model to provide a framework for quantifying the impact of future climates on the risk of disease occurrence and spread. The integrated model uses standard meteorological variables and can be easily adapted to various crop pathosystems characterized by airborne inoculum. In a case study, the framework was used with data defining the spatial distribution of potato crops in Scotland and spatially coherent, probabilistic climate change data to project the future connectivity of crop distributions for Phytophthora infestans (causal agent of potato late blight) inoculum and the subsequent risk of infection. Projections and control recommendations are provided for multiple combinations of potato cultivar and CO 2 emissions scenario, and temporal and spatial averaging schemes. Overall, we found that relative to current climatic conditions, the risk of late blight will increase in Scotland during the first half of the potato growing season and decrease during the second half. To guide adaptation strategies, we also investigated the potential impact of climate change-driven shifts in the cropping season. Advancing the start of the potato growing season by 1 month proved to be an effective strategy from both an agronomic and late blight management perspective. © 2016 John Wiley & Sons Ltd.

Infant mortality in South Africa - distribution, associations and policy implications, 2007: an ecological spatial analysis

PubMed Central

2011-01-01

Background Many sub-Saharan countries are confronted with persistently high levels of infant mortality because of the impact of a range of biological and social determinants. In particular, infant mortality has increased in sub-Saharan Africa in recent decades due to the HIV/AIDS epidemic. The geographic distribution of health problems and their relationship to potential risk factors can be invaluable for cost effective intervention planning. The objective of this paper is to determine and map the spatial nature of infant mortality in South Africa at a sub district level in order to inform policy intervention. In particular, the paper identifies and maps high risk clusters of infant mortality, as well as examines the impact of a range of determinants on infant mortality. A Bayesian approach is used to quantify the spatial risk of infant mortality, as well as significant associations (given spatial correlation between neighbouring areas) between infant mortality and a range of determinants. The most attributable determinants in each sub-district are calculated based on a combination of prevalence and model risk factor coefficient estimates. This integrated small area approach can be adapted and applied in other high burden settings to assist intervention planning and targeting. Results Infant mortality remains high in South Africa with seemingly little reduction since previous estimates in the early 2000's. Results showed marked geographical differences in infant mortality risk between provinces as well as within provinces as well as significantly higher risk in specific sub-districts and provinces. A number of determinants were found to have a significant adverse influence on infant mortality at the sub-district level. Following multivariable adjustment increasing maternal mortality, antenatal HIV prevalence, previous sibling mortality and male infant gender remained significantly associated with increased infant mortality risk. Of these antenatal HIV sero-prevalence, previous sibling mortality and maternal mortality were found to be the most attributable respectively. Conclusions This study demonstrates the usefulness of advanced spatial analysis to both quantify excess infant mortality risk at the lowest administrative unit, as well as the use of Bayesian modelling to quantify determinant significance given spatial correlation. The "novel" integration of determinant prevalence at the sub-district and coefficient estimates to estimate attributable fractions further elucidates the "high impact" factors in particular areas and has considerable potential to be applied in other locations. The usefulness of the paper, therefore, not only suggests where to intervene geographically, but also what specific interventions policy makers should prioritize in order to reduce the infant mortality burden in specific administration areas. PMID:22093084

Bovine respiratory syncytial virus and bovine coronavirus antibodies in bulk tank milk - risk factors and spatial analysis.

PubMed

Toftaker, Ingrid; Sanchez, Javier; Stokstad, Maria; Nødtvedt, Ane

2016-10-01

Bovine respiratory syncytial virus (BRSV) and bovine coronavirus (BCoV) are considered widespread among cattle in Norway and worldwide. This cross-sectional study was conducted based on antibody-ELISA of bulk tank milk (BTM) from 1347 herds in two neighboring counties in western Norway. The study aims were to determine the seroprevalence at herd level, to evaluate risk factors for BRSV and BCoV seropositivity, and to assess how these factors were associated with the spatial distribution of positive herds. The overall prevalence of BRSV and BCoV positive herds in the region was 46.2% and 72.2%, respectively. Isopleth maps of the prevalence risk distribution showed large differences in prevalence risk across the study area, with the highest prevalence in the northern region. Common risk factors of importance for both viruses were herd size, geographic location, and proximity to neighbors. Seropositivity for one virus was associated with increased odds of seropositivity for the other virus. Purchase of livestock was an additional risk factor for BCoV seropositivity, included in the model as in-degree, which was defined as the number of incoming movements from individual herds, through animal purchase, over a period of five years. Local dependence and the contribution of risk factors to this effect were assessed using the residuals from two logistic regression models for each virus. One model contained only the x- and y- coordinates as predictors, the other had all significant predictors included. Spatial clusters of high values of residuals were detected using the normal model of the spatial scan statistic and visualized on maps. Adjusting for the risk factors in the final models had different impact on the spatial clusters for the two viruses: For BRSV the number of clusters was reduced from six to four, for BCoV the number of clusters remained the same, however the log-likelihood ratios changed notably. This indicates that geographical differences in proximity to neighbors, herd size and animal movements explain some of the spatial clusters of BRSV- and BCoV seropositivity, but far from all. The remaining local dependence in the residuals show that the antibody status of one herd is influenced by the antibody status of its neighbors, indicating the importance of indirect transmission and that increased biosecurity routines might be an important preventive strategy. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Accuration of Time Series and Spatial Interpolation Method for Prediction of Precipitation Distribution on the Geographical Information System

NASA Astrophysics Data System (ADS)

Prasetyo, S. Y. J.; Hartomo, K. D.

2018-01-01

The Spatial Plan of the Province of Central Java 2009-2029 identifies that most regencies or cities in Central Java Province are very vulnerable to landslide disaster. The data are also supported by other data from Indonesian Disaster Risk Index (In Indonesia called Indeks Risiko Bencana Indonesia) 2013 that suggest that some areas in Central Java Province exhibit a high risk of natural disasters. This research aims to develop an application architecture and analysis methodology in GIS to predict and to map rainfall distribution. We propose our GIS architectural application of “Multiplatform Architectural Spatiotemporal” and data analysis methods of “Triple Exponential Smoothing” and “Spatial Interpolation” as our significant scientific contribution. This research consists of 2 (two) parts, namely attribute data prediction using TES method and spatial data prediction using Inverse Distance Weight (IDW) method. We conduct our research in 19 subdistricts in the Boyolali Regency, Central Java Province, Indonesia. Our main research data is the biweekly rainfall data in 2000-2016 Climatology, Meteorology, and Geophysics Agency (In Indonesia called Badan Meteorologi, Klimatologi, dan Geofisika) of Central Java Province and Laboratory of Plant Disease Observations Region V Surakarta, Central Java. The application architecture and analytical methodology of “Multiplatform Architectural Spatiotemporal” and spatial data analysis methodology of “Triple Exponential Smoothing” and “Spatial Interpolation” can be developed as a GIS application framework of rainfall distribution for various applied fields. The comparison between the TES and IDW methods show that relative to time series prediction, spatial interpolation exhibit values that are approaching actual. Spatial interpolation is closer to actual data because computed values are the rainfall data of the nearest location or the neighbour of sample values. However, the IDW’s main weakness is that some area might exhibit the rainfall value of 0. The representation of 0 in the spatial interpolation is mainly caused by the absence of rainfall data in the nearest sample point or too far distance that produces smaller weight.

The spatial distribution of gender differences in obesity prevalence differs from overall obesity prevalence among US adults.

PubMed

Gartner, Danielle R; Taber, Daniel R; Hirsch, Jana A; Robinson, Whitney R

2016-04-01

Although obesity disparities between racial and socioeconomic groups have been well characterized, those based on gender and geography have not been as thoroughly documented. This study describes obesity prevalence by state, gender, and race and/or ethnicity to (1) characterize obesity gender inequality, (2) determine if the geographic distribution of inequality is spatially clustered, and (3) contrast the spatial clustering patterns of obesity gender inequality with overall obesity prevalence. Data from the Centers for Disease Control and Prevention's 2013 Behavioral Risk Factor Surveillance System were used to calculate state-specific obesity prevalence and gender inequality measures. Global and local Moran's indices were calculated to determine spatial autocorrelation. Age-adjusted, state-specific obesity prevalence difference and ratio measures show spatial autocorrelation (z-score = 4.89, P-value < .001). Local Moran's indices indicate the spatial distributions of obesity prevalence and obesity gender inequalities are not the same. High and low values of obesity prevalence and gender inequalities cluster in different areas of the United States. Clustering of gender inequality suggests that spatial processes operating at the state level, such as occupational or physical activity policies or social norms, are involved in the etiology of the inequality and necessitate further attention to the determinates of obesity gender inequality. Copyright © 2016 Elsevier Inc. All rights reserved.

Geostatistical analysis of the flood risk perception queries in the village of Navaluenga (Central Spain)

NASA Astrophysics Data System (ADS)

Guardiola-Albert, Carolina; Díez-Herrero, Andrés; Amérigo, María; García, Juan Antonio; María Bodoque, José; Fernández-Naranjo, Nuria

2017-04-01

Flash floods provoke a high average mortality as they are usually unexpected events which evolve rapidly and affect relatively small areas. The short time available for minimizing risks requires preparedness and response actions to be put into practice. Therefore, it is necessary the development of emergency response plans to evacuate and rescue people in the context of a flash-flood hazard. In this framework, risk management has to integrate the social dimension of flash-flooding and its spatial distribution by understanding the characteristics of local communities in order to enhance community resilience during a flash-flood. In this regard, the flash-flood social risk perception of the village of Navaluenga (Central Spain) has been recently assessed, as well as the level of awareness of civil protection and emergency management strategies (Bodoque et al., 2016). This has been done interviewing 254 adults, representing roughly 12% of the population census. The present study wants to go further in the analysis of the resulting questionnaires, incorporating in the analysis the location of home spatial coordinates in order to characterize the spatial distribution and possible geographical interpretation of flood risk perception. We apply geostatistical methods to analyze spatial relations of social risk perception and level of awareness with distance to the rivers (Alberche and Chorrerón) or to the flood-prone areas (50-year, 100-year and 500-year flood plains). We want to discover spatial patterns, if any, using correlation functions (variograms). Geostatistical analyses results can help to either confirm the logical pattern (i.e., less awareness further to the rivers or high return period of flooding) or reveal departures from expected. It can also be possible to identify hot spots, cold spots, and spatial outliers. The interpretation of these spatial patterns can give valuable information to define strategies to improve the awareness regarding preparedness and response actions, such as designing optimal evacuation routes during flood emergencies. Geostatistical tools also provide a set of interpolation techniques for the prediction of the variable value at unstudied similar locations, basing on the sample point values and other variables related with the measured variable. We attempt different geostatistical interpolation methods to obtain continuous surfaces of the risk perception and level of awareness in the study area. The use of these maps for future extensions and actualizations of the Civil Protection Plan is evaluated. References Bodoque, J. M., Amérigo, M., Díez-Herrero, A., García, J. A., Cortés, B., Ballesteros-Cánovas, J. A., & Olcina, J. (2016). Improvement of resilience of urban areas by integrating social perception in flash-flood risk management.Journal of Hydrology.

Analysis of spatial distribution and transmission characters for highly pathogenic avian influenza in Chinese mainland in 2004

NASA Astrophysics Data System (ADS)

Liu, Y. L.; Wei, C. J.; Yan, L.; Chi, T. H.; Wu, X. B.; Xiao, C. S.

2006-03-01

After the outbreak of highly pathogenic Avian Influenza (HPAI) in South Korea in the end of year 2003, estimates of the impact of HPAI in affected countries vary greatly, the total direct losses are about 3 billion US dollars, and it caused 15 million birds and poultry flocks death. It is significant to understand the spatial distribution and transmission characters of HPAI for its prevention and control. According to 50 outbreak cases for HPAI in Chinese mainland during 2004, this paper introduces the approach of spatial distribution and transmission characters for HPAI and its results. Its approach is based on remote sensing and GIS techniques. Its supporting data set involves normalized difference vegetation index (NDVI) and land surface temperature (Ts) derived from a time-series of remote sensing data of 1 kilometer-resolution NOAA/AVHRR, birds' migration routes, topology geographic map, lake and wetland maps, and meteorological observation data. In order to analyze synthetically using these data, a supporting platform for analysis Avian Influenza epidemic situation (SPAS/AI) was developed. Supporting by SPAS/AI, the integrated information from multi-sources can be easily used to the analysis of the spatial distribution and transmission character of HPAI. The results show that the range of spatial distribution and transmission of HPAI in China during 2004 connected to environment factors NDVI, Ts and the distributions of lake and wetland, and especially to bird migration routes. To some extent, the results provide some suggestions for the macro-decision making for the prevention and control of HPAI in the areas of potential risk and reoccurrence.

Participatory Risk Mapping of Malaria Vector Exposure in Northern South America using Environmental and Population Data

PubMed Central

Fuller, D.O.; Troyo, A.; Alimi, T.O.; Beier, J.C.

2014-01-01

Malaria elimination remains a major public health challenge in many tropical regions, including large areas of northern South America. In this study, we present a new high spatial resolution (90 × 90 m) risk map for Colombia and surrounding areas based on environmental and human population data. The map was created through a participatory multi-criteria decision analysis in which expert opinion was solicited to determine key environmental and population risk factors, different fuzzy functions to standardize risk factor inputs, and variable factor weights to combine risk factors in a geographic information system. The new risk map was compared to a map of malaria cases in which cases were aggregated to the municipio (municipality) level. The relationship between mean municipio risk scores and total cases by muncípio showed a weak correlation. However, the relationship between pixel-level risk scores and vector occurrence points for two dominant vector species, Anopheles albimanus and An. darlingi, was significantly different (p < 0.05) from a random point distribution, as was a pooled point distribution for these two vector species and An. nuneztovari. Thus, we conclude that the new risk map derived based on expert opinion provides an accurate spatial representation of risk of potential vector exposure rather than malaria transmission as shown by the pattern of malaria cases, and therefore it may be used to inform public health authorities as to where vector control measures should be prioritized to limit human-vector contact in future malaria outbreaks. PMID:24976656

Wildfire risk for main vegetation units in a biodiversity hotspot: modeling approach in New Caledonia, South Pacific.

PubMed

Gomez, Céline; Mangeas, Morgan; Curt, Thomas; Ibanez, Thomas; Munzinger, Jérôme; Dumas, Pascal; Jérémy, André; Despinoy, Marc; Hély, Christelle

2015-01-01

Wildfire has been recognized as one of the most ubiquitous disturbance agents to impact on natural environments. In this study, our main objective was to propose a modeling approach to investigate the potential impact of wildfire on biodiversity. The method is illustrated with an application example in New Caledonia where conservation and sustainable biodiversity management represent an important challenge. Firstly, a biodiversity loss index, including the diversity and the vulnerability indexes, was calculated for every vegetation unit in New Caledonia and mapped according to its distribution over the New Caledonian mainland. Then, based on spatially explicit fire behavior simulations (using the FLAMMAP software) and fire ignition probabilities, two original fire risk assessment approaches were proposed: a one-off event model and a multi-event burn probability model. The spatial distribution of fire risk across New Caledonia was similar for both indices with very small localized spots having high risk. The patterns relating to highest risk are all located around the remaining sclerophyll forest fragments and are representing 0.012% of the mainland surface. A small part of maquis and areas adjacent to dense humid forest on ultramafic substrates should also be monitored. Vegetation interfaces between secondary and primary units displayed high risk and should represent priority zones for fire effects mitigation. Low fire ignition probability in anthropogenic-free areas decreases drastically the risk. A one-off event associated risk allowed localizing of the most likely ignition areas with potential for extensive damage. Emergency actions could aim limiting specific fire spread known to have high impact or consist of on targeting high risk areas to limit one-off fire ignitions. Spatially explicit information on burning probability is necessary for setting strategic fire and fuel management planning. Both risk indices provide clues to preserve New Caledonia hot spot of biodiversity facing wildfires.

Wildfire risk for main vegetation units in a biodiversity hotspot: modeling approach in New Caledonia, South Pacific

PubMed Central

Gomez, Céline; Mangeas, Morgan; Curt, Thomas; Ibanez, Thomas; Munzinger, Jérôme; Dumas, Pascal; Jérémy, André; Despinoy, Marc; Hély, Christelle

2015-01-01

Wildfire has been recognized as one of the most ubiquitous disturbance agents to impact on natural environments. In this study, our main objective was to propose a modeling approach to investigate the potential impact of wildfire on biodiversity. The method is illustrated with an application example in New Caledonia where conservation and sustainable biodiversity management represent an important challenge. Firstly, a biodiversity loss index, including the diversity and the vulnerability indexes, was calculated for every vegetation unit in New Caledonia and mapped according to its distribution over the New Caledonian mainland. Then, based on spatially explicit fire behavior simulations (using the FLAMMAP software) and fire ignition probabilities, two original fire risk assessment approaches were proposed: a one-off event model and a multi-event burn probability model. The spatial distribution of fire risk across New Caledonia was similar for both indices with very small localized spots having high risk. The patterns relating to highest risk are all located around the remaining sclerophyll forest fragments and are representing 0.012% of the mainland surface. A small part of maquis and areas adjacent to dense humid forest on ultramafic substrates should also be monitored. Vegetation interfaces between secondary and primary units displayed high risk and should represent priority zones for fire effects mitigation. Low fire ignition probability in anthropogenic-free areas decreases drastically the risk. A one-off event associated risk allowed localizing of the most likely ignition areas with potential for extensive damage. Emergency actions could aim limiting specific fire spread known to have high impact or consist of on targeting high risk areas to limit one-off fire ignitions. Spatially explicit information on burning probability is necessary for setting strategic fire and fuel management planning. Both risk indices provide clues to preserve New Caledonia hot spot of biodiversity facing wildfires. PMID:25691965

Spatial analysis of county-based gonorrhoea incidence in mainland China, from 2004 to 2009.

PubMed

Yin, Fei; Feng, Zijian; Li, Xiaosong

2012-07-01

Gonorrhoea is one of the most common sexually transmissible infections in mainland China. Effective spatial monitoring of gonorrhoea incidence is important for successful implementation of control and prevention programs. The county-level gonorrhoea incidence rates for all of mainland China was monitored through examining spatial patterns. County-level data on gonorrhoea cases between 2004 and 2009 were obtained from the China Information System for Disease Control and Prevention. Bayesian smoothing and exploratory spatial data analysis (ESDA) methods were used to characterise the spatial distribution pattern of gonorrhoea cases. During the 6-year study period, the average annual gonorrhoea incidence was 12.41 cases per 100000 people. Using empirical Bayes smoothed rates, the local Moran test identified one significant single-centre cluster and two significant multi-centre clusters of high gonorrhoea risk (all P-values <0.01). Bayesian smoothing and ESDA methods can assist public health officials in using gonorrhoea surveillance data to identify high risk areas. Allocating more resources to such areas could effectively reduce gonorrhoea incidence.

Analysis of the spatial and temporal distribution of malaria in an area of Northern Guatemala with seasonal malaria transmission.

PubMed

Malvisi, Lucio; Troisi, Catherine L; Selwyn, Beatrice J

2018-06-23

The risk of malaria infection displays spatial and temporal variability that is likely due to interaction between the physical environment and the human population. In this study, we performed a spatial analysis at three different time points, corresponding to three cross-sectional surveys conducted as part of an insecticide-treated bed nets efficacy study, to reveal patterns of malaria incidence distribution in an area of Northern Guatemala characterized by low malaria endemicity. A thorough understanding of the spatial and temporal patterns of malaria distribution is essential for targeted malaria control programs. Two methods, the local Moran's I and the Getis-Ord G * (d), were used for the analysis, providing two different statistical approaches and allowing for a comparison of results. A distance band of 3.5 km was considered to be the most appropriate distance for the analysis of data based on epidemiological and entomological factors. Incidence rates were higher at the first cross-sectional survey conducted prior to the intervention compared to the following two surveys. Clusters or hot spots of malaria incidence exhibited high spatial and temporal variations. Findings from the two statistics were similar, though the G * (d) detected cold spots using a higher distance band (5.5 km). The high spatial and temporal variability in the distribution of clusters of high malaria incidence seems to be consistent with an area of unstable malaria transmission. In such a context, a strong surveillance system and the use of spatial analysis may be crucial for targeted malaria control activities.

Spatial clustering of malaria and associated risk factors during an epidemic in a highland area of western Kenya.

PubMed

Brooker, Simon; Clarke, Siân; Njagi, Joseph Kiambo; Polack, Sarah; Mugo, Benbolt; Estambale, Benson; Muchiri, Eric; Magnussen, Pascal; Cox, Jonathan

2004-07-01

The epidemiology of malaria over small areas remains poorly understood, and this is particularly true for malaria during epidemics in highland areas of Africa, where transmission intensity is low and characterized by acute within and between year variations. We report an analysis of the spatial distribution of clinical malaria during an epidemic and investigate putative risk factors. Active case surveillance was undertaken in three schools in Nandi District, Western Kenya for 10 weeks during a malaria outbreak in May-July 2002. Household surveys of cases and age-matched controls were conducted to collect information on household construction, exposure factors and socio-economic status. Household geographical location and altitude were determined using a hand-held geographical positioning system and landcover types were determined using high spatial resolution satellite sensor data. Among 129 cases identified during the surveillance, which were matched to 155 controls, we identified significant spatial clusters of malaria cases as determined using the spatial scan statistic. Conditional multiple logistic regression analysis showed that the risk of malaria was higher in children who were underweight, who lived at lower altitudes, and who lived in households where drugs were not kept at home. Copyright 2004 Blackwell Publishing Ltd

Determining Global Population Distribution: Methods, Applications and Data

PubMed Central

Balk, D.L.; Deichmann, U.; Yetman, G.; Pozzi, F.; Hay, S.I.; Nelson, A.

2011-01-01

Evaluating the total numbers of people at risk from infectious disease in the world requires not just tabular population data, but data that are spatially explicit and global in extent at a moderate resolution. This review describes the basic methods for constructing estimates of global population distribution with attention to recent advances in improving both spatial and temporal resolution. To evaluate the optimal resolution for the study of disease, the native resolution of the data inputs as well as that of the resulting outputs are discussed. Assumptions used to produce different population data sets are also described, with their implications for the study of infectious disease. Lastly, the application of these population data sets in studies to assess disease distribution and health impacts is reviewed. The data described in this review are distributed in the accompanying DVD. PMID:16647969

Spatial analysis of under-5 mortality and potential risk factors in the Basse Health and Demographic Surveillance System, the Gambia.

PubMed

Quattrochi, John; Jasseh, Momodou; Mackenzie, Grant; Castro, Marcia C

2015-07-01

To describe the spatial pattern in under-5 mortality rates in the Basse Health and Demographic Surveillance System (BHDSS) and to test for associations between under-5 deaths and biodemographic and socio-economic risk factors. Using data on child survival from 2007 to 2011 in the BHDSS, we mapped under-5 mortality by km(2) . We tested for spatial clustering of high or low death rates using Kulldorff's spatial scan statistic. Associations between child death and a variety of biodemographic and socio-economic factors were assessed with Cox proportional hazards models, and deviance residuals from the best-fitting model were tested for spatial clustering. The overall death rate among children under 5 was 0.0195 deaths per child-year. We found two spatial clusters of high death rates and one spatial cluster of low death rates; children in the two high clusters died at a rate of 0.0264 and 0.0292 deaths per child-year, while in the low cluster, the rate was 0.0144 deaths per child-year. We also found that children born to Fula mothers experienced, on average, a higher hazard of death, whereas children born in the households in the upper two quintiles of asset ownership experienced, on average, a lower hazard of death. After accounting for the spatial distribution of biodemographic and socio-economic characteristics, we found no residual spatial pattern in child mortality risk. This study demonstrates that significant inequality in under-5 death rates can occur within a relatively small area (1100 km(2) ). Risks of under-5 mortality were associated with mother's ethnicity and household wealth. If high mortality clusters persist, then equity concerns may require additional public health efforts in those areas. © 2015 John Wiley & Sons Ltd.

Resonant imaging of carotenoid pigments in the human retina

NASA Astrophysics Data System (ADS)

Gellermann, Werner; Emakov, Igor V.; McClane, Robert W.

2002-06-01

We have generated high spatial resolution images showing the distribution of carotenoid macular pigments in the human retina using Raman spectroscopy. A low level of macular pigments is associated with an increased risk of developing age-related macular degeneration, a leading cause of irreversible blindness. Using excised human eyecups and resonant excitation of the pigment molecules with narrow bandwidth blue light from a mercury arc lamp, we record Raman images originating from the carbon-carbon double bond stretch vibrations of lutein and zeaxanthin, the carotenoids comprising human macular pigments. Our Raman images reveal significant differences among subjects, both in regard to absolute levels as well as spatial distribution within the macula. Since the light levels used to obtain these images are well below established safety limits, this technique holds promise for developing a rapid screening diagnostic in large populations at risk for vision loss from age-related macular degeneration.

Spatial Distribution of Dengue in a Brazilian Urban Slum Setting: Role of Socioeconomic Gradient in Disease Risk.

PubMed

Kikuti, Mariana; Cunha, Geraldo M; Paploski, Igor A D; Kasper, Amelia M; Silva, Monaise M O; Tavares, Aline S; Cruz, Jaqueline S; Queiroz, Tássia L; Rodrigues, Moreno S; Santana, Perla M; Lima, Helena C A V; Calcagno, Juan; Takahashi, Daniele; Gonçalves, André H O; Araújo, Josélio M G; Gauthier, Kristine; Diuk-Wasser, Maria A; Kitron, Uriel; Ko, Albert I; Reis, Mitermayer G; Ribeiro, Guilherme S

2015-01-01

Few studies of dengue have shown group-level associations between demographic, socioeconomic, or geographic characteristics and the spatial distribution of dengue within small urban areas. This study aimed to examine whether specific characteristics of an urban slum community were associated with the risk of dengue disease. From 01/2009 to 12/2010, we conducted enhanced, community-based surveillance in the only public emergency unit in a slum in Salvador, Brazil to identify acute febrile illness (AFI) patients with laboratory evidence of dengue infection. Patient households were geocoded within census tracts (CTs). Demographic, socioeconomic, and geographical data were obtained from the 2010 national census. Associations between CTs characteristics and the spatial risk of both dengue and non-dengue AFI were assessed by Poisson log-normal and conditional auto-regressive models (CAR). We identified 651 (22.0%) dengue cases among 2,962 AFI patients. Estimated risk of symptomatic dengue was 21.3 and 70.2 cases per 10,000 inhabitants in 2009 and 2010, respectively. All the four dengue serotypes were identified, but DENV2 predominated (DENV1: 8.1%; DENV2: 90.7%; DENV3: 0.4%; DENV4: 0.8%). Multivariable CAR regression analysis showed increased dengue risk in CTs with poorer inhabitants (RR: 1.02 for each percent increase in the frequency of families earning ≤1 times the minimum wage; 95% CI: 1.01-1.04), and decreased risk in CTs located farther from the health unit (RR: 0.87 for each 100 meter increase; 95% CI: 0.80-0.94). The same CTs characteristics were also associated with non-dengue AFI risk. This study highlights the large burden of symptomatic dengue on individuals living in urban slums in Brazil. Lower neighborhood socioeconomic status was independently associated with increased risk of dengue, indicating that within slum communities with high levels of absolute poverty, factors associated with the social gradient influence dengue transmission. In addition, poor geographic access to health services may be a barrier to identifying both dengue and non-dengue AFI cases. Therefore, further spatial studies should account for this potential source of bias.

Microscale spatial distribution and health assessment of PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) at nine communities in Xi'an, China.

PubMed

Xu, Hongmei; Ho, Steven Sai Hang; Gao, Meiling; Cao, Junji; Guinot, Benjamin; Ho, Kin Fai; Long, Xin; Wang, Jingzhi; Shen, Zhenxing; Liu, Suixin; Zheng, Chunli; Zhang, Qian

2016-11-01

Spatial variability of polycyclic aromatic hydrocarbons (PAHs) associated with fine particulate matter (PM 2.5 ) was investigated in Xi'an, China, in summer of 2013. Sixteen priority PAHs were quantified in 24-h integrated air samples collected simultaneously at nine urban and suburban communities. The total quantified PAHs mass concentrations ranged from 32.4 to 104.7 ng m -3 , with an average value of 57.1 ± 23.0 ng m -3 . PAHs were observed higher concentrations at suburban communities (average: 86.3 ng m -3 ) than at urban ones (average: 48.8 ng m -3 ) due to a better enforcement of the pollution control policies at the urban scale, and meanwhile the disorganized management of motor vehicles and massive building constructions in the suburbs. Elevated PAH levels were observed in the industrialized regions (west and northwest of Xi'an) from Kriging interpolation analysis. Satellite-based visual interpretations of land use were also applied for the supporting the spatial distribution of PAHs among the communities. The average benzo[a]pyrene-equivalent toxicity (Σ[BaP] eq ) at the nine communities was 6.9 ± 2.2 ng m -3 during the sampling period, showing a generally similar spatial distribution to PAHs levels. On average, the excess inhalation lifetime cancer risk derived from Σ[BaP] eq indicated that eight persons per million of community residents would develop cancer due to PM 2.5 -bound PAHs exposure in Xi'an. The great in-city spatial variability of PAHs confirmed the importance of multiple points sampling to conduct exposure health risk assessment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prevalence and spatial distribution of Theileria parva in cattle under crop-livestock farming systems in Tororo District, Eastern Uganda

PubMed Central

2014-01-01

Background Tick-borne diseases (TBDs) present a major economic burden to communities across East Africa. Farmers in East Africa must use acaracides to target ticks and prevent transmission of tick-borne diseases such as anaplasmosis, babesiosis, cowdriosis and theileriosis; the major causes of cattle mortality and morbidity. The costs of controlling East Coast Fever (ECF), caused by Theileria parva, in Uganda are significant and measures taken to control ticks, to be cost-effective, should take into account the burden of disease. The aim of the present work was to estimate the burden presented by T. parva and its spatial distribution in a crop-livestock production system in Eastern Uganda. Methods A cross sectional study was carried out to determine the prevalence and spatial distribution of T. parva in Tororo District, Uganda. Blood samples were taken from all cattle (n: 2,658) in 22 randomly selected villages across Tororo District from September to December 2011. Samples were analysed by PCR and T. parva prevalence and spatial distribution determined. Results The overall prevalence of T. parva was found to be 5.3%. Herd level prevalence ranged from 0% to 21% with majority of the infections located in the North, North-Eastern and South-Eastern parts of Tororo District. No statistically significant differences in risk of infection were found between age classes, sex and cattle breed. Conclusions T. parva infection is widely distributed in Tororo District, Uganda. The prevalence and distribution of T. parva is most likely determined by spatial distribution of R. appendiculatus, restricted grazing of calves and preferential tick control targeting draft animals. PMID:24589227

Characterization, distribution, and risk assessment of heavy metals in agricultural soil and products around mining and smelting areas of Hezhang, China.

PubMed

Briki, Meryem; Ji, Hongbing; Li, Cai; Ding, Huaijian; Gao, Yang

2015-12-01

Mining and smelting have been releasing huge amount of toxic substances into the environment. In the present study, agricultural soil and different agricultural products (potato, Chinese cabbage, garlic bolt, corn) were analyzed to examine the source, spatial distribution, and risk of 12 elements (As, Be, Bi, Cd, Co, Cr, Cu, Hg, Ni, Pb, Sb, and Zn) in agricultural soil near mine fields, smelting fields, and mountain field around Hezhang County, west of Guizhou Province, China. Multivariate statistical analysis indicated that in mining area, As, Bi, Cd, Cu, Hg, Pb, Sb, and Zn were generated from anthropogenic sources; in smelting area, As, Be, Cd, Co, Cu, Pb, Sb, and Zn were derived from anthropogenic sources through zinc smelting ceased in 2004. The enrichment factors (EFs) and ecological risk index (RI) of soil in mining area are the most harmful, showing extremely high enrichment and very high ecological risk of As, Bi, Cd, Cu, Hg, Pb, Sb, and Zn. Zinc is the most significant enriched in the smelting area; however, mountain area has a moderate enrichment and ecological risk and do not present any ecological risk. According to spatial distribution, the concentrations depend on the nearby mining and smelting activities. Transfer factors (TFs) in the smelting area and mountain are high, implying a threat for human consumption. Therefore, further studies should be carried out taking into account the harm of those heavy metals and potential negative health effects from the consumption of agricultural products in these circumstances.

The spatial-temporal distribution of the atmospheric polluting agents during the period 2000-2005 in the Urban Area of Guadalajara, Jalisco, Mexico.

PubMed

Sánchez, Hermes U Ramírez; García, María D Andrade; Bejaran, Rubén; Guadalupe, Mario E García; Vázquez, Antonio Wallo; Toledano, Ana C Pompa; Villasenor, Odila de la Torre

2009-06-15

In the large cities, the disordered urban development, the industrial activities, and the transport, have caused elevated concentrations of polluting agents and possible risks to the health of the population. The metropolises located in valleys with little ventilation (such as the Urban Area of Guadalajara: UAG) present low dispersion of polluting agents can cause high risk of respiratory and cardiovascular diseases. The objective of this work was to describe the spatial-temporal distribution of the atmospheric polluting agents: carbon monoxide (CO), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), particles smaller than 10 microns (microm) (PM(10)) and ozone (O(3)) in the UAG during the period 2000-2005. A spatial-temporal distribution analysis was made by means of graphic interpolation (Kriging method) of the statistical parameters of CO, NO(2), SO(2), PM(10) and O(3) with the collected data from eight stations of atmospheric monitoring in the UAG. The results show that the distributions of the atmospheric polluting agents are variable during the analyzed years. The polluting agent with highest concentration is PM(10) (265.42 microg/m(3)), followed by O(3) (0.11 ppm), NO(2) (0.11 ppm), CO (9.17 ppm) and SO(2) (0.05 ppm). The most affected zone is the southeast of the UAG. The results showed that an important percentage of days exceed the Mexican norms of air quality (93-199 days/year).

Assessing spatial heterogeneity of MDR-TB in a high burden country

PubMed Central

Jenkins, Helen E.; Plesca, Valeriu; Ciobanu, Anisoara; Crudu, Valeriu; Galusca, Irina; Soltan, Viorel; Serbulenco, Aliona; Zignol, Matteo; Dadu, Andrei; Dara, Masoud; Cohen, Ted

2013-01-01

Multidrug-resistant tuberculosis (MDR-TB) is a major concern in countries of the former Soviet Union. The reported risk of resistance among TB cases in the Republic of Moldova is among the highest in the world. We aimed to produce high-resolution spatial maps of MDR-TB risk and burden in this setting. We analyzed national TB surveillance data collected between 2007 and 2010 in Moldova. High drug susceptibility testing coverage and detailed location data permitted identification of sub-regional areas of higher MDR-TB risk. We investigated whether the distribution of cases with MDR-TB risk factors could explain this observed spatial variation in MDR-TB. 3,447 MDR-TB cases were notified during this period; 24% of new and 62% of previously treated patients had MDR-TB. Nationally, the estimated annual MDR-TB incidence was 54 cases/100,000 persons and >1,000 cases/100,000 persons within penitentiaries. We identified substantial geographic variation in MDR-TB burden and hotspots of MDR-TB. Locations with a higher percentage of previously incarcerated TB cases were at greater risk of being MDR-TB hotspots. Spatial analyses revealed striking geographic heterogeneity of MDR-TB. Methods to identify locations of high MDR-TB risk and burden should allow for better resource allocation and more appropriate targeting of studies to understand local mechanisms driving resistance. PMID:23100496

Risk assessment of urban flood disaster in Jingdezhen City based on analytic hierarchy process and geographic information system

NASA Astrophysics Data System (ADS)

Sun, D. C.; Huang, J.; Wang, H. M.; Wang, Z. Q.; Wang, W. Q.

2017-08-01

The research of urban flood risk assessment and management are of great academic and practical importance, which has become a widespread concern throughout the world. It’s significant to understand the spatial-temporal distribution of the flood risk before making the risk response measures. In this study, the urban region of Jingdezhen City is selected as the study area. The assessment indicators are selected from four aspects: disaster-causing factors, disaster-pregnant environment, disaster-bearing body and the prevention and mitigation ability, by consideration of the formation process of urban flood risk. And then, a small-scale flood disaster risk assessment model is developed based on Analytic Hierarchy Process(AHP) and Geographic Information System(GIS), and the spatial-temporal distribution of flood risk in Jingdezhen City is analysed. The results show that the risk decreases gradually from the centre line of Changjiang River to the surrounding, and the areas of high flood disaster risk is decreasing from 2010 to 2013 while the risk areas are more concentred. The flood risk of the areas along the Changjiang River is the largest, followed by the low-lying areas in Changjiang District. And the risk is also large in Zhushan District where the population, the industries and commerce are concentrated. The flood risk in the western part of Changjiang District and the north-eastern part of the study area is relatively low. The results can provide scientific support for flood control construction and land development planning in Jingdezhen City.

The Spatial Distributions and Variations of Water Environmental Risk in Yinma River Basin, China.

PubMed

Di, Hui; Liu, Xingpeng; Zhang, Jiquan; Tong, Zhijun; Ji, Meichen

2018-03-15

Water environmental risk is the probability of the occurrence of events caused by human activities or the interaction of human activities and natural processes that will damage a water environment. This study proposed a water environmental risk index (WERI) model to assess the water environmental risk in the Yinma River Basin based on hazards, exposure, vulnerability, and regional management ability indicators in a water environment. The data for each indicator were gathered from 2000, 2005, 2010, and 2015 to assess the spatial and temporal variations in water environmental risk using particle swarm optimization and the analytic hierarchy process (PSO-AHP) method. The results showed that the water environmental risk in the Yinma River Basin decreased from 2000 to 2015. The risk level of the water environment was high in Changchun, while the risk levels in Yitong and Yongji were low. The research methods provide information to support future decision making by the risk managers in the Yinma River Basin, which is in a high-risk water environment. Moreover, water environment managers could reduce the risks by adjusting the indicators that affect water environmental risks.

[Spatial mobility on reaching adult age].

PubMed

De Coninck, F

1990-12-01

"Starting with longitudinal data on two cohorts of women living in the Alpes-Maritimes [France] in 1982 (a sample of 1,500 women in total) we try to establish the role of the spatial distribution of opportunities at a number of key stages in the life cycle: marriage, birth of first child, making professional use of qualifications, confrontation of a situation of professional risk and professional mobility during the years immediately following the completion of studies. The underlying hypothesis is that control of social location often depends on the control of spatial location." (SUMMARY IN ENG) excerpt

Social deprivation, inequality, and the neighborhood-level incidence of psychotic syndromes in East London.

PubMed

Kirkbride, James B; Jones, Peter B; Ullrich, Simone; Coid, Jeremy W

2014-01-01

Although urban birth, upbringing, and living are associated with increased risk of nonaffective psychotic disorders, few studies have used appropriate multilevel techniques accounting for spatial dependency in risk to investigate social, economic, or physical determinants of psychosis incidence. We adopted Bayesian hierarchical modeling to investigate the sociospatial distribution of psychosis risk in East London for DSM-IV nonaffective and affective psychotic disorders, ascertained over a 2-year period in the East London first-episode psychosis study. We included individual and environmental data on 427 subjects experiencing first-episode psychosis to estimate the incidence of disorder across 56 neighborhoods, having standardized for age, sex, ethnicity, and socioeconomic status. A Bayesian model that included spatially structured neighborhood-level random effects identified substantial unexplained variation in nonaffective psychosis risk after controlling for individual-level factors. This variation was independently associated with greater levels of neighborhood income inequality (SD increase in inequality: Bayesian relative risks [RR]: 1.25; 95% CI: 1.04-1.49), absolute deprivation (RR: 1.28; 95% CI: 1.08-1.51) and population density (RR: 1.18; 95% CI: 1.00-1.41). Neighborhood ethnic composition effects were associated with incidence of nonaffective psychosis for people of black Caribbean and black African origin. No variation in the spatial distribution of the affective psychoses was identified, consistent with the possibility of differing etiological origins of affective and nonaffective psychoses. Our data suggest that both absolute and relative measures of neighborhood social composition are associated with the incidence of nonaffective psychosis. We suggest these associations are consistent with a role for social stressors in psychosis risk, particularly when people live in more unequal communities.

The landscape of fear conceptual framework: definition and review of current applications and misuses.

PubMed

Bleicher, Sonny S

2017-01-01

Landscapes of Fear (LOF), the spatially explicit distribution of perceived predation risk as seen by a population, is increasingly cited in ecological literature and has become a frequently used "buzz-word". With the increase in popularity, it became necessary to clarify the definition for the term, suggest boundaries and propose a common framework for its use. The LOF, as a progeny of the "ecology of fear" conceptual framework, defines fear as the strategic manifestation of the cost-benefit analysis of food and safety tradeoffs. In addition to direct predation risk, the LOF is affected by individuals' energetic-state, inter- and intra-specific competition and is constrained by the evolutionary history of each species. Herein, based on current applications of the LOF conceptual framework, I suggest the future research in this framework will be directed towards: (1) finding applied management uses as a trait defining a population's habitat-use and habitat-suitability; (2) studying multi-dimensional distribution of risk-assessment through time and space; (3) studying variability between individuals within a population; (4) measuring eco-neurological implications of risk as a feature of environmental heterogeneity and (5) expanding temporal and spatial scales of empirical studies.

AIDS in adults 50 years of age and over: characteristics, trends and spatial distribution of the risk.

PubMed

Nogueira, Jordana de Almeida; Silva, Antônia Oliveira; Sá, Laísa Ribeiro de; Almeida, Sandra Aparecida de; Monroe, Aline Aparecida; Villa, Tereza Cristina Scatena

2014-01-01

to analyze the sociodemographic characteristics, epidemic trend and spatial distribution of the risk of AIDS in adults 50 years of age and over. population-based, ecological study, that used secondary data from the Notifiable Disease Information System (Sinan/AIDS) of Paraíba state from the period January 2000 to December 2010. during the study period, 307 cases of AIDS were reported among people 50 years of age or over. There was a predominance of males (205/66, 8%), mixed race, and low education levels. The municipalities with populations above 100 thousand inhabitants reported 58.5% of the cases. There was a progressive increase in cases among women; an increasing trend in the incidence (positive linear correlation); and an advance in the geographical spread of the disease, with expansion to the coastal region and to the interior of the state, reaching municipalities with populations below 30 thousand inhabitants. In some locations the risk of disease was 100 times greater than the relative risk for the state. aging, with the feminization and interiorization of the epidemic in adults 50 years of age and over, confirms the need for the induction of affirmative policies targeted toward this age group.

Risk assessment, spatial distribution, and source apportionment of heavy metals in Chinese surface soils from a typically tobacco cultivated area.

PubMed

Liu, Haiwei; Wang, Haiyun; Zhang, Yan; Yuan, Jumin; Peng, Yaodong; Li, Xiuchun; Shi, Yi; He, Kuanxin; Zhang, Qiming

2018-06-01

The heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) in the surface soils of tobacco (Nicotiana tabacum L.) fields in Jiangxi Province were analyzed, and the mean heavy metal concentrations were 3.55, 0.19, 25.89, 14.96, 0.25, 10.89, 27.80, and 44.00 mg/kg, respectively. Spatial distribution analysis showed that the highest concentrations were recorded in the north-western, south-western, and mid-eastern parts of the study area. The index of geo-accumulation and pollution index indicated modest enrichment with Cd and Hg, which were the only two metals posing a potentially high ecological risk to the local agricultural environment. The health risk assessment showed no considerable non-carcinogenic or carcinogenic risks for children and adults from these elements. The principal component analysis (PCA) and cluster analysis (CA) found that the variations in the Cr and Ni concentrations were largely on account of the soil parent rocks, but the As, Cd, Cu, and Hg variations in the soil were largely owing to agricultural practices of years. However, the main factor influencing Pb and Zn was atmospheric deposition.

The landscape of fear conceptual framework: definition and review of current applications and misuses

PubMed Central

2017-01-01

Landscapes of Fear (LOF), the spatially explicit distribution of perceived predation risk as seen by a population, is increasingly cited in ecological literature and has become a frequently used “buzz-word”. With the increase in popularity, it became necessary to clarify the definition for the term, suggest boundaries and propose a common framework for its use. The LOF, as a progeny of the “ecology of fear” conceptual framework, defines fear as the strategic manifestation of the cost-benefit analysis of food and safety tradeoffs. In addition to direct predation risk, the LOF is affected by individuals’ energetic-state, inter- and intra-specific competition and is constrained by the evolutionary history of each species. Herein, based on current applications of the LOF conceptual framework, I suggest the future research in this framework will be directed towards: (1) finding applied management uses as a trait defining a population’s habitat-use and habitat-suitability; (2) studying multi-dimensional distribution of risk-assessment through time and space; (3) studying variability between individuals within a population; (4) measuring eco-neurological implications of risk as a feature of environmental heterogeneity and (5) expanding temporal and spatial scales of empirical studies. PMID:28929015

An index for estimating the potential metal pollution contribution to atmospheric particulate matter from road dust in Beijing.

PubMed

Zhao, Hongtao; Shao, Yaping; Yin, Chengqing; Jiang, Yan; Li, Xuyong

2016-04-15

The resuspension of road dust from street surfaces could be a big contributor to atmospheric particulate pollution in the rapid urbanization context in the world. However, to date what its potential contribution to the spatial pattern is little known. Here we developed an innovative index model called the road dust index (RI<105μm) and it combines source and transport factors for road dust particles <105μm in diameter. It could quantify and differentiate the impact of the spatial distribution of the potential risks posed by metals associated with road dust on atmospheric suspended particles. The factors were ranked and weighted based on road dust characteristics (the amounts, grain sizes, and mobilities of the road dust, and the concentrations and toxicities of metals in the road dust). We then applied the RI<105μm in the Beijing region to assess the spatial distribution of the potential risks posed by metals associated with road dust on atmospheric suspended particles. The results demonstrated that the road dust in urban areas has higher potential risk of metal to atmospheric particles than that in rural areas. The RI<105μm method offers a new and useful tool for assessing the potential risks posed by metals associated with road dust on atmospheric suspended particles and for controlling atmospheric particulate pollution caused by road dust emissions. Copyright © 2016 Elsevier B.V. All rights reserved.

Meteorological risks are drivers of environmental innovation in agro-ecosystem management

NASA Astrophysics Data System (ADS)

Gobin, Anne; Van de Vijver, Hans; Vanwindekens, Frédéric; de Frutos Cachorro, Julia; Verspecht, Ann; Planchon, Viviane; Buyse, Jeroen

2017-04-01

Agricultural crop production is to a great extent determined by weather conditions. The research hypothesis is that meteorological risks act as drivers of environmental innovation in agro-ecosystem management. The methodology comprised five major parts: the hazard, its impact on different agro-ecosystems, vulnerability, risk management and risk communication. Generalized Extreme Value (GEV) theory was used to model annual maxima of meteorological variables based on a location-, scale- and shape-parameter that determine the center of the distribution, the deviation of the location-parameter and the upper tail decay, respectively. Spatial interpolation of GEV-derived return levels resulted in spatial temperature extremes, precipitation deficits and wet periods. The temporal overlap between extreme weather conditions and sensitive periods in the agro-ecosystem was realised using a bio-physically based modelling framework that couples phenology, a soil water balance and crop growth. 20-year return values for drought and waterlogging during different crop stages were related to arable yields. The method helped quantify agricultural production risks and rate both weather and crop-based agricultural insurance. The spatial extent of vulnerability is developed on different layers of geo-information to include meteorology, soil-landscapes, crop cover and management. Vulnerability of agroecosystems was mapped based on rules set by experts' knowledge and implemented by Fuzzy Inference System modelling and Geographical Information System tools. The approach was applied for cropland vulnerability to heavy rain and grassland vulnerability to drought. The level of vulnerability and resilience of an agro-ecosystem was also determined by risk management which differed across sectors and farm types. A calibrated agro-economic model demonstrated a marked influence of climate adapted land allocation and crop management on individual utility. The "chain of risk" approach allowed for investigating the hypothesis that meteorological risks act as drivers for agricultural innovation. Risk types were quantified in terms of probability and distribution, and further distinguished according to production type. Examples of strategies and options were provided at field, farm and policy level using different modelling methods.

Defining the Global Spatial Limits of Malaria Transmission in 2005

PubMed Central

Guerra, C.A.; Snow, R.W.; Hay, S.I.

2011-01-01

There is no accurate contemporary global map of the distribution of malaria. We show how guidelines formulated to advise travellers on appropriate chemoprophylaxis for areas of reported Plasmodium falciparum and Plasmodium vivax malaria risk can be used to generate crude spatial limits. We first review and amalgamate information on these guidelines to define malaria risk at national and sub-national administrative boundary levels globally. We then adopt an iterative approach to reduce these extents by applying a series of biological limits imposed by altitude, climate and population density to malaria transmission, specific to the local dominant vector species. Global areas of, and population at risk from, P. falciparum and often-neglected P. vivax malaria are presented for 2005 for all malaria endemic countries. These results reveal that more than 3 billion people were at risk of malaria in 2005. PMID:16647970

Neighborhood-Level and Spatial Characteristics Associated with Lay Naloxone Reversal Events and Opioid Overdose Deaths.

PubMed

Rowe, Christopher; Santos, Glenn-Milo; Vittinghoff, Eric; Wheeler, Eliza; Davidson, Peter; Coffin, Philip O

2016-02-01

There were over 23,000 opioid overdose deaths in the USA in 2013, and opioid-related mortality is increasing. Increased access to naloxone, particularly through community-based lay naloxone distribution, is a widely supported strategy to reduce opioid overdose mortality; however, little is known about the ecological and spatial patterns of the distribution and utilization of lay naloxone. This study aims to investigate the neighborhood-level correlates and spatial relationships of lay naloxone distribution and utilization and opioid overdose deaths. We determined the locations of lay naloxone distribution sites and the number of unintentional opioid overdose deaths and reported reversal events in San Francisco census tracts (n = 195) from 2010 to 2012. We used Wilcoxon rank-sum tests to compare census tract characteristics across tracts adjacent and not adjacent to distribution sites and multivariable negative binomial regression models to assess the association between census tract characteristics, including distance to the nearest site, and counts of opioid overdose deaths and naloxone reversal events. Three hundred forty-two opioid overdose deaths and 316 overdose reversals with valid location data were included in our analysis. Census tracts including or adjacent to a distribution site had higher income inequality, lower percentage black or African American residents, more drug arrests, higher population density, more overdose deaths, and more reversal events (all p < 0.05). In multivariable analysis, greater distance to the nearest distribution site (up to a distance of 4000 m) was associated with a lower count of Naloxone reversals [incidence rate ratio (IRR) = 0.51 per 500 m increase, 95% CI 0.39-0.67, p < 0.001] but was not significantly associated with opioid overdose deaths. These findings affirm that locating lay naloxone distribution sites in areas with high levels of substance use and overdose risk facilitates reversals of opioid overdoses in those immediate areas but suggests that alternative delivery methods may be necessary to reach individuals in other areas with less concentrated risk.

Ecological Risk Assessment of Land Use Change in the Poyang Lake Eco-economic Zone, China

PubMed Central

Xie, Hualin; Wang, Peng; Huang, Hongsheng

2013-01-01

Land use/land cover change has been attracting increasing attention in the field of global environmental change research because of its role in the social and ecological environment. To explore the ecological risk characteristics of land use change in the Poyang Lake Eco-economic Zone of China, an eco-risk index was established in this study by the combination of a landscape disturbance index with a landscape fragmentation index. Spatial distribution and gradient difference of land use eco-risk are analyzed by using the methods of spatial autocorrelation and semivariance. Results show that ecological risk in the study area has a positive correlation, and there is a decreasing trend with the increase of grain size both in 1995 and 2005. Because the area of high eco-risk value increased from 1995 to 2005, eco-environment quality declined slightly in the study area. There are distinct spatial changes in the concentrated areas with high land use eco-risk values from 1995 to 2005. The step length of spatial separation of land use eco-risk is comparatively long—58 km in 1995 and 11 km in 2005—respectively. There are still nonstructural factors affecting the quality of the regional ecological environment at some small-scales. Our research results can provide some useful information for land eco-management, eco-environmental harnessing and restoration. In the future, some measures should be put forward in the regions with high eco-risk value, which include strengthening land use management, avoiding unreasonable types of land use and reducing the degree of fragmentation and separation. PMID:23343986

Ecological and health risks assessment and spatial distribution of residual heavy metals in the soil of an e-waste circular economy park in Tianjin, China.

PubMed

Han, Wei; Gao, Guanghai; Geng, Jinyao; Li, Yao; Wang, Yingying

2018-04-01

Ziya Circular Economy Park is the biggest e-waste recycle park in North China before 2011, its function was then transformed in response to regulations and rules. In this paper, investigation was conducted to research the residual concentrations of 14 analytes (12 heavy metals and 2 non-metals) in the surface soil of Ziya Circular Economy Park and surrounding area. Both ecological and health assessments were evaluated using GI (geo-accumulation index) and NPI (Nemerow pollution index), and associated health risk was assessed by using USEPA model. According to the ecological risk assessment, Cu, Sb, Cd, Zn and Co were seriously enriched in the soil of the studied area. The health risk assessment proposed by USEPA indicated no significant health risks to the population. Soil properties, such as pH and organic matter, were found to correlate with the enrichment of heavy metals. Arsenic concentrations in the soil were found positively correlated to dead bacteria concentrations. Spatial distribution of heavy metals revealed that Ziya Circular Economy Park was the dominant pollution source in the studied area. Findings in this study suggest that enough attention should be payed to the heavy metal pollution in Ziya Circular Economy Park. Copyright © 2018 Elsevier Ltd. All rights reserved.

Spatial distribution and risk assessment of heavy metals in soil near a Pb/Zn smelter in Feng County, China.

PubMed

Shen, Feng; Liao, Renmei; Ali, Amjad; Mahar, Amanullah; Guo, Di; Li, Ronghua; Xining, Sun; Awasthi, Mukesh Kumar; Wang, Quan; Zhang, Zengqiang

2017-05-01

A large scale survey and a small scale continuous monitoring was conducted to evaluate the impact of Pb/Zn smelting on soil heavy metals (HMs) accumulation and potential ecological risk in Feng County, Shaanxi province of China. Soil parameters including pH, texture, CEC, spatial and temporal distribution of HMs (Cd, Cu, Ni, Pb and Zn), and BCR fractionation were monitored accordingly. The results showed the topsoil in the proximity of smelter, especially the smelter area and county seat, were highly polluted by HMs in contrast to the river basins. Fractionation of Cd and Zn in soil samples revealed higher proportion of mobile fractions than other HMs. The soil Cd and Zn contents decreased vertically, but still exceeded the second level limits of Environmental Quality Standard for Soils of China (EQSS) within 80cm. The dominated soil pollutant (Cd) had higher ecological risk than Cu, Ni, Zn and Pb. The potential ecological risk (PER) factor of Cd were 65.7% and 100% in surrounding county and smelter area, respectively. The long-term smelter dust emission mainly contributed to the HMs pollution and posed serious environment risk to living beings. Copyright © 2017 Elsevier Inc. All rights reserved.

Spatial distribution of the risk of dengue fever in southeast Brazil, 2006-2007

PubMed Central

2011-01-01

Background Many factors have been associated with circulation of the dengue fever virus and vector, although the dynamics of transmission are not yet fully understood. The aim of this work is to estimate the spatial distribution of the risk of dengue fever in an area of continuous dengue occurrence. Methods This is a spatial population-based case-control study that analyzed 538 cases and 727 controls in one district of the municipality of Campinas, São Paulo, Brazil, from 2006-2007, considering socio-demographic, ecological, case severity, and household infestation variables. Information was collected by in-home interviews and inspection of living conditions in and around the homes studied. Cases were classified as mild or severe according to clinical data, and they were compared with controls through a multinomial logistic model. A generalized additive model was used in order to include space in a non-parametric fashion with cubic smoothing splines. Results Variables associated with increased incidence of all dengue cases in the multiple binomial regression model were: higher larval density (odds ratio (OR) = 2.3 (95%CI: 2.0-2.7)), reports of mosquito bites during the day (OR = 1.8 (95%CI: 1.4-2.4)), the practice of water storage at home (OR = 2.5 (95%CI: 1.4, 4.3)), low frequency of garbage collection (OR = 2.6 (95%CI: 1.6-4.5)) and lack of basic sanitation (OR = 2.9 (95%CI: 1.8-4.9)). Staying at home during the day was protective against the disease (OR = 0.5 (95%CI: 0.3-0.6)). When cases were analyzed by categories (mild and severe) in the multinomial model, age and number of breeding sites more than 10 were significant only for the occurrence of severe cases (OR = 0.97, (95%CI: 0.96-0.99) and OR = 2.1 (95%CI: 1.2-3.5), respectively. Spatial distribution of risks of mild and severe dengue fever differed from each other in the 2006/2007 epidemic, in the study area. Conclusions Age and presence of more than 10 breeding sites were significant only for severe cases. Other predictors of mild and severe cases were similar in the multiple models. The analyses of multinomial models and spatial distribution maps of dengue fever probabilities suggest an area-specific epidemic with varying clinical and demographic characteristics. PMID:21599980

The Applications of Model-Based Geostatistics in Helminth Epidemiology and Control

PubMed Central

Magalhães, Ricardo J. Soares; Clements, Archie C.A.; Patil, Anand P.; Gething, Peter W.; Brooker, Simon

2011-01-01

Funding agencies are dedicating substantial resources to tackle helminth infections. Reliable maps of the distribution of helminth infection can assist these efforts by targeting control resources to areas of greatest need. The ability to define the distribution of infection at regional, national and subnational levels has been enhanced greatly by the increased availability of good quality survey data and the use of model-based geostatistics (MBG), enabling spatial prediction in unsampled locations. A major advantage of MBG risk mapping approaches is that they provide a flexible statistical platform for handling and representing different sources of uncertainty, providing plausible and robust information on the spatial distribution of infections to inform the design and implementation of control programmes. Focussing on schistosomiasis and soil-transmitted helminthiasis, with additional examples for lymphatic filariasis and onchocerciasis, we review the progress made to date with the application of MBG tools in large-scale, real-world control programmes and propose a general framework for their application to inform integrative spatial planning of helminth disease control programmes. PMID:21295680

Assessment ecological risk of heavy metal caused by high-intensity land reclamation in Bohai Bay, China

PubMed Central

Li, Tuoyu; Ma, Zongwen; Xu, Xuegong

2017-01-01

The article examines the detailed spatial and temporal distributions of coastal reclamation in the northwest coast of Bohai Bay experiencing rapid coastal reclamation in China from 1974 to 2010 in annual intervals. Moreover, soil elements properties and spatial distribution in reclaimed area and inform the future coastal ecosystems management was also analyzed. The results shows that 910.7 km2 of coastal wetlands have been reclaimed and conversed to industrial land during the past 36 years. It covers intertidal beach, shallow sea and island with a percentage of 76.0%, 23.5% and 0.5%, respectively. The average concentration of Mn is 686.91mg/kg and the order of concentration of heavy metal are Cr>Zn>As>Ni>Cu>Pb>Cd>Hg. We used the "space for time substitution" method to test the soil properties changes after reclamation. The potential ecological risk of heavy metal is in low level and the risk of Cd and As is relatively higher. The ecosystem-based coastal protection and management are urgent to support sustainable coastal ecosystems in Bohai bay in the future. PMID:28422982

Assessment ecological risk of heavy metal caused by high-intensity land reclamation in Bohai Bay, China.

PubMed

Zhu, Gaoru; Xie, Zhenglei; Li, Tuoyu; Ma, Zongwen; Xu, Xuegong

2017-01-01

The article examines the detailed spatial and temporal distributions of coastal reclamation in the northwest coast of Bohai Bay experiencing rapid coastal reclamation in China from 1974 to 2010 in annual intervals. Moreover, soil elements properties and spatial distribution in reclaimed area and inform the future coastal ecosystems management was also analyzed. The results shows that 910.7 km2 of coastal wetlands have been reclaimed and conversed to industrial land during the past 36 years. It covers intertidal beach, shallow sea and island with a percentage of 76.0%, 23.5% and 0.5%, respectively. The average concentration of Mn is 686.91mg/kg and the order of concentration of heavy metal are Cr>Zn>As>Ni>Cu>Pb>Cd>Hg. We used the "space for time substitution" method to test the soil properties changes after reclamation. The potential ecological risk of heavy metal is in low level and the risk of Cd and As is relatively higher. The ecosystem-based coastal protection and management are urgent to support sustainable coastal ecosystems in Bohai bay in the future.

Heavy metal contamination and ecological risk assessment in the surface sediments of the coastal area surrounding the industrial complex of Gabes city, Gulf of Gabes, SE Tunisia.

PubMed

El Zrelli, Radhouan; Courjault-Radé, Pierre; Rabaoui, Lotfi; Castet, Sylvie; Michel, Sylvain; Bejaoui, Nejla

2015-12-30

In the present study, the concentrations of 6 trace metals (Hg, Cd, Cu, Pb, Cr and Zn) were assessed in the surface sediments of the central coastal area of Gabes Gulf to determine their contamination status, source, spatial distribution and ecological risks. The ranking of metal contents was found to be Zn>Cd>Cr>Pb>Cu>Hg. Correlation analysis indicated that Cd and Zn derived mainly from the Tunisian Chemical Group phosphogypsum. The other pollutants may originate from other industrial wastes. Metallic contamination was detected in the south of chemical complex, especially in the inter-harbor zone, where the ecological risk of surface sediments is the highest, implying potential negative impacts of industrial pollutants. The spatial distribution of pollutants seems to be due to the effect of harbor installations and coastal currents. The metallic pollution status of surface sediments of Gabes Gulf is obvious, very worrying and requires rapid intervention. Copyright © 2015 Elsevier Ltd. All rights reserved.

Mapping spatial patterns of people's risk perception of landslides

NASA Astrophysics Data System (ADS)

Kofler, Christian; Pedoth, Lydia; Elzbieta Stawinoga, Agnieszka; Schneiderbauer, Stefan

2016-04-01

The resilience of communities against natural hazards is largely influenced by how the individuals perceive risk. A good understanding of people's risk perception, awareness and hazard knowledge is crucial for developing and improving risk management and communication strategies between authorities and the affected population. A lot of research has been done in investigating the social aspects of risks to natural hazards by means of interviews or questionnaires. However, there is still a lack of research in the investigation of the influence of the spatial distance to a hazard event on peoples risk perception. While the spatial dimension of a natural hazard event is always assessed in works with a natural science approach, it is often neglected in works on social aspects of natural hazards. In the present study, we aimed to overcome these gaps by combining methods from different disciplines and assessing and mapping the spatial pattern of risk perception through multivariate statistical approaches based on empirical data from questionnaires. We will present results from a case study carried out in Badia, located in the Province of South Tyrol- Italy, where in December 2012 a landslide destroyed four residential buildings and led to the evacuation of 36 people. By means of questionnaires distributed to all adults living in the case study area we assessed people's risk perception and asked respondents to allocate their place of residence on a map of the case study area subdivided in 7 zones. Based on the data of the questionnaire results we developed a risk perception factor in order to express various assessed aspects linked to risk perception with one metric. We analyzed and mapped this factor according to the different zones reflecting the spatial distance to the event. Furthermore, a cluster analysis identified various risk behavior profiles within the population. We also investigated the spatial patterns of these risk profiles. We revealed that the residential zone in the immediate proximity to the landslide event showed significantly different results than all other zones. Though we have been able to observe spatial patterns of our developed metrics that changed significantly with geographic distance, our results led to the assumption that risk perception cannot be expressed in units of length. The appropriate spatial unit rather seems to be "immediate proximity" to the event. The results of our study can support response forces and authorities in planning and adopting different communication and management strategies tailored to different groups of affected persons.

The Geographic Distribution of Genetic Risk as Compared to Social Risk for Chronic Diseases in the United States.

PubMed

Rehkopf, David H; Domingue, Benjamin W; Cullen, Mark R

2016-01-01

There is an association between chronic disease and geography, and there is evidence that the environment plays a critical role in this relationship. Yet at the same time, there is known to be substantial geographic variation by ancestry across the United States. Resulting geographic genetic variation-that is, the extent to which single nucleotide polymorphisms (SNPs) related to chronic disease vary spatially-could thus drive some part of the association between geography and disease. We describe the variation in chronic disease genetic risk by state of birth by taking risk SNPs from genome-wide association study meta-analyses for coronary artery disease, diabetes, and ischemic stroke and creating polygenic risk scores. We compare the amount of variability across state of birth in these polygenic scores to the variability in parental education, own education, earnings, and wealth. Our primary finding is that the polygenic risk scores are only weakly differentially distributed across U.S. states. The magnitude of the differences in geographic distribution is very small in comparison to the distribution of social and economic factors and thus is not likely sufficient to have a meaningful effect on geographic disease differences by U.S. state.

Spatiotemporal clusters of malaria cases at village level, northwest Ethiopia.

PubMed

Alemu, Kassahun; Worku, Alemayehu; Berhane, Yemane; Kumie, Abera

2014-06-06

Malaria attacks are not evenly distributed in space and time. In highland areas with low endemicity, malaria transmission is highly variable and malaria acquisition risk for individuals is unevenly distributed even within a neighbourhood. Characterizing the spatiotemporal distribution of malaria cases in high-altitude villages is necessary to prioritize the risk areas and facilitate interventions. Spatial scan statistics using the Bernoulli method were employed to identify spatial and temporal clusters of malaria in high-altitude villages. Daily malaria data were collected, using a passive surveillance system, from patients visiting local health facilities. Georeference data were collected at villages using hand-held global positioning system devices and linked to patient data. Bernoulli model using Bayesian approaches and Marcov Chain Monte Carlo (MCMC) methods were used to identify the effects of factors on spatial clusters of malaria cases. The deviance information criterion (DIC) was used to assess the goodness-of-fit of the different models. The smaller the DIC, the better the model fit. Malaria cases were clustered in both space and time in high-altitude villages. Spatial scan statistics identified a total of 56 spatial clusters of malaria in high-altitude villages. Of these, 39 were the most likely clusters (LLR = 15.62, p < 0.00001) and 17 were secondary clusters (LLR = 7.05, p < 0.03). The significant most likely temporal malaria clusters were detected between August and December (LLR = 17.87, p < 0.001). Travel away home, males and age above 15 years had statistically significant effect on malaria clusters at high-altitude villages. The study identified spatial clusters of malaria cases occurring at high elevation villages within the district. A patient who travelled away from home to a malaria-endemic area might be the most probable source of malaria infection in a high-altitude village. Malaria interventions in high altitude villages should address factors associated with malaria clustering.

A hot spot for systemic lupus erythematosus, but not for psoriatic arthritis, identified by spatial analysis suggests an interaction between ethnicity and place of residence.

PubMed

Al-Maini, Mustafa; Jeyalingam, Thurarshen; Brown, Patrick; Lee, Jennifer J Y; Li, Lennon; Su, Jiandong; Gladman, Dafna D; Fortin, Paul R

2013-06-01

To describe the spatial distribution of incident cases of systemic lupus erythematosus (SLE) using geographic information systems (GIS). Spatial analyses were carried out on 890 SLE patients and 541 psoriatic arthritis (PsA) patients (controls). Age- and sex-adjusted rates for SLE/PsA for each census tract were calculated using denominator population values from the Canadian census. Spatial variations in relative risk were estimated by modeling risk as the product of a time effect, an age effect, and a spatially autocorrelated risk surface to identify hot spots. Patients within the detected hot spot were compared to those outside the hot spot to identify explanatory factors. SLE patients were predominantly female (87.75%) and the incidence rate was highest among those 15-19 years of age (2.4 cases/100,000 person-years). In an SLE hot spot containing 59 patients, 100% of the patients were female and 49.1% (n = 29) were Caucasian, while outside of the hot spot, 86.9% (n = 722) of the patients were female and 68.4% (n = 568) were Caucasian. The proportion of cases of Chinese ethnicity was significantly greater within the hot spot. An interaction was found between Chinese ethnicity and residence within the hot spot, with the risk of SLE to the Chinese population found to be twice the risk to the non-Chinese population. GIS was used to map SLE cases and a hot spot was identified after adjustment for age and sex. Ethnicity by itself did not confer an increased risk of SLE, but the interaction of ethnicity with location of residence significantly increased the risk of SLE. Copyright © 2013 by the American College of Rheumatology.

A high resolution spatial population database of Somalia for disease risk mapping.

PubMed

Linard, Catherine; Alegana, Victor A; Noor, Abdisalan M; Snow, Robert W; Tatem, Andrew J

2010-09-14

Millions of Somali have been deprived of basic health services due to the unstable political situation of their country. Attempts are being made to reconstruct the health sector, in particular to estimate the extent of infectious disease burden. However, any approach that requires the use of modelled disease rates requires reasonable information on population distribution. In a low-income country such as Somalia, population data are lacking, are of poor quality, or become outdated rapidly. Modelling methods are therefore needed for the production of contemporary and spatially detailed population data. Here land cover information derived from satellite imagery and existing settlement point datasets were used for the spatial reallocation of populations within census units. We used simple and semi-automated methods that can be implemented with free image processing software to produce an easily updatable gridded population dataset at 100 × 100 meters spatial resolution. The 2010 population dataset was matched to administrative population totals projected by the UN. Comparison tests between the new dataset and existing population datasets revealed important differences in population size distributions, and in population at risk of malaria estimates. These differences are particularly important in more densely populated areas and strongly depend on the settlement data used in the modelling approach. The results show that it is possible to produce detailed, contemporary and easily updatable settlement and population distribution datasets of Somalia using existing data. The 2010 population dataset produced is freely available as a product of the AfriPop Project and can be downloaded from: http://www.afripop.org.

A high resolution spatial population database of Somalia for disease risk mapping

PubMed Central

2010-01-01

Background Millions of Somali have been deprived of basic health services due to the unstable political situation of their country. Attempts are being made to reconstruct the health sector, in particular to estimate the extent of infectious disease burden. However, any approach that requires the use of modelled disease rates requires reasonable information on population distribution. In a low-income country such as Somalia, population data are lacking, are of poor quality, or become outdated rapidly. Modelling methods are therefore needed for the production of contemporary and spatially detailed population data. Results Here land cover information derived from satellite imagery and existing settlement point datasets were used for the spatial reallocation of populations within census units. We used simple and semi-automated methods that can be implemented with free image processing software to produce an easily updatable gridded population dataset at 100 × 100 meters spatial resolution. The 2010 population dataset was matched to administrative population totals projected by the UN. Comparison tests between the new dataset and existing population datasets revealed important differences in population size distributions, and in population at risk of malaria estimates. These differences are particularly important in more densely populated areas and strongly depend on the settlement data used in the modelling approach. Conclusions The results show that it is possible to produce detailed, contemporary and easily updatable settlement and population distribution datasets of Somalia using existing data. The 2010 population dataset produced is freely available as a product of the AfriPop Project and can be downloaded from: http://www.afripop.org. PMID:20840751

Spatial dynamics of bovine tuberculosis in the Autonomous Community of Madrid, Spain (2010-2012).

PubMed

de la Cruz, Maria Luisa; Perez, Andres; Bezos, Javier; Pages, Enrique; Casal, Carmen; Carpintero, Jesus; Romero, Beatriz; Dominguez, Lucas; Barker, Christopher M; Diaz, Rosa; Alvarez, Julio

2014-01-01

Progress in control of bovine tuberculosis (bTB) is often not uniform, usually due to the effect of one or more sometimes unknown epidemiological factors impairing the success of eradication programs. Use of spatial analysis can help to identify clusters of persistence of disease, leading to the identification of these factors thus allowing the implementation of targeted control measures, and may provide some insights of disease transmission, particularly when combined with molecular typing techniques. Here, the spatial dynamics of bTB in a high prevalence region of Spain were assessed during a three year period (2010-2012) using data from the eradication campaigns to detect clusters of positive bTB herds and of those infected with certain Mycobacterium bovis strains (characterized using spoligotyping and VNTR typing). In addition, the within-herd transmission coefficient (β) was estimated in infected herds and its spatial distribution and association with other potential outbreak and herd variables was evaluated. Significant clustering of positive herds was identified in the three years of the study in the same location ("high risk area"). Three spoligotypes (SB0339, SB0121 and SB1142) accounted for >70% of the outbreaks detected in the three years. VNTR subtyping revealed the presence of few but highly prevalent strains within the high risk area, suggesting maintained transmission in the area. The spatial autocorrelation found in the distribution of the estimated within-herd transmission coefficients in herds located within distances <14 km and the results of the spatial regression analysis, support the hypothesis of shared local factors affecting disease transmission in farms located at a close proximity.

Spatial modelling of disease using data- and knowledge-driven approaches.

PubMed

Stevens, Kim B; Pfeiffer, Dirk U

2011-09-01

The purpose of spatial modelling in animal and public health is three-fold: describing existing spatial patterns of risk, attempting to understand the biological mechanisms that lead to disease occurrence and predicting what will happen in the medium to long-term future (temporal prediction) or in different geographical areas (spatial prediction). Traditional methods for temporal and spatial predictions include general and generalized linear models (GLM), generalized additive models (GAM) and Bayesian estimation methods. However, such models require both disease presence and absence data which are not always easy to obtain. Novel spatial modelling methods such as maximum entropy (MAXENT) and the genetic algorithm for rule set production (GARP) require only disease presence data and have been used extensively in the fields of ecology and conservation, to model species distribution and habitat suitability. Other methods, such as multicriteria decision analysis (MCDA), use knowledge of the causal factors of disease occurrence to identify areas potentially suitable for disease. In addition to their less restrictive data requirements, some of these novel methods have been shown to outperform traditional statistical methods in predictive ability (Elith et al., 2006). This review paper provides details of some of these novel methods for mapping disease distribution, highlights their advantages and limitations, and identifies studies which have used the methods to model various aspects of disease distribution. Copyright © 2011. Published by Elsevier Ltd.

Spatial analysis and temporal trends of porcine reproductive and respiratory syndrome in Denmark from 2007 to 2010 based on laboratory submission data.

PubMed

Antunes, Ana Carolina Lopes; Halasa, Tariq; Lauritsen, Klara Tølbøl; Kristensen, Charlotte Sonne; Larsen, Lars Erik; Toft, Nils

2015-12-21

Porcine reproductive and respiratory syndrome (PRRS) has been a cause for great concern to the Danish pig industry since it was first diagnosed in 1992. The causative agent of PRRS is an RNA virus which is divided into different genotypes. The clinical signs, as well as its morbidity and mortality, is highly variable between herds and regions. Two different genotypes of PRRS virus (PRRSV) are found in Denmark: type 1 and type 2. Approximately 40% of Danish swine herds are seropositive for one or both PRRSV types. The objective of this study was to describe the temporal trend and spatial distribution of PRRSV in Danish swine herds from 2007 to 2010, based on type-specific serological tests from the PRRS surveillance and control program in Denmark using the results stored in the information management system at the National Veterinary Institute, Technical University of Denmark (DTU Vet). The average monthly seroprevalence of PRRSV type 1 was 9% (minimum of 5%; maximum of 13%) in breeding herds, and 20% (minimum of 14%; maximum of 26%) in production herds; PRRSV type 2 had an average seroprevalence of 3% (minimum of 1%; maximum of 9%) in breeding herds and of 9% (minimum of 5%; maximum of 13%) within production herds. The seroconversion rate followed a similar and consistent pattern, being higher for type 1 than for type 2 for both PRRSV types. Regarding the spatiotemporal results, the relative risk distribution maps changed over time as a consequence of the changes in PRRSV seroprevalence, suggesting a general decline in the extent of areas with higher relative risk for both type 1 and 2. Local spatial analysis results demonstrated the existence of statistically significant clusters in areas where the relative risk was higher for both herds. PRRSV type 1 seroprevalence was constantly higher than for PRRSV type 2 in both herd types. Significant spatial clusters were consistently found in Denmark, suggesting that PRRSV is endemic in these areas. Furthermore, relative risk distribution maps revealed different patterns over time as a consequence of the changes in seroprevalence.

Strongyloides stercoralis and hookworm co-infection: spatial distribution and determinants in Preah Vihear Province, Cambodia.

PubMed

Forrer, Armelle; Khieu, Virak; Schär, Fabian; Vounatsou, Penelope; Chammartin, Frédérique; Marti, Hanspeter; Muth, Sinuon; Odermatt, Peter

2018-01-12

Strongyloides stercoralis and hookworm are two soil-transmitted helminths (STH) that are highly prevalent in Cambodia. Strongyloides stercoralis causes long-lasting infections and significant morbidity but is largely neglected, while hookworm causes the highest public health burden among STH. The two parasites have the same infection route, i.e. skin penetration. The extent of co-distribution, which could result in potential high co-morbidities, is unknown in highly endemic settings like Cambodia. The aim of this study was to predict the spatial distribution of S. stercoralis-hookworm co-infection risk and to investigate determinants of co-infection in Preah Vihear Province, North Cambodia. A cross-sectional survey was conducted in 2010 in 60 villages of Preah Vihear Province. Diagnosis was performed on two stool samples, using combined Baermann technique and Koga agar culture plate for S. stercoralis and Kato-Katz technique for hookworm. Bayesian multinomial geostatistical models were used to assess demographic, socioeconomic, and behavioural determinants of S. stercoralis-hookworm co-infection and to predict co-infection risk at non-surveyed locations. Of the 2576 participants included in the study, 48.6% and 49.0% were infected with S. stercoralis and hookworm, respectively; 43.8% of the cases were co-infections. Females, preschool aged children, adults aged 19-49 years, and participants who reported regularly defecating in toilets, systematically boiling drinking water and having been treated with anthelmintic drugs had lower odds of co-infection. While S. stercoralis infection risk did not appear to be spatially structured, hookworm mono-infection and co-infection exhibited spatial correlation at about 20 km. Co-infection risk was positively associated with longer walking distances to a health centre and exhibited a small clustering tendency. The association was only partly explained by climatic variables, suggesting a role for underlying factors, such as living conditions and remoteness. Both parasites were ubiquitous in the province, with co-infections accounting for almost half of all cases. The high prevalence of S. stercoralis calls for control measures. Despite several years of school-based de-worming programmes, hookworm infection levels remain high. Mebendazole efficacy, as well as coverage of and compliance to STH control programmes should be investigated.

Remote-sensing based approach to forecast habitat quality under climate change scenarios.

PubMed

Requena-Mullor, Juan M; López, Enrique; Castro, Antonio J; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

2017-01-01

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071-2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios.

Remote-sensing based approach to forecast habitat quality under climate change scenarios

PubMed Central

Requena-Mullor, Juan M.; López, Enrique; Castro, Antonio J.; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

2017-01-01

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071–2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios. PMID:28257501

Image processing techniques revealing the relationship between the field-measured ambient gamma dose equivalent rate and geological conditions at a granitic area, Velence Mountains, Hungary

NASA Astrophysics Data System (ADS)

Beltran Torres, Silvana; Petrik, Attila; Zsuzsanna Szabó, Katalin; Jordan, Gyozo; Szabó, Csaba

2017-04-01

In order to estimate the annual dose that the public receive from natural radioactivity, the identification of the potential risk areas is required which, in turn, necessitates understanding the relationship between the spatial distribution of natural radioactivity and the geogenic risk factors (e.g., rock types, dykes, faults, soil conditions, etc.). A detailed spatial analysis of ambient gamma dose equivalent rate was performed in the western side of Velence Mountains, the largest outcropped granitic area in Hungary. In order to assess the role of local geology in the spatial distribution of ambient gamma dose rates, field measurements were carried out at ground level at 300 sites along a 250 m x 250 m regular grid in a total surface of 14.7 km2. Digital image processing methods were applied to identify anomalies, heterogeneities and spatial patterns in the measured gamma dose rates, including local maxima and minima determination, digital cross sections, gradient magnitude and gradient direction, second derivative profile curvature, local variability, lineament density, 2D autocorrelation and directional variogram analyses. Statistical inference showed that different gamma dose rate levels are associated with the rock types (i.e., Carboniferous granite, Pleistocene colluvial, proluvial, deluvial sediments and talus, and Pannonian sand and pebble), with the highest level on the Carboniferous granite including outlying values. Moreover, digital image processing revealed that linear gamma dose rate spatial features are parallel to the SW-NE dyke system and possibly to the NW-SE main fractures. The results of this study underline the importance of understanding the role of geogenic risk factors influencing the ambient gamma dose rate received by public. The study also demonstrates the power of the image processing techniques for the identification of spatial pattern in field-measured geogenic radiation.

Method for Assessing the Integrated Risk of Soil Pollution in Industrial and Mining Gathering Areas

PubMed Central

Guan, Yang; Shao, Chaofeng; Gu, Qingbao; Ju, Meiting; Zhang, Qian

2015-01-01

Industrial and mining activities are recognized as major sources of soil pollution. This study proposes an index system for evaluating the inherent risk level of polluting factories and introduces an integrated risk assessment method based on human health risk. As a case study, the health risk, polluting factories and integrated risks were analyzed in a typical industrial and mining gathering area in China, namely, Binhai New Area. The spatial distribution of the risk level was determined using a Geographic Information System. The results confirmed the following: (1) Human health risk in the study area is moderate to extreme, with heavy metals posing the greatest threat; (2) Polluting factories pose a moderate to extreme inherent risk in the study area. Such factories are concentrated in industrial and urban areas, but are irregularly distributed and also occupy agricultural land, showing a lack of proper planning and management; (3) The integrated risks of soil are moderate to high in the study area. PMID:26580644

Prevalence and Risk Factors for Toxoplasmosis in Middle Java, Indonesia.

PubMed

Retmanasari, Annisa; Widartono, Barandi Sapta; Wijayanti, Mahardika Agus; Artama, Wayan Tunas

2017-03-01

Toxoplasmosis is a zoonosis caused by Toxoplasma gondii. Risk factors include consumption of undercooked meat, raw vegetables, and unfiltered water. This study aims to determine the seroprevalence and spatial distribution of toxoplasmosis in Middle Java, Indonesia, using an EcoHealth approach, combined with geographic information system (GIS). A total of 630 participants were randomly selected from seven districts. Each participant completed a questionnaire and provided a blood sample. The seroprevalence of toxoplasmosis was 62.5%. Of those who were seropositive, 90.1% were IgG+, and 9.9% were IgG+ and IgM+. Several risk factors were identified, including living at elevations of ≤200 m, compared with >200 m (OR = 56.2; P < 0.001), daily contact with raw meat (OR = 1.8; P = 0.001), unfiltered water (OR = 1.7; P = 0.003), and density of cats (OR = 1.4; P = 0.045). Visualizing the spatial distribution of seropositive respondents highlighted clustering in lowland areas. This study highlighted that Middle Java has a high prevalence of toxoplasmosis and identified some important environmental, ecological, and demographic risk factors. When researching diseases, such as toxoplasmosis, where animal hosts, human lifestyle, and environmental factors are involved in transmission, an EcoHealth method is essential to ensure a fully collaborative approach to developing interventions to reduce the risk of transmission in high-risk populations.

Connecting the Dots Between Health, Poverty and Place in Accra, Ghana

PubMed Central

Weeks, John R.; Getis, Arthur; Stow, Douglas A.; Hill, Allan G.; Rain, David; Engstrom, Ryan; Stoler, Justin; Lippitt, Christopher; Jankowska, Marta; Lopez-Carr, Anna Carla; Coulter, Lloyd; Ofiesh, Caetlin

2013-01-01

West Africa has a rapidly growing population, an increasing fraction of which lives in urban informal settlements characterized by inadequate infrastructure and relatively high health risks. Little is known, however, about the spatial or health characteristics of cities in this region or about the spatial inequalities in health within them. In this article we show how we have been creating a data-rich field laboratory in Accra, Ghana, to connect the dots between health, poverty, and place in a large city in West Africa. Our overarching goal is to test the hypothesis that satellite imagery, in combination with census and limited survey data, such as that found in demographic and health surveys (DHSs), can provide clues to the spatial distribution of health inequalities in cities where fewer data exist than those we have collected for Accra. To this end, we have created the first digital boundary file of the city, obtained high spatial resolution satellite imagery for two dates, collected data from a longitudinal panel of 3,200 women spatially distributed throughout Accra, and obtained microlevel data from the census. We have also acquired water, sewerage, and elevation layers and then coupled all of these data with extensive field research on the neighborhood structure of Accra. We show that the proportional abundance of vegetation in a neighborhood serves as a key indicator of local levels of health and well-being and that local perceptions of health risk are not always consistent with objective measures. PMID:24532846

MosquitoMap and the Mal-area calculator: new web tools to relate mosquito species distribution with vector borne disease

PubMed Central

2010-01-01

Background Mosquitoes are important vectors of diseases but, in spite of various mosquito faunistic surveys globally, there is a need for a spatial online database of mosquito collection data and distribution summaries. Such a resource could provide entomologists with the results of previous mosquito surveys, and vector disease control workers, preventative medicine practitioners, and health planners with information relating mosquito distribution to vector-borne disease risk. Results A web application called MosquitoMap was constructed comprising mosquito collection point data stored in an ArcGIS 9.3 Server/SQL geodatabase that includes administrative area and vector species x country lookup tables. In addition to the layer containing mosquito collection points, other map layers were made available including environmental, and vector and pathogen/disease distribution layers. An application within MosquitoMap called the Mal-area calculator (MAC) was constructed to quantify the area of overlap, for any area of interest, of vector, human, and disease distribution models. Data standards for mosquito records were developed for MosquitoMap. Conclusion MosquitoMap is a public domain web resource that maps and compares georeferenced mosquito collection points to other spatial information, in a geographical information system setting. The MAC quantifies the Mal-area, i.e. the area where it is theoretically possible for vector-borne disease transmission to occur, thus providing a useful decision tool where other disease information is limited. The Mal-area approach emphasizes the independent but cumulative contribution to disease risk of the vector species predicted present. MosquitoMap adds value to, and makes accessible, the results of past collecting efforts, as well as providing a template for other arthropod spatial databases. PMID:20167090

MosquitoMap and the Mal-area calculator: new web tools to relate mosquito species distribution with vector borne disease.

PubMed

Foley, Desmond H; Wilkerson, Richard C; Birney, Ian; Harrison, Stanley; Christensen, Jamie; Rueda, Leopoldo M

2010-02-18

Mosquitoes are important vectors of diseases but, in spite of various mosquito faunistic surveys globally, there is a need for a spatial online database of mosquito collection data and distribution summaries. Such a resource could provide entomologists with the results of previous mosquito surveys, and vector disease control workers, preventative medicine practitioners, and health planners with information relating mosquito distribution to vector-borne disease risk. A web application called MosquitoMap was constructed comprising mosquito collection point data stored in an ArcGIS 9.3 Server/SQL geodatabase that includes administrative area and vector species x country lookup tables. In addition to the layer containing mosquito collection points, other map layers were made available including environmental, and vector and pathogen/disease distribution layers. An application within MosquitoMap called the Mal-area calculator (MAC) was constructed to quantify the area of overlap, for any area of interest, of vector, human, and disease distribution models. Data standards for mosquito records were developed for MosquitoMap. MosquitoMap is a public domain web resource that maps and compares georeferenced mosquito collection points to other spatial information, in a geographical information system setting. The MAC quantifies the Mal-area, i.e. the area where it is theoretically possible for vector-borne disease transmission to occur, thus providing a useful decision tool where other disease information is limited. The Mal-area approach emphasizes the independent but cumulative contribution to disease risk of the vector species predicted present. MosquitoMap adds value to, and makes accessible, the results of past collecting efforts, as well as providing a template for other arthropod spatial databases.

Bulk tank milk prevalence and production losses, spatial analysis, and predictive risk mapping of Ostertagia ostertagi infections in Mexican cattle herds.

PubMed

Villa-Mancera, Abel; Pastelín-Rojas, César; Olivares-Pérez, Jaime; Córdova-Izquierdo, Alejandro; Reynoso-Palomar, Alejandro

2018-05-01

This study investigated the prevalence, production losses, spatial clustering, and predictive risk mapping in different climate zones in five states of Mexico. The bulk tank milk samples obtained between January and April 2015 were analyzed for antibodies against Ostertagia ostertagi using the Svanovir ELISA. A total of 1204 farm owners or managers answered the questionnaire. The overall herd prevalence and mean optical density ratio (ODR) of parasite were 61.96% and 0.55, respectively. Overall, the production loss was approximately 0.542 kg of milk per parasited cow per day (mean ODR = 0.92, 142 farms, 11.79%). The spatial disease cluster analysis using SatScan software indicated that two high-risk clusters were observed. In the multivariable analysis, three models were tested for potential association with the ELISA results supported by climatic, environmental, and management factors. The final logistic regression model based on both climatic/environmental and management variables included the factors rainfall, elevation, land surface temperature (LST) day, and parasite control program that were significantly associated with an increased risk of infection. Geostatistical kriging was applied to generate a risk map for the presence of parasite in dairy cattle herds in Mexico. The results indicate that climatic and meteorological factors had a higher potential impact on the spatial distribution of O. ostertagi than the management factors.

Spatial-temporal trend and health implications of polycyclic aromatic hydrocarbons (PAHs) in resident oysters, South China Sea: A case study of Eastern Guangdong coast.

PubMed

Yu, Zi-Ling; Lin, Qin; Gu, Yang-Guang; Ke, Chang-Liang; Sun, Run-Xia

2016-09-15

Spatial and temporal distributions of polycyclic aromatic hydrocarbons (PAHs) were investigated in Eastern Guangdong coast, China. Total PAH concentrations in oysters ranged from 231 to 1178ng/g with a mean concentration of 622ng/g dry weight. Compared with other bays and estuaries, PAH levels in oysters were moderate. Spatial distribution of PAHs was site specific, with relatively high PAH concentrations observed in Zhelin Bay and Kaozhouyang Bay. Based on the Spearman test analysis, only PAH concentration in oysters from Jiazi Harbor showed a significant increasing trend (P<0.05). Three-ring PAHs were the most abundant, accounting for 54.2%-88.4% of total PAHs. Diagnostic ratios suggested that PAHs were derived mainly from petroleum origin. BaP and ∑4PAH concentrations were well within the European Union limits (5ng/g and 30ng/g wet weight, respectively). The incremental lifetime cancer risks (ILCR) for PAHs were <10(-5), indicating that the adverse health risks associated with oyster consumption in this area were minimal. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatial analysis to identify high risk areas for traffic crashes resulting in death of pedestrians in Tehran

PubMed Central

Moradi, Ali; Soori, Hamid; Kavousi, Amir; Eshghabadi, Farshid; Jamshidi, Ensiyeh; Zeini, Salahdien

2016-01-01

Background: More than 20% of deaths from traffic crashes are related to pedestrians. This figure in Tehran, the capital of Iran, reaches to 40%. This study aimed to determine the high-risk areas and spatially analyze the traffic crashes, causing death to pedestrians in Tehran. Methods: Mapping was used to display the distribution of the crashes. Determining the distribution pattern of crashes and the hot spots/ low-risk areas were done, using Moran’s I index and Getis-Ord G, respectively. Results: A total of 198 crashes were studied; 92 of which, (46.4%) occurred in 2013 to 2014 and other 106 cases (63.6%) occurred in 2014 to 2015. The highest and the lowest frequency of crashes was related to January (26 cases) and June (10 cases), respectively. One hundred fifty- eight cases (79.8%) of crashes occurred in Tehran highways. Moran’s index showed that the studied traffic crashes had a cluster distribution (p<0.001). Getis- Ord General G index indicated that the distribution of hot and cold spots of the studied crashes was statistically significant (p<0.001). Conclusion: The majority of traffic crashes causing death to pedestrians occurred in highways located in the main entrances and exits of Tehran. Given the important role of environmental factors in the occurrence of traffic crashes related to pedestrians, identification of these factors requires more studies with casual inferences. PMID:28210615

[Spatial distribution prediction of surface soil Pb in a battery contaminated site].

PubMed

Liu, Geng; Niu, Jun-Jie; Zhang, Chao; Zhao, Xin; Guo, Guan-Lin

2014-12-01

In order to enhance the reliability of risk estimation and to improve the accuracy of pollution scope determination in a battery contaminated site with the soil characteristic pollutant Pb, four spatial interpolation models, including Combination Prediction Model (OK(LG) + TIN), kriging model (OK(BC)), Inverse Distance Weighting model (IDW), and Spline model were employed to compare their effects on the spatial distribution and pollution assessment of soil Pb. The results showed that Pb concentration varied significantly and the data was severely skewed. The variation coefficient of the site was higher in the local region. OK(LG) + TIN was found to be more accurate than the other three models in predicting the actual pollution situations of the contaminated site. The prediction accuracy of other models was lower, due to the effect of the principle of different models and datum feature. The interpolation results of OK(BC), IDW and Spline could not reflect the detailed characteristics of seriously contaminated areas, and were not suitable for mapping and spatial distribution prediction of soil Pb in this site. This study gives great contributions and provides useful references for defining the remediation boundary and making remediation decision of contaminated sites.

Spatial Distribution and Fuzzy Health Risk Assessment of Trace Elements in Surface Water from Honghu Lake.

PubMed

Li, Fei; Qiu, Zhenzhen; Zhang, Jingdong; Liu, Chaoyang; Cai, Ying; Xiao, Minsi

2017-09-04

Previous studies revealed that Honghu Lake was polluted by trace elements due to anthropogenic activities. This study investigated the spatial distribution of trace elements in Honghu Lake, and identified the major pollutants and control areas based on the fuzzy health risk assessment at screening level. The mean total content of trace elements in surface water decreased in the order of Zn (18.04 μg/L) > Pb (3.42 μg/L) > Cu (3.09 μg/L) > Cr (1.63 μg/L) > As (0.99 μg/L) > Cd (0.14 μg/L), within limits of Drinking Water Guidelines. The results of fuzzy health risk assessment indicated that there was no obvious non-carcinogenic risk to human health, while carcinogenic risk was observed in descending order of As > Cr > Cd > Pb. As was regarded to have the highest carcinogenic risk among selected trace elements because it generally accounted for 64% of integrated carcinogenic risk. Potential carcinogenic risk of trace elements in each sampling site was approximately at medium risk level (10 -5 to 10 -4 ). The areas in the south (S4, S13, and S16) and northeast (S8, S18, and S19) of Honghu Lake were regarded as the risk priority control areas. However, the corresponding maximum memberships of integrated carcinogenic risk in S1, S3, S10-S13, S15, and S18 were of relatively low credibility (50-60%), and may mislead the decision-makers in identifying the risk priority areas. Results of fuzzy assessment presented the subordinate grade and corresponding reliability of risk, and provided more full-scale results for decision-makers, which made up for the deficiency of certainty assessment to a certain extent.

Spatial Distribution and Fuzzy Health Risk Assessment of Trace Elements in Surface Water from Honghu Lake

PubMed Central

Qiu, Zhenzhen; Zhang, Jingdong; Liu, Chaoyang; Cai, Ying; Xiao, Minsi

2017-01-01

Previous studies revealed that Honghu Lake was polluted by trace elements due to anthropogenic activities. This study investigated the spatial distribution of trace elements in Honghu Lake, and identified the major pollutants and control areas based on the fuzzy health risk assessment at screening level. The mean total content of trace elements in surface water decreased in the order of Zn (18.04 μg/L) > Pb (3.42 μg/L) > Cu (3.09 μg/L) > Cr (1.63 μg/L) > As (0.99 μg/L) > Cd (0.14 μg/L), within limits of Drinking Water Guidelines. The results of fuzzy health risk assessment indicated that there was no obvious non-carcinogenic risk to human health, while carcinogenic risk was observed in descending order of As > Cr > Cd > Pb. As was regarded to have the highest carcinogenic risk among selected trace elements because it generally accounted for 64% of integrated carcinogenic risk. Potential carcinogenic risk of trace elements in each sampling site was approximately at medium risk level (10−5 to 10−4). The areas in the south (S4, S13, and S16) and northeast (S8, S18, and S19) of Honghu Lake were regarded as the risk priority control areas. However, the corresponding maximum memberships of integrated carcinogenic risk in S1, S3, S10–S13, S15, and S18 were of relatively low credibility (50–60%), and may mislead the decision-makers in identifying the risk priority areas. Results of fuzzy assessment presented the subordinate grade and corresponding reliability of risk, and provided more full-scale results for decision-makers, which made up for the deficiency of certainty assessment to a certain extent. PMID:28869576

[Distribution and pollution assessment of heavy metals in soil of relocation areas from the Danjiangkou Reservoir].

PubMed

Zhang, Lei; Qin, Yan-Wen; Zheng, Bing-Hui; Shi, Yao; Han, Chao-Nan

2013-01-01

The aim of this article is to explore the pollution level and potential ecological risk of heavy metals in soil of the relocation areas from the Danjiangkou Reservoir. The contents and spatial distribution of Cd, Pb, Cu, Zn, Cr and As in soil of the relocation areas from the Danjiangkou Reservoir were analyzed. The integrated pollution index and potential ecological risk index were used to evaluate the contamination degree and potential ecological risk of these elements. The results indicated that the average contents of Cd, Pb, Cu, Zn, Cr and As in the samples were 0.61, 23.11, 58.25, 22.65, 58.99 and 16.95 mg x kg(-1), respectively. Compared with the background value of soils from Henan province, all these 6 elements except Zn were enriched to some extent, especially Cd. Similar patterns were observed for the spatial distribution of Cu, Zn, and Pb. Compared with the contents of heavy metals in surface sediments of the typical domestic reservoirs, Cd and As in soil of the relocation areas from the Danjiangkou Reservoir were heavily accumulated. The correlation analysis showed that there were significant positive correlations among Pb, Cu, and Zn. And there was also significant positive correlation between Cr and Pb. In contrast, negative correlation was found between Cr and As. To sum up, the comprehensive assessment results showed that Cd was the primary element with high ecological risk.

Monitoring of emerging pollutants in Guadiamar River basin (South of Spain): analytical method, spatial distribution and environmental risk assessment.

PubMed

Garrido, Eva; Camacho-Muñoz, Dolores; Martín, Julia; Santos, Antonio; Santos, Juan Luis; Aparicio, Irene; Alonso, Esteban

2016-12-01

Guadiamar River is located in the southwest of the Iberian Peninsula and connects two protected areas in the South of Spain: Sierra Morena and Doñana National Park. It is sited in an area affected by urban, industrial and agriculture sewage pollution and with tradition on intensive mining activities. Most of the studies performed in this area have been mainly focused on the presence of heavy metals and, until now, little is known about the occurrence of other contaminants such as emerging organic pollutants (EOPs). In this work, an analytical method has been optimized and validated for monitoring of forty-seven EOPs in surface water. The analytical method has been applied to study the distribution and environmental risk of these pollutants in Guadiamar River basin. The analytical method was based on solid-phase extraction and determination by liquid chromatography-triple quadrupole-tandem mass spectrometry. The 60 % of the target compounds were found in the analyzed samples. The highest concentrations were found for two plasticizers (bisphenol A and di(2-ethyhexyl)phthalate, mean concentration up to 930 ng/L) and two pharmaceutical compounds (caffeine (up to 623 ng/L) and salicylic acid (up to 318 ng/L)). This study allowed to evaluate the potential sources (industrial or urban) of the studied compounds and the spatial distribution of their concentrations along the river. Environmental risk assessment showed a major risk on the south of the river, mainly due to discharges of wastewater effluents.

Spatial and space-time clustering of tuberculosis in Gurage Zone, Southern Ethiopia.

PubMed

Tadesse, Sebsibe; Enqueselassie, Fikre; Hagos, Seifu

2018-01-01

Spatial targeting is advocated as an effective method that contributes for achieving tuberculosis control in high-burden countries. However, there is a paucity of studies clarifying the spatial nature of the disease in these countries. This study aims to identify the location, size and risk of purely spatial and space-time clusters for high occurrence of tuberculosis in Gurage Zone, Southern Ethiopia during 2007 to 2016. A total of 15,805 patient data that were retrieved from unit TB registers were included in the final analyses. The spatial and space-time cluster analyses were performed using the global Moran's I, Getis-Ord [Formula: see text] and Kulldorff's scan statistics. Eleven purely spatial and three space-time clusters were detected (P <0.001).The clusters were concentrated in border areas of the Gurage Zone. There were considerable spatial variations in the risk of tuberculosis by year during the study period. This study showed that tuberculosis clusters were mainly concentrated at border areas of the Gurage Zone during the study period, suggesting that there has been sustained transmission of the disease within these locations. The findings may help intensify the implementation of tuberculosis control activities in these locations. Further study is warranted to explore the roles of various ecological factors on the observed spatial distribution of tuberculosis.

[Spatiotemporal dynamic fuzzy evaluation of wetland environmental pollution risk in Dayang estuary of Liaoning Province, Northeast China based on remote sensing].

PubMed

Sun, Yong-Guang; Zhao, Dong-Zhi; Zhang, Feng-Shou; Wei, Bao-Quan; Chu, Jia-Lan; Su, Xiu

2012-11-01

Based on the aerial image data of Dayang estuary in 2008, and by virtue of Analytic Hierarchy Process (AHP) , remote sensing technology, and GIS spatial analysis, a spatiotemporal evaluation was made on the comprehensive level of wetland environmental pollution risk in Dayang estuary, with the impacts of typical human activities on the dynamic variation of this comprehensive level discussed. From 1958 to 2008, the comprehensive level of the environmental pollution risk in study area presented an increasing trend. Spatially, this comprehensive level declined from land to ocean, and showed a zonal distribution. Tourism development activities unlikely led to the increase of the comprehensive level, while human inhabitation, transportation, and aquaculture would exacerbate the risk of environmental pollution. This study could provide reference for the sea area use planning, ecological function planning, and pollutants control of estuary region.

Spatio-temporal patterns of Campylobacter colonization in Danish broilers.

PubMed

Chowdhury, S; Themudo, G E; Sandberg, M; Ersbøll, A K

2013-05-01

Despite a number of risk-factor studies in different countries, the epidemiology of Campylobacter colonization in broilers, particularly spatial dependencies, is still not well understood. A series of analyses (visualization and exploratory) were therefore conducted in order to obtain a better understanding of the spatial and temporal distribution of Campylobacter in the Danish broiler population. In this study, we observed a non-random temporal occurrence of Campylobacter, with high prevalence during summer and low during winter. Significant spatio-temporal clusters were identified in the same areas in the summer months from 2007 to 2009. Range of influence between broiler farms were estimated at distances of 9.6 km and 13.5 km in different years. Identification of areas and time with greater risk indicates variable presence of risk factors with space and time. Implementation of safety measures on farms within high-risk clusters during summer could have an impact in reducing prevalence.

Spatial distribution and ecological risk assessment of heavy metal on surface sediment in west part of Java Sea

NASA Astrophysics Data System (ADS)

Effendi, Hefni; Wardiatno, Yusli; Kawaroe, Mujizat; Mursalin; Fauzia Lestari, Dea

2017-01-01

The surface sediments were identified from west part of Java Sea to evaluate spatial distribution and ecological risk potential of heavy metals (Hg, As, Cd, Cr, Cu, Pb, Zn and Ni). The samples were taken from surface sediment (<0.5 m) in 26 m up to 80 m water depth with Eikman grab. The average material composition on sediment samples were clay (9.86%), sand (8.57%) and mud sand (81.57%). The analysis showed that Pb (11.2%), Cd (49.7%), and Ni (59.5%) exceeded of Probably Effect Level (PEL). Base on ecological risk analysis, {{Cd }}≤ft( {E_r^i:300.64} \\right) and {{Cr }}≤ft( {E_r^i:0.02} \\right) were categorized to high risk and low risk criteria. The ecological risk potential sequences of this study were Cd>Hg>Pb>Ni>Cu>As>Zn>Cr. Furthermore, the result of multivariate statistical analysis shows that correlation among heavy metals (As/Ni, Cd/Ni, and Cu/Zn) and heavy metals with Risk Index (Cd/Ri and Ni/Ri) had positive correlation in significance level p<0.05. Total variance of analysis factor was 80.04% and developed into 3 factors (eigenvalues >1). On the cluster analysis, Cd, Ni, Pb were identified as fairly high contaminations level (cluster 1), Hg as moderate contamination level (cluster 2) and Cu, Zn, Cr with lower contamination level (cluster 3).

Spatial distributions, fractionation characteristics, and ecological risk assessment of trace elements in sediments of Chaohu Lake, a large eutrophic freshwater lake in eastern China.

PubMed

Wu, Lei; Liu, Guijian; Zhou, Chuncai; Liu, Rongqiong; Xi, Shanshan; Da, Chunnian; Liu, Fei

2018-01-01

The concentrations, spatial distribution, fractionation characteristics, and potential ecological risks of trace elements (Cu, Pb, Zn, Cr, Ni, and Co) in the surface sediment samples collected from 32 sites in Chaohu Lake were investigated. The improved BCR sequential extraction procedure was applied to analyze the chemical forms of trace elements in sediments. The enrichment factor (EF), sediment quality guidelines (SQGs), potential ecological risk index (PERI), and risk assessment code (RAC) were employed to evaluate the pollution levels and the potential ecological risks. The results found that the concentrations of Cu, Pb, Zn, Cr, Ni, and Co in the surface sediments were 78.59, 36.91, 161.84, 98.87, 38.92, and 10.09 mg kg -1 , respectively. The lower concentrations of Cu, Pb, Zn, Cr, and Ni were almost found in the middle part of the lake, while Co increased from the western toward the eastern parts of the lake. Cr, Ni, Co, and Zn predominantly existed in the residual fractions, with the average values of 76.35, 59.22, 45.60, and 44.30%, respectively. Cu and Pb were mainly combined with Fe/Mn oxides in reducible fraction, with the average values of 66.4 and 69.1%, respectively. The pollution levels were different among the selected elements. Cu had the highest potential ecological risk, while Cr had the lowest potential ecological risk.

The Spatial Scaling of Global Rainfall Extremes

NASA Astrophysics Data System (ADS)

Devineni, N.; Xi, C.; Lall, U.; Rahill-Marier, B.

2013-12-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (upto 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances. We also investigate the connection of persistent rainfall events at different latitudinal bands to large-scale climate phenomena such as ENSO. Finally, we present the scaling phenomena of contiguous flooded areas as a result of large scale organization of long duration rainfall events. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional and portfolio analysis can be developed.

[AVS concentrations in Xinan Creek and the influencing factors].

PubMed

Liu, Xiao-Bing; Wen, Yan-Mao; Li, Feng; Wu, Chang-Hua; Duan, Zhi-Peng

2012-07-01

Sediment and overlying water samples were collected at 10 sampling stations at Xinan Creek, a tidal river in Pearl River Delta, and analyzed for physical and chemical characteristics as well as microbial incicators, in order to reveal the main factors dominating the spatial distribution of acid volatile sulfide (AVS). The effects of Eh, SRB OC and TS on the spatial distribution of AVS were investigated and the impact of AVS on the toxicity of heavy metals in the studied area was evaluated. The results showed that the range of AVS was 0.207-41.453 micromol x g(-1), with an average of 6.684 micromol x g(-1), which is relatively high compared to the results in other studies. The AVS value of the surface layer was higher than the bottom layer in 5 stations. The AVS values in both the surface layer and the bottom layer were highly variable, the coefficients of variation being 93.61% and 153.09% , respectively. The analytical results revealed that TS was the factor with the greatest impact on the spatial distribution of AVS, and the order was TS > OC > Eh > SRB. Potential ecological risk of heavy metals existed in 60% of the smpling stations based on the value of Sigma (SEM5-AVS), however, with the criterion of [Sigma(SEM5-AVS)]/foc, none of them had inacceptable ecological risk. Furthermore, in terms of single species of heavy metals, there was certain risk of toxic effect for all the five heavy metals (Cd, Ni, Cu, Zn and Pb). The above mentioned results will provide valuable data for the in-depth study of the formation mechanism of AVS and helpful reference for environmental impact assessment and scientific rehabilitation of heavy metals in polluted rivers.

Geostatistical modelling of household malaria in Malawi

NASA Astrophysics Data System (ADS)

Chirombo, J.; Lowe, R.; Kazembe, L.

2012-04-01

Malaria is one of the most important diseases in the world today, common in tropical and subtropical areas with sub-Saharan Africa being the region most burdened, including Malawi. This region has the right combination of biotic and abiotic components, including socioeconomic, climatic and environmental factors that sustain transmission of the disease. Differences in these conditions across the country consequently lead to spatial variation in risk of the disease. Analysis of nationwide survey data that takes into account this spatial variation is crucial in a resource constrained country like Malawi for targeted allocation of scare resources in the fight against malaria. Previous efforts to map malaria risk in Malawi have been based on limited data collected from small surveys. The Malaria Indicator Survey conducted in 2010 is the most comprehensive malaria survey carried out in Malawi and provides point referenced data for the study. The data has been shown to be spatially correlated. We use Bayesian logistic regression models with spatial correlation to model the relationship between malaria presence in children and covariates such as socioeconomic status of households and meteorological conditions. This spatial model is then used to assess how malaria varies spatially and a malaria risk map for Malawi is produced. By taking intervention measures into account, the developed model is used to assess whether they have an effect on the spatial distribution of the disease and Bayesian kriging is used to predict areas where malaria risk is more likely to increase. It is hoped that this study can help reveal areas that require more attention from the authorities in the continuing fight against malaria, particularly in children under the age of five.

Predicting disease risk, identifying stakeholders, and informing control strategies: A case study of anthrax in Montana

PubMed Central

Morris, Lillian R.; Blackburn, Jason K.

2018-01-01

Infectious diseases that affect wildlife and livestock are challenging to manage, and can lead to large scale die offs, economic losses, and threats to human health. The management of infectious diseases in wildlife and livestock is made easier with knowledge of disease risk across space and identifying stakeholders associated with high risk landscapes. This study focuses on anthrax, caused by the bacterium Bacillus anthracis, risk to wildlife and livestock in Montana. There is a history of anthrax in Montana, but the spatial extent of disease risk and subsequent wildlife species at risk are not known. Our objective was to predict the potential geographic distribution of anthrax risk across Montana, identify wildlife species at risk and their distributions, and define stakeholders. We used an ecological niche model to predict the potential distribution of anthrax risk. We overlaid susceptible wildlife species distributions and land ownership delineations on our risk map. We found that there was an extensive region across Montana predicted as potential anthrax risk. These potentially risky landscapes overlapped the ranges of all 6 ungulate species considered in the analysis and livestock grazing allotments, and this overlap was on public and private land for all species. Our findings suggest that there is the potential for a multi species anthrax outbreak on multiple landscapes across Montana. Our potential anthrax risk map can be used to prioritize landscapes for surveillance and for implementing livestock vaccination programs. PMID:27169560

Predicting Disease Risk, Identifying Stakeholders, and Informing Control Strategies: A Case Study of Anthrax in Montana.

PubMed

Morris, Lillian R; Blackburn, Jason K

2016-06-01

Infectious diseases that affect wildlife and livestock are challenging to manage and can lead to large-scale die-offs, economic losses, and threats to human health. The management of infectious diseases in wildlife and livestock is made easier with knowledge of disease risk across space and identifying stakeholders associated with high-risk landscapes. This study focuses on anthrax, caused by the bacterium Bacillus anthracis, risk to wildlife and livestock in Montana. There is a history of anthrax in Montana, but the spatial extent of disease risk and subsequent wildlife species at risk are not known. Our objective was to predict the potential geographic distribution of anthrax risk across Montana, identify wildlife species at risk and their distributions, and define stakeholders. We used an ecological niche model to predict the potential distribution of anthrax risk. We overlaid susceptible wildlife species distributions and land ownership delineations on our risk map. We found that there was an extensive region across Montana predicted as potential anthrax risk. These potentially risky landscapes overlapped the ranges of all 6 ungulate species considered in the analysis and livestock grazing allotments, and this overlap was on public and private land for all species. Our findings suggest that there is the potential for a multi-species anthrax outbreak on multiple landscapes across Montana. Our potential anthrax risk map can be used to prioritize landscapes for surveillance and for implementing livestock vaccination programs.

The Spatial Distributions and Variations of Water Environmental Risk in Yinma River Basin, China

PubMed Central

Di, Hui; Liu, Xingpeng; Tong, Zhijun; Ji, Meichen

2018-01-01

Water environmental risk is the probability of the occurrence of events caused by human activities or the interaction of human activities and natural processes that will damage a water environment. This study proposed a water environmental risk index (WERI) model to assess the water environmental risk in the Yinma River Basin based on hazards, exposure, vulnerability, and regional management ability indicators in a water environment. The data for each indicator were gathered from 2000, 2005, 2010, and 2015 to assess the spatial and temporal variations in water environmental risk using particle swarm optimization and the analytic hierarchy process (PSO-AHP) method. The results showed that the water environmental risk in the Yinma River Basin decreased from 2000 to 2015. The risk level of the water environment was high in Changchun, while the risk levels in Yitong and Yongji were low. The research methods provide information to support future decision making by the risk managers in the Yinma River Basin, which is in a high-risk water environment. Moreover, water environment managers could reduce the risks by adjusting the indicators that affect water environmental risks. PMID:29543706

Comparative Epidemiology of Highly Pathogenic Avian Influenza Virus H5N1 and H5N6 in Vietnamese Live Bird Markets: Spatiotemporal Patterns of Distribution and Risk Factors.

PubMed

Mellor, Kate C; Meyer, Anne; Elkholly, Doaa A; Fournié, Guillaume; Long, Pham T; Inui, Ken; Padungtod, Pawin; Gilbert, Marius; Newman, Scott H; Vergne, Timothée; Pfeiffer, Dirk U; Stevens, Kim B

2018-01-01

Highly pathogenic avian influenza (HPAI) H5N1 virus has been circulating in Vietnam since 2003, whilst outbreaks of HPAI H5N6 virus are more recent, having only been reported since 2014. Although the spatial distribution of H5N1 outbreaks and risk factors for virus occurrence has been extensively studied, there have been no comparative studies for H5N6. Data collected through active surveillance of Vietnamese live bird markets (LBMs) between 2011 and 2015 were used to explore and compare the spatiotemporal distributions of H5N1- and H5N6-positive LBMs. Conditional autoregressive models were developed to quantify spatiotemporal associations between agroecological factors and the two HPAI strains using the same set of predictor variables. Unlike H5N1, which exhibited a strong north-south divide, with repeated occurrence in the extreme south of a cluster of high-risk provinces, H5N6 was homogeneously distributed throughout Vietnam. Similarly, different agroecological factors were associated with each strain. Sample collection in the months of January and February and higher average maximum temperature were associated with higher likelihood of H5N1-positive market-day status. The likelihood of market days being positive for H5N6 increased with decreased river density, and with successive Rounds of data collection. This study highlights marked differences in spatial patterns and risk factors for H5N1 and H5N6 in Vietnam, suggesting the need for tailored surveillance and control approaches.

Comparative Epidemiology of Highly Pathogenic Avian Influenza Virus H5N1 and H5N6 in Vietnamese Live Bird Markets: Spatiotemporal Patterns of Distribution and Risk Factors

PubMed Central

Mellor, Kate C.; Meyer, Anne; Elkholly, Doaa A.; Fournié, Guillaume; Long, Pham T.; Inui, Ken; Padungtod, Pawin; Gilbert, Marius; Newman, Scott H.; Vergne, Timothée; Pfeiffer, Dirk U.; Stevens, Kim B.

2018-01-01

Highly pathogenic avian influenza (HPAI) H5N1 virus has been circulating in Vietnam since 2003, whilst outbreaks of HPAI H5N6 virus are more recent, having only been reported since 2014. Although the spatial distribution of H5N1 outbreaks and risk factors for virus occurrence has been extensively studied, there have been no comparative studies for H5N6. Data collected through active surveillance of Vietnamese live bird markets (LBMs) between 2011 and 2015 were used to explore and compare the spatiotemporal distributions of H5N1- and H5N6-positive LBMs. Conditional autoregressive models were developed to quantify spatiotemporal associations between agroecological factors and the two HPAI strains using the same set of predictor variables. Unlike H5N1, which exhibited a strong north–south divide, with repeated occurrence in the extreme south of a cluster of high-risk provinces, H5N6 was homogeneously distributed throughout Vietnam. Similarly, different agroecological factors were associated with each strain. Sample collection in the months of January and February and higher average maximum temperature were associated with higher likelihood of H5N1-positive market-day status. The likelihood of market days being positive for H5N6 increased with decreased river density, and with successive Rounds of data collection. This study highlights marked differences in spatial patterns and risk factors for H5N1 and H5N6 in Vietnam, suggesting the need for tailored surveillance and control approaches. PMID:29675418

Intelligent judgements over health risks in a spatial agent-based model.

PubMed

Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

2018-03-20

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of several macro metrics of interest: an epidemic curve, a risk perception curve, and a distribution of different types of coping strategies over time. Our results emphasize the importance of integrating behavioral aspects of decision making under risk into spatial disease ABMs using machine learning algorithms. This is especially relevant when studying cumulative impacts of behavioral changes and possible intervention strategies.

Spatial environmental risk factors for pedestrian injury collisions in Ciudad Juárez, Mexico (2008-2009): implications for urban planning.

PubMed

Fuentes, Cesar Mario; Hernandez, Vladimir

2013-01-01

The aim of this study is to examine the spatial distribution of pedestrian injury collisions and analyse the environmental (social and physical) risk factors in Ciudad Juarez, Mexico. More specifically, this study investigates the influence of land use, density, traffic and socio-economic characteristics. This cross sectional study is based on pedestrian injury collision data that were collected by the Municipal Transit Police during 2008-2009. This research presents an analysis of vehicle-pedestrian collisions and their spatial risk determinants using mixed methods that included (1) spatial/geographical information systems (GIS) analysis of pedestrian collision data and (2) ordinary least squares (OLS) regression analysis to explain the density of pedestrian collisions data. In our model, we found a higher probability for pedestrian collisions in census tracts with population and employment density, large concentration of commercial/retail land uses and older people (65 and more). Interventions to alleviate this situation including transportation planning such as decentralisation of municipal transport system, investment in road infrastructure - density of traffic lights, pedestrian crossing, road design, improves lane demarcation. Besides, land use planning interventions should be implemented in commercial/retail areas, in particular separating pedestrian and vehicular spaces.

Trace metal contamination in surface sediments of intertidal zone from Qinhuangdao, China, revealed by geochemical and magnetic approaches: Distribution, sources, and health risk assessment.

PubMed

Zhu, Zongmin; Xue, Junhui; Deng, Yuzhen; Chen, Lin; Liu, Jiangfeng

2016-04-15

Based on geochemical and magnetic approaches, the distribution, sources, and health risk of trace metals in surface sediments from a seashore tourist city were investigated. A significant correlation was found between magnetic susceptibility (χ) and trace metals, which suggested that levels of trace metals in the sediments can be effectively depicted by the magnetic approach. The spatial distribution of χ and trace metals matched well with the city layout with relatively higher values being found in the port and busy tourist areas. This result, together with enrichment factors (EFs) and Tomlinson pollution load index (PLI) of metals, suggested that the influence of human activities on the coastal environment was noticeable. Principal component analysis (PCA) indicated that trace metals in the sediments were derived from both anthropogenic and natural sources. Noncarcinogenic risk assessment showed that there was no potential health risk of exposure to metals by means of ingestion or inhalation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Geographic analysis of shigellosis in Vietnam.

PubMed

Kim, Deok Ryun; Ali, Mohammad; Thiem, Vu Dinh; Park, Jin-Kyung; von Seidlein, Lorenz; Clemens, John

2008-12-01

Geographic and ecological analysis may provide investigators useful ecological information for the control of shigellosis. This paper provides distribution of individual Shigella species in space, and ecological covariates for shigellosis in Nha Trang, Vietnam. Data on shigellosis in neighborhoods were used to identify ecological covariates. A Bayesian hierarchical model was used to obtain joint posterior distribution of model parameters and to construct smoothed risk maps for shigellosis. Neighborhoods with a high proportion of worshippers of traditional religion, close proximity to hospital, or close proximity to the river had increased risk for shigellosis. The ecological covariates associated with Shigella flexneri differed from the covariates for Shigella sonnei. In contrast the spatial distribution of the two species was similar. The disease maps can help identify high-risk areas of shigellosis that can be targeted for interventions. This approach may be useful for the selection of populations and the analysis of vaccine trials.

Spatial analysis of the tuberculosis treatment dropout, Buenos Aires, Argentina

PubMed Central

Herrero, María Belén; Arrossi, Silvina; Ramos, Silvina; Braga, Jose Ueleres

2015-01-01

OBJECTIVE Identify spatial distribution patterns of the proportion of nonadherence to tuberculosis treatment and its associated factors. METHODS We conducted an ecological study based on secondary and primary data from municipalities of the metropolitan area of Buenos Aires, Argentina. An exploratory analysis of the characteristics of the area and the distributions of the cases included in the sample (proportion of nonadherence) was also carried out along with a multifactor analysis by linear regression. The variables related to the characteristics of the population, residences and families were analyzed. RESULTS Areas with higher proportion of the population without social security benefits (p = 0.007) and of households with unsatisfied basic needs had a higher risk of nonadherence (p = 0.032). In addition, the proportion of nonadherence was higher in areas with the highest proportion of households with no public transportation within 300 meters (p = 0.070). CONCLUSIONS We found a risk area for the nonadherence to treatment characterized by a population living in poverty, with precarious jobs and difficult access to public transportation. PMID:26270011

Spatial analysis of the tuberculosis treatment dropout, Buenos Aires, Argentina.

PubMed

Herrero, María Belén; Arrossi, Silvina; Ramos, Silvina; Braga, Jose Ueleres

2015-01-01

OBJECTIVE Identify spatial distribution patterns of the proportion of nonadherence to tuberculosis treatment and its associated factors. METHODS We conducted an ecological study based on secondary and primary data from municipalities of the metropolitan area of Buenos Aires, Argentina. An exploratory analysis of the characteristics of the area and the distributions of the cases included in the sample (proportion of nonadherence) was also carried out along with a multifactor analysis by linear regression. The variables related to the characteristics of the population, residences and families were analyzed. RESULTS Areas with higher proportion of the population without social security benefits (p = 0.007) and of households with unsatisfied basic needs had a higher risk of nonadherence (p = 0.032). In addition, the proportion of nonadherence was higher in areas with the highest proportion of households with no public transportation within 300 meters (p = 0.070). CONCLUSIONS We found a risk area for the nonadherence to treatment characterized by a population living in poverty, with precarious jobs and difficult access to public transportation.

Use of prospective hospital surveillance data to define spatiotemporal heterogeneity of malaria risk in coastal Kenya.

PubMed

Bisanzio, Donal; Mutuku, Francis; LaBeaud, Angelle D; Mungai, Peter L; Muinde, Jackson; Busaidy, Hajara; Mukoko, Dunstan; King, Charles H; Kitron, Uriel

2015-12-01

Malaria in coastal Kenya shows spatial heterogeneity and seasonality, which are important factors to account for when planning an effective control system. Routinely collected data at health facilities can be used as a cost-effective method to acquire information on malaria risk for large areas. Here, data collected at one specific hospital in coastal Kenya were used to assess the ability of such passive surveillance to capture spatiotemporal heterogeneity of malaria and effectiveness of an augmented control system. Fever cases were tested for malaria at Msambweni sub-County Referral Hospital, Kwale County, Kenya, from October 2012 to March 2015. Remote sensing data were used to classify the development level of each monitored community and to identify the presence of rice fields nearby. An entomological study was performed to acquire data on the seasonality of malaria vectors in the study area. Rainfall data were obtained from a weather station located in proximity of the study area. Spatial analysis was applied to investigate spatial patterns of malarial and non-malarial fever cases. A space-time Bayesian model was performed to evaluate risk factors and identify locations at high malaria risk. Vector seasonality was analysed using a generalized additive mixed model (GAMM). Among the 25,779 tested febrile cases, 28.7 % were positive for Plasmodium infection. Malarial and non-malarial fever cases showed a marked spatial heterogeneity. High risk of malaria was linked to patient age, community development level and presence of rice fields. The peak of malaria prevalence was recorded close to rainy seasons, which correspond to periods of high vector abundance. Results from the Bayesian model identified areas with significantly high malaria risk. The model also showed that the low prevalence of malaria recorded during late 2012 and early 2013 was associated with a large-scale bed net distribution initiative in the study area during mid-2012. The results indicate that the use of passive surveillance was an effective method to detect spatiotemporal patterns of malaria risk in coastal Kenya. Furthermore, it was possible to estimate the impact of extensive bed net distribution on malaria prevalence among local fever cases over time. Passive surveillance based on georeferenced malaria testing is an important tool that control agencies can use to improve the effectiveness of interventions targeting malaria (and other causes of fever) in such high-risk locations.

AIDS in adults 50 years of age and over: characteristics, trends and spatial distribution of the risk1

PubMed Central

Nogueira, Jordana de Almeida; Silva, Antônia Oliveira; de Sá, Laísa Ribeiro; de Almeida, Sandra Aparecida; Monroe, Aline Aparecida; Villa, Tereza Cristina Scatena

2014-01-01

Objective to analyze the sociodemographic characteristics, epidemic trend and spatial distribution of the risk of AIDS in adults 50 years of age and over. Method population-based, ecological study, that used secondary data from the Notifiable Disease Information System (Sinan/AIDS) of Paraíba state from the period January 2000 to December 2010. Results during the study period, 307 cases of AIDS were reported among people 50 years of age or over. There was a predominance of males (205/66, 8%), mixed race, and low education levels. The municipalities with populations above 100 thousand inhabitants reported 58.5% of the cases. There was a progressive increase in cases among women; an increasing trend in the incidence (positive linear correlation); and an advance in the geographical spread of the disease, with expansion to the coastal region and to the interior of the state, reaching municipalities with populations below 30 thousand inhabitants. In some locations the risk of disease was 100 times greater than the relative risk for the state. Conclusion aging, with the feminization and interiorization of the epidemic in adults 50 years of age and over, confirms the need for the induction of affirmative policies targeted toward this age group. PMID:25029044

Integrating Entropy-Based Naïve Bayes and GIS for Spatial Evaluation of Flood Hazard.

PubMed

Liu, Rui; Chen, Yun; Wu, Jianping; Gao, Lei; Barrett, Damian; Xu, Tingbao; Li, Xiaojuan; Li, Linyi; Huang, Chang; Yu, Jia

2017-04-01

Regional flood risk caused by intensive rainfall under extreme climate conditions has increasingly attracted global attention. Mapping and evaluation of flood hazard are vital parts in flood risk assessment. This study develops an integrated framework for estimating spatial likelihood of flood hazard by coupling weighted naïve Bayes (WNB), geographic information system, and remote sensing. The north part of Fitzroy River Basin in Queensland, Australia, was selected as a case study site. The environmental indices, including extreme rainfall, evapotranspiration, net-water index, soil water retention, elevation, slope, drainage proximity, and density, were generated from spatial data representing climate, soil, vegetation, hydrology, and topography. These indices were weighted using the statistics-based entropy method. The weighted indices were input into the WNB-based model to delineate a regional flood risk map that indicates the likelihood of flood occurrence. The resultant map was validated by the maximum inundation extent extracted from moderate resolution imaging spectroradiometer (MODIS) imagery. The evaluation results, including mapping and evaluation of the distribution of flood hazard, are helpful in guiding flood inundation disaster responses for the region. The novel approach presented consists of weighted grid data, image-based sampling and validation, cell-by-cell probability inferring and spatial mapping. It is superior to an existing spatial naive Bayes (NB) method for regional flood hazard assessment. It can also be extended to other likelihood-related environmental hazard studies. © 2016 Society for Risk Analysis.

A framework for spatial risk assessments: Potential impacts of nonindigenous invasive species on native species

USGS Publications Warehouse

Allen, Craig R.; Johnson, A.R.; Parris, L.

2006-01-01

Many populations of wild animals and plants are declining and face increasing threats from habitat fragmentation and loss as well as exposure to stressors ranging from toxicants to diseases to invasive nonindigenous species. We describe and demonstrate a spatially explicit ecological risk assessment that allows for the incorporation of a broad array of information that may influence the distribution of an invasive species, toxicants, or other stressors, and the incorporation of landscape variables that may influence the spread of a species or substances. The first step in our analyses is to develop species models and quantify spatial overlap between stressor and target organisms. Risk is assessed as the product of spatial overlap and a hazard index based on target species vulnerabilities to the stressor of interest. We illustrate our methods with an example in which the stressor is the ecologically destructive nonindigenous ant, Solenopsis invicta, and the targets are two declining vertebrate species in the state of South Carolina, USA. A risk approach that focuses on landscapes and that is explicitly spatial is of particular relevance as remaining undeveloped lands become increasingly uncommon and isolated and more important in the management and recovery of species and ecological systems. Effective ecosystem management includes the control of multiple stressors, including invasive species with large impacts, understanding where those impacts may be the most severe, and implementing management strategies to reduce impacts. Copyright ?? 2006 by the author(s).

[Ecological risk assessment of rural-urban ecotone based on landscape pattern: A case study in Daiyue District of Tai' an City, Shandong Province of East China].

PubMed

Shi, Hao-Peng; Yu, Kai-Qin; Feng, Yong-jun

2013-03-01

Based on the remote sensing data in 2000, 2005, and 2010, this paper analyzed the variation trends of the land use type and landscape pattern in Daiyue District of Tai' an City from 2000 to 2010. The ecological risk index was built, that of the District was re-sampled and spatially interpolated, and the spatiotemporal pattern of the ecological risk in the rural-urban ecotone of the District was analyzed. In 2000-2010, the main variation trend of the land use type in the District was the shift from natural landscape to artificial landscape. The intensity of human disturbance was larger in cultivated land, garden plot, and forestland than in other landscape types, while the human disturbance in water area was smaller. The ecological loss degree of cultivated land and water area decreased somewhat, while that of the other land use types presented an increasing trend. The ecological risk distribution in the District was discrete in 2000 and 2010, but most centralized in 2005. The ecological risk of each ecological risk sub-area had an increasing trend in 2000-2005, but was in adverse in 2005-2010. In 2000-2010, the ecological risk of the District was mainly at medium level. Spatially, the distribution of the ecological risk in the District had an obvious differentiation, with an overall diffusive increasing from forestland as the center to the surrounding areas. In the District, the ecological risk was mainly at medium and higher levels, the area with lower ecological risk had an obvious dynamic change, while that with the lowest and highest ecological risk had less change.

Mapping risk of plague in Qinghai-Tibetan Plateau, China.

PubMed

Qian, Quan; Zhao, Jian; Fang, Liqun; Zhou, Hang; Zhang, Wenyi; Wei, Lan; Yang, Hong; Yin, Wenwu; Cao, Wuchun; Li, Qun

2014-07-10

Qinghai-Tibetan Plateau of China is known to be the plague endemic region where marmot (Marmota himalayana) is the primary host. Human plague cases are relatively low incidence but high mortality, which presents unique surveillance and public health challenges, because early detection through surveillance may not always be feasible and infrequent clinical cases may be misdiagnosed. Based on plague surveillance data and environmental variables, Maxent was applied to model the presence probability of plague host. 75% occurrence points were randomly selected for training model, and the rest 25% points were used for model test and validation. Maxent model performance was measured as test gain and test AUC. The optimal probability cut-off value was chosen by maximizing training sensitivity and specificity simultaneously. We used field surveillance data in an ecological niche modeling (ENM) framework to depict spatial distribution of natural foci of plague in Qinghai-Tibetan Plateau. Most human-inhabited areas at risk of exposure to enzootic plague are distributed in the east and south of the Plateau. Elevation, temperature of land surface and normalized difference vegetation index play a large part in determining the distribution of the enzootic plague. This study provided a more detailed view of spatial pattern of enzootic plague and human-inhabited areas at risk of plague. The maps could help public health authorities decide where to perform plague surveillance and take preventive measures in Qinghai-Tibetan Plateau.

Spatial Dynamics of Bovine Tuberculosis in the Autonomous Community of Madrid, Spain (2010–2012)

PubMed Central

de la Cruz, Maria Luisa; Perez, Andres; Bezos, Javier; Pages, Enrique; Casal, Carmen; Carpintero, Jesus; Romero, Beatriz; Dominguez, Lucas; Barker, Christopher M.; Diaz, Rosa; Alvarez, Julio

2014-01-01

Progress in control of bovine tuberculosis (bTB) is often not uniform, usually due to the effect of one or more sometimes unknown epidemiological factors impairing the success of eradication programs. Use of spatial analysis can help to identify clusters of persistence of disease, leading to the identification of these factors thus allowing the implementation of targeted control measures, and may provide some insights of disease transmission, particularly when combined with molecular typing techniques. Here, the spatial dynamics of bTB in a high prevalence region of Spain were assessed during a three year period (2010–2012) using data from the eradication campaigns to detect clusters of positive bTB herds and of those infected with certain Mycobacterium bovis strains (characterized using spoligotyping and VNTR typing). In addition, the within-herd transmission coefficient (β) was estimated in infected herds and its spatial distribution and association with other potential outbreak and herd variables was evaluated. Significant clustering of positive herds was identified in the three years of the study in the same location (“high risk area”). Three spoligotypes (SB0339, SB0121 and SB1142) accounted for >70% of the outbreaks detected in the three years. VNTR subtyping revealed the presence of few but highly prevalent strains within the high risk area, suggesting maintained transmission in the area. The spatial autocorrelation found in the distribution of the estimated within-herd transmission coefficients in herds located within distances <14 km and the results of the spatial regression analysis, support the hypothesis of shared local factors affecting disease transmission in farms located at a close proximity. PMID:25536514

Spatial demographic models to inform conservation planning of golden eagles in renewable energy landscapes

USGS Publications Warehouse

Wiens, J. David; Schumaker, Nathan H.; Inman, Richard D.; Esque, Todd C.; Longshore, Kathleen M.; Nussear, Kenneth E

2017-01-01

Spatial demographic models can help guide monitoring and management activities targeting at-risk species, even in cases where baseline data are lacking. Here, we provide an example of how site-specific changes in land use and anthropogenic stressors can be incorporated into a spatial demographic model to investigate effects on population dynamics of Golden Eagles (Aquila chrysaetos). Our study focused on a population of Golden Eagles exposed to risks associated with rapid increases in renewable energy development in southern California, U.S.A. We developed a spatially explicit, individual-based simulation model that integrated empirical data on demography of Golden Eagles with spatial data on the arrangement of nesting habitats, prey resources, and planned renewable energy development sites. Our model permitted simulated eagles of different stage-classes to disperse, establish home ranges, acquire prey resources, prospect for breeding sites, and reproduce. The distribution of nesting habitats, prey resources, and threats within each individual's home range influenced movement, reproduction, and survival. We used our model to explore potential effects of alternative disturbance scenarios, and proposed conservation strategies, on the future distribution and abundance of Golden Eagles in the study region. Results from our simulations suggest that probable increases in mortality associated with renewable energy infrastructure (e.g., collisions with wind turbines and vehicles, electrocution on power poles) could have negative consequences for population trajectories, but that site-specific conservation actions could reduce the magnitude of negative effects. Our study demonstrates the use of a flexible and expandable modeling framework to incorporate spatially dependent processes when determining relative effects of proposed management options to Golden Eagles and their habitats.

Spatial prediction and validation of zoonotic hazard through micro-habitat properties: where does Puumala hantavirus hole - up?

PubMed

Khalil, Hussein; Olsson, Gert; Magnusson, Magnus; Evander, Magnus; Hörnfeldt, Birger; Ecke, Frauke

2017-07-26

To predict the risk of infectious diseases originating in wildlife, it is important to identify habitats that allow the co-occurrence of pathogens and their hosts. Puumala hantavirus (PUUV) is a directly-transmitted RNA virus that causes hemorrhagic fever in humans, and is carried and transmitted by the bank vole (Myodes glareolus). In northern Sweden, bank voles undergo 3-4 year population cycles, during which their spatial distribution varies greatly. We used boosted regression trees; a technique inspired by machine learning, on a 10 - year time-series (fall 2003-2013) to develop a spatial predictive model assessing seasonal PUUV hazard using micro-habitat variables in a landscape heavily modified by forestry. We validated the models in an independent study area approx. 200 km away by predicting seasonal presence of infected bank voles in a five-year-period (2007-2010 and 2015). The distribution of PUUV-infected voles varied seasonally and inter-annually. In spring, micro-habitat variables related to cover and food availability in forests predicted both bank vole and infected bank vole presence. In fall, the presence of PUUV-infected voles was generally restricted to spruce forests where cover was abundant, despite the broad landscape distribution of bank voles in general. We hypothesize that the discrepancy in distribution between infected and uninfected hosts in fall, was related to higher survival of PUUV and/or PUUV-infected voles in the environment, especially where cover is plentiful. Moist and mesic old spruce forests, with abundant cover such as large holes and bilberry shrubs, also providing food, were most likely to harbor infected bank voles. The models developed using long-term and spatially extensive data can be extrapolated to other areas in northern Fennoscandia. To predict the hazard of directly transmitted zoonoses in areas with unknown risk status, models based on micro-habitat variables and developed through machine learning techniques in well-studied systems, could be used.

Spatial mapping and prediction of Plasmodium falciparum infection risk among school-aged children in Côte d'Ivoire.

PubMed

Houngbedji, Clarisse A; Chammartin, Frédérique; Yapi, Richard B; Hürlimann, Eveline; N'Dri, Prisca B; Silué, Kigbafori D; Soro, Gotianwa; Koudou, Benjamin G; Assi, Serge-Brice; N'Goran, Eliézer K; Fantodji, Agathe; Utzinger, Jürg; Vounatsou, Penelope; Raso, Giovanna

2016-09-07

In Côte d'Ivoire, malaria remains a major public health issue, and thus a priority to be tackled. The aim of this study was to identify spatially explicit indicators of Plasmodium falciparum infection among school-aged children and to undertake a model-based spatial prediction of P. falciparum infection risk using environmental predictors. A cross-sectional survey was conducted, including parasitological examinations and interviews with more than 5,000 children from 93 schools across Côte d'Ivoire. A finger-prick blood sample was obtained from each child to determine Plasmodium species-specific infection and parasitaemia using Giemsa-stained thick and thin blood films. Household socioeconomic status was assessed through asset ownership and household characteristics. Children were interviewed for preventive measures against malaria. Environmental data were gathered from satellite images and digitized maps. A Bayesian geostatistical stochastic search variable selection procedure was employed to identify factors related to P. falciparum infection risk. Bayesian geostatistical logistic regression models were used to map the spatial distribution of P. falciparum infection and to predict the infection prevalence at non-sampled locations via Bayesian kriging. Complete data sets were available from 5,322 children aged 5-16 years across Côte d'Ivoire. P. falciparum was the predominant species (94.5 %). The Bayesian geostatistical variable selection procedure identified land cover and socioeconomic status as important predictors for infection risk with P. falciparum. Model-based prediction identified high P. falciparum infection risk in the north, central-east, south-east, west and south-west of Côte d'Ivoire. Low-risk areas were found in the south-eastern area close to Abidjan and the south-central and west-central part of the country. The P. falciparum infection risk and related uncertainty estimates for school-aged children in Côte d'Ivoire represent the most up-to-date malaria risk maps. These tools can be used for spatial targeting of malaria control interventions.

Effects of large Saduria entomon (Isopoda) on spatial distribution of their small S. entomon and Monoporeia affinis (Amphipoda) prey.

PubMed

Sparrevik, Erik; Leonardsson, Kjell

1995-02-01

We performed laboratory experiments to investigate the effects of predator avoidance and numerical effects of predation on spatial distribution of small Saduria entomon (Isopoda) and Monoporeia affinis (Amphipoda), with large S. entomon as predators. The horizontal distribution and mortality of the prey species, separately and together, were studied in aquaria with a spatial horizontal refuge. We also estimated effects of refuge on mortality of small S. entomon and M. affinis by experiments without the refuge net. In addition, we investigated whether predation risk from large S. entomon influenced the swimming activity of M. affinis, to clarify the mechanisms behind the spatial distribution. Both small S. entomon and M. affinis avoided large S. entomon. The avoidance behaviour of M. fffinis contributed about 10 times more to the high proportion in the refuge than numerical effects of predation. Due to the low mortality of small S. entomon the avoidance behaviour of this species was even more important for the spatial distribution. The combined effect of avoidance behaviour and predation in both species was aggregation, producting a positive correlation between the species in density. M. affinis showed two types of avoidance behaviour. In the activity experiments they reduced activity by 36% and buried themselves in the sediment. In the refuge experiments we also observed avoidance behaviour with the emigration rate from the predator compartment being twice the immigration rate. The refuge did not lower predation mortality in M. affinis, probably due to the small scale of the experimental units in relation to the mobility of the species. Predation mortality in small S. entomon was higher in absence of a refuge and especially high in absence of M. affinis.

Accumulation risk assessment for the flooding hazard

NASA Astrophysics Data System (ADS)

Roth, Giorgio; Ghizzoni, Tatiana; Rudari, Roberto

2010-05-01

One of the main consequences of the demographic and economic development and of markets and trades globalization is represented by risks cumulus. In most cases, the cumulus of risks intuitively arises from the geographic concentration of a number of vulnerable elements in a single place. For natural events, risks cumulus can be associated, in addition to intensity, also to event's extension. In this case, the magnitude can be such that large areas, that may include many regions or even large portions of different countries, are stroked by single, catastrophic, events. Among natural risks, the impact of the flooding hazard cannot be understated. To cope with, a variety of mitigation actions can be put in place: from the improvement of monitoring and alert systems to the development of hydraulic structures, throughout land use restrictions, civil protection, financial and insurance plans. All of those viable options present social and economic impacts, either positive or negative, whose proper estimate should rely on the assumption of appropriate - present and future - flood risk scenarios. It is therefore necessary to identify proper statistical methodologies, able to describe the multivariate aspects of the involved physical processes and their spatial dependence. In hydrology and meteorology, but also in finance and insurance practice, it has early been recognized that classical statistical theory distributions (e.g., the normal and gamma families) are of restricted use for modeling multivariate spatial data. Recent research efforts have been therefore directed towards developing statistical models capable of describing the forms of asymmetry manifest in data sets. This, in particular, for the quite frequent case of phenomena whose empirical outcome behaves in a non-normal fashion, but still maintains some broad similarity with the multivariate normal distribution. Fruitful approaches were recognized in the use of flexible models, which include the normal distribution as a special or limiting case (e.g., the skew-normal or skew-t distributions). The present contribution constitutes an attempt to provide a better estimation of the joint probability distribution able to describe flood events in a multi-site multi-basin fashion. This goal will be pursued through the multivariate skew-t distribution, which allows to analytically define the joint probability distribution. Performances of the skew-t distribution will be discussed with reference to the Tanaro River in Northwestern Italy. To enhance the characteristics of the correlation structure, both nested and non-nested gauging stations will be selected, with significantly different contributing areas.

Application of receptor-specific risk distribution in the arsenic contaminated land management.

PubMed

Chen, I-chun; Ng, Shane; Wang, Gen-shuh; Ma, Hwong-wen

2013-11-15

Concerns over health risks and financial costs have caused difficulties in the management of arsenic contaminated land in Taiwan. Inflexible risk criteria and lack of economic support often result in failure of a brownfields regeneration project. To address the issue of flexible risk criteria, this study is aimed to develop maps with receptor-specific risk distribution to facilitate scenario analysis of contaminated land management. A contaminated site risk map model (ArcGIS for risk assessment and management, abbreviated as Arc-RAM) was constructed by combining the four major steps of risk assessment with Geographic Information Systems. Sampling of contaminated media, survey of exposure attributes, and modeling of multimedia transport were integrated to produce receptor group-specific maps that depicted the probabilistic spatial distribution of risks of various receptor groups. Flexible risk management schemes can then be developed and assessed. In this study, a risk management program that took into account the ratios of various land use types at specified risk levels was explored. A case study of arsenic contaminated land of 6.387 km(2) has found that for a risk value between 1.00E-05 and 1.00E-06, the proposed flexible risk management of agricultural land achieves improved utilization of land. Using this method, the investigated case can reduce costs related to compensation for farmland totaling approximately NTD 5.94 million annually. Copyright © 2012 Elsevier B.V. All rights reserved.

Identifying public water facilities with low spatial variability of disinfection by-products for epidemiological investigations

PubMed Central

Hinckley, A; Bachand, A; Nuckols, J; Reif, J

2005-01-01

Background and Aims: Epidemiological studies of disinfection by-products (DBPs) and reproductive outcomes have been hampered by misclassification of exposure. In most epidemiological studies conducted to date, all persons living within the boundaries of a water distribution system have been assigned a common exposure value based on facility-wide averages of trihalomethane (THM) concentrations. Since THMs do not develop uniformly throughout a distribution system, assignment of facility-wide averages may be inappropriate. One approach to mitigate this potential for misclassification is to select communities for epidemiological investigations that are served by distribution systems with consistently low spatial variability of THMs. Methods and Results: A feasibility study was conducted to develop methods for community selection using the Information Collection Rule (ICR) database, assembled by the US Environmental Protection Agency. The ICR database contains quarterly DBP concentrations collected between 1997 and 1998 from the distribution systems of 198 public water facilities with minimum service populations of 100 000 persons. Facilities with low spatial variation of THMs were identified using two methods; 33 facilities were found with low spatial variability based on one or both methods. Because brominated THMs may be important predictors of risk for adverse reproductive outcomes, sites were categorised into three exposure profiles according to proportion of brominated THM species and average TTHM concentration. The correlation between THMs and haloacetic acids (HAAs) in these facilities was evaluated to see whether selection by total trihalomethanes (TTHMs) corresponds to low spatial variability for HAAs. TTHMs were only moderately correlated with HAAs (r = 0.623). Conclusions: Results provide a simple method for a priori selection of sites with low spatial variability from state or national public water facility datasets as a means to reduce exposure misclassification in epidemiological studies of DBPs. PMID:15961627

Exploration of health risks related to air pollution and temperature in three Latin American cities

NASA Astrophysics Data System (ADS)

Romero-Lankao, P.; Borbor Cordova, M.; Qin, H.

2013-12-01

We explore whether the health risks related to air pollution and temperature extremes are spatially and socioeconomically differentiated within three Latin American cities: Bogota, Colombia, Mexico City, Mexico, and Santiago, Chile. Based on a theoretical review of three relevant approaches to risk analysis (risk society, environmental justice, and urban vulnerability as impact), we hypothesize that health risks from exposure to air pollution and temperature in these cities do not necessarily depend on socio-economic inequalities. To test this hypothesis, we gathered, validated, and analyzed temperature, air pollution, mortality and socioeconomic vulnerability data from the three study cities. Our results show the association between air pollution levels and socioeconomic vulnerabilities did not always correlate within the study cities. Furthermore, the spatial differences in socioeconomic vulnerabilities within cities do not necessarily correspond with the spatial distribution of health impacts. The present study improves our understanding of the multifaceted nature of health risks and vulnerabilities associated with global environmental change. The findings suggest that health risks from atmospheric conditions and pollutants exist without boundaries or social distinctions, even exhibiting characteristics of a boomerang effect (i.e., affecting rich and poor alike) on a smaller scale such as areas within urban regions. We used human mortality, a severe impact, to measure health risks from air pollution and extreme temperatures. Public health data of better quality (e.g., morbidity, hospital visits) are needed for future research to advance our understanding of the nature of health risks related to climate hazards.

Regional multi-compartment ecological risk assessment: Establishing cadmium pollution risk in the northern Bohai Rim, China.

PubMed

Shi, Yajuan; Wang, Ruoshi; Lu, Yonglong; Song, Shuai; Johnson, Andrew C; Sweetman, Andrew; Jones, Kevin

2016-09-01

Ecological risk assessment (ERA) has been widely applied in characterizing the risk of chemicals to organisms and ecosystems. The paucity of toxicity data on local biota living in the different compartments of an ecosystem and the absence of a suitable methodology for multi-compartment spatial risk assessment at the regional scale has held back this field. The major objective of this study was to develop a methodology to quantify and distinguish the spatial distribution of risk to ecosystems at a regional scale. A framework for regional multi-compartment probabilistic ecological risk assessment (RMPERA) was constructed and corroborated using a bioassay of a local species. The risks from cadmium (Cd) pollution in river water, river sediment, coastal water, coastal surface sediment and soil in northern Bohai Rim were examined. The results indicated that the local organisms in soil, river, coastal water, and coastal sediment were affected by Cd. The greatest impacts from Cd were identified in the Tianjin and Huludao areas. The overall multi-compartment risk was 31.4% in the region. The methodology provides a new approach for regional multi-compartment ecological risk assessment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Principles of landscape-geochemical studies in the zones contaminated by technogenical radionuclides for ecological and geochemical mapping

NASA Astrophysics Data System (ADS)

Korobova, Elena; Romanov, Sergey

2013-04-01

Efficiency of landscape-geochemical approach was proved to be helpful in spatial and temporal evaluation of the Chernobyl radionuclide distribution in the environment. The peculiarity of such approach is in hierarchical consideration of factors responsible for radionuclide redistribution and behavior in a system of inter-incorporated landscape-geochemical structures of the local and regional scales with due regard to the density of the initial fallout and patterns of radionuclide migration in soil-water-plant systems. The approach has been applied in the studies of distribution of Cs-137, Sr-90 and some other radionuclides in soils and vegetation cover and in evaluation of contribution of the stable iodine supply in soils to spatial variation of risk of thyroid cancer in areas subjected to radioiodine contamination after the Chernobyl accident. The main feature of the proposed approach is simultaneous consideration of two types of spatial heterogeneities: firstly, the inhomogeneity of external radiation exposure due to a complex structure of the contamination field, and, secondly, the landscape geochemical heterogeneity of the affected area, so that the resultant effect of radionuclide impact could significantly vary in space. The main idea of risk assessment in this respect was to reproduce as accurately as possible the result of interference of two surfaces in the form of risk map. The approach, although it demands to overcome a number of methodological difficulties, allows to solve the problems associated with spatially adequate protection of the affected population and optimization of the use of contaminated areas. In general it can serve the basis for development of the idea of the two-level structure of modern radiobiogeochemical provinces formed by superposition of the natural geochemical structures and the fields of technogenic contamination accompanied by the corresponding peculiar and integral biological reactions.

Spatiotemporal dynamics of the Southern California Asian citrus psyllid (Diaphorina citri) invasion.

PubMed

Bayles, Brett R; Thomas, Shyam M; Simmons, Gregory S; Grafton-Cardwell, Elizabeth E; Daugherty, Mathew P

2017-01-01

Biological invasions are governed by spatial processes that tend to be distributed in non-random ways across landscapes. Characterizing the spatial and temporal heterogeneities of the introduction, establishment, and spread of non-native insect species is a key aspect of effectively managing their geographic expansion. The Asian citrus psyllid (Diaphorina citri), a vector of the bacterium associated with huanglongbing (HLB), poses a serious threat to commercial and residential citrus trees. In 2008, D. citri first began expanding northward from Mexico into parts of Southern California. Using georeferenced D. citri occurrence data from 2008-2014, we sought to better understand the extent of the geographic expansion of this invasive vector species. Our objectives were to: 1) describe the spatial and temporal distribution of D. citri in Southern California, 2) identify the locations of statistically significant D. citri hotspots, and 3) quantify the dynamics of anisotropic spread. We found clear evidence that the spatial and temporal distribution of D. citri in Southern California is non-random. Further, we identified the existence of statistically significant hotspots of D. citri occurrence and described the anisotropic dispersion across the Southern California landscape. For example, the dominant hotspot surrounding Los Angeles showed rapid and strongly asymmetric spread to the south and east. Our study demonstrates the feasibility of quantitative invasive insect risk assessment with the application of a spatial epidemiology framework.

Spatiotemporal dynamics of the Southern California Asian citrus psyllid (Diaphorina citri) invasion

PubMed Central

Thomas, Shyam M.; Simmons, Gregory S.; Grafton-Cardwell, Elizabeth E.; Daugherty, Mathew P.

2017-01-01

Biological invasions are governed by spatial processes that tend to be distributed in non-random ways across landscapes. Characterizing the spatial and temporal heterogeneities of the introduction, establishment, and spread of non-native insect species is a key aspect of effectively managing their geographic expansion. The Asian citrus psyllid (Diaphorina citri), a vector of the bacterium associated with huanglongbing (HLB), poses a serious threat to commercial and residential citrus trees. In 2008, D. citri first began expanding northward from Mexico into parts of Southern California. Using georeferenced D. citri occurrence data from 2008–2014, we sought to better understand the extent of the geographic expansion of this invasive vector species. Our objectives were to: 1) describe the spatial and temporal distribution of D. citri in Southern California, 2) identify the locations of statistically significant D. citri hotspots, and 3) quantify the dynamics of anisotropic spread. We found clear evidence that the spatial and temporal distribution of D. citri in Southern California is non-random. Further, we identified the existence of statistically significant hotspots of D. citri occurrence and described the anisotropic dispersion across the Southern California landscape. For example, the dominant hotspot surrounding Los Angeles showed rapid and strongly asymmetric spread to the south and east. Our study demonstrates the feasibility of quantitative invasive insect risk assessment with the application of a spatial epidemiology framework. PMID:28278188

The applications of model-based geostatistics in helminth epidemiology and control.

PubMed

Magalhães, Ricardo J Soares; Clements, Archie C A; Patil, Anand P; Gething, Peter W; Brooker, Simon

2011-01-01

Funding agencies are dedicating substantial resources to tackle helminth infections. Reliable maps of the distribution of helminth infection can assist these efforts by targeting control resources to areas of greatest need. The ability to define the distribution of infection at regional, national and subnational levels has been enhanced greatly by the increased availability of good quality survey data and the use of model-based geostatistics (MBG), enabling spatial prediction in unsampled locations. A major advantage of MBG risk mapping approaches is that they provide a flexible statistical platform for handling and representing different sources of uncertainty, providing plausible and robust information on the spatial distribution of infections to inform the design and implementation of control programmes. Focussing on schistosomiasis and soil-transmitted helminthiasis, with additional examples for lymphatic filariasis and onchocerciasis, we review the progress made to date with the application of MBG tools in large-scale, real-world control programmes and propose a general framework for their application to inform integrative spatial planning of helminth disease control programmes. Copyright © 2011 Elsevier Ltd. All rights reserved.

Order-Constrained Reference Priors with Implications for Bayesian Isotonic Regression, Analysis of Covariance and Spatial Models

NASA Astrophysics Data System (ADS)

Gong, Maozhen

Selecting an appropriate prior distribution is a fundamental issue in Bayesian Statistics. In this dissertation, under the framework provided by Berger and Bernardo, I derive the reference priors for several models which include: Analysis of Variance (ANOVA)/Analysis of Covariance (ANCOVA) models with a categorical variable under common ordering constraints, the conditionally autoregressive (CAR) models and the simultaneous autoregressive (SAR) models with a spatial autoregression parameter rho considered. The performances of reference priors for ANOVA/ANCOVA models are evaluated by simulation studies with comparisons to Jeffreys' prior and Least Squares Estimation (LSE). The priors are then illustrated in a Bayesian model of the "Risk of Type 2 Diabetes in New Mexico" data, where the relationship between the type 2 diabetes risk (through Hemoglobin A1c) and different smoking levels is investigated. In both simulation studies and real data set modeling, the reference priors that incorporate internal order information show good performances and can be used as default priors. The reference priors for the CAR and SAR models are also illustrated in the "1999 SAT State Average Verbal Scores" data with a comparison to a Uniform prior distribution. Due to the complexity of the reference priors for both CAR and SAR models, only a portion (12 states in the Midwest) of the original data set is considered. The reference priors can give a different marginal posterior distribution compared to a Uniform prior, which provides an alternative for prior specifications for areal data in Spatial statistics.

Spatial distribution of a population at risk: an important factor for understanding the recent rise in tick-borne diseases (Lyme borreliosis and tick-borne encephalitis in the Czech Republic).

PubMed

Zeman, Petr; Benes, Cestmir

2013-12-01

Recent rise in tick-borne diseases in many parts of Europe is a phenomenon in need of an explanation. We analyzed temporal trends in spatial distribution of a population at risk of Lyme borreliosis, tick-borne encephalitis, and as a control, also of a 'non-tick-borne disease' in the Czech Republic in 1997-2010. Analysis revealed that the population's exposure had been increasingly confined to the nearest surroundings of residences or in totally residential locations and that the incidence of the diseases depended in some causal way on how close to residences people exposed themselves to the risk. The rise in Lyme borreliosis and tick-borne encephalitis was solely due to infections acquired at or near patients' homes (<5 km), while the number of cases acquired further away was decreasing. The detected patterns in the data question some of the hypotheses which may be applicable in explaining the rise in disease incidences in the Czech Republic including the effect of climate change. Potentially causal factors are discussed. Copyright © 2013 Elsevier GmbH. All rights reserved.

Contemporary Remotely Sensed Data Products Refine Invasive Plants Risk Mapping in Data Poor Regions.

PubMed

Truong, Tuyet T A; Hardy, Giles E St J; Andrew, Margaret E

2017-01-01

Invasive weeds are a serious problem worldwide, threatening biodiversity and damaging economies. Modeling potential distributions of invasive weeds can prioritize locations for monitoring and control efforts, increasing management efficiency. Forecasts of invasion risk at regional to continental scales are enabled by readily available downscaled climate surfaces together with an increasing number of digitized and georeferenced species occurrence records and species distribution modeling techniques. However, predictions at a finer scale and in landscapes with less topographic variation may require predictors that capture biotic processes and local abiotic conditions. Contemporary remote sensing (RS) data can enhance predictions by providing a range of spatial environmental data products at fine scale beyond climatic variables only. In this study, we used the Global Biodiversity Information Facility (GBIF) and empirical maximum entropy (MaxEnt) models to model the potential distributions of 14 invasive plant species across Southeast Asia (SEA), selected from regional and Vietnam's lists of priority weeds. Spatial environmental variables used to map invasion risk included bioclimatic layers and recent representations of global land cover, vegetation productivity (GPP), and soil properties developed from Earth observation data. Results showed that combining climate and RS data reduced predicted areas of suitable habitat compared with models using climate or RS data only, with no loss in model accuracy. However, contributions of RS variables were relatively limited, in part due to uncertainties in the land cover data. We strongly encourage greater adoption of quantitative remotely sensed estimates of ecosystem structure and function for habitat suitability modeling. Through comprehensive maps of overall predicted area and diversity of invasive species, we found that among lifeforms (herb, shrub, and vine), shrub species have higher potential invasion risk in SEA. Native invasive species, which are often overlooked in weed risk assessment, may be as serious a problem as non-native invasive species. Awareness of invasive weeds and their environmental impacts is still nascent in SEA and information is scarce. Freely available global spatial datasets, not least those provided by Earth observation programs, and the results of studies such as this one provide critical information that enables strategic management of environmental threats such as invasive species.

Contemporary Remotely Sensed Data Products Refine Invasive Plants Risk Mapping in Data Poor Regions

PubMed Central

Truong, Tuyet T. A.; Hardy, Giles E. St. J.; Andrew, Margaret E.

2017-01-01

Invasive weeds are a serious problem worldwide, threatening biodiversity and damaging economies. Modeling potential distributions of invasive weeds can prioritize locations for monitoring and control efforts, increasing management efficiency. Forecasts of invasion risk at regional to continental scales are enabled by readily available downscaled climate surfaces together with an increasing number of digitized and georeferenced species occurrence records and species distribution modeling techniques. However, predictions at a finer scale and in landscapes with less topographic variation may require predictors that capture biotic processes and local abiotic conditions. Contemporary remote sensing (RS) data can enhance predictions by providing a range of spatial environmental data products at fine scale beyond climatic variables only. In this study, we used the Global Biodiversity Information Facility (GBIF) and empirical maximum entropy (MaxEnt) models to model the potential distributions of 14 invasive plant species across Southeast Asia (SEA), selected from regional and Vietnam’s lists of priority weeds. Spatial environmental variables used to map invasion risk included bioclimatic layers and recent representations of global land cover, vegetation productivity (GPP), and soil properties developed from Earth observation data. Results showed that combining climate and RS data reduced predicted areas of suitable habitat compared with models using climate or RS data only, with no loss in model accuracy. However, contributions of RS variables were relatively limited, in part due to uncertainties in the land cover data. We strongly encourage greater adoption of quantitative remotely sensed estimates of ecosystem structure and function for habitat suitability modeling. Through comprehensive maps of overall predicted area and diversity of invasive species, we found that among lifeforms (herb, shrub, and vine), shrub species have higher potential invasion risk in SEA. Native invasive species, which are often overlooked in weed risk assessment, may be as serious a problem as non-native invasive species. Awareness of invasive weeds and their environmental impacts is still nascent in SEA and information is scarce. Freely available global spatial datasets, not least those provided by Earth observation programs, and the results of studies such as this one provide critical information that enables strategic management of environmental threats such as invasive species. PMID:28555147

Risk factors and prediction analysis of cutaneous leishmaniasis due to Leishmania tropica in Southwestern Morocco.

PubMed

El Alem, Mohamed Mahmoud Mohamed; Hakkour, Maryam; Hmamouch, Asmae; Halhali, Meryem; Delouane, Bouchra; Habbari, Khalid; Fellah, Hajiba; Sadak, Abderrahim; Sebti, Faiza

2018-07-01

Cutaneous leishmaniasis is currently a serious public health problem in northern Africa, especially in Morocco. The causative parasite is transmitted to a human host through the bite of infected female sandflies of the genus Phlebotomus. The objective of the present study is to characterize the causative organisms and to predict the risk of cutaneous leishmaniasis (CL) cases in six provinces in southwestern Morocco, based on the spatial distribution of cases in relation to environmental factors and other risk factors such as socio-economic status and demographics. A molecular study was carried out using ITS1 PCR-RFLP method of the ribosomal DNA of Leishmania. An epidemiological study on CL cases was reported between 2000 and 2016 in this current investigation in six provinces in southwestern Morocco. Statistical analysis was performed using a linear regression model to identify the impact as well as the interaction between all predictor variables on the distribution of CL in the studied provinces. The forecast Holt-Winters (HW) method was used to describe the trend and seasonality of CL cases. The ITS1-PCR- RFLP analysis revealed the presence of Leishmania tropica in all studied provinces. The spatial distribution of CL cases documented in all studied provinces during the sixteen years showed a heterogeneous pattern and fluctuation trend with an average prevalence of 9.92 per 100,000 inhabitants. In addition, the forecast HW model predicts continued variability of trend and seasonality of CL cases in the upcoming years. This study confirmed the importance of socioeconomic factors, in particular poverty and the vulnerability rate, on distribution and emergence of CL. This study revealed a relationship between increasing risk of CL occurrence due to Leishmania tropica, as well as the distribution and emergence thereof, and socioeconomic factors in the investigated area. Copyright © 2018 Elsevier B.V. All rights reserved.

Harnessing landscape heterogeneity for managing future disturbance risks in forest ecosystems.

PubMed

Seidl, Rupert; Albrich, Katharina; Thom, Dominik; Rammer, Werner

2018-03-01

In order to prevent irreversible impacts of climate change on the biosphere it is imperative to phase out the use of fossil fuels. Consequently, the provisioning of renewable resources such as timber and biomass from forests is an ecosystem service of increasing importance. However, risk factors such as changing disturbance regimes are challenging the continuous provisioning of ecosystem services, and are thus a key concern in forest management. We here used simulation modeling to study different risk management strategies in the context of timber production under changing climate and disturbance regimes, focusing on a 8127 ha forest landscape in the Northern Front Range of the Alps in Austria. We show that under a continuation of historical management, disturbances from wind and bark beetles increase by +39.5% on average over 200 years in response to future climate change. Promoting mixed forests and climate-adapted tree species as well as increasing management intensity effectively reduced future disturbance risk. Analyzing the spatial patterns of disturbance on the landscape, we found a highly uneven distribution of risk among stands (Gini coefficients up to 0.466), but also a spatially variable effectiveness of silvicultural risk reduction measures. This spatial variability in the contribution to and control of risk can be used to inform disturbance management: Stands which have a high leverage on overall risk and for which risks can effectively be reduced (24.4% of the stands in our simulations) should be a priority for risk mitigation measures. In contrast, management should embrace natural disturbances for their beneficial effects on biodiversity in areas which neither contribute strongly to landscape-scale risk nor respond positively to risk mitigation measures (16.9% of stands). We here illustrate how spatial heterogeneity in forest landscapes can be harnessed to address both positive and negative effects of changing natural disturbance regimes in ecosystem management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Harnessing landscape heterogeneity for managing future disturbance risks in forest ecosystems

PubMed Central

Seidl, Rupert; Albrich, Katharina; Thom, Dominik; Rammer, Werner

2018-01-01

In order to prevent irreversible impacts of climate change on the biosphere it is imperative to phase out the use of fossil fuels. Consequently, the provisioning of renewable resources such as timber and biomass from forests is an ecosystem service of increasing importance. However, risk factors such as changing disturbance regimes are challenging the continuous provisioning of ecosystem services, and are thus a key concern in forest management. We here used simulation modeling to study different risk management strategies in the context of timber production under changing climate and disturbance regimes, focusing on a 8127 ha forest landscape in the Northern Front Range of the Alps in Austria. We show that under a continuation of historical management, disturbances from wind and bark beetles increase by +39.5% on average over 200 years in response to future climate change. Promoting mixed forests and climate-adapted tree species as well as increasing management intensity effectively reduced future disturbance risk. Analyzing the spatial patterns of disturbance on the landscape, we found a highly uneven distribution of risk among stands (Gini coefficients up to 0.466), but also a spatially variable effectiveness of silvicultural risk reduction measures. This spatial variability in the contribution to and control of risk can be used to inform disturbance management: Stands which have a high leverage on overall risk and for which risks can effectively be reduced (24.4% of the stands in our simulations) should be a priority for risk mitigation measures. In contrast, management should embrace natural disturbances for their beneficial effects on biodiversity in areas which neither contribute strongly to landscape-scale risk nor respond positively to risk mitigation measures (16.9% of stands). We here illustrate how spatial heterogeneity in forest landscapes can be harnessed to address both positive and negative effects of changing natural disturbance regimes in ecosystem management. PMID:29275284

Inhalation of expiratory droplets in aircraft cabins.

PubMed

Gupta, J K; Lin, C-H; Chen, Q

2011-08-01

Airliner cabins have high occupant density and long exposure time, so the risk of airborne infection transmission could be high if one or more passengers are infected with an airborne infectious disease. The droplets exhaled by an infected passenger may contain infectious agents. This study developed a method to predict the amount of expiratory droplets inhaled by the passengers in an airliner cabin for any flight duration. The spatial and temporal distribution of expiratory droplets for the first 3 min after the exhalation from the index passenger was obtained using the computational fluid dynamics simulations. The perfectly mixed model was used for beyond 3 min after the exhalation. For multiple exhalations, the droplet concentration in a zone can be obtained by adding the droplet concentrations for all the exhalations until the current time with a time shift via the superposition method. These methods were used to determine the amount of droplets inhaled by the susceptible passengers over a 4-h flight under three common scenarios. The method, if coupled with information on the viability and the amount of infectious agent in the droplet, can aid in evaluating the infection risk. The distribution of the infectious agents contained in the expiratory droplets of an infected occupant in an indoor environment is transient and non-uniform. The risk of infection can thus vary with time and space. The investigations developed methods to predict the spatial and temporal distribution of expiratory droplets, and the inhalation of these droplets in an aircraft cabin. The methods can be used in other indoor environments to assess the relative risk of infection in different zones, and suitable measures to control the spread of infection can be adopted. Appropriate treatment can be implemented for the zone identified as high-risk zones. © 2011 John Wiley & Sons A/S.

Spatial Distribution of Phlebotomine Sand Fly Species (Diptera: Psychodidae) in Qom Province, Central Iran.

PubMed

Saghafipour, Abedin; Vatandoost, Hassan; Zahraei-Ramazani, Ali Reza; Yaghoobi-Ershadi, Mohammad Reza; Rassi, Yavar; Shirzadi, Mohammad Reza; Akhavan, Amir Ahmad

2017-01-01

Zoonotic cutaneous leishmaniasis (ZCL) is transmitted to humans by phlebotomine sand fly bites. ZCL is a major health problem in Iran, where basic knowledge gaps about sand fly species diversity persist in some ZCL-endemic areas. This paper describes the richness and spatial distribution of sand fly species, collected with sticky traps, in Qom province, a ZCL-endemic area in central Iran, where sand fly fauna has been poorly studied. Collected species were mapped on urban and rural digital maps based on a scale of 1/50,000. All analyses were undertaken with rural- and urban-level precision, i.e., rural and urban levels were our basic units of analysis. After identifying the sand flies, high-risk foci were determined. For spatial analysis of vector species population, the entomological sampling sites were geo-referenced using GPS. Arc GIS 9.3 software was used to determine the foci with leishmaniasis vector species. Following the analyses, two genera (Phlebotomus and Sergentomyia) and 14 species were identified. Based on the mapping and sand fly dispersion analysis, the rural districts were categorized into three groups-infection reported, without infection, and no report. Based on Geographical Information System analyses, Kahak and Markazi districts were identified as high-risk foci with leishmaniasis vector species. These findings can act as a help guide to direct active control measures to the identified high-risk foci and, eventually, lead to reduction in incidence of the disease. © Crown copyright 2016.

Spatial analysis of binary health indicators with local smoothing techniques The Viadana study.

PubMed

Girardi, Paolo; Marcon, Alessandro; Rava, Marta; Pironi, Vanda; Ricci, Paolo; de Marco, Roberto

2012-01-01

When pollution data from a monitoring network is not available, mapping the spatial distribution of disease can be useful to identify populations at risk and to suggest a potential role for suspected emission sources. We aimed at obtaining a continuous spatial representation of the prevalence of symptoms that are potentially associated with the exposure to the pollutants emitted from the wood factories in the children who live in the district of Viadana (Northern Italy). In 2006, all the parents of the children aged 3-14 years residing in the Viadana district (n = 3854), filled in a questionnaire on respiratory symptoms, irritation symptoms of the eyes and skin, use of health services. The children's residential addresses were also collected and geocoded. Generalized additive models and local weighted regression (LOWESS) were used to estimate the distribution of the symptoms, to test for spatial trends of the symptoms' prevalence and to control for potential confounders. Permutation tests were used to identify the areas of significantly increased risk ("hot spots"). The prevalence of respiratory symptoms, eye symptoms and the use of health services showed a statistically significant spatial variation (p < 0.05), but skin symptoms did not. Symptoms' prevalence was lower in the northern part of the district, where no wood factories were present, and it was higher in the southern part, where the two big chipboard industries were located. Hot spots were identified fairly near to one of the two chipboard industries in the district. The north-to-south trend in the prevalence of respiratory and eye symptoms, but not of skin symptoms, as well as the location of hot spots, are consistent with the potential exposure to air pollutants both emitted by the wood factories and related to traffic. In these "high risk areas" monitoring of pollution and preventive actions are clearly needed. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.

Targeting trachoma control through risk mapping: the example of Southern Sudan.

PubMed

Clements, Archie C A; Kur, Lucia W; Gatpan, Gideon; Ngondi, Jeremiah M; Emerson, Paul M; Lado, Mounir; Sabasio, Anthony; Kolaczinski, Jan H

2010-08-17

Trachoma is a major cause of blindness in Southern Sudan. Its distribution has only been partially established and many communities in need of intervention have therefore not been identified or targeted. The present study aimed to develop a tool to improve targeting of survey and control activities. A national trachoma risk map was developed using Bayesian geostatistics models, incorporating trachoma prevalence data from 112 geo-referenced communities surveyed between 2001 and 2009. Logistic regression models were developed using active trachoma (trachomatous inflammation follicular and/or trachomatous inflammation intense) in 6345 children aged 1-9 years as the outcome, and incorporating fixed effects for age, long-term average rainfall (interpolated from weather station data) and land cover (i.e. vegetation type, derived from satellite remote sensing), as well as geostatistical random effects describing spatial clustering of trachoma. The model predicted the west of the country to be at no or low trachoma risk. Trachoma clusters in the central, northern and eastern areas had a radius of 8 km after accounting for the fixed effects. In Southern Sudan, large-scale spatial variation in the risk of active trachoma infection is associated with aridity. Spatial prediction has identified likely high-risk areas to be prioritized for more data collection, potentially to be followed by intervention.

Integrating population dynamics into mapping human exposure to seismic hazard

NASA Astrophysics Data System (ADS)

Freire, S.; Aubrecht, C.

2012-11-01

Disaster risk is not fully characterized without taking into account vulnerability and population exposure. Assessment of earthquake risk in urban areas would benefit from considering the variation of population distribution at more detailed spatial and temporal scales, and from a more explicit integration of this improved demographic data with existing seismic hazard maps. In the present work, "intelligent" dasymetric mapping is used to model population dynamics at high spatial resolution in order to benefit the analysis of spatio-temporal exposure to earthquake hazard in a metropolitan area. These night- and daytime-specific population densities are then classified and combined with seismic intensity levels to derive new spatially-explicit four-class-composite maps of human exposure. The presented approach enables a more thorough assessment of population exposure to earthquake hazard. Results show that there are significantly more people potentially at risk in the daytime period, demonstrating the shifting nature of population exposure in the daily cycle and the need to move beyond conventional residence-based demographic data sources to improve risk analyses. The proposed fine-scale maps of human exposure to seismic intensity are mainly aimed at benefiting visualization and communication of earthquake risk, but can be valuable in all phases of the disaster management process where knowledge of population densities is relevant for decision-making.

Targeting Trachoma Control through Risk Mapping: The Example of Southern Sudan

PubMed Central

Clements, Archie C. A.; Kur, Lucia W.; Gatpan, Gideon; Ngondi, Jeremiah M.; Emerson, Paul M.; Lado, Mounir; Sabasio, Anthony; Kolaczinski, Jan H.

2010-01-01

Background Trachoma is a major cause of blindness in Southern Sudan. Its distribution has only been partially established and many communities in need of intervention have therefore not been identified or targeted. The present study aimed to develop a tool to improve targeting of survey and control activities. Methods/Principal Findings A national trachoma risk map was developed using Bayesian geostatistics models, incorporating trachoma prevalence data from 112 geo-referenced communities surveyed between 2001 and 2009. Logistic regression models were developed using active trachoma (trachomatous inflammation follicular and/or trachomatous inflammation intense) in 6345 children aged 1–9 years as the outcome, and incorporating fixed effects for age, long-term average rainfall (interpolated from weather station data) and land cover (i.e. vegetation type, derived from satellite remote sensing), as well as geostatistical random effects describing spatial clustering of trachoma. The model predicted the west of the country to be at no or low trachoma risk. Trachoma clusters in the central, northern and eastern areas had a radius of 8 km after accounting for the fixed effects. Conclusion In Southern Sudan, large-scale spatial variation in the risk of active trachoma infection is associated with aridity. Spatial prediction has identified likely high-risk areas to be prioritized for more data collection, potentially to be followed by intervention. PMID:20808910

Spatial distribution and sources of heavy metals in natural pasture soil around copper-molybdenum mine in Northeast China.

PubMed

Wang, Zhiqiang; Hong, Chen; Xing, Yi; Wang, Kang; Li, Yifei; Feng, Lihui; Ma, Silu

2018-06-15

The characterization of the content and source of heavy metals are essential to assess the potential threat of metals to human health. The present study collected 140 topsoil samples around a Cu-Mo mine (Wunugetushan, China) and investigated the concentrations and spatial distribution pattern of Cr, Ni, Zn, Cu, Mo and Cd in soil using multivariate and geostatistical analytical methods. Results indicated that the average concentrations of six heavy metals, especially Cu and Mo, were obviously higher than the local background values. Correlation analysis and principal component analysis divided these metals into three groups, including Cr and Ni, Cu and Mo, Zn and Cd. Meanwhile, the spatial distribution maps of heavy metals indicated that Cr and Ni in soil were no notable anthropogenic inputs and mainly controlled by natural factors because their spatial maps exhibited non-point source contamination. The concentrations of Cu and Mo gradually decreased with distance away from the mine area, suggesting that human mining activities may be crucial in the spreading of contaminants. Soil contamination of Zn were associated with livestock manure produced from grazing. In addition, the environmental risk of heavy metal pollution was assessed by geo-accumulation index. All the results revealed that the spatial distribution of heavy metals in soil were in agreement with the local human activities. Investigating and identifying the origin of heavy metals in pasture soil will lay the foundation for taking effective measures to preserve soil from the long-term accumulation of heavy metals. Copyright © 2018 Elsevier Inc. All rights reserved.

Health risk assessment of China's main air pollutants.

PubMed

Sun, Jian; Zhou, Tiancai

2017-02-20

With the rapid development of China's economy, air pollution has attracted public concern because of its harmful effects on health. The source apportioning of air pollution, the spatial distribution characteristics, and the relationship between atmospheric contamination, and the risk of exposure were explored. The in situ daily concentrations of the principal air pollutants (PM 2.5 , PM 10 , SO 2 , NO 2 , CO and O 3 ) were obtained from 188 main cities with many continuous air-monitoring stations across China (2014 and 2015). The results indicate positive correlations between PM 2.5 and SO 2 (R 2  = 0.395/0.404, P < 0.0001), CO (R 2  = 0.187/0.365, P < 0.0001), and NO 2 (R 2  = 0.447/0.533, P < 0.0001), but weak correlations with O 3 (P > 0.05) for both 2014 and 2015. Additionally, a significant relationship between SO 2 , NO 2, and CO was discovered using regression analysis (P < 0.0001), indicating that the origin of air pollutants is likely to be vehicle exhaust, coal consumption, and biomass open-burning. For the spatial pattern of air pollutants, we found that the highest concentration of SO 2 , NO 2, and CO were mainly distributed in north China (Beijing-Tianjin-Hebei regions), Shandong, Shanxi and Henan provinces, part of Xinjiang and central Inner Mongolia (2014 and 2015). The highest concentration and risk of PM 2.5 was observed in the Beijing-Tianjin-Hebei economic belts, and Shandong, Henan, Shanxi, Hubei and Anhui provinces. Nevertheless, the highest concentration of O 3 was irregularly distributed in most areas of China. A high-risk distribution of PM 10 , SO 2 and NO 2 was also observed in these regions, with the high risk of PM 10 and NO 2 observed in the Hebei and Shandong province, and high-risk of PM 10 in Urumchi. The high-risk of NO 2 distributed in Beijing-Yangtze River Delta region-Pearl River Delta region-central. Although atmospheric contamination slightly improved in 2015 compared to 2014, humanity faces the challenge of reducing the environmental and public health effects of air pollution by altering the present mode of growth to achieve sustainable social and economic development.

Species distribution models: A comparison of statistical approaches for livestock and disease epidemics.

PubMed

Hollings, Tracey; Robinson, Andrew; van Andel, Mary; Jewell, Chris; Burgman, Mark

2017-01-01

In livestock industries, reliable up-to-date spatial distribution and abundance records for animals and farms are critical for governments to manage and respond to risks. Yet few, if any, countries can afford to maintain comprehensive, up-to-date agricultural census data. Statistical modelling can be used as a proxy for such data but comparative modelling studies have rarely been undertaken for livestock populations. Widespread species, including livestock, can be difficult to model effectively due to complex spatial distributions that do not respond predictably to environmental gradients. We assessed three machine learning species distribution models (SDM) for their capacity to estimate national-level farm animal population numbers within property boundaries: boosted regression trees (BRT), random forests (RF) and K-nearest neighbour (K-NN). The models were built from a commercial livestock database and environmental and socio-economic predictor data for New Zealand. We used two spatial data stratifications to test (i) support for decision making in an emergency response situation, and (ii) the ability for the models to predict to new geographic regions. The performance of the three model types varied substantially, but the best performing models showed very high accuracy. BRTs had the best performance overall, but RF performed equally well or better in many simulations; RFs were superior at predicting livestock numbers for all but very large commercial farms. K-NN performed poorly relative to both RF and BRT in all simulations. The predictions of both multi species and single species models for farms and within hypothetical quarantine zones were very close to observed data. These models are generally applicable for livestock estimation with broad applications in disease risk modelling, biosecurity, policy and planning.

Species distribution models: A comparison of statistical approaches for livestock and disease epidemics

PubMed Central

Robinson, Andrew; van Andel, Mary; Jewell, Chris; Burgman, Mark

2017-01-01

In livestock industries, reliable up-to-date spatial distribution and abundance records for animals and farms are critical for governments to manage and respond to risks. Yet few, if any, countries can afford to maintain comprehensive, up-to-date agricultural census data. Statistical modelling can be used as a proxy for such data but comparative modelling studies have rarely been undertaken for livestock populations. Widespread species, including livestock, can be difficult to model effectively due to complex spatial distributions that do not respond predictably to environmental gradients. We assessed three machine learning species distribution models (SDM) for their capacity to estimate national-level farm animal population numbers within property boundaries: boosted regression trees (BRT), random forests (RF) and K-nearest neighbour (K-NN). The models were built from a commercial livestock database and environmental and socio-economic predictor data for New Zealand. We used two spatial data stratifications to test (i) support for decision making in an emergency response situation, and (ii) the ability for the models to predict to new geographic regions. The performance of the three model types varied substantially, but the best performing models showed very high accuracy. BRTs had the best performance overall, but RF performed equally well or better in many simulations; RFs were superior at predicting livestock numbers for all but very large commercial farms. K-NN performed poorly relative to both RF and BRT in all simulations. The predictions of both multi species and single species models for farms and within hypothetical quarantine zones were very close to observed data. These models are generally applicable for livestock estimation with broad applications in disease risk modelling, biosecurity, policy and planning. PMID:28837685

Spatial Prediction of Coxiella burnetii Outbreak Exposure via Notified Case Counts in a Dose-Response Model.

PubMed

Brooke, Russell J; Kretzschmar, Mirjam E E; Hackert, Volker; Hoebe, Christian J P A; Teunis, Peter F M; Waller, Lance A

2017-01-01

We develop a novel approach to study an outbreak of Q fever in 2009 in the Netherlands by combining a human dose-response model with geostatistics prediction to relate probability of infection and associated probability of illness to an effective dose of Coxiella burnetii. The spatial distribution of the 220 notified cases in the at-risk population are translated into a smooth spatial field of dose. Based on these symptomatic cases, the dose-response model predicts a median of 611 asymptomatic infections (95% range: 410, 1,084) for the 220 reported symptomatic cases in the at-risk population; 2.78 (95% range: 1.86, 4.93) asymptomatic infections for each reported case. The low attack rates observed during the outbreak range from (Equation is included in full-text article.)to (Equation is included in full-text article.). The estimated peak levels of exposure extend to the north-east from the point source with an increasing proportion of asymptomatic infections further from the source. Our work combines established methodology from model-based geostatistics and dose-response modeling allowing for a novel approach to study outbreaks. Unobserved infections and the spatially varying effective dose can be predicted using the flexible framework without assuming any underlying spatial structure of the outbreak process. Such predictions are important for targeting interventions during an outbreak, estimating future disease burden, and determining acceptable risk levels.

Spatial, seasonal and climatic predictive models of Rift Valley fever disease across Africa.

PubMed

Redding, David W; Tiedt, Sonia; Lo Iacono, Gianni; Bett, Bernard; Jones, Kate E

2017-07-19

Understanding the emergence and subsequent spread of human infectious diseases is a critical global challenge, especially for high-impact zoonotic and vector-borne diseases. Global climate and land-use change are likely to alter host and vector distributions, but understanding the impact of these changes on the burden of infectious diseases is difficult. Here, we use a Bayesian spatial model to investigate environmental drivers of one of the most important diseases in Africa, Rift Valley fever (RVF). The model uses a hierarchical approach to determine how environmental drivers vary both spatially and seasonally, and incorporates the effects of key climatic oscillations, to produce a continental risk map of RVF in livestock (as a proxy for human RVF risk). We find RVF risk has a distinct seasonal spatial pattern influenced by climatic variation, with the majority of cases occurring in South Africa and Kenya in the first half of an El Niño year. Irrigation, rainfall and human population density were the main drivers of RVF cases, independent of seasonal, climatic or spatial variation. By accounting more subtly for the patterns in RVF data, we better determine the importance of underlying environmental drivers, and also make space- and time-sensitive predictions to better direct future surveillance resources.This article is part of the themed issue 'One Health for a changing world: zoonoses, ecosystems and human well-being'. © 2017 The Authors.

Spatial, seasonal and climatic predictive models of Rift Valley fever disease across Africa

PubMed Central

2017-01-01

Understanding the emergence and subsequent spread of human infectious diseases is a critical global challenge, especially for high-impact zoonotic and vector-borne diseases. Global climate and land-use change are likely to alter host and vector distributions, but understanding the impact of these changes on the burden of infectious diseases is difficult. Here, we use a Bayesian spatial model to investigate environmental drivers of one of the most important diseases in Africa, Rift Valley fever (RVF). The model uses a hierarchical approach to determine how environmental drivers vary both spatially and seasonally, and incorporates the effects of key climatic oscillations, to produce a continental risk map of RVF in livestock (as a proxy for human RVF risk). We find RVF risk has a distinct seasonal spatial pattern influenced by climatic variation, with the majority of cases occurring in South Africa and Kenya in the first half of an El Niño year. Irrigation, rainfall and human population density were the main drivers of RVF cases, independent of seasonal, climatic or spatial variation. By accounting more subtly for the patterns in RVF data, we better determine the importance of underlying environmental drivers, and also make space- and time-sensitive predictions to better direct future surveillance resources. This article is part of the themed issue ‘One Health for a changing world: zoonoses, ecosystems and human well-being’. PMID:28584173

Spatial patterns of leprosy in an urban area of central Brazil.

PubMed

Martelli, C M; Moraes Neto, O L; Andrade, A L; Silva, S A; Silva, I M; Zicker, F

1995-01-01

Reported is the spatial variation of leprosy in an urban area of Brazil and its correlation with socioeconomic indicators. From November 1991 to October 1992 a total of 752 newly diagnosed leprosy patients who were attending all outpatient clinics in Goiânia city, central Brazil, were identified. A database o leprosy cases was set up linking patients' addresses to 64 urban districts. Leprosy cases were detected in 86% of the districts and three risk strata were identified. The highest-risk area for leprosy was in the outskirts of the city and detection rates increased on moving from more developed to poorer areas. The risk of detecting leprosy cases was 5.3-fold greater (95% CI: 3.8-7.4) in the outskirts of the town than in the central zone. Discussed are the methodological issues related to leprosy case ascertainment, completeness and reliability of information, and the interpretation of the spatial distribution of leprosy per unit area. Highlighted also are the lack of leprosy control activities in primary health care units and the usefulness of geographical analysis in planning health services.

Spatial patterns of leprosy in an urban area of central Brazil.

PubMed Central

Martelli, C. M.; Moraes Neto, O. L.; Andrade, A. L.; Silva, S. A.; Silva, I. M.; Zicker, F.

1995-01-01

Reported is the spatial variation of leprosy in an urban area of Brazil and its correlation with socioeconomic indicators. From November 1991 to October 1992 a total of 752 newly diagnosed leprosy patients who were attending all outpatient clinics in Goiânia city, central Brazil, were identified. A database o leprosy cases was set up linking patients' addresses to 64 urban districts. Leprosy cases were detected in 86% of the districts and three risk strata were identified. The highest-risk area for leprosy was in the outskirts of the city and detection rates increased on moving from more developed to poorer areas. The risk of detecting leprosy cases was 5.3-fold greater (95% CI: 3.8-7.4) in the outskirts of the town than in the central zone. Discussed are the methodological issues related to leprosy case ascertainment, completeness and reliability of information, and the interpretation of the spatial distribution of leprosy per unit area. Highlighted also are the lack of leprosy control activities in primary health care units and the usefulness of geographical analysis in planning health services. PMID:7614663

Assessing the risk of ships striking large whales in marine spatial planning.

PubMed

Redfern, J V; McKenna, M F; Moore, T J; Calambokidis, J; Deangelis, M L; Becker, E A; Barlow, J; Forney, K A; Fiedler, P C; Chivers, S J

2013-04-01

Marine spatial planning provides a comprehensive framework for managing multiple uses of the marine environment and has the potential to minimize environmental impacts and reduce conflicts among users. Spatially explicit assessments of the risks to key marine species from human activities are a requirement of marine spatial planning. We assessed the risk of ships striking humpback (Megaptera novaeangliae), blue (Balaenoptera musculus), and fin (Balaenoptera physalus) whales in alternative shipping routes derived from patterns of shipping traffic off Southern California (U.S.A.). Specifically, we developed whale-habitat models and assumed ship-strike risk for the alternative shipping routes was proportional to the number of whales predicted by the models to occur within each route. This definition of risk assumes all ships travel within a single route. We also calculated risk assuming ships travel via multiple routes. We estimated the potential for conflict between shipping and other uses (military training and fishing) due to overlap with the routes. We also estimated the overlap between shipping routes and protected areas. The route with the lowest risk for humpback whales had the highest risk for fin whales and vice versa. Risk to both species may be ameliorated by creating a new route south of the northern Channel Islands and spreading traffic between this new route and the existing route in the Santa Barbara Channel. Creating a longer route may reduce the overlap between shipping and other uses by concentrating shipping traffic. Blue whales are distributed more evenly across our study area than humpback and fin whales; thus, risk could not be ameliorated by concentrating shipping traffic in any of the routes we considered. Reducing ship-strike risk for blue whales may be necessary because our estimate of the potential number of strikes suggests that they are likely to exceed allowable levels of anthropogenic impacts established under U.S. laws. Conservation Biology © 2013 Society for Conservation Biology No claim to original US government works.

The spatial and temporal `cost' of volcanic eruptions: assessing economic impact, business inoperability, and spatial distribution of risk in the Auckland region, New Zealand

NASA Astrophysics Data System (ADS)

McDonald, Garry W.; Smith, Nicola J.; Kim, Joon-hwan; Cronin, Shane J.; Proctor, Jon N.

2017-07-01

Volcanic risk assessment has historically concentrated on quantifying the frequency, magnitude, and potential diversity of physical processes of eruptions and their consequent impacts on life and property. A realistic socio-economic assessment of volcanic impact must however take into account dynamic properties of businesses and extend beyond only measuring direct infrastructure/property loss. The inoperability input-output model, heralded as one of the 10 most important accomplishments in risk analysis over the last 30 years (Kujawaski Syst Eng. 9:281-295, 2006), has become prominent over the last decade in the economic impact assessment of business disruptions. We develop a dynamic inoperability input-output model to assess the economic impacts of a hypothetical volcanic event occurring at each of 7270 unique spatial locations throughout the Auckland Volcanic Field, New Zealand. This field of at least 53 volcanoes underlies the country's largest urban area, the Auckland region, which is home to 1.4 million people and responsible for 35.3% (NZ201481.2 billion) of the nation's GDP (Statistics New Zealand 2015). We apply volcanic event characteristics for a small-medium-scale volcanic eruption scenario and assess the economic impacts of an `average' eruption in the Auckland region. Economic losses are quantified both with, and without, business mitigation and intervention responses in place. We combine this information with a recent spatial hazard probability map (Bebbington and Cronin Bull Volcanol. 73(1):55-72, 2011) to produce novel spatial economic activity `at risk' maps. Our approach demonstrates how business inoperability losses sit alongside potential life and property damage assessment in enhancing our understanding of volcanic risk mitigation.

Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

PubMed Central

2011-01-01

The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular. PMID:22206355

Evaluation of Green Infrastructure on Peak Flow Mitigation Focusing on the Connectivity of Impervious Areas

NASA Astrophysics Data System (ADS)

Seo, Y.; Hwang, J.; Kwon, Y.

2017-12-01

The existence of impervious areas is one of the most distinguishing characteristics of urban catchments. It decreases infiltration and increases direct runoff in urban catchments. The recent introduction of green infrastructure in urban catchments for the purpose of sustainable development contributes to the decrease of the directly connected impervious areas (DCIA) by isolating existing impervious areas and consequently, to the flood risk mitigation. This study coupled the width function-based instantaneous hydrograph (WFIUH), which is able to handle the spatial distribution of the impervious areas, with the concept of the DCIA to assess the impact of decreasing DCIA on the shape of direct runoff hydrographs. Using several scenarios for typical green infrastructure and corresponding changes of DCIA in a test catchment, this study evaluated the effect of green infrastructure on the shape of the resulting direct runoff hydrographs and peak flows. The results showed that the changes in the DCIA immediately affects the shape of the direct runoff hydrograph and decreases peak flows depending on spatial implementation scenarios. The quantitative assessment of the spatial distribution of impervious areas and also the changes to the DCIA suggests effective and well-planned green infrastructure can be introduced in urban environments for flood risk management.

Poultry, pig and the risk of BSE following the feed ban in France--a spatial analysis.

PubMed

Abrial, David; Calavas, Didier; Jarrige, Nathalie; Ducrot, Christian

2005-01-01

A spatial analysis was carried out in order to analyse the reason why the risk of Bovine Spongiform Encephalopathy (BSE) was spatially heterogeneous in France, during the period following the feed ban of Meat and Bone Meal to cattle. The hypothesis of cross-contamination between cattle feedstuff and monogastric feedstuff, which was strongly suggested from previous investigations, was assessed, with the assumption that the higher the pig or poultry density is in a given area, the higher the risk of cross-contamination and cattle infection might be. The data concerned the 467 BSE cases born in France after the ban of meat and bone meal (July 1990) and detected between July 1st, 2001 and December 31, 2003, when the surveillance system was optimal and not spatially biased. The disease mapping models were elaborated with the Bayesian graphical modelling methods and based on a Poisson distribution with spatial smoothing (hierarchical approach) and covariates. The parameters were estimated by a Markov Chain Monte Carlo simulation method. The main result was that the poultry density did not significantly influence the risk of BSE whereas the pig density was significantly associated with an increase in the risk of 2.4% per 10 000 pigs. The areas with a significant pig effect were located in regions with a high pig density as well as a high ratio of pigs to cattle. Despite the absence of a global effect of poultry density on the BSE risk, some areas had a significant poultry effect and the risk was better explained in some others when considering both pig and poultry densities. These findings were in agreement with the hypothesis of cross-contamination, which could take place at the feedstuff factory, during the shipment of food or on the farm. Further studies are needed to more precisely explore how the cross-contamination happened.

Carbon emissions risk map from deforestation in the tropical Amazon

NASA Astrophysics Data System (ADS)

Ometto, J.; Soler, L. S.; Assis, T. D.; Oliveira, P. V.; Aguiar, A. P.

2011-12-01

Assis, Pedro Valle This work aims to estimate the carbon emissions from tropical deforestation in the Brazilian Amazon associated to the risk assessment of future land use change. The emissions are estimated by incorporating temporal deforestation dynamics, accounting for the biophysical and socioeconomic heterogeneity in the region, as well secondary forest growth dynamic in abandoned areas. The land cover change model that supported the risk assessment of deforestation, was run based on linear regressions. This method takes into account spatial heterogeneity of deforestation as the spatial variables adopted to fit the final regression model comprise: environmental aspects, economic attractiveness, accessibility and land tenure structure. After fitting a suitable regression models for each land cover category, the potential of each cell to be deforested (25x25km and 5x5 km of resolution) in the near future was used to calculate the risk assessment of land cover change. The carbon emissions model combines high-resolution new forest clear-cut mapping and four alternative sources of spatial information on biomass distribution for different vegetation types. The risk assessment map of CO2 emissions, was obtained by crossing the simulation results of the historical land cover changes to a map of aboveground biomass contained in the remaining forest. This final map represents the risk of CO2 emissions at 25x25km and 5x5 km until 2020, under a scenario of carbon emission reduction target.

The application of seismic risk-benefit analysis to land use planning in Taipei City.

PubMed

Hung, Hung-Chih; Chen, Liang-Chun

2007-09-01

In the developing countries of Asia local authorities rarely use risk analysis instruments as a decision-making support mechanism during planning and development procedures. The main purpose of this paper is to provide a methodology to enable planners to undertake such analyses. We illustrate a case study of seismic risk-benefit analysis for the city of Taipei, Taiwan, using available land use maps and surveys as well as a new tool developed by the National Science Council in Taiwan--the HAZ-Taiwan earthquake loss estimation system. We use three hypothetical earthquakes to estimate casualties and total and annualised direct economic losses, and to show their spatial distribution. We also characterise the distribution of vulnerability over the study area using cluster analysis. A risk-benefit ratio is calculated to express the levels of seismic risk attached to alternative land use plans. This paper suggests ways to perform earthquake risk evaluations and the authors intend to assist city planners to evaluate the appropriateness of their planning decisions.

Spatiotemporal Dynamics of Bumblebees Foraging under Predation Risk

NASA Astrophysics Data System (ADS)

Lenz, Friedrich; Ings, Thomas C.; Chittka, Lars; Chechkin, Aleksei V.; Klages, Rainer

2012-03-01

We analyze 3D flight paths of bumblebees searching for nectar in a laboratory experiment with and without predation risk from artificial spiders. For the flight velocities we find mixed probability distributions reflecting the access to the food sources while the threat posed by the spiders shows up only in the velocity correlations. The bumblebees thus adjust their flight patterns spatially to the environment and temporally to predation risk. Key information on response to environmental changes is contained in temporal correlation functions, as we explain by a simple emergent model.

Local environmental and meteorological conditions influencing the invasive mosquito Ae. albopictus and arbovirus transmission risk in New York City.

PubMed

Little, Eliza; Bajwa, Waheed; Shaman, Jeffrey

2017-08-01

Ae. albopictus, an invasive mosquito vector now endemic to much of the northeastern US, is a significant public health threat both as a nuisance biter and vector of disease (e.g. chikungunya virus). Here, we aim to quantify the relationships between local environmental and meteorological conditions and the abundance of Ae. albopictus mosquitoes in New York City. Using statistical modeling, we create a fine-scale spatially explicit risk map of Ae. albopictus abundance and validate the accuracy of spatiotemporal model predictions using observational data from 2016. We find that the spatial variability of annual Ae. albopictus abundance is greater than its temporal variability in New York City but that both local environmental and meteorological conditions are associated with Ae. albopictus numbers. Specifically, key land use characteristics, including open spaces, residential areas, and vacant lots, and spring and early summer meteorological conditions are associated with annual Ae. albopictus abundance. In addition, we investigate the distribution of imported chikungunya cases during 2014 and use these data to delineate areas with the highest rates of arboviral importation. We show that the spatial distribution of imported arboviral cases has been mostly discordant with mosquito production and thus, to date, has provided a check on local arboviral transmission in New York City. We do, however, find concordant areas where high Ae. albopictus abundance and chikungunya importation co-occur. Public health and vector control officials should prioritize control efforts to these areas and thus more cost effectively reduce the risk of local arboviral transmission. The methods applied here can be used to monitor and identify areas of risk for other imported vector-borne diseases.

Local environmental and meteorological conditions influencing the invasive mosquito Ae. albopictus and arbovirus transmission risk in New York City

PubMed Central

Bajwa, Waheed; Shaman, Jeffrey

2017-01-01

Ae. albopictus, an invasive mosquito vector now endemic to much of the northeastern US, is a significant public health threat both as a nuisance biter and vector of disease (e.g. chikungunya virus). Here, we aim to quantify the relationships between local environmental and meteorological conditions and the abundance of Ae. albopictus mosquitoes in New York City. Using statistical modeling, we create a fine-scale spatially explicit risk map of Ae. albopictus abundance and validate the accuracy of spatiotemporal model predictions using observational data from 2016. We find that the spatial variability of annual Ae. albopictus abundance is greater than its temporal variability in New York City but that both local environmental and meteorological conditions are associated with Ae. albopictus numbers. Specifically, key land use characteristics, including open spaces, residential areas, and vacant lots, and spring and early summer meteorological conditions are associated with annual Ae. albopictus abundance. In addition, we investigate the distribution of imported chikungunya cases during 2014 and use these data to delineate areas with the highest rates of arboviral importation. We show that the spatial distribution of imported arboviral cases has been mostly discordant with mosquito production and thus, to date, has provided a check on local arboviral transmission in New York City. We do, however, find concordant areas where high Ae. albopictus abundance and chikungunya importation co-occur. Public health and vector control officials should prioritize control efforts to these areas and thus more cost effectively reduce the risk of local arboviral transmission. The methods applied here can be used to monitor and identify areas of risk for other imported vector-borne diseases. PMID:28832586

'Fracking', Induced Seismicity and the Critical Earth

NASA Astrophysics Data System (ADS)

Leary, P.; Malin, P. E.

2012-12-01

Issues of 'fracking' and induced seismicity are reverse-analogous to the equally complex issues of well productivity in hydrocarbon, geothermal and ore reservoirs. In low hazard reservoir economics, poorly producing wells and low grade ore bodies are many while highly producing wells and high grade ores are rare but high pay. With induced seismicity factored in, however, the same distribution physics reverses the high/low pay economics: large fracture-connectivity systems are hazardous hence low pay, while high probability small fracture-connectivity systems are non-hazardous hence high pay. Put differently, an economic risk abatement tactic for well productivity and ore body pay is to encounter large-scale fracture systems, while an economic risk abatement tactic for 'fracking'-induced seismicity is to avoid large-scale fracture systems. Well productivity and ore body grade distributions arise from three empirical rules for fluid flow in crustal rock: (i) power-law scaling of grain-scale fracture density fluctuations; (ii) spatial correlation between spatial fluctuations in well-core porosity and the logarithm of well-core permeability; (iii) frequency distributions of permeability governed by a lognormality skewness parameter. The physical origin of rules (i)-(iii) is the universal existence of a critical-state-percolation grain-scale fracture-density threshold for crustal rock. Crustal fractures are effectively long-range spatially-correlated distributions of grain-scale defects permitting fluid percolation on mm to km scales. The rule is, the larger the fracture system the more intense the percolation throughput. As percolation pathways are spatially erratic and unpredictable on all scales, they are difficult to model with sparsely sampled well data. Phenomena such as well productivity, induced seismicity, and ore body fossil fracture distributions are collectively extremely difficult to predict. Risk associated with unpredictable reservoir well productivity and ore body distributions can be managed by operating in a context which affords many small failures for a few large successes. In reverse view, 'fracking' and induced seismicity could be rationally managed in a context in which many small successes can afford a few large failures. However, just as there is every incentive to acquire information leading to higher rates of productive well drilling and ore body exploration, there are equal incentives for acquiring information leading to lower rates of 'fracking'-induced seismicity. Current industry practice of using an effective medium approach to reservoir rock creates an uncritical sense that property distributions in rock are essentially uniform. Well-log data show that the reverse is true: the larger the length scale the greater the deviation from uniformity. Applying the effective medium approach to large-scale rock formations thus appears to be unnecessarily hazardous. It promotes the notion that large scale fluid pressurization acts against weakly cohesive but essentially uniform rock to produce large-scale quasi-uniform tensile discontinuities. Indiscriminate hydrofacturing appears to be vastly more problematic in reality than as pictured by the effective medium hypothesis. The spatial complexity of rock, especially at large scales, provides ample reason to find more controlled pressurization strategies for enhancing in situ flow.

[Ecological risk assessment of Taihu Lake basin based on landscape pattern].

PubMed

Xie, Xiao Ping; Chen, Zhi Cong; Wang, Fang; Bai, Mao Wei; Xu, Wen Yang

2017-10-01

Taihu Lake basin was selected as the study site. Based on the landscape data of 2000, 2005, 2010 and 2015, the Markov and CLUE-S models were used to simulate the landscape types with different scenarios in 2030, and landscape ecological risk index was constructed. The shift of gravity center and spatial statistics were used to reveal landscape ecological risk of Taihu Lake basin with temporal and spatial characteristics. The results showed that the ecological risk mainly was at medium and low levels in Taihu Lake basin, and the higher ecological risk areas were mainly distributed at the Taihu Lake area during 2000 to 2015, and the low ecological risk was transferred from the southwest and south of Taihu Lake to the developed areas in the northern part of Taihu Lake area. Spatial analysis showed that landscape ecological risk had negative correlation with natural factors, which was weakened gradually, while the correlation with socioeconomic factors trended to become stronger, with human disturbance affecting the landscape ecological risk significantly. The impact of socioeconomic factors on landscape ecological risks differed in different urbanization stages. In the developing area, with the economic development, the landscape was increasingly fragmented and the ecological risk was correspondingly increased. While in the developed area, with the further development of the economy, the aggregation index was increased, and fragmentation and separation indexes were decreased, ecological construction was restored, and the landscape ecological risk began to decline. CLUE-S model simulation showed that the ecological risk of Taihu Lake basin would be reduced in future, mainly on the low and relatively low levels. Taihu Lake area, both in history and the future, is a high ecological risk zone, and its management and protection should be strengthened.

Spatio-temporal distribution of dengue fever under scenarios of climate change in the southern Taiwan

NASA Astrophysics Data System (ADS)

Lee, Chieh-Han; Yu, Hwa-Lung

2014-05-01

Dengue fever has been recognized as the most important widespread vector-borne infectious disease in recent decades. Over 40% of the world's population is risk from dengue and about 50-100 million people are infected world wide annually. Previous studies have found that dengue fever is highly correlated with climate covariates. Thus, the potential effects of global climate change on dengue fever are crucial to epidemic concern, in particular, the transmission of the disease. This present study investigated the nonlinearity of time-delayed impact of climate on spatio-temporal variations of dengue fever in the southern Taiwan during 1998 to 2011. A distributed lag nonlinear model (DLNM) is used to assess the nonlinear lagged effects of meteorology. The statistically significant meteorological factors are considered, including weekly minimum temperature and maximum 24-hour rainfall. The relative risk and the distribution of dengue fever then predict under various climate change scenarios. The result shows that the relative risk is similar for different scenarios. In addition, the impact of rainfall on the incidence risk is higher than temperature. Moreover, the incidence risk is associated to spatially population distribution. The results can be served as practical reference for environmental regulators for the epidemic prevention under climate change scenarios.

Modeling the spatial distribution of African buffalo (Syncerus caffer) in the Kruger National Park, South Africa

PubMed Central

Hughes, Kristen; Budke, Christine M.; Ward, Michael P.; Kerry, Ruth; Ingram, Ben

2017-01-01

The population density of wildlife reservoirs contributes to disease transmission risk for domestic animals. The objective of this study was to model the African buffalo distribution of the Kruger National Park. A secondary objective was to collect field data to evaluate models and determine environmental predictors of buffalo detection. Spatial distribution models were created using buffalo census information and archived data from previous research. Field data were collected during the dry (August 2012) and wet (January 2013) seasons using a random walk design. The fit of the prediction models were assessed descriptively and formally by calculating the root mean square error (rMSE) of deviations from field observations. Logistic regression was used to estimate the effects of environmental variables on the detection of buffalo herds and linear regression was used to identify predictors of larger herd sizes. A zero-inflated Poisson model produced distributions that were most consistent with expected buffalo behavior. Field data confirmed that environmental factors including season (P = 0.008), vegetation type (P = 0.002), and vegetation density (P = 0.010) were significant predictors of buffalo detection. Bachelor herds were more likely to be detected in dense vegetation (P = 0.005) and during the wet season (P = 0.022) compared to the larger mixed-sex herds. Static distribution models for African buffalo can produce biologically reasonable results but environmental factors have significant effects and therefore could be used to improve model performance. Accurate distribution models are critical for the evaluation of disease risk and to model disease transmission. PMID:28902858

Longitudinal study on the temporal and micro-spatial distribution of Galba truncatula in four farms in Belgium as a base for small-scale risk mapping of Fasciola hepatica.

PubMed

Charlier, Johannes; Soenen, Karen; De Roeck, Els; Hantson, Wouter; Ducheyne, Els; Van Coillie, Frieke; De Wulf, Robert; Hendrickx, Guy; Vercruysse, Jozef

2014-11-26

The trematode parasite Fasciola hepatica causes important economic losses in ruminants worldwide. Current spatial distribution models do not provide sufficient detail to support farm-specific control strategies. A technology to reliably assess the spatial distribution of intermediate host snail habitats on farms would be a major step forward to this respect. The aim of this study was to conduct a longitudinal field survey in Flanders (Belgium) to (i) characterise suitable small water bodies (SWB) for Galba truncatula and (ii) describe the population dynamics of G. truncatula. Four F. hepatica-infected farms from two distinct agricultural regions were examined for the abundance of G. truncatula from the beginning (April 2012) until the end (November 2012) of the grazing season. Per farm, 12 to 18 SWB were selected for monthly examination, using a 10 m transect analysis. Observations on G. truncatula abundance were coupled with meteorological and (micro-)environmental factors and the within-herd prevalence of F. hepatica using simple comparison or negative binomial regression models. A total of 54 examined SWB were classified as a pond, ditch, trench, furrow or moist area. G. truncatula abundance was significantly associated with SWB-type, region and total monthly precipitation, but not with monthly temperature. The clear differences in G. truncatula abundance between the 2 studied regions did not result in comparable differences in F. hepatica prevalence in the cattle. Exploration of the relationship of G. truncatula abundance with (micro)-environmental variables revealed a positive association with soil and water pH and the occurrence of Ranunculus sp. and a negative association with mowed pastures, water temperature and presence of reed-like plant species. Farm-level predictions of G. truncatula risk and subsequent risk for F. hepatica occurrence would require a rainfall, soil type (representing the agricultural region) and SWB layer in a geographic information system. While rainfall and soil type information is easily accessible, the recent advances in very high spatial resolution cameras carried on board of satellites, planes or drones should allow the delineation of SWBs in the future.

Analysis of field-scale spatial correlations and variations of soil nutrients using geostatistics.

PubMed

Liu, Ruimin; Xu, Fei; Yu, Wenwen; Shi, Jianhan; Zhang, Peipei; Shen, Zhenyao

2016-02-01

Spatial correlations and soil nutrient variations are important for soil nutrient management. They help to reduce the negative impacts of agricultural nonpoint source pollution. Based on the sampled available nitrogen (AN), available phosphorus (AP), and available potassium (AK), soil nutrient data from 2010, the spatial correlation, was analyzed, and the probabilities of the nutrient's abundance or deficiency were discussed. This paper presents a statistical approach to spatial analysis, the spatial correlation analysis (SCA), which was originally developed for describing heterogeneity in the presence of correlated variation and based on ordinary kriging (OK) results. Indicator kriging (IK) was used to assess the susceptibility of excess of soil nutrients based on crop needs. The kriged results showed there was a distinct spatial variability in the concentration of all three soil nutrients. High concentrations of these three soil nutrients were found near Anzhou. As the distance from the center of town increased, the concentration of the soil nutrients gradually decreased. Spatially, the relationship between AN and AP was negative, and the relationship between AP and AK was not clear. The IK results showed that there were few areas with a risk of AN and AP overabundance. However, almost the entire study region was at risk of AK overabundance. Based on the soil nutrient distribution results, it is clear that the spatial variability of the soil nutrients differed throughout the study region. This spatial soil nutrient variability might be caused by different fertilizer types and different fertilizing practices.

Sustainable and Smart City Planning Using Spatial Data in Wallonia

NASA Astrophysics Data System (ADS)

Stephenne, N.; Beaumont, B.; Hallot, E.; Wolff, E.; Poelmans, L.; Baltus, C.

2016-09-01

Simulating population distribution and land use changes in space and time offer opportunities for smart city planning. It provides a holistic and dynamic vision of fast changing urban environment to policy makers. Impacts, such as environmental and health risks or mobility issues, of policies can be assessed and adapted consequently. In this paper, we suppose that "Smart" city developments should be sustainable, dynamic and participative. This paper addresses these three smart objectives in the context of urban risk assessment in Wallonia, Belgium. The sustainable, dynamic and participative solution includes (i) land cover and land use mapping using remote sensing and GIS, (ii) population density mapping using dasymetric mapping, (iii) predictive modelling of land use changes and population dynamics and (iv) risk assessment. The comprehensive and long-term vision of the territory should help to draw sustainable spatial planning policies, to adapt remote sensing acquisition, to update GIS data and to refine risk assessment from regional to city scale.

Malaria Disease Mapping in Malaysia based on Besag-York-Mollie (BYM) Model

NASA Astrophysics Data System (ADS)

Azah Samat, Nor; Mey, Liew Wan

2017-09-01

Disease mapping is the visual representation of the geographical distribution which give an overview info about the incidence of disease within a population through spatial epidemiology data. Based on the result of map, it helps in monitoring and planning resource needs at all levels of health care and designing appropriate interventions, tailored towards areas that deserve closer scrutiny or communities that lead to further investigations to identify important risk factors. Therefore, the choice of statistical model used for relative risk estimation is important because production of disease risk map relies on the model used. This paper proposes Besag-York-Mollie (BYM) model to estimate the relative risk for Malaria in Malaysia. The analysis involved using the number of Malaria cases that obtained from the Ministry of Health Malaysia. The outcomes of analysis are displayed through graph and map, including Malaria disease risk map that constructed according to the estimation of relative risk. The distribution of high and low risk areas of Malaria disease occurrences for all states in Malaysia can be identified in the risk map.

Characterizing the spatial distribution of multiple pollutants and populations at risk in Atlanta, Georgia.

PubMed

Pearce, John L; Waller, Lance A; Sarnat, Stefanie E; Chang, Howard H; Klein, Mitch; Mulholland, James A; Tolbert, Paige E

2016-08-01

Exposure metrics that identify spatial contrasts in multipollutant air quality are needed to better understand multipollutant geographies and health effects from air pollution. Our aim is to improve understanding of: (1) long-term spatial distributions of multiple pollutants; and (2) demographic characteristics of populations residing within areas of differing air quality. We obtained average concentrations for ten air pollutants (p=10) across a 12 km grid (n=253) covering Atlanta, Georgia for 2002-2008. We apply a self-organizing map (SOM) to our data to derive multipollutant patterns observed across our grid and classify locations under their most similar pattern (i.e, multipollutant spatial type (MST)). Finally, we geographically map classifications to delineate regions of similar multipollutant characteristics and characterize associated demographics. We found six MSTs well describe our data, with profiles highlighting a range of combinations, from locations experiencing generally clean air to locations experiencing conditions that were relatively dirty. Mapping MSTs highlighted that downtown areas were dominated by primary pollution and that suburban areas experienced relatively higher levels of secondary pollution. Demographics show the largest proportion of the overall population resided in downtown locations experiencing higher levels of primary pollution. Moreover, higher proportions of nonwhites and children in poverty reside in these areas when compared to suburban populations that resided in areas exhibiting relatively lower pollution. Our approach reveals the nature and spatial distribution of differential pollutant combinations across urban environments and provides helpful insights for identifying spatial exposure and demographic contrasts for future health studies. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Integrated flood hazard assessment based on spatial ordered weighted averaging method considering spatial heterogeneity of risk preference.

PubMed

Xiao, Yangfan; Yi, Shanzhen; Tang, Zhongqian

2017-12-01

Flood is the most common natural hazard in the world and has caused serious loss of life and property. Assessment of flood prone areas is of great importance for watershed management and reduction of potential loss of life and property. In this study, a framework of multi-criteria analysis (MCA) incorporating geographic information system (GIS), fuzzy analytic hierarchy process (AHP) and spatial ordered weighted averaging (OWA) method was developed for flood hazard assessment. The factors associated with geographical, hydrological and flood-resistant characteristics of the basin were selected as evaluation criteria. The relative importance of the criteria was estimated through fuzzy AHP method. The OWA method was utilized to analyze the effects of different risk attitudes of the decision maker on the assessment result. The spatial ordered weighted averaging method with spatially variable risk preference was implemented in the GIS environment to integrate the criteria. The advantage of the proposed method is that it has considered spatial heterogeneity in assigning risk preference in the decision-making process. The presented methodology has been applied to the area including Hanyang, Caidian and Hannan of Wuhan, China, where flood events occur frequently. The outcome of flood hazard distribution presents a tendency of high risk towards populated and developed areas, especially the northeast part of Hanyang city, which has suffered frequent floods in history. The result indicates where the enhancement projects should be carried out first under the condition of limited resources. Finally, sensitivity of the criteria weights was analyzed to measure the stability of results with respect to the variation of the criteria weights. The flood hazard assessment method presented in this paper is adaptable for hazard assessment of a similar basin, which is of great significance to establish counterplan to mitigate life and property losses. Copyright © 2017 Elsevier B.V. All rights reserved.

Epidemiological analysis, detection, and comparison of space-time patterns of Beijing hand-foot-mouth disease (2008-2012).

PubMed

Wang, Jiaojiao; Cao, Zhidong; Zeng, Daniel Dajun; Wang, Quanyi; Wang, Xiaoli; Qian, Haikun

2014-01-01

Hand, foot, and mouth disease (HFMD) mostly affects the health of infants and preschool children. Many studies of HFMD in different regions have been published. However, the epidemiological characteristics and space-time patterns of individual-level HFMD cases in a major city such as Beijing are unknown. The objective of this study was to investigate epidemiological features and identify high relative risk space-time HFMD clusters at a fine spatial scale. Detailed information on age, occupation, pathogen and gender was used to analyze the epidemiological features of HFMD epidemics. Data on individual-level HFMD cases were examined using Local Indicators of Spatial Association (LISA) analysis to identify the spatial autocorrelation of HFMD incidence. Spatial filtering combined with scan statistics methods were used to detect HFMD clusters. A total of 157,707 HFMD cases (60.25% were male, 39.75% were female) reported in Beijing from 2008 to 2012 included 1465 severe cases and 33 fatal cases. The annual average incidence rate was 164.3 per 100,000 (ranged from 104.2 in 2008 to 231.5 in 2010). Male incidence was higher than female incidence for the 0 to 14-year age group, and 93.88% were nursery children or lived at home. Areas at a higher relative risk were mainly located in the urban-rural transition zones (the percentage of the population at risk ranged from 33.89% in 2011 to 39.58% in 2012) showing High-High positive spatial association for HFMD incidence. The most likely space-time cluster was located in the mid-east part of the Fangshan district, southwest of Beijing. The spatial-time patterns of Beijing HFMD (2008-2012) showed relatively steady. The population at risk were mainly distributed in the urban-rural transition zones. Epidemiological features of Beijing HFMD were generally consistent with the previous research. The findings generated computational insights useful for disease surveillance, risk assessment and early warning.

Seasonal and Spatial Variations of Heavy Metals in Two Typical Chinese Rivers: Concentrations, Environmental Risks, and Possible Sources

PubMed Central

Yao, Hong; Qian, Xin; Gao, Hailong; Wang, Yulei; Xia, Bisheng

2014-01-01

Ten metals were analyzed in samples collected in three seasons (the dry season, the early rainy season, and the late rainy season) from two rivers in China. No observed toxic effect concentrations were used to estimate the risks. The possible sources of the metals in each season, and the dominant source(s) at each site, were assessed using principal components analysis. The metal concentrations in the area studied were found, using t-tests, to vary both seasonally and spatially (P = 0.05). The potential risks in different seasons decreased in the order: early rainy season > dry season > late rainy season, and Cd was the dominant contributor to the total risks associated with heavy metal pollution in the two rivers. The high population and industrial site densities in the Taihu basin have had negative influences on the two rivers. The river that is used as a source of drinking water (the Taipu River) had a low average level of risks caused by the metals. Metals accumulated in environmental media were the main possible sources in the dry season, and emissions from mechanical manufacturing enterprises were the main possible sources in the rainy season. The river in the industrial area (the Wusong River) had a moderate level of risk caused by the metals, and the main sources were industrial emissions. The seasonal and spatial distributions of the heavy metals mean that risk prevention and mitigation measures should be targeted taking these variations into account. PMID:25407421

Communicating Flood Risk with Street-Level Data

NASA Astrophysics Data System (ADS)

Sanders, B. F.; Matthew, R.; Houston, D.; Cheung, W. H.; Karlin, B.; Schubert, J.; Gallien, T.; Luke, A.; Contreras, S.; Goodrich, K.; Feldman, D.; Basolo, V.; Serrano, K.; Reyes, A.

2015-12-01

Coastal communities around the world face significant and growing flood risks that require an accelerating adaptation response, and fine-resolution urban flood models could serve a pivotal role in enabling communities to meet this need. Such models depict impacts at the level of individual buildings and land parcels or "street level" - the same spatial scale at which individuals are best able to process flood risk information - constituting a powerful tool to help communities build better understandings of flood vulnerabilities and identify cost-effective interventions. To measure understanding of flood risk within a community and the potential impact of street-level models, we carried out a household survey of flood risk awareness in Newport Beach, California, a highly urbanized coastal lowland that presently experiences nuisance flooding from high tides, waves and rainfall and is expected to experience a significant increase in flood frequency and intensity with climate change. Interviews were completed with the aid of a wireless-enabled tablet device that respondents could use to identify areas they understood to be at risk of flooding and to view either a Federal Emergency Management Agency (FEMA) flood map or a more detailed map prepared with a hydrodynamic urban coastal flood model (UCI map) built with grid cells as fine as 3 m resolution and validated with historical flood data. Results indicate differences in the effectiveness of the UCI and FEMA maps at communicating the spatial distribution of flood risk, gender differences in how the maps affect flood understanding, and spatial biases in the perception of flood vulnerabilities.

Spatial analysis and risk mapping of soil-transmitted helminth infections in Brazil, using Bayesian geostatistical models.

PubMed

Scholte, Ronaldo G C; Schur, Nadine; Bavia, Maria E; Carvalho, Edgar M; Chammartin, Frédérique; Utzinger, Jürg; Vounatsou, Penelope

2013-11-01

Soil-transmitted helminths (Ascaris lumbricoides, Trichuris trichiura and hookworm) negatively impact the health and wellbeing of hundreds of millions of people, particularly in tropical and subtropical countries, including Brazil. Reliable maps of the spatial distribution and estimates of the number of infected people are required for the control and eventual elimination of soil-transmitted helminthiasis. We used advanced Bayesian geostatistical modelling, coupled with geographical information systems and remote sensing to visualize the distribution of the three soil-transmitted helminth species in Brazil. Remotely sensed climatic and environmental data, along with socioeconomic variables from readily available databases were employed as predictors. Our models provided mean prevalence estimates for A. lumbricoides, T. trichiura and hookworm of 15.6%, 10.1% and 2.5%, respectively. By considering infection risk and population numbers at the unit of the municipality, we estimate that 29.7 million Brazilians are infected with A. lumbricoides, 19.2 million with T. trichiura and 4.7 million with hookworm. Our model-based maps identified important risk factors related to the transmission of soiltransmitted helminths and confirm that environmental variables are closely associated with indices of poverty. Our smoothed risk maps, including uncertainty, highlight areas where soil-transmitted helminthiasis control interventions are most urgently required, namely in the North and along most of the coastal areas of Brazil. We believe that our predictive risk maps are useful for disease control managers for prioritising control interventions and for providing a tool for more efficient surveillance-response mechanisms.

Exploration of health risks related to air pollution and temperature in three Latin American cities.

PubMed

Romero-Lankao, Patricia; Qin, Hua; Borbor-Cordova, Mercy

2013-04-01

This paper explores whether the health risks related to air pollution and temperature extremes are spatially and socioeconomically differentiated within three Latin American cities: Bogota, Colombia, Mexico City, Mexico, and Santiago, Chile. Based on a theoretical review of three relevant approaches to risk analysis (risk society, environmental justice, and urban vulnerability as impact), we hypothesize that health risks from exposure to air pollution and temperature in these cities do not necessarily depend on socio-economic inequalities. To test this hypothesis, we gathered, validated, and analyzed temperature, air pollution, mortality and socioeconomic vulnerability data from the three study cities. Our results show the association between air pollution levels and socioeconomic vulnerabilities did not always correlate within the study cities. Furthermore, the spatial differences in socioeconomic vulnerabilities within cities do not necessarily correspond with the spatial distribution of health impacts. The present study improves our understanding of the multifaceted nature of health risks and vulnerabilities associated with global environmental change. The findings suggest that health risks from atmospheric conditions and pollutants exist without boundaries or social distinctions, even exhibiting characteristics of a boomerang effect (i.e., affecting rich and poor alike) on a smaller scale such as areas within urban regions. We used human mortality, a severe impact, to measure health risks from air pollution and extreme temperatures. Public health data of better quality (e.g., morbidity, hospital visits) are needed for future research to advance our understanding of the nature of health risks related to climate hazards. Copyright © 2013 Elsevier Ltd. All rights reserved.

Geochemical baseline distribution of harmful elements in the surface soils of Campania region.

NASA Astrophysics Data System (ADS)

Albanese, Stefano; Lima, Annamaria; Qu, Chengkai; Cicchella, Domenico; Buccianti, Antonella; De Vivo, Benedetto

2015-04-01

Environmental geochemical mapping has assumed an increasing relevance and the separation of values to discriminate between anthropogenic pollution and natural (geogenic) sources has become crucial to address environmental problems affecting the quality of life of human beings. In the last decade, a number of geochemical prospecting projects, mostly focused on surface soils (topsoils), were carried out at different scales (from regional to local) across the whole Campania region (Italy) to characterize the distribution of both harmful elements and persistent organic pollutants (POP) in the environment and to generating a valuable database to serve as reference in developing geomedical studies. During the 2014, a database reporting the distribution of 53 chemical elements in 3536 topsoil samples, collected across the whole region, was completed. The geochemical data, after necessary quality controls, were georeferenced and processed in a geochemistry dedicated GIS software named GEODAS. For each considered element a complete set of maps was generated to depict both the discrete and the spatially continuous (interpolated) distribution of elemental concentrations across the region. The interpolated maps were generated using the Multifractal Inverse Distance eighted (MIDW) algorithm. Subsequently, the S-A method, also implemented in GEODAS, was applied to MIDW maps to eliminate spatially limited anomalies from the original grid and to generate the distribution patterns of geochemical baselines for each element. For a selected group of elements geochemical data were also treated by means of a Compositional Data Analysis (CoDA) aiming at investigating the regionalised structure of the data by considering the joint behaviour of several elements constituting for each sample its whole composition. A regional environmental risk assessment was run on the basis of the regional distribution of heavy metals in soil, land use types and population. The risk assessment produced a ranking of priorities and located areas of regional territory where human health risk is more relevant and follow-up activities are required.

The co-distribution of Plasmodium falciparum and hookworm among African schoolchildren

PubMed Central

Brooker, Simon; Clements, Archie CA; Hotez, Peter J; Hay, Simon I; Tatem, Andrew J; Bundy, Donald AP; Snow, Robert W

2006-01-01

Background Surprisingly little is known about the geographical overlap between malaria and other tropical diseases, including helminth infections. This is despite the potential public health importance of co-infection and synergistic opportunities for control. Methods Statistical models are presented that predict the large-scale distribution of hookworm in sub-Saharan Africa (SSA), based on the relationship between prevalence of infection among schoolchildren and remotely sensed environmental variables. Using a climate-based spatial model of the transmission potential for Plasmodium falciparum malaria, adjusted for urbanization, the spatial congruence of populations at coincident risk of infection is determined. Results The model of hookworm indicates that the infection is widespread throughout Africa and that, of the 179.3 million school-aged children who live on the continent, 50.0 (95% CI: 48.9–51.1) million (27.9% of total population) are infected with hookworm and 45.1 (95% CI: 43.9–46) million are estimated to be at risk of coincident infection. Conclusion Malaria and hookworm infection are widespread throughout SSA and over a quarter of school-aged children in sub-Saharan Africa appear to be at risk of coincident infection and thus at enhanced risk of clinical disease. The results suggest that the control of parasitic helminths and of malaria in school children could be viewed as essential co-contributors to promoting the health of schoolchildren. PMID:17083720

Distribution and risk assessment of 82 pesticides in Jiulong River and estuary in South China.

PubMed

Zheng, Senllin; Chen, Bin; Qiu, Xiaoyan; Chen, Meng; Ma, Zhiyuan; Yu, Xingguang

2016-02-01

To discover the distribution and risk of pesticides in Jiulong River and estuary, the residues of 102 pesticides were analyzed in water, sediment and clam samples collected from 35 sites in different seasons. A total number of 82 pesticides were detected and the occurrence and the risk to human and fish were assessed. Most of pesticides with high frequency were medium or low toxic except for DDTs. DDTs were the significant contaminant and the widely used dicofol was the new source of DDTs. The spatial and seasonal variation of pesticide distribution was linked with the distribution of orchards and farmlands. Health risk from river water consumption was low (RQ < 0.1) while that from clam consumption was medium (RQ = 0.84). Pesticides in water posed great risk to fish and among the 76 water samples analyzed, 65 of them showed high risk (RQ > 1) and 6 showed medium risk (0.1 ≤ QR < 1). The single chemical posed high risk to fish included DDTs, triazophos, fenvalerate, bifenthrin and cyfluthrin, and those showed medium risk included dicofol, butachlor, isocarbophos, terbufos and cyhalothrin. There were 14 single pesticides detected with concentration above 100 ng L(-1) in this study and the pesticide with the highest concentration was procymidone (3904 ng L(-1)). Further experiments illustrated that procymidone could disrupt the expression of vitellogenin in the estuarine fish even at environmental concentrations. DDTs, dicofol, triazophos, isocarbophos, terbufos, cyfluthrin, bifenthrin, fenvalerate, cyhalothrin, butachlor and procymidone have become the significant pesticides and should be considered in aquatic ecosystem risk management. Copyright © 2015 Elsevier Ltd. All rights reserved.

Development of the first georeferenced map of Rhipicephalus (Boophilus) spp. in Mexico from 1970 to date and prediction of its spatial distribution.

PubMed

Alcala-Canto, Yazmin; Figueroa-Castillo, Juan Antonio; Ibarra-Velarde, Froylán; Vera-Montenegro, Yolanda; Cervantes-Valencia, María Eugenia; Salem, Abdelfattah Z M; Cuéllar-Ordaz, Jorge Alfredo

2018-05-07

The tick genus Ripicephalus (Boophilus), particularly R. microplus, is one of the most important ectoparasites that affects livestock health and considered an epidemiological risk because it causes significant economic losses due, mainly, to restrictions in the export of infested animals to several countries. Its spatial distribution has been tied to environmental factors, mainly warm temperatures and high relative humidity. In this work, we integrated a dataset consisting of 5843 records of Rhipicephalus spp., in Mexico covering close to 50 years to know which environmental variables mostly influence this ticks' distribution. Occurrences were georeferenced using the software DIVA-GIS and the potential current distribution was modelled using the maximum entropy method (Maxent). The algorithm generated a map of high predictive capability (Area under the curve = 0.942), providing the various contribution and permutation importance of the tested variables. Precipitation seasonality, particularly in March, and isothermality were found to be the most significant climate variables in determining the probability of spatial distribution of Rhipicephalus spp. in Mexico (15.7%, 36.0% and 11.1%, respectively). Our findings demonstrate that Rhipicephalus has colonized Mexico widely, including areas characterized by different types of climate. We conclude that the Maxent distribution model using Rhipicephalus records and a set of environmental variables can predict the extent of the tick range in this country, information that should support the development of integrated control strategies.

Impacts of urbanization on the distribution of heavy metals in soils along the Huangpu River, the drinking water source for Shanghai.

PubMed

Bai, Yang; Wang, Min; Peng, Chi; Alatalo, Juha M

2016-03-01

We investigated the horizontal and vertical distribution of heavy metals (Hg, Pb, Zn, Cu, Cd, As, Ni, and Cr) in soils in the water source protection zone for Shanghai to study the origins of these metals, their connections with urbanization, and their potential risk posed on the ecosystem. Determination of metal concentrations in 50 topsoil samples and nine soil profiles indicated that Hg, Pb, Zn, and Cu were present in significantly higher concentrations in topsoil than in deep soil layers. The spatial distributions of Hg, Pb, Zn, and Cu and contamination hotspots for these metals in the study area were similar to those near heavy industries and urban built-up areas. Emissions from automobiles resulted in increased soil concentrations of Cu, Pb, and Zn along roadsides, while high concentrations of Hg in the soil resulted from recent atmospheric deposition. Calculation of the potential ecological risk indicated that the integrative risk of these heavy metals in most areas was low, but a few sites surrounding high density of factories showed moderate risks.

Confounding environmental colour and distribution shape leads to underestimation of population extinction risk.

PubMed

Fowler, Mike S; Ruokolainen, Lasse

2013-01-01

The colour of environmental variability influences the size of population fluctuations when filtered through density dependent dynamics, driving extinction risk through dynamical resonance. Slow fluctuations (low frequencies) dominate in red environments, rapid fluctuations (high frequencies) in blue environments and white environments are purely random (no frequencies dominate). Two methods are commonly employed to generate the coloured spatial and/or temporal stochastic (environmental) series used in combination with population (dynamical feedback) models: autoregressive [AR(1)] and sinusoidal (1/f) models. We show that changing environmental colour from white to red with 1/f models, and from white to red or blue with AR(1) models, generates coloured environmental series that are not normally distributed at finite time-scales, potentially confounding comparison with normally distributed white noise models. Increasing variability of sample Skewness and Kurtosis and decreasing mean Kurtosis of these series alter the frequency distribution shape of the realised values of the coloured stochastic processes. These changes in distribution shape alter patterns in the probability of single and series of extreme conditions. We show that the reduced extinction risk for undercompensating (slow growing) populations in red environments previously predicted with traditional 1/f methods is an artefact of changes in the distribution shapes of the environmental series. This is demonstrated by comparison with coloured series controlled to be normally distributed using spectral mimicry. Changes in the distribution shape that arise using traditional methods lead to underestimation of extinction risk in normally distributed, red 1/f environments. AR(1) methods also underestimate extinction risks in traditionally generated red environments. This work synthesises previous results and provides further insight into the processes driving extinction risk in model populations. We must let the characteristics of known natural environmental covariates (e.g., colour and distribution shape) guide us in our choice of how to best model the impact of coloured environmental variation on population dynamics.

Revisiting crash spatial heterogeneity: A Bayesian spatially varying coefficients approach.

PubMed

Xu, Pengpeng; Huang, Helai; Dong, Ni; Wong, S C

2017-01-01

This study was performed to investigate the spatially varying relationships between crash frequency and related risk factors. A Bayesian spatially varying coefficients model was elaborately introduced as a methodological alternative to simultaneously account for the unstructured and spatially structured heterogeneity of the regression coefficients in predicting crash frequencies. The proposed method was appealing in that the parameters were modeled via a conditional autoregressive prior distribution, which involved a single set of random effects and a spatial correlation parameter with extreme values corresponding to pure unstructured or pure spatially correlated random effects. A case study using a three-year crash dataset from the Hillsborough County, Florida, was conducted to illustrate the proposed model. Empirical analysis confirmed the presence of both unstructured and spatially correlated variations in the effects of contributory factors on severe crash occurrences. The findings also suggested that ignoring spatially structured heterogeneity may result in biased parameter estimates and incorrect inferences, while assuming the regression coefficients to be spatially clustered only is probably subject to the issue of over-smoothness. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatial Analysis of Hospital Incidence and in Hospital Mortality of Abdominal Aortic Aneurysms in Germany: Secondary Data Analysis of Nationwide Hospital Episode (DRG) Data.

PubMed

Kuehnl, Andreas; Salvermoser, Michael; Erk, Alexander; Trenner, Matthias; Schmid, Volker; Eckstein, Hans-Henning

2018-06-01

This study aimed to analyze the spatial distribution and regional variation of the hospital incidence and in hospital mortality of abdominal aortic aneurysms (AAA) in Germany. German DRG statistics (2011-2014) were analysed. Patients with ruptured AAA (rAAA, I71.3, treated or not) and patients with non-ruptured AAA (nrAAA, I71.4, treated by open or endovascular aneurysm repair) were included. Age, sex, and risk standardisation was done using standard statistical procedures. Regional variation was quantified using systematic component of variation. To analyse spatial auto-correlation and spatial pattern, global Moran's I and Getis-Ord Gi* were calculated. A total of 50,702 cases were included. Raw hospital incidence of AAA was 15.7 per 100,000 inhabitants (nrAAA 13.1; all rAAA 2.7; treated rAAA 1.6). The standardised hospital incidence of AAA ranged from 6.3 to 30.3 per 100,000. Systematic component of variation proportion was 96% in nrAAA and 55% in treated rAAA. Incidence rates of all AAA were significantly clustered with above average values in the northwestern parts of Germany and below average values in the south and eastern regions. Standardised mortality of nrAAA ranged from 1.7% to 4.3%, with that of treated rAAA ranging from 28% to 52%. Regional variation and spatial distribution of standardised mortality was not different from random. There was significant regional variation and clustering of the hospital incidence of AAA in Germany, with higher rates in the northwest and lower rates in the southeast. There was no significant variation in standardised (age/sex/risk) mortality between counties. Copyright © 2018. Published by Elsevier B.V.

[Ecological risk assessment of typical karst basin based on land use change: A case study of Lijiang River basin, Southern China].

PubMed

Hu, Jin Long; Zhou, Zhi Xiang; Teng, Ming Jun; Luo, Nan

2017-06-18

Taking Lijiang River basin as study area, and based on the remote sensing images of 1973, 1986, 2000 and 2013, the land-use data were extracted, the ecological risk index was constructed, and the characteristics of spatiotemporal variation of ecological risk were analyzed by "3S" technique. The results showed that land use structure of Lijiang River basin was under relatively reasonable state and it was constantly optimizing during 1973-2013. Overall, the ecological risk of Lijiang River basin was maintained at a low level. Lowest and lower ecological risk region was dominant in Lijiang River basin, but the area of highest ecological risk expanded quickly. The spatial distribution of ecological risk was basically stable and showed an obvious ring structure, which gra-dually decreased from the axis of Xingan County Town-Lingchuan County Town-Guilin City-Yangshuo County Town to other regions. Region with lowest ecological risk mainly distributed in natural mountain forest area of the north and mid-eastern parts of Lijiang River basin, and region with highe-st ecological risk concentrated in Guilin City. The ecological risk distribution of Lijiang River basin presented significant slope and altitude differences, and it decreased with increasing slope and altitude. During the study period, the area of low ecological risk converted to high ecological risk gra-dually decreased and vice versa. On the whole, the ecological risk tended to decline rapidly in the Lijiang River basin.

Assessing Risks from Cyclones for Human Lives and Livelihoods in the Coastal Region of Bangladesh

PubMed Central

Khan, Amanat Ullah; Kervyn, Matthieu

2017-01-01

As a disaster prone country, Bangladesh is regularly hit by natural hazards, including devastating cyclones, such as in 1970, 1991 and 2007. Although the number of cyclones’ fatalities reduced from 0.3 million in 1970 to a few thousand or fewer in recent events, loss of lives and impact on livelihoods remains a concern. It depends on the meteorological characteristics of cyclone and the general vulnerability and capacity of the exposed population. In that perspective, a spatially explicit risk assessment is an essential step towards targeted disaster risk reduction. This study aims at analyzing the spatial variation of the different factors contributing to the risk for coastal communities at regional scale, including the distribution of the hazards, exposure, vulnerability and capacity. An exploratory factor analysis method is used to map vulnerability contrasts between local administrative units. Indexing and ranking using geospatial techniques are used to produce maps of exposure, hazard, vulnerability, capacities and risk. Results show that vulnerable populations and exposed areas are distributed along the land sea boundary, islands and major inland rivers. The hazard, assessed from the density of historical cyclone paths, is highest in the southwestern part of the coast. Whereas cyclones shelters are shown to properly serve the most vulnerable populations as priority evacuation centers, the overall pattern of capacity accounting for building quality and road network shows a more complex pattern. Resultant risk maps also provide a reasonable basis from which to take further structural measures to minimize loss of lives in the upcoming cyclones. PMID:28757550

Comparative Spatial Dynamics of Japanese Encephalitis and Acute Encephalitis Syndrome in Nepal

PubMed Central

Robertson, Colin; Pant, Dhan Kumar; Joshi, Durga Datt; Sharma, Minu; Dahal, Meena; Stephen, Craig

2013-01-01

Japanese Encephalitis (JE) is a vector-borne disease of major importance in Asia. Recent increases in cases have spawned the development of more stringent JE surveillance. Due to the difficulty of making a clinical diagnosis, increased tracking of common symptoms associated with JE—generally classified as the umbrella term, acute encephalitis syndrome (AES) has been developed in many countries. In Nepal, there is some debate as to what AES cases are, and how JE risk factors relate to AES risk. Three parts of this analysis included investigating the temporal pattern of cases, examining the age and vaccination status patterns among AES surveillance data, and then focusing on spatial patterns of risk factors. AES and JE cases from 2007–2011 reported at a district level (n = 75) were examined in relation to landscape risk factors. Landscape pattern indices were used to quantify landscape patterns associated with JE risk. The relative spatial distribution of landscape risk factors were compared using geographically weighted regression. Pattern indices describing the amount of irrigated land edge density and the degree of landscape mixing for irrigated areas were positively associated with JE and AES, while fragmented forest measured by the number of forest patches were negatively associated with AES and JE. For both JE and AES, the local GWR models outperformed global models, indicating spatial heterogeneity in risks. Temporally, the patterns of JE and AES risk were almost identical; suggesting the relative higher caseload of AES compared to JE could provide a valuable early-warning signal for JE surveillance and reduce diagnostic testing costs. Overall, the landscape variables associated with a high degree of landscape mixing and small scale irrigated agriculture were positively linked to JE and AES risk, highlighting the importance of integrating land management policies, disease prevention strategies and promoting healthy sustainable livelihoods in both rural and urban-fringe developing areas. PMID:23894277

Spatially varying density dependence drives a shifting mosaic of survival in a recovering apex predator (Canis lupus).

PubMed

O'Neil, Shawn T; Bump, Joseph K; Beyer, Dean E

2017-11-01

Understanding landscape patterns in mortality risk is crucial for promoting recovery of threatened and endangered species. Humans affect mortality risk in large carnivores such as wolves ( Canis lupus ), but spatiotemporally varying density dependence can significantly influence the landscape of survival. This potentially occurs when density varies spatially and risk is unevenly distributed. We quantified spatiotemporal sources of variation in survival rates of gray wolves ( C. lupus ) during a 21-year period of population recovery in the Upper Peninsula of Michigan, USA. We focused on mapping risk across time using Cox Proportional Hazards (CPH) models with time-dependent covariates, thus exploring a shifting mosaic of survival. Extended CPH models and time-dependent covariates revealed influences of seasonality, density dependence and experience, as well as individual-level factors and landscape predictors of risk. We used results to predict the shifting landscape of risk at the beginning, middle, and end of the wolf recovery time series. Survival rates varied spatially and declined over time. Long-term change was density-dependent, with landscape predictors such as agricultural land cover and edge densities contributing negatively to survival. Survival also varied seasonally and depended on individual experience, sex, and resident versus transient status. The shifting landscape of survival suggested that increasing density contributed to greater potential for human conflict and wolf mortality risk. Long-term spatial variation in key population vital rates is largely unquantified in many threatened, endangered, and recovering species. Variation in risk may indicate potential for source-sink population dynamics, especially where individuals preemptively occupy suitable territories, which forces new individuals into riskier habitat types as density increases. We encourage managers to explore relationships between adult survival and localized changes in population density. Density-dependent risk maps can identify increasing conflict areas or potential habitat sinks which may persist due to high recruitment in adjacent habitats.

Despotism and risk of infanticide influence grizzly bear den-site selection.

PubMed

Libal, Nathan S; Belant, Jerrold L; Leopold, Bruce D; Wang, Guiming; Owen, Patricia A

2011-01-01

Given documented social dominance and intraspecific predation in bear populations, the ideal despotic distribution model and sex hypothesis of sexual segregation predict adult female grizzly bears (Ursus arctos) will avoid areas occupied by adult males to reduce risk of infanticide. Under ideal despotic distribution, juveniles should similarly avoid adult males to reduce predation risk. Den-site selection and use is an important component of grizzly bear ecology and may be influenced by multiple factors, including risk from conspecifics. To test the role of predation risk and the sex hypothesis of sexual segregation, we compared adult female (n = 142), adult male (n = 36), and juvenile (n = 35) den locations in Denali National Park and Preserve, Alaska, USA. We measured elevation, aspect, slope, and dominant land cover for each den site, and used maximum entropy modeling to determine which variables best predicted den sites. We identified the global model as the best-fitting model for adult female (area under curve (AUC) = 0.926) and elevation as the best predictive variable for adult male (AUC = 0.880) den sites. The model containing land cover and elevation best-predicted juvenile (AUC = 0.841) den sites. Adult females spatially segregated from adult males, with dens characterized by higher elevations (mean= 1,412 m, SE = 52) and steeper slopes (mean = 21.9°, SE = 1.1) than adult male (elevation: mean = 1,209 m, SE = 76; slope: mean = 15.6°, SE = 1.9) den sites. Juveniles used a broad range of landscape attributes but did not avoid adult male denning areas. Observed spatial segregation by adult females supports the sex hypothesis of sexual segregation and we suggest is a mechanism to reduce risk of infanticide. Den site selection of adult males is likely related to distribution of food resources during spring.

Efficient and Flexible Climate Analysis with Python in a Cloud-Based Distributed Computing Framework

NASA Astrophysics Data System (ADS)

Gannon, C.

2017-12-01

As climate models become progressively more advanced, and spatial resolution further improved through various downscaling projects, climate projections at a local level are increasingly insightful and valuable. However, the raw size of climate datasets presents numerous hurdles for analysts wishing to develop customized climate risk metrics or perform site-specific statistical analysis. Four Twenty Seven, a climate risk consultancy, has implemented a Python-based distributed framework to analyze large climate datasets in the cloud. With the freedom afforded by efficiently processing these datasets, we are able to customize and continually develop new climate risk metrics using the most up-to-date data. Here we outline our process for using Python packages such as XArray and Dask to evaluate netCDF files in a distributed framework, StarCluster to operate in a cluster-computing environment, cloud computing services to access publicly hosted datasets, and how this setup is particularly valuable for generating climate change indicators and performing localized statistical analysis.

Spatial distribution of soil cadmium and its influencing factors in peri-urban farmland: a case study in the Jingyang District, Sichuan, China.

PubMed

Li, Bing; Xiao, Rui; Wang, Changquan; Cao, Linhai; Zhang, Yi; Zheng, Shunqiang; Yang, Lan; Guo, Yong

2017-01-01

Semi-agricultural ecosystems in peri-urban areas are susceptible to contamination. The spatial distribution and influencing factors of such pollution are unclear and poorly constrained in many areas worldwide. Therefore, studying the problems of soil pollution in peri-urban areas is critical for environmental management and agricultural production. In this paper, with cadmium (Cd) as the target pollutant, the spatiotemporal variations of soil cadmium pollution and the relative importance of the affecting factors were analyzed at a peri-urban area from the Jingyang District, Sichuan, China. Statistical results showed that the farmland in the study area could be considered moderately soil Cd-polluted, under the dual influence of natural factors and human activity. In particular, the soil Cd concentration in Tianyuan and Bajiaojing exceeded 0.5 mg kg -1 , for intensive industrial enterprises are distributed in these areas. Correspondingly, the geoaccumulation index also showed that the contamination of Cd in this area was moderately polluted. Moreover, the ecological risk index was 80% in the study area, indicating that the soil Cd pollution potential risk was moderate to high. High geological background values (soil Cd = 0.29 mg kg -1 ), river migration, industrial enterprises, and traffic significantly influenced soil Cd pollution, with natural geological factors playing greater roles. The significant horizontal-spatial effective distances away from Shiting River, Deyang-Aba Highway, and chemical plants were 200, 400, and 100 m, respectively. These results will be useful in guiding farmland cultivation and pollution remediation effectively in the peri-urban areas.

Temporal evolution and spatial distribution of maternal death

PubMed Central

Carreno, Ioná; Bonilha, Ana Lúcia de Lourenzi; da Costa, Juvenal Soares Dias

2014-01-01

OBJECTIVE To analyze the temporal evolution of maternal mortality and its spatial distribution. METHODS Ecological study with a sample made up of 845 maternal deaths in women between 10 and 49 years, registered from 1999 to 2008 in the state of Rio Grande do Sul, Southern Brazil. Data were obtained from Information System on Mortality of Ministry of Health. The maternal mortality ratio and the specific maternal mortality ratio were calculated from records, and analyzed by the Poisson regression model. In the spatial distribution, three maps of the state were built with the rates in the geographical macro-regions, in 1999, 2003, and 2008. RESULTS There was an increase of 2.0% in the period of ten years (95%CI 1.00;1.04; p = 0.01), with no significant change in the magnitude of the maternal mortality ratio. The Serra macro-region presented the highest maternal mortality ratio (1.15, 95%CI 1.08;1.21; p < 0.001). Most deaths in Rio Grande do Sul were of white women over 40 years, with a lower level of education. The time of delivery/abortion and postpartum are times of increased maternal risk, with a greater negative impact of direct causes such as hypertension and bleeding. CONCLUSIONS The lack of improvement in maternal mortality ratio indicates that public policies had no impact on women’s reproductive and maternal health. It is needed to qualify the attention to women’s health, especially in the prenatal period, seeking to identify and prevent risk factors, as a strategy of reducing maternal death. PMID:25210825

Spatial distribution and health risk assessment for groundwater contamination from intensive pesticide use in arid areas.

PubMed

El Alfy, Mohamed; Faraj, Turki

2017-02-01

Arid and semiarid areas face major challenges in the management of scarce groundwater. This valuable resource is under pressures of population, economic expansion, contamination and over-exploitation. This research investigates groundwater vulnerability to pesticide contamination in the Al-Kharj area of Saudi Arabia. It explores the spatial distribution of pesticide concentrations in groundwater and other relevant factors. Thin permeable soils, permeable aquifers and shallow water tables, which are prevalent in the area, are especially vulnerable to pesticides. Analyses of 40 groundwater samples were performed using a gas chromatograph mass spectrometer coupled with a quadrupole mass spectrometer with a GC column. The analysis was conducted to detect 32 pesticides from different chemical families, and a total of 22 pesticides were detected. All 40 water samples were positive for at least one of the pesticides studied. In total, 21 compounds were above the quantification limit and 10 of them exceeded the legal limit. Total pesticide levels ranged from 0.18 to 2.21 μg/L, and 68 % of the analyzed samples exceeded the maximum allowable pesticide concentrations established by the European Community. Comparison of the daily intake peak (DIP) and daily intake mean (DIM) relative to the acceptable daily intake (ADI) shows that groundwater contamination with pesticides is a serious problem. Prolonged exposure to pesticides can cause adverse effects to human health and the ecosystem. Spatial distribution maps of groundwater contamination were developed using GIS. These maps will help risk managers identify vulnerable sources and provide a relative assessment of pesticide hazards to human health and the environment.

Spatial distribution of soil contamination by Toxoplasma gondii in relation to cat defecation behaviour in an urban area.

PubMed

Afonso, Eve; Lemoine, Mélissa; Poulle, Marie-Lazarine; Ravat, Marie-Caroline; Romand, Stéphane; Thulliez, Philippe; Villena, Isabelle; Aubert, Dominique; Rabilloud, Muriel; Riche, Benjamin; Gilot-Fromont, Emmanuelle

2008-07-01

In urban areas, there may be a high local risk of zoonosis due to high densities of stray cat populations. In this study, soil contamination by oocysts of Toxoplasma gondii was searched for, and its spatial distribution was analysed in relation to defecation behaviour of cats living in a high-density population present in one area of Lyon (France). Sixteen defecation sites were first identified. Cats were then repeatedly fed with marked food and the marked faeces were searched for in the defecation sites. Of 260 markers, 72 were recovered from 24 different cats. Defecation sites were frequented by up to 15 individuals. Soil samples were also examined in order to detect the presence of T. gondii using real-time PCR. The entire study area was then sampled according to cat density and vegetation cover type. Only three of 55 samples were positive and all came from defecation sites. In a second series of observations, 16 defecation sites were sampled. Eight of 62 samples tested positive, originating in five defecation sites. Laboratory experiments using experimental seeding of soil showed that the inoculated dose that can be detected in 50% of assays equals 100-1000oocysts/g, depending on the strain. This study shows that high concentrations of oocysts can be detected in soil samples using molecular methods and suggests that spatial distribution of contamination areas is highly heterogeneous. Positive samples were only found in some of the defecation sites, signifying that at-risk points for human and animal infection may be very localised.

Spatial quantification of the world population potentially exposed to Zika virus.

PubMed

Alaniz, Alberto J; Bacigalupo, Antonella; Cattan, Pedro E

2017-06-01

Zika virus is an emerging Flaviviridae virus, which has spread rapidly in the last few years. It has raised concern because it has been associated with fetus microcephaly when pregnant women are infected. The main vector is the mosquito Aedes aegypti , distributed in tropical areas. Niche modelling techniques were used to estimate the potential distribution area of A. aegypti. This was overlapped with human population density, determining areas of potential transmission risk worldwide. Afterwards, we quantified the population at risk according to risk level. The vector transmission risk is distributed mainly in Asia and Oceania on the shores of the Indian Ocean. In America, the risk concentrates in the Atlantic coast of South America and in the Caribbean Sea shores in Central and North America. In Africa, the major risk is concentrated in the Pacific and Atlantic coasts of Central and South Africa. The world population under high and very high risk levels includes 2.261 billion people. These results illustrate Zika virus risk at the global level and provide maps to target the prevention and control measures especially in areas with higher risk, in countries with less sanitation and poorer resources. Many countries without previous vector reports could become active transmission zones in the future, so vector surveillance should be implemented or reinforced in these areas. © The Author 2017; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association

Soil pH Errors Propagation from Measurements to Spatial Predictions - Cost Benefit Analysis and Risk Assessment Implications for Practitioners and Modelers

NASA Astrophysics Data System (ADS)

Owens, P. R.; Libohova, Z.; Seybold, C. A.; Wills, S. A.; Peaslee, S.; Beaudette, D.; Lindbo, D. L.

2017-12-01

The measurement errors and spatial prediction uncertainties of soil properties in the modeling community are usually assessed against measured values when available. However, of equal importance is the assessment of errors and uncertainty impacts on cost benefit analysis and risk assessments. Soil pH was selected as one of the most commonly measured soil properties used for liming recommendations. The objective of this study was to assess the error size from different sources and their implications with respect to management decisions. Error sources include measurement methods, laboratory sources, pedotransfer functions, database transections, spatial aggregations, etc. Several databases of measured and predicted soil pH were used for this study including the United States National Cooperative Soil Survey Characterization Database (NCSS-SCDB), the US Soil Survey Geographic (SSURGO) Database. The distribution of errors among different sources from measurement methods to spatial aggregation showed a wide range of values. The greatest RMSE of 0.79 pH units was from spatial aggregation (SSURGO vs Kriging), while the measurement methods had the lowest RMSE of 0.06 pH units. Assuming the order of data acquisition based on the transaction distance i.e. from measurement method to spatial aggregation the RMSE increased from 0.06 to 0.8 pH units suggesting an "error propagation". This has major implications for practitioners and modeling community. Most soil liming rate recommendations are based on 0.1 pH unit increments, while the desired soil pH level increments are based on 0.4 to 0.5 pH units. Thus, even when the measured and desired target soil pH are the same most guidelines recommend 1 ton ha-1 lime, which translates in 111 ha-1 that the farmer has to factor in the cost-benefit analysis. However, this analysis need to be based on uncertainty predictions (0.5-1.0 pH units) rather than measurement errors (0.1 pH units) which would translate in 555-1,111 investment that need to be assessed against the risk. The modeling community can benefit from such analysis, however, error size and spatial distribution for global and regional predictions need to be assessed against the variability of other drivers and impact on management decisions.

Oregon Cascades Play Fairway Analysis: Raster Datasets and Models

DOE Data Explorer

Adam Brandt

2015-11-15

This submission includes maps of the spatial distribution of basaltic, and felsic rocks in the Oregon Cascades. It also includes a final Play Fairway Analysis (PFA) model, with the heat and permeability composite risk segments (CRS) supplied separately. Metadata for each raster dataset can be found within the zip files, in the TIF images

Modeling current climate conditions for forest pest risk assessment

Treesearch

Frank H. Koch; John W. Coulston

2010-01-01

Current information on broad-scale climatic conditions is essential for assessing potential distribution of forest pests. At present, sophisticated spatial interpolation approaches such as the Parameter-elevation Regressions on Independent Slopes Model (PRISM) are used to create high-resolution climatic data sets. Unfortunately, these data sets are based on 30-year...

Identifying landscape features associated with Rift Valley fever virus transmission, Ferlo region, Senegal, using very high spatial resolution satellite imagery.

PubMed

Soti, Valérie; Chevalier, Véronique; Maura, Jonathan; Bégué, Agnès; Lelong, Camille; Lancelot, Renaud; Thiongane, Yaya; Tran, Annelise

2013-03-01

Dynamics of most of vector-borne diseases are strongly linked to global and local environmental changes. Landscape changes are indicators of human activities or natural processes that are likely to modify the ecology of the diseases. Here, a landscape approach developed at a local scale is proposed for extracting mosquito favourable biotopes, and for testing ecological parameters when identifying risk areas of Rift Valley fever (RVF) transmission. The study was carried out around Barkedji village, Ferlo region, Senegal. In order to test whether pond characteristics may influence the density and the dispersal behaviour of RVF vectors, and thus the spatial variation in RVFV transmission, we used a very high spatial resolution remote sensing image (2.4 m resolution) provided by the Quickbird sensor to produce a detailed land-cover map of the study area. Based on knowledge of vector and disease ecology, seven landscape attributes were defined at the pond level and computed from the land-cover map. Then, the relationships between landscape attributes and RVF serologic incidence rates in small ruminants were analyzed through a beta-binomial regression. Finally, the best statistical model according to the Akaike Information Criterion corrected for small samples (AICC), was used to map areas at risk for RVF. Among the derived landscape variables, the vegetation density index (VDI) computed within a 500 m buffer around ponds was positively correlated with serologic incidence (p<0.001), suggesting that the risk of RVF transmission was higher in the vicinity of ponds surrounded by a dense vegetation cover. The final risk map of RVF transmission displays a heterogeneous spatial distribution, corroborating previous findings from the same area. Our results highlight the potential of very high spatial resolution remote sensing data for identifying environmental risk factors and mapping RVF risk areas at a local scale.

Identifying landscape features associated with Rift Valley fever virus transmission, Ferlo region, Senegal, using very high spatial resolution satellite imagery

PubMed Central

2013-01-01

Introduction Dynamics of most of vector-borne diseases are strongly linked to global and local environmental changes. Landscape changes are indicators of human activities or natural processes that are likely to modify the ecology of the diseases. Here, a landscape approach developed at a local scale is proposed for extracting mosquito favourable biotopes, and for testing ecological parameters when identifying risk areas of Rift Valley fever (RVF) transmission. The study was carried out around Barkedji village, Ferlo region, Senegal. Methods In order to test whether pond characteristics may influence the density and the dispersal behaviour of RVF vectors, and thus the spatial variation in RVFV transmission, we used a very high spatial resolution remote sensing image (2.4 m resolution) provided by the Quickbird sensor to produce a detailed land-cover map of the study area. Based on knowledge of vector and disease ecology, seven landscape attributes were defined at the pond level and computed from the land-cover map. Then, the relationships between landscape attributes and RVF serologic incidence rates in small ruminants were analyzed through a beta-binomial regression. Finally, the best statistical model according to the Akaike Information Criterion corrected for small samples (AICC), was used to map areas at risk for RVF. Results Among the derived landscape variables, the vegetation density index (VDI) computed within a 500 m buffer around ponds was positively correlated with serologic incidence (p<0.001), suggesting that the risk of RVF transmission was higher in the vicinity of ponds surrounded by a dense vegetation cover. The final risk map of RVF transmission displays a heterogeneous spatial distribution, corroborating previous findings from the same area. Conclusions Our results highlight the potential of very high spatial resolution remote sensing data for identifying environmental risk factors and mapping RVF risk areas at a local scale. PMID:23452759

Distribution of RF energy emitted by mobile phones in anatomical structures of the brain.

PubMed

Cardis, E; Deltour, I; Mann, S; Moissonnier, M; Taki, M; Varsier, N; Wake, K; Wiart, J

2008-06-07

The rapid worldwide increase in mobile phone use in the last decade has generated considerable interest in possible carcinogenic effects of radio frequency (RF). Because exposure to RF from phones is localized, if a risk exists it is likely to be greatest for tumours in regions with greatest energy absorption. The objective of the current paper was to characterize the spatial distribution of RF energy in the brain, using results of measurements made in two laboratories on 110 phones used in Europe or Japan. Most (97-99% depending on frequency) appears to be absorbed in the brain hemisphere on the side where the phone is used, mainly (50-60%) in the temporal lobe. The average relative SAR is highest in the temporal lobe (6-15%, depending on frequency, of the spatial peak SAR in the most exposed region of the brain) and the cerebellum (2-10%) and decreases very rapidly with increasing depth, particularly at higher frequencies. The SAR distribution appears to be fairly similar across phone models, between older and newer phones and between phones with different antenna types and positions. Analyses of risk by location of tumour are therefore important for the interpretation of results of studies of brain tumours in relation to mobile phone use.

Spatial decision on allocating automated external defibrillators (AED) in communities by multi-criterion two-step floating catchment area (MC2SFCA).

PubMed

Lin, Bo-Cheng; Chen, Chao-Wen; Chen, Chien-Chou; Kuo, Chiao-Ling; Fan, I-Chun; Ho, Chi-Kung; Liu, I-Chuan; Chan, Ta-Chien

2016-05-25

The occurrence of out-of-hospital cardiac arrest (OHCA) is a critical life-threatening event which frequently warrants early defibrillation with an automated external defibrillator (AED). The optimization of allocating a limited number of AEDs in various types of communities is challenging. We aimed to propose a two-stage modeling framework including spatial accessibility evaluation and priority ranking to identify the highest gaps between demand and supply for allocating AEDs. In this study, a total of 6135 OHCA patients were defined as demand, and the existing 476 publicly available AEDs locations and 51 emergency medical service (EMS) stations were defined as supply. To identify the demand for AEDs, Bayesian spatial analysis with the integrated nested Laplace approximation (INLA) method is applied to estimate the composite spatial risks from multiple factors. The population density, proportion of elderly people, and land use classifications are identified as risk factors. Then, the multi-criterion two-step floating catchment area (MC2SFCA) method is used to measure spatial accessibility of AEDs between the spatial risks and the supply of AEDs. Priority ranking is utilized for prioritizing deployment of AEDs among communities because of limited resources. Among 6135 OHCA patients, 56.85 % were older than 65 years old, and 79.04 % were in a residential area. The spatial distribution of OHCA incidents was found to be concentrated in the metropolitan area of Kaohsiung City, Taiwan. According to the posterior mean estimated by INLA, the spatial effects including population density and proportion of elderly people, and land use classifications are positively associated with the OHCA incidence. Utilizing the MC2SFCA for spatial accessibility, we found that supply of AEDs is less than demand in most areas, especially in rural areas. Under limited resources, we identify priority places for deploying AEDs based on transportation time to the nearest hospital and population size of the communities. The proposed method will be beneficial for optimizing resource allocation while considering multiple local risks. The optimized deployment of AEDs can broaden EMS coverage and minimize the problems of the disparity in urban areas and the deficiency in rural areas.

Empirical evaluation of spatial and non-spatial European-scale multimedia fate models: results and implications for chemical risk assessment.

PubMed

Armitage, James M; Cousins, Ian T; Hauck, Mara; Harbers, Jasper V; Huijbregts, Mark A J

2007-06-01

Multimedia environmental fate models are commonly-applied tools for assessing the fate and distribution of contaminants in the environment. Owing to the large number of chemicals in use and the paucity of monitoring data, such models are often adopted as part of decision-support systems for chemical risk assessment. The purpose of this study was to evaluate the performance of three multimedia environmental fate models (spatially- and non-spatially-explicit) at a European scale. The assessment was conducted for four polycyclic aromatic hydrocarbons (PAHs) and hexachlorobenzene (HCB) and compared predicted and median observed concentrations using monitoring data collected for air, water, sediments and soils. Model performance in the air compartment was reasonable for all models included in the evaluation exercise as predicted concentrations were typically within a factor of 3 of the median observed concentrations. Furthermore, there was good correspondence between predictions and observations in regions that had elevated median observed concentrations for both spatially-explicit models. On the other hand, all three models consistently underestimated median observed concentrations in sediment and soil by 1-3 orders of magnitude. Although regions with elevated median observed concentrations in these environmental media were broadly identified by the spatially-explicit models, the magnitude of the discrepancy between predicted and median observed concentrations is of concern in the context of chemical risk assessment. These results were discussed in terms of factors influencing model performance such as the steady-state assumption, inaccuracies in emission estimates and the representativeness of monitoring data.

Patterning ecological risk of pesticide contamination at the river basin scale.

PubMed

Faggiano, Leslie; de Zwart, Dick; García-Berthou, Emili; Lek, Sovan; Gevrey, Muriel

2010-05-01

Ecological risk assessment was conducted to determine the risk posed by pesticide mixtures to the Adour-Garonne river basin (south-western France). The objectives of this study were to assess the general state of this basin with regard to pesticide contamination using a risk assessment procedure and to detect patterns in toxic mixture assemblages through a self-organizing map (SOM) methodology in order to identify the locations at risk. Exposure assessment, risk assessment with species sensitivity distribution, and mixture toxicity rules were used to compute six relative risk predictors for different toxic modes of action: the multi-substance potentially affected fraction of species depending on the toxic mode of action of compounds found in the mixture (msPAF CA(TMoA) values). Those predictors computed for the 131 sampling sites assessed in this study were then patterned through the SOM learning process. Four clusters of sampling sites exhibiting similar toxic assemblages were identified. In the first cluster, which comprised 83% of the sampling sites, the risk caused by pesticide mixture toward aquatic species was weak (mean msPAF value for those sites<0.0036%), while in another cluster the risk was significant (mean msPAF<1.09%). GIS mapping allowed an interesting spatial pattern of the distribution of sampling sites for each cluster to be highlighted with a significant and highly localized risk in the French department called "Lot et Garonne". The combined use of the SOM methodology, mixture toxicity modelling and a clear geo-referenced representation of results not only revealed the general state of the Adour-Garonne basin with regard to contamination by pesticides but also enabled to analyze the spatial pattern of toxic mixture assemblage in order to prioritize the locations at risk and to detect the group of compounds causing the greatest risk at the basin scale. Copyright 2010 Elsevier B.V. All rights reserved.

Spatial Distribution of the Risk of Dengue and the Entomological Indicators in Sumaré, State of São Paulo, Brazil

PubMed Central

Barbosa, Gerson Laurindo; Donalísio, Maria Rita; Stephan, Celso; Lourenço, Roberto Wagner; Andrade, Valmir Roberto; Arduino, Marylene de Brito; de Lima, Virgilia Luna Castor

2014-01-01

Dengue fever is a major public health problem worldwide, caused by any of four virus (DENV-1, DENV-2, DENV-3 and DENV-4; Flaviviridae: Flavivirus), transmitted by Aedes aegypti mosquito. Reducing the levels of infestation by A. aegypti is one of the few current strategies to control dengue fever. Entomological indicators are used by dengue national control program to measure the infestation of A. aegypti, but little is known about predictive power of these indicators to measure dengue risk. In this spatial case-control study, we analyzed the spatial distribution of the risk of dengue and the influence of entomological indicators of A. aegypti in its egg, larva-pupa and adult stages occurring in a mid-size city in the state of São Paulo. The dengue cases were those confirmed by the city's epidemiological surveillance system and the controls were obtained through random selection of points within the perimeter of the inhabited area. The values of the entomological indicators were extrapolated for the entire study area through the geostatistical ordinary kriging technique. For each case and control, the respective indicator values were obtained, according with its geographical coordinates and analyzed by using a generalized additive model. Dengue incidence demonstrated a seasonal behavior, as well as the entomological indicators of all mosquito's evolutionary stages. The infestation did not present a significant variation in intensity and was not a limiting or determining factor of the occurrence of cases in the municipality. The risk maps of the disease from crude and adjusted generalized additive models did not present differences, suggesting that areas with the highest values of entomological indicators were not associated with the incidence of dengue. The inclusion of other variables in the generalized additive models may reveal the modulatory effect for the risk of the disease, which is not found in this study. PMID:24831806

Spatial distribution of the risk of dengue and the entomological indicators in Sumaré, state of São Paulo, Brazil.

PubMed

Barbosa, Gerson Laurindo; Donalísio, Maria Rita; Stephan, Celso; Lourenço, Roberto Wagner; Andrade, Valmir Roberto; Arduino, Marylene de Brito; de Lima, Virgilia Luna Castor

2014-05-01

Dengue fever is a major public health problem worldwide, caused by any of four virus (DENV-1, DENV-2, DENV-3 and DENV-4; Flaviviridae: Flavivirus), transmitted by Aedes aegypti mosquito. Reducing the levels of infestation by A. aegypti is one of the few current strategies to control dengue fever. Entomological indicators are used by dengue national control program to measure the infestation of A. aegypti, but little is known about predictive power of these indicators to measure dengue risk. In this spatial case-control study, we analyzed the spatial distribution of the risk of dengue and the influence of entomological indicators of A. aegypti in its egg, larva-pupa and adult stages occurring in a mid-size city in the state of São Paulo. The dengue cases were those confirmed by the city's epidemiological surveillance system and the controls were obtained through random selection of points within the perimeter of the inhabited area. The values of the entomological indicators were extrapolated for the entire study area through the geostatistical ordinary kriging technique. For each case and control, the respective indicator values were obtained, according with its geographical coordinates and analyzed by using a generalized additive model. Dengue incidence demonstrated a seasonal behavior, as well as the entomological indicators of all mosquito's evolutionary stages. The infestation did not present a significant variation in intensity and was not a limiting or determining factor of the occurrence of cases in the municipality. The risk maps of the disease from crude and adjusted generalized additive models did not present differences, suggesting that areas with the highest values of entomological indicators were not associated with the incidence of dengue. The inclusion of other variables in the generalized additive models may reveal the modulatory effect for the risk of the disease, which is not found in this study.

A Probabilistic Analysis of Surface Water Flood Risk in London.

PubMed

Jenkins, Katie; Hall, Jim; Glenis, Vassilis; Kilsby, Chris

2018-06-01

Flooding in urban areas during heavy rainfall, often characterized by short duration and high-intensity events, is known as "surface water flooding." Analyzing surface water flood risk is complex as it requires understanding of biophysical and human factors, such as the localized scale and nature of heavy precipitation events, characteristics of the urban area affected (including detailed topography and drainage networks), and the spatial distribution of economic and social vulnerability. Climate change is recognized as having the potential to enhance the intensity and frequency of heavy rainfall events. This study develops a methodology to link high spatial resolution probabilistic projections of hourly precipitation with detailed surface water flood depth maps and characterization of urban vulnerability to estimate surface water flood risk. It incorporates probabilistic information on the range of uncertainties in future precipitation in a changing climate. The method is applied to a case study of Greater London and highlights that both the frequency and spatial extent of surface water flood events are set to increase under future climate change. The expected annual damage from surface water flooding is estimated to be to be £171 million, £343 million, and £390 million/year under the baseline, 2030 high, and 2050 high climate change scenarios, respectively. © 2017 Society for Risk Analysis.

Health risks from large-scale water pollution: trends in Central Asia.

PubMed

Törnqvist, Rebecka; Jarsjö, Jerker; Karimov, Bakhtiyor

2011-02-01

Limited data on the pollution status of spatially extensive water systems constrain health-risk assessments at basin-scales. Using a recipient measurement approach in a terminal water body, we show that agricultural and industrial pollutants in groundwater-surface water systems of the Aral Sea Drainage Basin (covering the main part of Central Asia) yield cumulative health hazards above guideline values in downstream surface waters, due to high concentrations of copper, arsenic, nitrite, and to certain extent dichlorodiphenyltrichloroethane (DDT). Considering these high-impact contaminants, we furthermore perform trend analyses of their upstream spatial-temporal distribution, investigating dominant large-scale spreading mechanisms. The ratio between parent DDT and its degradation products showed that discharges into or depositions onto surface waters are likely to be recent or ongoing. In river water, copper concentrations peak during the spring season, after thawing and snow melt. High spatial variability of arsenic concentrations in river water could reflect its local presence in the top soil of nearby agricultural fields. Overall, groundwaters were associated with much higher health risks than surface waters. Health risks can therefore increase considerably, if the downstream population must switch to groundwater-based drinking water supplies during surface water shortage. Arid regions are generally vulnerable to this problem due to ongoing irrigation expansion and climate changes. Copyright © 2010 Elsevier Ltd. All rights reserved.

Modelling the spatial distribution of Fasciola hepatica in bovines using decision tree, logistic regression and GIS query approaches for Brazil.

PubMed

Bennema, S C; Molento, M B; Scholte, R G; Carvalho, O S; Pritsch, I

2017-11-01

Fascioliasis is a condition caused by the trematode Fasciola hepatica. In this paper, the spatial distribution of F. hepatica in bovines in Brazil was modelled using a decision tree approach and a logistic regression, combined with a geographic information system (GIS) query. In the decision tree and the logistic model, isothermality had the strongest influence on disease prevalence. Also, the 50-year average precipitation in the warmest quarter of the year was included as a risk factor, having a negative influence on the parasite prevalence. The risk maps developed using both techniques, showed a predicted higher prevalence mainly in the South of Brazil. The prediction performance seemed to be high, but both techniques failed to reach a high accuracy in predicting the medium and high prevalence classes to the entire country. The GIS query map, based on the range of isothermality, minimum temperature of coldest month, precipitation of warmest quarter of the year, altitude and the average dailyland surface temperature, showed a possibility of presence of F. hepatica in a very large area. The risk maps produced using these methods can be used to focus activities of animal and public health programmes, even on non-evaluated F. hepatica areas.

Use of wild bird surveillance, human case data and GIS spatial analysis for predicting spatial distributions of West Nile virus in Greece.

PubMed

Valiakos, George; Papaspyropoulos, Konstantinos; Giannakopoulos, Alexios; Birtsas, Periklis; Tsiodras, Sotirios; Hutchings, Michael R; Spyrou, Vassiliki; Pervanidou, Danai; Athanasiou, Labrini V; Papadopoulos, Nikolaos; Tsokana, Constantina; Baka, Agoritsa; Manolakou, Katerina; Chatzopoulos, Dimitrios; Artois, Marc; Yon, Lisa; Hannant, Duncan; Petrovska, Liljana; Hadjichristodoulou, Christos; Billinis, Charalambos

2014-01-01

West Nile Virus (WNV) is the causative agent of a vector-borne, zoonotic disease with a worldwide distribution. Recent expansion and introduction of WNV into new areas, including southern Europe, has been associated with severe disease in humans and equids, and has increased concerns regarding the need to prevent and control future WNV outbreaks. Since 2010, 524 confirmed human cases of the disease have been reported in Greece with greater than 10% mortality. Infected mosquitoes, wild birds, equids, and chickens have been detected and associated with human disease. The aim of our study was to establish a monitoring system with wild birds and reported human cases data using Geographical Information System (GIS). Potential distribution of WNV was modelled by combining wild bird serological surveillance data with environmental factors (e.g. elevation, slope, land use, vegetation density, temperature, precipitation indices, and population density). Local factors including areas of low altitude and proximity to water were important predictors of appearance of both human and wild bird cases (Odds Ratio = 1,001 95%CI = 0,723-1,386). Using GIS analysis, the identified risk factors were applied across Greece identifying the northern part of Greece (Macedonia, Thrace) western Greece and a number of Greek islands as being at highest risk of future outbreaks. The results of the analysis were evaluated and confirmed using the 161 reported human cases of the 2012 outbreak predicting correctly (Odds = 130/31 = 4,194 95%CI = 2,841-6,189) and more areas were identified for potential dispersion in the following years. Our approach verified that WNV risk can be modelled in a fast cost-effective way indicating high risk areas where prevention measures should be implemented in order to reduce the disease incidence.

Spatial distribution, risk factors and haemato-biochemical alterations associated with Theileria equi infected equids of Punjab (India) diagnosed by indirect ELISA and nested PCR.

PubMed

Sumbria, Deepak; Singla, L D; Kumar, Sanjay; Sharma, Amrita; Dahiya, Rajesh K; Setia, Raj

2016-03-01

Equine piroplasmosis is a febrile, tick-borne disease of equids predominately caused by obligatory intra-erythrocytic protozoa Theileria equi in the Indian sub-continent. A cross-sectional study was carried out on 464 equids (426 horses and 38 donkeys/mules) in Punjab, India to assess the level of exposure to equine piroplasmosis by 18S rRNA gene nested polymerase chain reaction (nPCR) and equine merozoite antigen-2 (EMA2) indirect-ELISA (enzyme linked immunosorbent assay), to investigate risk factors and haemato-biochemical alterations associated with the infection. The endemicity of the disease was confirmed by positive PCR amplification in 21.77% and positive antibody titers in 49.78% equid samples. There was a fair agreement between these two diagnostic techniques (Kappa coefficient=0.326). The spatial distribution analysis revealed an increasing trend of T. equi prevalence from north-eastern to south-western region of Punjab by both the techniques correspondingly, which proffered a direct relation with temperature and inverse with humidity variables. The relatively prominent risk factor associated with sero-positivity was the presence of other domestic animals in the herd, while the propensity of finding a positive PCR amplification was higher in donkeys/mules, animal kept at unorganised farm or those used for commercial purposes as compared to their counterparts. There was a significant increase in globulins, gamma glutamyl-transferase, total bilirubin, direct bilirubin, indirect bilirubin, glucose levels and decrease in total erythrocyte count, haemoglobin, packed cell volume by animals, which were revealed positive by nPCR (may or may not positive by indirect-ELISA) and increase in creatinine, total bilirubin, direct bilirubin, glucose and decrease in total erythrocytes count by animals, which were revealed positive by indirect-ELISA (alone). To our knowledge, this study, for the first time, brings out a comprehensive report on the status on spatial distribution of T. equi in Punjab (India) state, thoroughly investigated by molecular and serological techniques, evaluating various environmental and demographic risk factors along with the haemato-biochemical alterations in the exposed animals. Copyright © 2015 Elsevier B.V. All rights reserved.

Micro-spatial variation of elemental distribution in estuarine sediment and their accumulation in mangroves of Indian Sundarban.

PubMed

Bakshi, Madhurima; Ram, S S; Ghosh, Somdeep; Chakraborty, Anindita; Sudarshan, M; Chaudhuri, Punarbasu

2017-05-01

This work describes the micro-spatial variation of elemental distribution in estuarine sediment and bioaccumulation of those elements in different mangrove species of the Indian Sundarbans. The potential ecological risk due to such elemental load on this mangrove-dominated habitat is also discussed. The concentrations of elements in mangrove leaves and sediments were determined using energy-dispersive X-ray fluorescence spectroscopy. Sediment quality and potential ecological risks were assessed from the calculated indices. Our data reflects higher concentration of elements, e.g., Al, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, and Pb, in the sediment, as compared to that reported by earlier workers. Biological concentration factors for K, Ca, Mn, Fe, Cu, and Zn in different mangroves indicated gradual elemental bioaccumulation in leaf tissues (0.002-1.442). Significant variation was observed for elements, e.g., Ni, Mn, and Ca, in the sediments of all the sites, whereas in the plants, significant variation was found for P, S, Cl, K, Ca, Mn, Fe, Cu, and Zn. This was mostly due to the differences in uptake and accumulation potential of the plants. Various sediment quality indices suggested the surface sediments to be moderately contaminated and suffering from progressive deterioration. Cu, Cr, Zn, Mn, and Ni showed higher enrichment factors (0.658-1.469), contamination factors (1.02-2.7), and geo-accumulation index (0.043-0.846) values. The potential ecological risk index values considering Cu, Cr, Pb, and Zn were found to be within "low ecological risk" category (20.04-24.01). However, Cr and Ni in the Sundarban mangroves exceeded the effect range low and probable effect level limits. Strong correlation of Zn with Fe and K was observed, reflecting their similar transportation and accumulation process in both sediment and plant systems. The plant-sediment elemental correlation was found to be highly non-linear, suggesting role of some physiological and edaphic factors in the accumulation process. Overall, the study of micro-spatial distribution of elements can act as a useful tool for determining health of estuarine ecosystem.

[Assessment of heavy metal pollution and potential ecological risks of urban soils in Kaifeng City, China].

PubMed

Li, Yi-Meng; Ma, Jian-Hua; Liu, De-Xin; Sun, Yan-Li; Chen, Yan-Fang

2015-03-01

Ninety-nine topsoil (0-15 cm) samples were collected from Kaifeng City, China using the grid method, and then the concentrations of As, Cd, Cr, Cu, Ni, Pb and Zn in the samples were measured by standard methods. Soil pollution levels and potential ecological risks of the heavy metals were assessed using the pollution load index (PLI) and potential ecological risk index (RI), respectively. Ordinary Kriging interpolation technique was employed to investigate the spatial distribution of PLI and RI of the city. The results showed that high pollution of Cd occurred in Kaifeng urban soils, and there was moderate pollution of Zn, slight pollution of Pb and Cu, and no pollution of Ni, Cr and As. Very high ecological risk was posed by Cd and low risk by other metals. The mean PLI of the 7 metals from all sample points was 2.53, which was categorized as moderate pollution. The average RI was 344.58 which represented a considerable ecological risk. PLI and RI shared a similar spatial distribution with high values centralized in the old industrial area in the southeast and railway stations for passengers and goods in the south of the city, followed by the old town within the ancient city wall, and low values located in the north and west areas. Cadmium was the main factor for both soil pollution and potential ecological risk primarily due to farmland topsoil in the eastern suburb of Kaifeng City with high Cd concentrations resulted from sewage irrigation deposited in the urban area by wind, human activities such as soot discharged from the chemical fertilizer plant of Kaifeng, transportation and coal combustion.

Erosion Resistance Index (ERI) to Assess Surface Stability in Desert Environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamada, Yuki; Grippo, Mark A.

2015-11-01

A new spectral index—erosion resistance index (ERI)—was developed to assess erosion risks in desert landscapes. The index was developed by applying trigonometry to the combination of the green/red band-ratio and the red/near infrared band-ratio from very high spatial resolution imagery. The resultant ERI maps showed spatially cohesive distributions of high and low index values across the study areas. High index values were observed over areas that were resistant to erosion (such as desert pavement and dense vegetation), while low index values overlapped with areas likely dominated by loose sandy soils, such as stream beds and access roads. Although further investigationmore » is warranted, this new index, ERI, shows promise for the assessment of erosion risks in desert regions.« less

The international limits and population at risk of Plasmodium vivax transmission in 2009.

PubMed

Guerra, Carlos A; Howes, Rosalind E; Patil, Anand P; Gething, Peter W; Van Boeckel, Thomas P; Temperley, William H; Kabaria, Caroline W; Tatem, Andrew J; Manh, Bui H; Elyazar, Iqbal R F; Baird, J Kevin; Snow, Robert W; Hay, Simon I

2010-08-03

A research priority for Plasmodium vivax malaria is to improve our understanding of the spatial distribution of risk and its relationship with the burden of P. vivax disease in human populations. The aim of the research outlined in this article is to provide a contemporary evidence-based map of the global spatial extent of P. vivax malaria, together with estimates of the human population at risk (PAR) of any level of transmission in 2009. The most recent P. vivax case-reporting data that could be obtained for all malaria endemic countries were used to classify risk into three classes: malaria free, unstable (<0.1 case per 1,000 people per annum (p.a.)) and stable (> or =0.1 case per 1,000 p.a.) P. vivax malaria transmission. Risk areas were further constrained using temperature and aridity data based upon their relationship with parasite and vector bionomics. Medical intelligence was used to refine the spatial extent of risk in specific areas where transmission was reported to be absent (e.g., large urban areas and malaria-free islands). The PAR under each level of transmission was then derived by combining the categorical risk map with a high resolution population surface adjusted to 2009. The exclusion of large Duffy negative populations in Africa from the PAR totals was achieved using independent modelling of the gene frequency of this genetic trait. It was estimated that 2.85 billion people were exposed to some risk of P. vivax transmission in 2009, with 57.1% of them living in areas of unstable transmission. The vast majority (2.59 billion, 91.0%) were located in Central and South East (CSE) Asia, whilst the remainder were located in America (0.16 billion, 5.5%) and in the Africa+ region (0.10 billion, 3.5%). Despite evidence of ubiquitous risk of P. vivax infection in Africa, the very high prevalence of Duffy negativity throughout Central and West Africa reduced the PAR estimates substantially. After more than a century of development and control, P. vivax remains more widely distributed than P. falciparum and is a potential cause of morbidity and mortality amongst the 2.85 billion people living at risk of infection, the majority of whom are in the tropical belt of CSE Asia. The probability of infection is reduced massively across Africa by the frequency of the Duffy negative trait, but transmission does occur on the continent and is a concern for Duffy positive locals and travellers. The final map provides the spatial limits on which the endemicity of P. vivax transmission can be mapped to support future cartographic-based burden estimations.

Spatial relationships among soil biota in a contaminated grassland ecosystem at Aberdeen Proving Ground, Maryland

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuperman, R.; Williams, G.; Parmelee, R.

1995-12-31

Spatial relationships among soil nematodes and soil microorganisms were investigated in a grassland ecosystem contaminated with heavy metals in the US Army`s Aberdeen Proving Ground. The study quantified fungal and bacterial biomass, the abundance of soil protozoa, and nematodes. Geostatistical techniques were used to determine spatial distributions of these parameters and to evaluate various cross-correlations. The cross-correlations among soil biota numbers were analyzed using two methods: a cross general relative semi-variogram and an interactive graphical data representation using geostatistically estimated data distributions. Both the visualization technique and the cross general relative semi-variogram and an interactive graphical data representation using geostatisticallymore » estimated data distributions. Both the visualization technique and the cross general relative semi-variogram showed a negative correlation between the abundance of fungivore nematodes and fungal biomass, the abundance of bacterivore nematodes and bacterial biomass, the abundance of omnivore/predator nematodes and numbers of protozoa, and between numbers of protozoa and both fungal and bacterial biomass. The negative cross-correlation between soil biota and metal concentrations showed that soil fungi were particularly sensitive to heavy metal concentrations and can be used for quantitative ecological risk assessment of metal-contaminated soils. This study found that geostatistics are a useful tool for describing and analyzing spatial relationships among components of food webs in the soil community.« less

A systemic ecological risk assessment based on spatial distribution and source apportionment in the abandoned lead acid battery plant zone, China.

PubMed

Zhang, Yimei; Li, Shuai; Chen, Zhuang; Wang, Fei; Chen, Jie; Wang, Liqun

2018-07-15

In China, potential heavy metal hazard around abandoned lead-acid battery plant (ALBP) area has been a great concern but without detailed report. The distribution and sources of heavy metals in soils and so by risk assessment associated with ALBP are conducted in this contribution, based on geographies and statistics. Pb and Zn are quantitively identified to be still emitted from ALBP soil, and Cd as well As are from agricultural activity. We investigate vertical metal distribution, and fortunately find that metals migrate within limit of 40 cm below topsoil, which is higher than groundwater table. The visualized stable depths are Zn 40 cm, Pb, As 20 cm, and Cd 40 cm. The mapped pollution load index (PLI) suggests a high pollution level exists in ALBP soil. The estimation of potential ecological risk index (PERI) indicates a light ecological risk in studied area, while As and Cd mainly from agricultural activity possess 54% of total E ri . Health risk index (THI) is 0.178 for children, indicating non-cancer risks may be ignored in observed area. Though calculated risk is temporarily affordable, soil remediation and reduction of agricultural chemical reagents are recommended for preventing potential cumulative risk from further bioconcentration of heavy metals. Copyright © 2018 Elsevier B.V. All rights reserved.

Environmental risk assessment of white phosphorus from the use of munitions - a probabilistic approach.

PubMed

Voie, Øyvind Albert; Johnsen, Arnt; Strømseng, Arnljot; Longva, Kjetil Sager

2010-03-15

White phosphorus (P(4)) is a highly toxic compound used in various pyrotechnic products. Ammunitions containing P(4) are widely used in military training areas where the unburned products of P(4) contaminate soil and local ponds. Traditional risk assessment methods presuppose a homogeneous spatial distribution of pollutants. The distribution of P(4) in military training areas is heterogeneous, which reduces the probability of potential receptors being exposed to the P(4) by ingestion, for example. The current approach to assess the environmental risk from the use of P(4) suggests a Bayesian network (Bn) as a risk assessment tool. The probabilistic reasoning supported by a Bn allows us to take into account the heterogeneous distribution of P(4). Furthermore, one can combine empirical data and expert knowledge, which allows the inclusion of all kinds of data that are relevant to the problem. The current work includes an example of the use of the Bn as a risk assessment tool where the risk for P(4) poisoning in humans and grazing animals at a military shooting range in Northern Norway was calculated. P(4) was detected in several craters on the range at concentrations up to 5.7g/kg. The risk to human health was considered acceptable under the current land use. The risk for grazing animals such as sheep, however, was higher, suggesting that precautionary measures may be advisable.

Who is where at risk for Chronic Obstructive Pulmonary Disease? A spatial epidemiological analysis of health insurance claims for COPD in Northeastern Germany

PubMed Central

Maier, Werner; Schweikart, Jürgen; Keste, Andrea; Moskwyn, Marita

2018-01-01

Background Chronic obstructive pulmonary disease (COPD) has a high prevalence rate in Germany and a further increase is expected within the next years. Although risk factors on an individual level are widely understood, only little is known about the spatial heterogeneity and population-based risk factors of COPD. Background knowledge about broader, population-based processes could help to plan the future provision of healthcare and prevention strategies more aligned to the expected demand. The aim of this study is to analyze how the prevalence of COPD varies across northeastern Germany on the smallest spatial-scale possible and to identify the location-specific population-based risk factors using health insurance claims of the AOK Nordost. Methods To visualize the spatial distribution of COPD prevalence at the level of municipalities and urban districts, we used the conditional autoregressive Besag–York–Mollié (BYM) model. Geographically weighted regression modelling (GWR) was applied to analyze the location-specific ecological risk factors for COPD. Results The sex- and age-adjusted prevalence of COPD was 6.5% in 2012 and varied widely across northeastern Germany. Population-based risk factors consist of the proportions of insurants aged 65 and older, insurants with migration background, household size and area deprivation. The results of the GWR model revealed that the population at risk for COPD varies considerably across northeastern Germany. Conclusion Area deprivation has a direct and an indirect influence on the prevalence of COPD. Persons ageing in socially disadvantaged areas have a higher chance of developing COPD, even when they are not necessarily directly affected by deprivation on an individual level. This underlines the importance of considering the impact of area deprivation on health for planning of healthcare. Additionally, our results reveal that in some parts of the study area, insurants with migration background and persons living in multi-persons households are at elevated risk of COPD. PMID:29414997

The Spatial Distribution of Hepatitis C Virus Infections and Associated Determinants--An Application of a Geographically Weighted Poisson Regression for Evidence-Based Screening Interventions in Hotspots.

PubMed

Kauhl, Boris; Heil, Jeanne; Hoebe, Christian J P A; Schweikart, Jürgen; Krafft, Thomas; Dukers-Muijrers, Nicole H T M

2015-01-01

Hepatitis C Virus (HCV) infections are a major cause for liver diseases. A large proportion of these infections remain hidden to care due to its mostly asymptomatic nature. Population-based screening and screening targeted on behavioural risk groups had not proven to be effective in revealing these hidden infections. Therefore, more practically applicable approaches to target screenings are necessary. Geographic Information Systems (GIS) and spatial epidemiological methods may provide a more feasible basis for screening interventions through the identification of hotspots as well as demographic and socio-economic determinants. Analysed data included all HCV tests (n = 23,800) performed in the southern area of the Netherlands between 2002-2008. HCV positivity was defined as a positive immunoblot or polymerase chain reaction test. Population data were matched to the geocoded HCV test data. The spatial scan statistic was applied to detect areas with elevated HCV risk. We applied global regression models to determine associations between population-based determinants and HCV risk. Geographically weighted Poisson regression models were then constructed to determine local differences of the association between HCV risk and population-based determinants. HCV prevalence varied geographically and clustered in urban areas. The main population at risk were middle-aged males, non-western immigrants and divorced persons. Socio-economic determinants consisted of one-person households, persons with low income and mean property value. However, the association between HCV risk and demographic as well as socio-economic determinants displayed strong regional and intra-urban differences. The detection of local hotspots in our study may serve as a basis for prioritization of areas for future targeted interventions. Demographic and socio-economic determinants associated with HCV risk show regional differences underlining that a one-size-fits-all approach even within small geographic areas may not be appropriate. Future screening interventions need to consider the spatially varying association between HCV risk and associated demographic and socio-economic determinants.

Who is where at risk for Chronic Obstructive Pulmonary Disease? A spatial epidemiological analysis of health insurance claims for COPD in Northeastern Germany.

PubMed

Kauhl, Boris; Maier, Werner; Schweikart, Jürgen; Keste, Andrea; Moskwyn, Marita

2018-01-01

Chronic obstructive pulmonary disease (COPD) has a high prevalence rate in Germany and a further increase is expected within the next years. Although risk factors on an individual level are widely understood, only little is known about the spatial heterogeneity and population-based risk factors of COPD. Background knowledge about broader, population-based processes could help to plan the future provision of healthcare and prevention strategies more aligned to the expected demand. The aim of this study is to analyze how the prevalence of COPD varies across northeastern Germany on the smallest spatial-scale possible and to identify the location-specific population-based risk factors using health insurance claims of the AOK Nordost. To visualize the spatial distribution of COPD prevalence at the level of municipalities and urban districts, we used the conditional autoregressive Besag-York-Mollié (BYM) model. Geographically weighted regression modelling (GWR) was applied to analyze the location-specific ecological risk factors for COPD. The sex- and age-adjusted prevalence of COPD was 6.5% in 2012 and varied widely across northeastern Germany. Population-based risk factors consist of the proportions of insurants aged 65 and older, insurants with migration background, household size and area deprivation. The results of the GWR model revealed that the population at risk for COPD varies considerably across northeastern Germany. Area deprivation has a direct and an indirect influence on the prevalence of COPD. Persons ageing in socially disadvantaged areas have a higher chance of developing COPD, even when they are not necessarily directly affected by deprivation on an individual level. This underlines the importance of considering the impact of area deprivation on health for planning of healthcare. Additionally, our results reveal that in some parts of the study area, insurants with migration background and persons living in multi-persons households are at elevated risk of COPD.

The spatial distribution of pet dogs and pet cats on the island of Ireland

PubMed Central

2011-01-01

Background There is considerable international research regarding the link between human demographics and pet ownership. In several international studies, pet ownership was associated with household demographics including: the presence of children in the household, urban/rural location, level of education and age/family structure. What is lacking across all these studies, however, is an understanding of how these pets are spatially distributed throughout the regions under study. This paper describes the spatial distribution of pet dog and pet cat owning households on the island of Ireland. Results In 2006, there were an estimated 640,620 pet dog owning households and 215,542 pet cat owning households in Ireland. These estimates are derived from logistic regression modelling, based on household composition to determine pet dog ownership and the type of house to determine pet cat ownership. Results are presented using chloropleth maps. There is a higher density of pet dog owning households in the east of Ireland and in the cities than the west of Ireland and rural areas. However, in urban districts there are a lower proportion of households owning pet dogs than in rural districts. There are more households with cats in the urban areas, but the proportion of households with cats is greater in rural areas. Conclusions The difference in spatial distribution of dog ownership is a reflection of a generally higher density of households in the east of Ireland and in major cities. The higher proportion of ownership in the west is understandable given the higher proportion of farmers and rural dwellings in this area. Spatial representation allows us to visualise the impact of human household distribution on the density of both pet dogs and pet cats on the island of Ireland. This information can be used when analysing risk of disease spread, for market research and for instigating veterinary care. PMID:21663606

The spatial distribution of pet dogs and pet cats on the island of Ireland.

PubMed

Downes, Martin J; Clegg, Tracy A; Collins, Daniel M; McGrath, Guy; More, Simon J

2011-06-10

There is considerable international research regarding the link between human demographics and pet ownership. In several international studies, pet ownership was associated with household demographics including: the presence of children in the household, urban/rural location, level of education and age/family structure. What is lacking across all these studies, however, is an understanding of how these pets are spatially distributed throughout the regions under study. This paper describes the spatial distribution of pet dog and pet cat owning households on the island of Ireland. In 2006, there were an estimated 640,620 pet dog owning households and 215,542 pet cat owning households in Ireland. These estimates are derived from logistic regression modelling, based on household composition to determine pet dog ownership and the type of house to determine pet cat ownership. Results are presented using chloropleth maps. There is a higher density of pet dog owning households in the east of Ireland and in the cities than the west of Ireland and rural areas. However, in urban districts there are a lower proportion of households owning pet dogs than in rural districts. There are more households with cats in the urban areas, but the proportion of households with cats is greater in rural areas. The difference in spatial distribution of dog ownership is a reflection of a generally higher density of households in the east of Ireland and in major cities. The higher proportion of ownership in the west is understandable given the higher proportion of farmers and rural dwellings in this area. Spatial representation allows us to visualise the impact of human household distribution on the density of both pet dogs and pet cats on the island of Ireland. This information can be used when analysing risk of disease spread, for market research and for instigating veterinary care.

Direct measurement of the 3-dimensional DNA lesion distribution induced by energetic charged particles in a mouse model tissue

PubMed Central

Mirsch, Johanna; Tommasino, Francesco; Frohns, Antonia; Conrad, Sandro; Durante, Marco; Scholz, Michael; Friedrich, Thomas; Löbrich, Markus

2015-01-01

Charged particles are increasingly used in cancer radiotherapy and contribute significantly to the natural radiation risk. The difference in the biological effects of high-energy charged particles compared with X-rays or γ-rays is determined largely by the spatial distribution of their energy deposition events. Part of the energy is deposited in a densely ionizing manner in the inner part of the track, with the remainder spread out more sparsely over the outer track region. Our knowledge about the dose distribution is derived solely from modeling approaches and physical measurements in inorganic material. Here we exploited the exceptional sensitivity of γH2AX foci technology and quantified the spatial distribution of DNA lesions induced by charged particles in a mouse model tissue. We observed that charged particles damage tissue nonhomogenously, with single cells receiving high doses and many other cells exposed to isolated damage resulting from high-energy secondary electrons. Using calibration experiments, we transformed the 3D lesion distribution into a dose distribution and compared it with predictions from modeling approaches. We obtained a radial dose distribution with sub-micrometer resolution that decreased with increasing distance to the particle path following a 1/r2 dependency. The analysis further revealed the existence of a background dose at larger distances from the particle path arising from overlapping dose deposition events from independent particles. Our study provides, to our knowledge, the first quantification of the spatial dose distribution of charged particles in biologically relevant material, and will serve as a benchmark for biophysical models that predict the biological effects of these particles. PMID:26392532

Spatial clustering of high load ocular Chlamydia trachomatis infection in trachoma: a cross-sectional population-based study.

PubMed

Last, Anna; Burr, Sarah; Alexander, Neal; Harding-Esch, Emma; Roberts, Chrissy H; Nabicassa, Meno; Cassama, Eunice Teixeira da Silva; Mabey, David; Holland, Martin; Bailey, Robin

2017-07-31

Chlamydia trachomatis (Ct) is the most common cause of bacterial sexually transmitted infection and infectious cause of blindness (trachoma) worldwide. Understanding the spatial distribution of Ct infection may enable us to identify populations at risk and improve our understanding of Ct transmission. In this study, we sought to investigate the spatial distribution of Ct infection and the clinical features associated with high Ct load in trachoma-endemic communities on the Bijagós Archipelago (Guinea Bissau). We collected 1507 conjunctival samples and corresponding detailed clinical data during a cross-sectional population-based geospatially representative trachoma survey. We used droplet digital PCR to estimate Ct load on conjunctival swabs. Geostatistical tools were used to investigate clustering of ocular Ct infections. Spatial clusters (independent of age and gender) of individuals with high Ct loads were identified using local indicators of spatial association. We did not detect clustering of individuals with low load infections. These data suggest that infections with high bacterial load may be important in Ct transmission. These geospatial tools may be useful in the study of ocular Ct transmission dynamics and as part of trachoma surveillance post-treatment, to identify clusters of infection and thresholds of Ct load that may be important foci of re-emergent infection in communities. © FEMS 2017.

Spatial distribution of Parkinson's disease mortality in Spain, 1989-1998, as a guide for focused aetiological research or health-care intervention

PubMed Central

2009-01-01

Background Aetiologically, genetic and environmental factors having an uneven spatial distribution may underlie Parkinson's disease (PD). Undiagnosis of PD in selected regions might have limited access to treatment with levodopa and simultaneously, if present at death, determined PD underreporting at the death record. The purpose of this study was to describe and analyse municipal mortality due to PD in Spain in aetiological and interventional perspective. Methods PD mortality at a municipal level was modelled using the Besag-York- Molliè autoregressive spatial model, combining demographic information with cause-of-death diagnostic data (International Classification of Diseases 9th Revision (ICD-9) code 332.0). Municipal relative risks (RRs) were independently estimated for women, men and both sexes, and plotted on maps depicting smoothed RR estimates and the distribution of the posterior probability of RR>1. Results A south-north gradient, with large geographical areas suggesting clustered towns with high mortality, was seen in Asturias, the Basque Country, Balearic Islands and, particularly, in the Lower Ebro valley around Tarragona. Similarly, there was a suggestion that lowest mortality was clustered in the south-east and south-west. We identified some isolated or clustered municipalities with high mortality that were situated near industrial plants reported to be associated with environmental xenobiotic emissions. However, the same pattern was also observed for some cities with low mortality. Conclusion Municipal PD mortality in Spain was unevenly distributed. Patterns were roughly similar to reported provincial PD mortality and use of levodopa. While the overall pattern appears to result from spatially selective PD undiagnosis, and can not be ascribed to industrial emissions, it can not be excluded that selected "hot spots" reflect genetic factors and/or environmental exposures inducing parkinsonism. A few municipal populations, located in low-mortality-risk areas in the vicinity of polluting plants or registering high excess PD mortality, might constitute a priority for conducting direct etiological studies. Additionally, interventions aimed to reduce potential PD undiagnosis might be most appropriate in the South. PMID:19954536

Spatial distribution of vehicle emission inventories in the Federal District, Brazil

NASA Astrophysics Data System (ADS)

Réquia, Weeberb João; Koutrakis, Petros; Roig, Henrique Llacer

2015-07-01

Air pollution poses an important public health risk, especially in large urban areas. Information about the spatial distribution of air pollutants can be used as a tool for developing public policies to reduce source emissions. Air pollution monitoring networks provide information about pollutant concentrations; however, they are not available in every urban area. Among the 5570 cities in Brazil, for example, only 1.7% of them have air pollution monitoring networks. In this study we assess vehicle emissions for main traffic routes of the Federal District (state of Brazil) and characterize their spatial patterns. Toward this end, we used a bottom-up method to predict emissions and to characterize their spatial patterns using Global Moran's (Spatial autocorrelation analysis) and Getis-Ord General G (High/Low cluster analysis). Our findings suggested that light duty vehicles are primarily responsible for the vehicular emissions of CO (68.9%), CH4 (93.6%), and CO2 (57.9%), whereas heavy duty vehicles are primarily responsible for the vehicular emissions of NMHC (92.9%), NOx (90.7%), and PM (97.4%). Furthermore, CO2 is the pollutant with the highest emissions, over 30 million tons/year. In the spatial autocorrelation analysis was identified cluster (p < 0.01) for all types of vehicles and for all pollutants. However, we identified high cluster only for the light vehicles.

Influence of pedestrian age and gender on spatial and temporal distribution of pedestrian crashes.

PubMed

Toran Pour, Alireza; Moridpour, Sara; Tay, Richard; Rajabifard, Abbas

2018-01-02

Every year, about 1.24 million people are killed in traffic crashes worldwide and more than 22% of these deaths are pedestrians. Therefore, pedestrian safety has become a significant traffic safety issue worldwide. In order to develop effective and targeted safety programs, the location- and time-specific influences on vehicle-pedestrian crashes must be assessed. The main purpose of this research is to explore the influence of pedestrian age and gender on the temporal and spatial distribution of vehicle-pedestrian crashes to identify the hotspots and hot times. Data for all vehicle-pedestrian crashes on public roadways in the Melbourne metropolitan area from 2004 to 2013 are used in this research. Spatial autocorrelation is applied in examining the vehicle-pedestrian crashes in geographic information systems (GIS) to identify any dependency between time and location of these crashes. Spider plots and kernel density estimation (KDE) are then used to determine the temporal and spatial patterns of vehicle-pedestrian crashes for different age groups and genders. Temporal analysis shows that pedestrian age has a significant influence on the temporal distribution of vehicle-pedestrian crashes. Furthermore, men and women have different crash patterns. In addition, results of the spatial analysis shows that areas with high risk of vehicle-pedestrian crashes can vary during different times of the day for different age groups and genders. For example, for those between ages 18 and 65, most vehicle-pedestrian crashes occur in the central business district (CBD) during the day, but between 7:00 p.m. and 6:00 a.m., crashes among this age group occur mostly around hotels, clubs, and bars. This research reveals that temporal and spatial distributions of vehicle-pedestrian crashes vary for different pedestrian age groups and genders. Therefore, specific safety measures should be in place during high crash times at different locations for different age groups and genders to increase the effectiveness of the countermeasures in preventing and reducing vehicle-pedestrian crashes.

Geospatial Analysis on the Distributions of Tobacco Smoking and Alcohol Drinking in India

PubMed Central

Fu, Sze Hang; Jha, Prabhat; Gupta, Prakash C.; Kumar, Rajesh; Dikshit, Rajesh; Sinha, Dhirendra

2014-01-01

Background Tobacco smoking and binge alcohol drinking are two of the leading risk factors for premature mortality worldwide. In India, studies have examined the geographic distributions of tobacco smoking and alcohol drinking only at the state-level; sub-state variations and the spatial association between the two consumptions are poorly understood. Methodology We used data from the Special Fertility and Mortality Survey conducted in 1998 to examine the geographic distributions of tobacco smoking and alcohol drinking at the district and postal code levels. We used kriging interpolation to generate smoking and drinking distributions at the postal code level. We also examined spatial autocorrelations and identified spatial clusters of high and low prevalence of smoking and drinking. Finally, we used bivariate analyses to examine the spatial correlations between smoking and drinking, and between cigarette and bidi smoking. Results There was a high prevalence of any smoking in the central and northeastern states, and a high prevalence of any drinking in Himachal Pradesh, Arunachal Pradesh, and eastern Madhya Pradesh. Spatial clusters of early smoking (started smoking before age 20) were identified in the central states. Cigarette and bidi smoking showed distinctly different geographic patterns, with high levels of cigarette smoking in the northeastern states and high levels of bidi smoking in the central states. The geographic pattern of bidi smoking was similar to early smoking. Cigarette smoking was spatially associated with any drinking. Smoking prevalences in 1998 were correlated with prevalences in 2004 at the district level and 2010 at the state level. Conclusion These results along with earlier evidence on the complementarities between tobacco smoking and alcohol drinking suggest that local public health action on smoking might also help to reduce alcohol consumption, and vice versa. Surveys that properly represent tobacco and alcohol consumptions at the district level are recommended. PMID:25025379

A geographic analysis of individual and environmental risk factors for hypospadias births

PubMed Central

Winston, Jennifer J; Meyer, Robert E; Emch, Michael E

2014-01-01

Background Hypospadias is a relatively common birth defect affecting the male urinary tract. We explored the etiology of hypospadias by examining its spatial distribution in North Carolina and the spatial clustering of residuals from individual and environmental risk factors. Methods We used data collected by the North Carolina Birth Defects Monitoring Program from 2003-2005 to estimate local Moran's I statistics to identify geographic clustering of overall and severe hypospadias, using 995 overall cases and 16,013 controls. We conducted logistic regression and local Moran's I statistics on standardized residuals to consider the contribution of individual variables (maternal age, maternal race/ethnicity, maternal education, smoking, parity, and diabetes) and environmental variables (block group land cover) to this clustering. Results Local Moran's I statistics indicated significant clustering of overall and severe hypospadias in eastern central North Carolina. Spatial clustering of hypospadias persisted when controlling for individual factors, but diminished somewhat when controlling for environmental factors. In adjusted models, maternal residence in a block group with more than 5% crop cover was associated with overall hypospadias (OR = 1.22; 95% CI = 1.04 – 1.43); that is living in a block group with greater than 5% crop cover was associated with a 22% increase in the odds of having a baby with hypospadias. Land cover was not associated with severe hypospadias. Conclusions This study illustrates the potential contribution of mapping in generating hypotheses about disease etiology. Results suggest that environmental factors including proximity to agriculture may play some role in the spatial distribution of hypospadias. PMID:25196538

A preliminary spatial assessment of risk: Marine birds and chronic oil pollution on Canada's Pacific coast.

PubMed

Fox, C H; O'Hara, P D; Bertazzon, S; Morgan, K; Underwood, F E; Paquet, P C

2016-12-15

Chronic oil pollution poses substantial risks to marine birds and other marine wildlife worldwide. On Canada's Pacific coast, the negative ecological consequences to marine birds and marine ecosystems in general remain poorly understood. Using information relating to oil spill probability of occurrence, areas of overall importance to marine birds, and the at-sea distribution and density of 12 marine bird species and seven bird groups, including multiple Species at Risk, we undertook a spatial assessment of risk. Our results identify two main areas important to marine birds potentially at higher risk of exposure to oil. For individual bird species or species groups, those predicted to have elevated bird densities near the mainland and the northeast coast of Vancouver Island were identified as being at higher potential risk of exposure. Our results, however, should be considered preliminary. As with other anthropogenic stressors, in order to better understand and subsequently mitigate the consequences of chronic oil pollution on marine birds, improved information relating to marine birds and the occurrence of oil spills on Canada's Pacific coast is needed. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatio-Temporal Distribution of Vector-Host Contact (VHC) Ratios and Ecological Niche Modeling of the West Nile Virus Mosquito Vector, Culex quinquefasciatus, in the City of New Orleans, LA, USA

PubMed Central

Michaels, Sarah R.; Riegel, Claudia; Pereira, Roberto M.; Zipperer, Wayne; Lockaby, B. Graeme; Koehler, Philip G.

2017-01-01

The consistent sporadic transmission of West Nile Virus (WNV) in the city of New Orleans justifies the need for distribution risk maps highlighting human risk of mosquito bites. We modeled the influence of biophysical and socioeconomic metrics on the spatio-temporal distributions of presence/vector-host contact (VHC) ratios of WNV vector, Culex quinquefasciatus, within their flight range. Biophysical and socioeconomic data were extracted within 5-km buffer radii around sampling localities of gravid female Culex quinquefasciatus. The spatio-temporal correlations between VHC data and 33 variables, including climate, land use-land cover (LULC), socioeconomic, and land surface terrain were analyzed using stepwise linear regression models (RM). Using MaxEnt, we developed a distribution model using the correlated predicting variables. Only 12 factors showed significant correlations with spatial distribution of VHC ratios (R2 = 81.62, p < 0.01). Non-forested wetland (NFWL), tree density (TD) and residential-urban (RU) settings demonstrated the strongest relationship. The VHC ratios showed monthly environmental resilience in terms of number and type of influential factors. The highest prediction power of RU and other urban and built up land (OUBL), was demonstrated during May–August. This association was positively correlated with the onset of the mosquito WNV infection rate during June. These findings were confirmed by the Jackknife analysis in MaxEnt and independently collected field validation points. The spatial and temporal correlations of VHC ratios and their response to the predicting variables are discussed. PMID:28786934

Spatio-Temporal Distribution of Vector-Host Contact (VHC) Ratios and Ecological Niche Modeling of the West Nile Virus Mosquito Vector, Culex quinquefasciatus, in the City of New Orleans, LA, USA.

PubMed

Sallam, Mohamed F; Michaels, Sarah R; Riegel, Claudia; Pereira, Roberto M; Zipperer, Wayne; Lockaby, B Graeme; Koehler, Philip G

2017-08-08

The consistent sporadic transmission of West Nile Virus (WNV) in the city of New Orleans justifies the need for distribution risk maps highlighting human risk of mosquito bites. We modeled the influence of biophysical and socioeconomic metrics on the spatio-temporal distributions of presence/vector-host contact (VHC) ratios of WNV vector, Culex quinquefasciatus , within their flight range . Biophysical and socioeconomic data were extracted within 5-km buffer radii around sampling localities of gravid female Culex quinquefasciatus . The spatio-temporal correlations between VHC data and 33 variables, including climate, land use-land cover (LULC), socioeconomic, and land surface terrain were analyzed using stepwise linear regression models (RM). Using MaxEnt, we developed a distribution model using the correlated predicting variables. Only 12 factors showed significant correlations with spatial distribution of VHC ratios ( R ² = 81.62, p < 0.01). Non-forested wetland (NFWL), tree density (TD) and residential-urban (RU) settings demonstrated the strongest relationship. The VHC ratios showed monthly environmental resilience in terms of number and type of influential factors. The highest prediction power of RU and other urban and built up land (OUBL), was demonstrated during May-August. This association was positively correlated with the onset of the mosquito WNV infection rate during June. These findings were confirmed by the Jackknife analysis in MaxEnt and independently collected field validation points. The spatial and temporal correlations of VHC ratios and their response to the predicting variables are discussed.

Spatial and temporal relationships between the invasive snail Bithynia tentaculata and submersed aquatic vegetation in Pool 8 of the Upper Mississippi River

USGS Publications Warehouse

Weeks, Alicia M.; DeJager, Nathan R.; Haro, Roger J.; Sandland, Greg J.

2017-01-01

Bithynia tentaculata is an invasive snail that was first reported in Lake Michigan in 1871 and has since spread throughout a number of freshwater systems of the USA. This invasion has been extremely problematic in the Upper Mississippi River as the snails serve as intermediate hosts for several trematode parasites that have been associated with waterfowl mortality in the region. This study was designed to assess the abundance and distribution of B. tentaculata relative to submersed aquatic vegetation as macrophytes provide important nesting and food resources for migrating waterfowl. Temporal changes in both vegetation and snail densities were compared between 2007 and 2015. Between these years, B. tentaculata densities have nearly quadrupled despite minor changes in vegetation abundance, distribution and composition. Understanding the spatial distribution of B. tentaculata in relation to other habitat features, including submersed vegetation, and quantifying any further changes in the abundance and distribution of B. tentaculata over time will be important for better identifying areas of risk for disease transmission to waterfowl.

Exploring the small-scale spatial distribution of hypertension and its association to area deprivation based on health insurance claims in Northeastern Germany.

PubMed

Kauhl, B; Maier, W; Schweikart, J; Keste, A; Moskwyn, M

2018-01-10

Hypertension is one of the most frequently diagnosed chronic conditions in Germany. Targeted prevention strategies and allocation of general practitioners where they are needed most are necessary to prevent severe complications arising from high blood pressure. However, data on chronic diseases in Germany are mostly available through survey data, which do not only underestimate the actual prevalence but are also only available on coarse spatial scales. The discussion of including area deprivation for planning of healthcare is still relatively young in Germany, although previous studies have shown that area deprivation is associated with adverse health outcomes, irrespective of individual characteristics. The aim of this study is therefore to analyze the spatial distribution of hypertension at very fine geographic scales and to assess location-specific associations between hypertension, socio-demographic population characteristics and area deprivation based on health insurance claims of the AOK Nordost. To visualize the spatial distribution of hypertension prevalence at very fine geographic scales, we used the conditional autoregressive Besag-York-Mollié (BYM) model. Geographically weighted regression modelling (GWR) was applied to analyze the location-specific association of hypertension to area deprivation and further socio-demographic population characteristics. The sex- and age-adjusted prevalence of hypertension was 33.1% in 2012 and varied widely across northeastern Germany. The main risk factors for hypertension were proportions of insurants aged 45-64, 65 and older, area deprivation and proportion of persons commuting to work outside their residential municipality. The GWR model revealed important regional variations in the strength of the examined associations. Area deprivation has only a significant and therefore direct influence in large parts of Mecklenburg-West Pomerania. However, the spatially varying strength of the association between demographic variables and hypertension indicates that there also exists an indirect effect of area deprivation on the prevalence of hypertension. It can therefore be expected that persons ageing in deprived areas will be at greater risk of hypertension, irrespective of their individual characteristics. The future planning and allocation of primary healthcare in northeastern Germany would therefore greatly benefit from considering the effect of area deprivation.

Cluster analysis for determining distribution center location

NASA Astrophysics Data System (ADS)

Lestari Widaningrum, Dyah; Andika, Aditya; Murphiyanto, Richard Dimas Julian

2017-12-01

Determination of distribution facilities is highly important to survive in the high level of competition in today’s business world. Companies can operate multiple distribution centers to mitigate supply chain risk. Thus, new problems arise, namely how many and where the facilities should be provided. This study examines a fast-food restaurant brand, which located in the Greater Jakarta. This brand is included in the category of top 5 fast food restaurant chain based on retail sales. There were three stages in this study, compiling spatial data, cluster analysis, and network analysis. Cluster analysis results are used to consider the location of the additional distribution center. Network analysis results show a more efficient process referring to a shorter distance to the distribution process.

Temporal Dynamics and Spatial Patterns of Aedes aegypti Breeding Sites, in the Context of a Dengue Control Program in Tartagal (Salta Province, Argentina).

PubMed

Espinosa, Manuel; Weinberg, Diego; Rotela, Camilo H; Polop, Francisco; Abril, Marcelo; Scavuzzo, Carlos Marcelo

2016-05-01

Since 2009, Fundación Mundo Sano has implemented an Aedes aegypti Surveillance and Control Program in Tartagal city (Salta Province, Argentina). The purpose of this study was to analyze temporal dynamics of Ae. aegypti breeding sites spatial distribution, during five years of samplings, and the effect of control actions over vector population dynamics. Seasonal entomological (larval) samplings were conducted in 17,815 fixed sites in Tartagal urban area between 2009 and 2014. Based on information of breeding sites abundance, from satellite remote sensing data (RS), and by the use of Geographic Information Systems (GIS), spatial analysis (hotspots and cluster analysis) and predictive model (MaxEnt) were performed. Spatial analysis showed a distribution pattern with the highest breeding densities registered in city outskirts. The model indicated that 75% of Ae. aegypti distribution is explained by 3 variables: bare soil coverage percentage (44.9%), urbanization coverage percentage(13.5%) and water distribution (11.6%). This results have called attention to the way entomological field data and information from geospatial origin (RS/GIS) are used to infer scenarios which could then be applied in epidemiological surveillance programs and in the determination of dengue control strategies. Predictive maps development constructed with Ae. aegypti systematic spatiotemporal data, in Tartagal city, would allow public health workers to identify and target high-risk areas with appropriate and timely control measures. These tools could help decision-makers to improve health system responses and preventive measures related to vector control.

Temporal Dynamics and Spatial Patterns of Aedes aegypti Breeding Sites, in the Context of a Dengue Control Program in Tartagal (Salta Province, Argentina)

PubMed Central

Espinosa, Manuel; Weinberg, Diego; Rotela, Camilo H.; Polop, Francisco; Abril, Marcelo; Scavuzzo, Carlos Marcelo

2016-01-01

Background Since 2009, Fundación Mundo Sano has implemented an Aedes aegypti Surveillance and Control Program in Tartagal city (Salta Province, Argentina). The purpose of this study was to analyze temporal dynamics of Ae. aegypti breeding sites spatial distribution, during five years of samplings, and the effect of control actions over vector population dynamics. Methodology/Principal Findings Seasonal entomological (larval) samplings were conducted in 17,815 fixed sites in Tartagal urban area between 2009 and 2014. Based on information of breeding sites abundance, from satellite remote sensing data (RS), and by the use of Geographic Information Systems (GIS), spatial analysis (hotspots and cluster analysis) and predictive model (MaxEnt) were performed. Spatial analysis showed a distribution pattern with the highest breeding densities registered in city outskirts. The model indicated that 75% of Ae. aegypti distribution is explained by 3 variables: bare soil coverage percentage (44.9%), urbanization coverage percentage(13.5%) and water distribution (11.6%). Conclusions/Significance This results have called attention to the way entomological field data and information from geospatial origin (RS/GIS) are used to infer scenarios which could then be applied in epidemiological surveillance programs and in the determination of dengue control strategies. Predictive maps development constructed with Ae. aegypti systematic spatiotemporal data, in Tartagal city, would allow public health workers to identify and target high-risk areas with appropriate and timely control measures. These tools could help decision-makers to improve health system responses and preventive measures related to vector control. PMID:27223693

RISK FACTORS FOR AND SPATIAL DISTRIBUTION OF LYMPHOPROLIFERATIVE DISEASE VIRUS (LPDV) IN WILD TURKEYS (MELEAGRIS GALLOPAVO) IN NEW YORK STATE, USA.

PubMed

Alger, Katrina; Bunting, Elizabeth; Schuler, Krysten; Whipps, Christopher M

2017-07-01

Lymphoproliferative disease virus (LPDV) is an oncogenic avian retrovirus that was previously thought to exclusively infect domestic turkeys but was recently shown to be widespread in Wild Turkeys ( Meleagris gallopavo ) throughout most of the eastern US. In commercial flocks, the virus spreads between birds housed in close quarters, but there is little information about potential risk factors for infection in wild birds. Initial studies focused on distribution of LPDV nationally, but investigation of state-level data is necessary to assess potential predictors of infection and detect patterns in disease prevalence and distribution. We tested wild turkey bone marrow samples (n=2,538) obtained from hunter-harvested birds in New York State from 2012 to 2014 for LPDV infection. Statewide prevalence for those 3 yr was 55% with a 95% confidence interval (CI) of 53-57%. We evaluated a suite of demographic, anthropogenic, and land cover characteristics with logistic regression to identify potential predictors for infection based on odds ratio (OR). Age (OR=0.16, 95% CI=0.13-0.19) and sex (OR=1.3, 95% CI=1.03-1.24) were strong predictors of LPDV infection, with juveniles less likely to test positive than adults, and females more likely to test positive than males. The number of birds released during the state's 40-yr translocation program (OR=0.993, 95% CI=0.990-0.997) and the ratio of agriculture to forest cover (OR=1.13, 95% CI=1.03-1.19) were also predictive of LPDV infection. Prevalence distribution was analyzed using dual kernel density smoothing to produce a risk surface map, combined with Kulldorff's spatial scan statistic and the Anselin Local Moran's I to identify statistically significant geographic clusters of high or low prevalence. These methods revealed the prevalence of LPDV was high (>50%) throughout New York State, with regions of variation and several significant clusters. We revealed new information about the risk factors and distribution of LPDV in New York State, which may be beneficial to game bird managers and producers of organic or pasture-raised poultry.

Spatial response surface modelling in the presence of data paucity for the evaluation of potential human health risk due to the contamination of potable water resources.

PubMed

Liu, Shen; McGree, James; Hayes, John F; Goonetilleke, Ashantha

2016-10-01

Potential human health risk from waterborne diseases arising from unsatisfactory performance of on-site wastewater treatment systems is driven by landscape factors such as topography, soil characteristics, depth to water table, drainage characteristics and the presence of surface water bodies. These factors are present as random variables which are spatially distributed across a region. A methodological framework is presented that can be applied to model and evaluate the influence of various factors on waterborne disease potential. This framework is informed by spatial data and expert knowledge. For prediction at unsampled sites, interpolation methods were used to derive a spatially smoothed surface of disease potential which takes into account the uncertainty due to spatial variation at any pre-determined level of significance. This surface was constructed by accounting for the influence of multiple variables which appear to contribute to disease potential. The framework developed in this work strengthens the understanding of the characteristics of disease potential and provides predictions of this potential across a region. The study outcomes presented constitutes an innovative approach to environmental monitoring and management in the face of data paucity. Copyright © 2016 Elsevier B.V. All rights reserved.

Modelling the geographical distribution of soil-transmitted helminth infections in Bolivia.

PubMed

Chammartin, Frédérique; Scholte, Ronaldo G C; Malone, John B; Bavia, Mara E; Nieto, Prixia; Utzinger, Jürg; Vounatsou, Penelope

2013-05-25

The prevalence of infection with the three common soil-transmitted helminths (i.e. Ascaris lumbricoides, Trichuris trichiura, and hookworm) in Bolivia is among the highest in Latin America. However, the spatial distribution and burden of soil-transmitted helminthiasis are poorly documented. We analysed historical survey data using Bayesian geostatistical models to identify determinants of the distribution of soil-transmitted helminth infections, predict the geographical distribution of infection risk, and assess treatment needs and costs in the frame of preventive chemotherapy. Rigorous geostatistical variable selection identified the most important predictors of A. lumbricoides, T. trichiura, and hookworm transmission. Results show that precipitation during the wettest quarter above 400 mm favours the distribution of A. lumbricoides. Altitude has a negative effect on T. trichiura. Hookworm is sensitive to temperature during the coldest month. We estimate that 38.0%, 19.3%, and 11.4% of the Bolivian population is infected with A. lumbricoides, T. trichiura, and hookworm, respectively. Assuming independence of the three infections, 48.4% of the population is infected with any soil-transmitted helminth. Empirical-based estimates, according to treatment recommendations by the World Health Organization, suggest a total of 2.9 million annualised treatments for the control of soil-transmitted helminthiasis in Bolivia. We provide estimates of soil-transmitted helminth infections in Bolivia based on high-resolution spatial prediction and an innovative variable selection approach. However, the scarcity of the data suggests that a national survey is required for more accurate mapping that will govern spatial targeting of soil-transmitted helminthiasis control.

Partitioning the impacts of spatial and climatological rainfall variability in urban drainage modeling

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

2017-03-01

The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall input is uniformly distributed, i.e., derived from a single or very few rain gauges. When models are fed with a single uniformly distributed rainfall realization, the response of the urban drainage system to the rainfall variability remains unexplored. The goal of this study was to understand how climate variability and spatial rainfall variability, jointly or individually considered, affect the response of a calibrated hydrodynamic urban drainage model. A stochastic spatially distributed rainfall generator (STREAP - Space-Time Realizations of Areal Precipitation) was used to simulate many realizations of rainfall for a 30-year period, accounting for both climate variability and spatial rainfall variability. The generated rainfall ensemble was used as input into a calibrated hydrodynamic model (EPA SWMM - the US EPA's Storm Water Management Model) to simulate surface runoff and channel flow in a small urban catchment in the city of Lucerne, Switzerland. The variability of peak flows in response to rainfall of different return periods was evaluated at three different locations in the urban drainage network and partitioned among its sources. The main contribution to the total flow variability was found to originate from the natural climate variability (on average over 74 %). In addition, the relative contribution of the spatial rainfall variability to the total flow variability was found to increase with longer return periods. This suggests that while the use of spatially distributed rainfall data can supply valuable information for sewer network design (typically based on rainfall with return periods from 5 to 15 years), there is a more pronounced relevance when conducting flood risk assessments for larger return periods. The results show the importance of using multiple distributed rainfall realizations in urban hydrology studies to capture the total flow variability in the response of the urban drainage systems to heavy rainfall events.

Spatial study of mortality in motorcycle accidents in the State of Pernambuco, Northeastern Brazil.

PubMed

Silva, Paul Hindenburg Nobre de Vasconcelos; Lima, Maria Luiza Carvalho de; Moreira, Rafael da Silveira; Souza, Wayner Vieira de; Cabral, Amanda Priscila de Santana

2011-04-01

To analyze the spatial distribution of mortality due to motorcycle accidents in the state of Pernambuco, Northeastern Brazil. A population-based ecological study using data on mortality in motorcycle accidents from 01/01/2000 to 31/12/2005. The analysis units were the municipalities. For the spatial distribution analysis, an average mortality rate was calculated, using deaths from motorcycle accidents recorded in the Mortality Information System as the numerator, and as the denominator the population of the mid-period. Spatial analysis techniques, mortality smoothing coefficient estimate by the local empirical Bayesian method and Moran scatterplot, applied to the digital cartographic base of Pernambuco were used. The average mortality rate for motorcycle accidents in Pernambuco was 3.47 per 100 thousand inhabitants. Of the 185 municipalities, 16 were part of five clusters identified with average mortality rates ranging from 5.66 to 11.66 per 100 thousand inhabitants, and were considered critical areas. Three clusters are located in the area known as sertão and two in the agreste of the state. The risk of dying from a motorcycle accident is greater in conglomerate areas outside the metropolitan axis, and intervention measures should consider the economic, social and cultural contexts.

Design and analysis for thematic map accuracy assessment: Fundamental principles

Treesearch

Stephen V. Stehman; Raymond L. Czaplewski

1998-01-01

Land-cover maps are used in numerous natural resource applications to describe the spatial distribution and pattern of land-cover, to estimate areal extent of various cover classes, or as input into habitat suitability models, land-cover change analyses, hydrological models, and risk analyses. Accuracy assessment quantifies data quality so that map users may evaluate...

Nationwide assessment of nonpoint source threats to water quality

Treesearch

Thomas C. Brown; Pamela Froemke

2012-01-01

Water quality is a continuing national concern, in part because the containment of pollution from nonpoint (diffuse) sources remains a challenge. We examine the spatial distribution of nonpoint-source threats to water quality. On the basis of comprehensive data sets for a series of watershed stressors, the relative risk of water-quality impairment was estimated for the...

Spatial distribution and risk assessment of Johnsongrass (sorghum halepense) in Big Bend National Park, Texas

USDA-ARS?s Scientific Manuscript database

We used Landsat 7 ETM+ imagery to illustrate how remotely sensed data can model predicted Johnsongrass habitat. We used spectral reflectance values for three seasons of data across 5 years (fall 1999, summer and fall 2000, spring and fall 2001, spring 2002, and spring 2003) to capture Johnsongrass v...

Spatial estimation of the density and carbon content of host populations for Phytophthora ramorum in California and Oregon

Treesearch

Sanjay Lamsal; Richard C. Cobb; J. Hall Cushman; Qingmin Meng; David M. Rizzo; Ross K. Meentemeyer.

2011-01-01

Outbreak of the emerging infectious disease sudden oak death continues to threaten California and Oregon forests following introduction of the exotic plant pathogen Phytophthora ramorum. Identifying areas at risk and forecasting changes in forest carbon following disease outbreak requires an understanding of the geographical distribution of host...

Use of space-time models to investigate the stability of patterns of disease.

PubMed

Abellan, Juan Jose; Richardson, Sylvia; Best, Nicky

2008-08-01

The use of Bayesian hierarchical spatial models has become widespread in disease mapping and ecologic studies of health-environment associations. In this type of study, the data are typically aggregated over an extensive time period, thus neglecting the time dimension. The output of purely spatial disease mapping studies is therefore the average spatial pattern of risk over the period analyzed, but the results do not inform about, for example, whether a high average risk was sustained over time or changed over time. We investigated how including the time dimension in disease-mapping models strengthens the epidemiologic interpretation of the overall pattern of risk. We discuss a class of Bayesian hierarchical models that simultaneously characterize and estimate the stable spatial and temporal patterns as well as departures from these stable components. We show how useful rules for classifying areas as stable can be constructed based on the posterior distribution of the space-time interactions. We carry out a simulation study to investigate the sensitivity and specificity of the decision rules we propose, and we illustrate our approach in a case study of congenital anomalies in England. Our results confirm that extending hierarchical disease-mapping models to models that simultaneously consider space and time leads to a number of benefits in terms of interpretation and potential for detection of localized excesses.

Anticoagulant Rodenticides on our Public and Community Lands: Spatial Distribution of Exposure and Poisoning of a Rare Forest Carnivore

PubMed Central

Gabriel, Mourad W.; Woods, Leslie W.; Poppenga, Robert; Sweitzer, Rick A.; Thompson, Craig; Matthews, Sean M.; Higley, J. Mark; Keller, Stefan M.; Purcell, Kathryn; Barrett, Reginald H.; Wengert, Greta M.; Sacks, Benjamin N.; Clifford, Deana L.

2012-01-01

Anticoagulant rodenticide (AR) poisoning has emerged as a significant concern for conservation and management of non-target wildlife. The purpose for these toxicants is to suppress pest populations in agricultural or urban settings. The potential of direct and indirect exposures and illicit use of ARs on public and community forest lands have recently raised concern for fishers (Martes pennanti), a candidate for listing under the federal Endangered Species Act in the Pacific states. In an investigation of threats to fisher population persistence in the two isolated California populations, we investigate the magnitude of this previously undocumented threat to fishers, we tested 58 carcasses for the presence and quantification of ARs, conducted spatial analysis of exposed fishers in an effort to identify potential point sources of AR, and identified fishers that died directly due to AR poisoning. We found 46 of 58 (79%) fishers exposed to an AR with 96% of those individuals having been exposed to one or more second-generation AR compounds. No spatial clustering of AR exposure was detected and the spatial distribution of exposure suggests that AR contamination is widespread within the fisher’s range in California, which encompasses mostly public forest and park lands Additionally, we diagnosed four fisher deaths, including a lactating female, that were directly attributed to AR toxicosis and documented the first neonatal or milk transfer of an AR to an altricial fisher kit. These ARs, which some are acutely toxic, pose both a direct mortality or fitness risk to fishers, and a significant indirect risk to these isolated populations. Future research should be directed towards investigating risks to prey populations fishers are dependent on, exposure in other rare forest carnivores, and potential AR point sources such as illegal marijuana cultivation in the range of fishers on California public lands. PMID:22808110

Polycyclic aromatic hydrocarbons associated with total suspended particles and surface soils in Kunming, China: distribution, possible sources, and cancer risks.

PubMed

Yang, Xiaoxia; Ren, Dong; Sun, Wenwen; Li, Xiaoman; Huang, Bin; Chen, Rong; Lin, Chan; Pan, Xuejun

2015-05-01

The concentrations, distribution, possible sources, and cancer risks of polycyclic aromatic hydrocarbons (PAHs) in total suspended particles (TSPs) and surface soils collected from the same sampling spots were compared in Kunming, China. The total PAH concentrations were 9.35-75.01 ng/m(3) and 101.64-693.30 ng/g dry weight (d.w.), respectively, in TSPs and surface soils. Fluoranthene (FLA), pyrene (PYR), chrysene (CHR), and phenanthrene (PHE) were the abundant compounds in TSP samples, and phenanthrene (PHE), fluorene (FLO), fluoranthene (FLA), benzo[b]fluoranthene (BbF), and benzo[g,h,i]perylene (BghiP) were the abundant compounds in surface soil samples. The spatial distribution of PAHs in TSPs is closely related to the surrounding environment, which varied significantly as a result of variations in source emission and changes in meteorology. However, the spatial distribution of PAHs in surface soils is supposed to correlate with a city's urbanization history, and high levels of PAHs were always observed in industry district, or central or old district of city. Based on the diagnostic ratios and principal component analysis (PCA), vehicle emissions (especially diesel-powered vehicles) and coal and wood combustion were the main sources of PAHs in TSPs, and the combustion of wood and coal, and spills of unburnt petroleum were the main sources of PAHs in the surface soils. The benzo[a]pyrene equivalent concentration (BaPeq) for the TSPs and surface soil samples were 0.16-2.57 ng/m(3) and 11.44-116.03 ng/g d.w., respectively. The incremental lifetime cancer risk (ILCR) exposed to particulate PAHs ranged from 10(-4) to 10(-3) indicating high potential of carcinogenic risk, and the ILCR exposed to soil PAHs was from 10(-7) to 10(-6) indicating virtual safety. These presented results showed that particle-bound PAHs had higher potential carcinogenic ability for human than soil PAHs. And, the values of cancer risk for children were always higher than for adults, which demonstrated that children were sensitive to carcinogenic effects of PAHs.

The Estrada Real project and endemic diseases: the case of schistosomiasis, geoprocessing and tourism.

PubMed

Carvalho, Omar S; Scholte, Ronaldo G C; Guimarães, Ricardo J P S; Freitas, Corina C; Drummond, Sandra C; Amaral, Ronaldo S; Dutra, Luciano V; Oliveira, Guilherme; Massara, Cristiano L; Enk, Martin J

2010-07-01

Geographical Information System (GIS) is a tool that has recently been applied to better understand spatial disease distributions. Using meteorological, social, sanitation, mollusc distribution data and remote sensing variables, this study aimed to further develop the GIS technology by creating a model for the spatial distribution of schistosomiasis and to apply this model to an area with rural tourism in the Brazilian state of Minas Gerais (MG). The Estrada Real, covering about 1,400 km, is the largest and most important Brazilian tourism project, involving 163 cities in MG with different schistosomiasis prevalence rates. The model with three variables showed a R(2) = 0.34, with a standard deviation of risk estimated adequate for public health needs. The main variables selected for modelling were summer vegetation, summer minimal temperature and winter minimal temperature. The results confirmed the importance of Remote Sensing data and the valuable contribution of GIS in identifying priority areas for intervention in tourism regions which are endemic to schistosomiasis.

Developing a Hierarchical Model for the Spatial Analysis of PM10 Pollution Extremes in the Mexico City Metropolitan Area.

PubMed

Aguirre-Salado, Alejandro Ivan; Vaquera-Huerta, Humberto; Aguirre-Salado, Carlos Arturo; Reyes-Mora, Silvia; Olvera-Cervantes, Ana Delia; Lancho-Romero, Guillermo Arturo; Soubervielle-Montalvo, Carlos

2017-07-06

We implemented a spatial model for analysing PM 10 maxima across the Mexico City metropolitan area during the period 1995-2016. We assumed that these maxima follow a non-identical generalized extreme value (GEV) distribution and modeled the trend by introducing multivariate smoothing spline functions into the probability GEV distribution. A flexible, three-stage hierarchical Bayesian approach was developed to analyse the distribution of the PM 10 maxima in space and time. We evaluated the statistical model's performance by using a simulation study. The results showed strong evidence of a positive correlation between the PM 10 maxima and the longitude and latitude. The relationship between time and the PM 10 maxima was negative, indicating a decreasing trend over time. Finally, a high risk of PM 10 maxima presenting levels above 1000 μ g/m 3 (return period: 25 yr) was observed in the northwestern region of the study area.

Developing a Hierarchical Model for the Spatial Analysis of PM10 Pollution Extremes in the Mexico City Metropolitan Area

PubMed Central

Aguirre-Salado, Alejandro Ivan; Vaquera-Huerta, Humberto; Aguirre-Salado, Carlos Arturo; Reyes-Mora, Silvia; Olvera-Cervantes, Ana Delia; Lancho-Romero, Guillermo Arturo; Soubervielle-Montalvo, Carlos

2017-01-01

We implemented a spatial model for analysing PM10 maxima across the Mexico City metropolitan area during the period 1995–2016. We assumed that these maxima follow a non-identical generalized extreme value (GEV) distribution and modeled the trend by introducing multivariate smoothing spline functions into the probability GEV distribution. A flexible, three-stage hierarchical Bayesian approach was developed to analyse the distribution of the PM10 maxima in space and time. We evaluated the statistical model’s performance by using a simulation study. The results showed strong evidence of a positive correlation between the PM10 maxima and the longitude and latitude. The relationship between time and the PM10 maxima was negative, indicating a decreasing trend over time. Finally, a high risk of PM10 maxima presenting levels above 1000 μg/m3 (return period: 25 yr) was observed in the northwestern region of the study area. PMID:28684720

Determinants of the geographical distribution of endemic giardiasis in Ontario, Canada: a spatial modelling approach.

PubMed

Odoi, A; Martin, S W; Michel, P; Holt, J; Middleton, D; Wilson, J

2004-10-01

Giardiasis surveillance data as well as drinking water, socioeconomic and land-use data were used in spatial regression models to investigate determinants of the geographic distribution of endemic giardiasis in southern Ontario. Higher giardiasis rates were observed in areas using surface water [rate ratio (RR) 2.36, 95 % CI 1.38-4.05] and in rural areas (RR 1.79, 95 % CI 1.32-2.37). Lower rates were observed in areas using filtered water (RR 0.55, 95 % CI 0.42-0.94) and in those with high median income (RR 0.62, 95 % CI 0.42-0.92). Chlorination of drinking water, cattle density and intensity of manure application on farmland were not significant determinants. The study shows that waterborne transmission plays an important role in giardiasis distribution in southern Ontario and that well-collected routine surveillance data could be useful for investigation of disease determinants and identification of high-risk communities. This information is useful in guiding decisions on control strategies.

How selection structures species abundance distributions

PubMed Central

Magurran, Anne E.; Henderson, Peter A.

2012-01-01

How do species divide resources to produce the characteristic species abundance distributions seen in nature? One way to resolve this problem is to examine how the biomass (or capacity) of the spatial guilds that combine to produce an abundance distribution is allocated among species. Here we argue that selection on body size varies across guilds occupying spatially distinct habitats. Using an exceptionally well-characterized estuarine fish community, we show that biomass is concentrated in large bodied species in guilds where habitat structure provides protection from predators, but not in those guilds associated with open habitats and where safety in numbers is a mechanism for reducing predation risk. We further demonstrate that while there is temporal turnover in the abundances and identities of species that comprise these guilds, guild rank order is conserved across our 30-year time series. These results demonstrate that ecological communities are not randomly assembled but can be decomposed into guilds where capacity is predictably allocated among species. PMID:22787020

Statistical analysis of content of Cs-137 in soils in Bansko-Razlog region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kobilarov, R. G., E-mail: rkobi@tu-sofia.bg

Statistical analysis of the data set consisting of the activity concentrations of {sup 137}Cs in soils in Bansko–Razlog region is carried out in order to establish the dependence of the deposition and the migration of {sup 137}Cs on the soil type. The descriptive statistics and the test of normality show that the data set have not normal distribution. Positively skewed distribution and possible outlying values of the activity of {sup 137}Cs in soils were observed. After reduction of the effects of outliers, the data set is divided into two parts, depending on the soil type. Test of normality of themore » two new data sets shows that they have a normal distribution. Ordinary kriging technique is used to characterize the spatial distribution of the activity of {sup 137}Cs over an area covering 40 km{sup 2} (whole Razlog valley). The result (a map of the spatial distribution of the activity concentration of {sup 137}Cs) can be used as a reference point for future studies on the assessment of radiological risk to the population and the erosion of soils in the study area.« less

Geochemical background and ecological risk of heavy metals in surface sediments from the west Zhoushan Fishing Ground of East China Sea.

PubMed

Xu, Gang; Liu, Jian; Pei, Shaofeng; Hu, Gang; Kong, Xianghuai

2015-12-01

Surface sediment grain size as well as the spatial distribution, pollution status, and source identification of heavy metals in the west Zhoushan Fishing Ground (ZFG) of the East China Sea were analyzed to study the geochemical background concentrations of heavy metals and to assess their potential ecological risk. Our results show that surface sediments in the eastern part of study area were mainly composed of sand-sized components. Spatial distributions of heavy metals were mainly controlled by grain size and terrigenous materials, and their concentrations in the coarsest grain sediments formed primarily during the Holocene transgressive period could represent the element background values of our study area. Contamination factor suggests that there was no pollution of Pb, Zn, and Cr generally in our study area and slight pollution of Cu, Cd, and As (especially Cu) at some stations. In addition, ecological harm coefficient indicates that the ecological risk of each heavy metal, except for Cd, at two stations was low as well. These results are consistent with the pollution load index and ecological risk index, which suggest both the overall level of pollution and the overall ecological risk of six studied metals in sediment were relatively low in our study area. Enrichment factor indicates that the heavy metals came mostly from the natural source. Summarily, the quality level of sediment in our study area was relatively good, and heavy metals in sediments could not exert threat to aquatic lives in the ZFG until now.

Spatial distribution and ecological risk assessment of phthalic acid esters and phenols in surface sediment from urban rivers in Northeast China.

PubMed

Li, Bin; Liu, Ruixia; Gao, Hongjie; Tan, Ruijie; Zeng, Ping; Song, Yonghui

2016-12-01

Concentration and spatial distribution of six phthalic acid esters (PAEs) and eight phenols in sediments of urban rivers, namely the Xi River (XR) and Pu River (PR) in Shenyang city, Northeast China were investigated and the ecological risk of these target pollutants was assessed based on the risk quotient (RQ) approach. Target PAEs and phenols were detected in most of sediment samples collected from the XR and PR. The concentrations of total PAEs in sediments varied from 22.4 to 369 μg/g dw in the XR and 3.71-46.9 μg/g dw in the PR. The levels of phenols ranged from 2.72 to 106 μg/g dw in the XR and 0.811-25.0 μg/g dw in the PR, respectively. The dominant pollutants in both XR and PR were DEHP, phenol and 4-methylphnol. The sampling locations XR1-3 in the XR suffered severe contamination from PAEs and phenols. The sites PR1 and PR6 were heavily polluted by phenols and PAEs, respectively. Almost all target PAEs and phenolic compounds in sediment of the XR exhibited medium or high ecological risk to organisms and the ecological risk in the PR mainly originated from PEAs, phenol and 4-methylphenol. These results would provide guidance for individual pollutant control and indicate that it is imperative to take some effective measures to reduce the pollution of those contaminants. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatial distribution of traffic induced noise exposures in a US city: an analytic tool for assessing the health impacts of urban planning decisions

PubMed Central

Seto, Edmund Yet Wah; Holt, Ashley; Rivard, Tom; Bhatia, Rajiv

2007-01-01

Background: Vehicle traffic is the major source of noise in urban environments, which in turn has multiple impacts on health. In this paper we investigate the spatial distribution of community noise exposures and annoyance. Traffic data from the City of San Francisco were used to model noise exposure by neighborhood and road type. Remote sensing data were used in the model to estimate neighborhood-specific percentages of cars, trucks, and buses on arterial versus non-arterial streets. The model was validated on 235 streets. Finally, an exposure-response relationship was used to predict the prevalence of high annoyance for different neighborhoods. Results: Urban noise was found to increase 6.7 dB (p < 0.001) with 10-fold increased street traffic, with important contributors to noise being bus and heavy truck traffic. Living along arterial streets also increased risk of annoyance by 40%. The relative risk of annoyance in one of the City's fastest growing neighborhoods, the South of Market Area, was found to be 2.1 times that of lowest noise neighborhood. However, higher densities of exposed individuals were found in Chinatown and Downtown/Civic Center. Overall, we estimated that 17% of the city's population was at risk of high annoyance from traffic noise. Conclusion: The risk of annoyance from urban noise is large, and varies considerably between neighborhoods. Such risk should be considered in urban areas undergoing rapid growth. We present a relatively simple GIS-based noise model that may be used for routinely evaluating the health impacts of environmental noise. PMID:17584947

Novel microbiological and spatial statistical methods to improve strength of epidemiological evidence in a community-wide waterborne outbreak.

PubMed

Jalava, Katri; Rintala, Hanna; Ollgren, Jukka; Maunula, Leena; Gomez-Alvarez, Vicente; Revez, Joana; Palander, Marja; Antikainen, Jenni; Kauppinen, Ari; Räsänen, Pia; Siponen, Sallamaari; Nyholm, Outi; Kyyhkynen, Aino; Hakkarainen, Sirpa; Merentie, Juhani; Pärnänen, Martti; Loginov, Raisa; Ryu, Hodon; Kuusi, Markku; Siitonen, Anja; Miettinen, Ilkka; Santo Domingo, Jorge W; Hänninen, Marja-Liisa; Pitkänen, Tarja

2014-01-01

Failures in the drinking water distribution system cause gastrointestinal outbreaks with multiple pathogens. A water distribution pipe breakage caused a community-wide waterborne outbreak in Vuorela, Finland, July 2012. We investigated this outbreak with advanced epidemiological and microbiological methods. A total of 473/2931 inhabitants (16%) responded to a web-based questionnaire. Water and patient samples were subjected to analysis of multiple microbial targets, molecular typing and microbial community analysis. Spatial analysis on the water distribution network was done and we applied a spatial logistic regression model. The course of the illness was mild. Drinking untreated tap water from the defined outbreak area was significantly associated with illness (RR 5.6, 95% CI 1.9-16.4) increasing in a dose response manner. The closer a person lived to the water distribution breakage point, the higher the risk of becoming ill. Sapovirus, enterovirus, single Campylobacter jejuni and EHEC O157:H7 findings as well as virulence genes for EPEC, EAEC and EHEC pathogroups were detected by molecular or culture methods from the faecal samples of the patients. EPEC, EAEC and EHEC virulence genes and faecal indicator bacteria were also detected in water samples. Microbial community sequencing of contaminated tap water revealed abundance of Arcobacter species. The polyphasic approach improved the understanding of the source of the infections, and aided to define the extent and magnitude of this outbreak.

The assessment of spatial distribution of soil salinity risk using neural network.

PubMed

Akramkhanov, Akmal; Vlek, Paul L G

2012-04-01

Soil salinity in the Aral Sea Basin is one of the major limiting factors of sustainable crop production. Leaching of the salts before planting season is usually a prerequisite for crop establishment and predetermined water amounts are applied uniformly to fields often without discerning salinity levels. The use of predetermined water amounts for leaching perhaps partly emanate from the inability of conventional soil salinity surveys (based on collection of soil samples, laboratory analyses) to generate timely and high-resolution salinity maps. This paper has an objective to estimate the spatial distribution of soil salinity based on readily or cheaply obtainable environmental parameters (terrain indices, remote sensing data, distance to drains, and long-term groundwater observation data) using a neural network model. The farm-scale (∼15 km(2)) results were used to upscale soil salinity to a district area (∼300 km(2)). The use of environmental attributes and soil salinity relationships to upscale the spatial distribution of soil salinity from farm to district scale resulted in the estimation of essentially similar average soil salinity values (estimated 0.94 vs. 1.04 dS m(-1)). Visual comparison of the maps suggests that the estimated map had soil salinity that was uniform in distribution. The upscaling proved to be satisfactory; depending on critical salinity threshold values, around 70-90% of locations were correctly estimated.

Landscape heterogeneity shapes predation in a newly restored predator-prey system.

PubMed

Kauffman, Matthew J; Varley, Nathan; Smith, Douglas W; Stahler, Daniel R; MacNulty, Daniel R; Boyce, Mark S

2007-08-01

Because some native ungulates have lived without top predators for generations, it has been uncertain whether runaway predation would occur when predators are newly restored to these systems. We show that landscape features and vegetation, which influence predator detection and capture of prey, shape large-scale patterns of predation in a newly restored predator-prey system. We analysed the spatial distribution of wolf (Canis lupus) predation on elk (Cervus elaphus) on the Northern Range of Yellowstone National Park over 10 consecutive winters. The influence of wolf distribution on kill sites diminished over the course of this study, a result that was likely caused by territorial constraints on wolf distribution. In contrast, landscape factors strongly influenced kill sites, creating distinct hunting grounds and prey refugia. Elk in this newly restored predator-prey system should be able to mediate their risk of predation by movement and habitat selection across a heterogeneous risk landscape.

Landscape heterogeneity shapes predation in a newly restored predator-prey system

USGS Publications Warehouse

Kauffman, M.J.; Varley, N.; Smith, D.W.; Stahler, D.R.; MacNulty, D.R.; Boyce, M.S.

2007-01-01

Because some native ungulates have lived without top predators for generations, it has been uncertain whether runaway predation would occur when predators are newly restored to these systems. We show that landscape features and vegetation, which influence predator detection and capture of prey, shape large-scale patterns of predation in a newly restored predator-prey system. We analysed the spatial distribution of wolf (Canis lupus) predation on elk (Cervus elaphus) on the Northern Range of Yellowstone National Park over 10 consecutive winters. The influence of wolf distribution on kill sites diminished over the course of this study, a result that was likely caused by territorial constraints on wolf distribution. In contrast, landscape factors strongly influenced kill sites, creating distinct hunting grounds and prey refugia. Elk in this newly restored predator-prey system should be able to mediate their risk of predation by movement and habitat selection across a heterogeneous risk landscape. ?? 2007 Blackwell Publishing Ltd/CNRS.

Sparse modeling of spatial environmental variables associated with asthma

PubMed Central

Chang, Timothy S.; Gangnon, Ronald E.; Page, C. David; Buckingham, William R.; Tandias, Aman; Cowan, Kelly J.; Tomasallo, Carrie D.; Arndt, Brian G.; Hanrahan, Lawrence P.; Guilbert, Theresa W.

2014-01-01

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin’s Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5–50 years over a three-year period. Each patient’s home address was geocoded to one of 3,456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin’s geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. PMID:25533437

Sparse modeling of spatial environmental variables associated with asthma.

PubMed

Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W

2015-02-01

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.

Stability of Spatial Distributions of Stink Bugs, Boll Injury, and NDVI in Cotton.

PubMed

Reay-Jones, Francis P F; Greene, Jeremy K; Bauer, Philip J

2016-10-01

A 3-yr study was conducted to determine the degree of aggregation of stink bugs and boll injury in cotton, Gossypium hirsutum L., and their spatial association with a multispectral vegetation index (normalized difference vegetation index [NDVI]). Using the spatial analysis by distance indices analyses, stink bugs were less frequently aggregated (17% for adults and 4% for nymphs) than boll injury (36%). NDVI values were also significantly aggregated within fields in 19 of 48 analyses (40%), with the majority of significant indices occurring in July and August. Paired NDVI datasets from different sampling dates were frequently associated (86.5% for weekly intervals among datasets). Spatial distributions of both stink bugs and boll injury were less stable than for NDVI, with positive associations varying from 12.5 to 25% for adult stink bugs for weekly intervals, depending on species. Spatial distributions of boll injury from stink bug feeding were more stable than stink bugs, with 46% positive associations among paired datasets with weekly intervals. NDVI values were positively associated with boll injury from stink bug feeding in 11 out of 22 analyses, with no significant negative associations. This indicates that NDVI has potential as a component of site-specific management. Future work should continue to examine the value of remote sensing for insect management in cotton, with an aim to develop tools such as risk assessment maps that will help growers to reduce insecticide inputs. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

[Spatial distribution and potential ecological risk assessment of heavy metals in sediments of Yalu River estuary wetland mudflat.

PubMed

Zhang, Chun Peng; Li, Fu Xiang

2016-09-01

Kriging interpolation analysis was conducted with ArcGIS to find out the distribution characteristics of heavy metals concentrations in the surface sediments of the coastal wetland mudflat on the Yalu River estuary, environmental risk index and Hakanson potential ecological risk index were used to assess their extents of pollution in this area.The concentrations of heavy metals in the surface sediments of the study area were at a relatively high level compared with the typical estuarine wetland. The concentration of heavy metals in the east was higher than that in the west, and in the human activity area, the concentration was higher. Cu was found to contribute the most to the pollution status based on environmental risk index method, while Hg and Cd produced the greatest potential ecological harm according to Hankanson Potential ecological risk index method. The average potential ecological risk index (RI) of the Yalu River estuary wetland was 189.30 (ranged from 93.65-507.20), suggesting a moderate ecological risk. However, the potential ecological risk was highest in the east and should be treated as the major heavy metal pollution prevention area in the future.

Antibiotics in the agricultural soils from the Yangtze River Delta, China.

PubMed

Sun, Jianteng; Zeng, Qingtao; Tsang, Daniel C W; Zhu, L Z; Li, X D

2017-12-01

This study focused on the occurrence and spatial distribution of 13 common antibiotics in the agricultural soils of the Yangtze River Delta (YRD), China. Antibiotics were detected in all the 241 soil samples (i.e., 100% detection rate) with the total concentrations ranging from 4.55 to 2,010 ng/g dry weight. The concentrations of three antibiotic classes decreased in the order: quinolones (mean 48.8 ng/g) > tetracyclines (mean 34.9 ng/g) > sulfonamides (mean 2.35 ng/g). Ciprofloxacin was the prevalent compound with a mean concentration of 27.7 ng/g, followed by oxytetracycline (mean of 18.9 ng/g). A distinct spatial distribution was observed, where high concentrations of antibiotics were detected in the sites adjacent to the livestock and poultry farms. The potential sources of antibiotics in the agricultural soils were the application of manure and wastewater irrigation in this region. Risk assessment for single antibiotic compound indicated that tetracyclines and quinolones could pose a potential risk, in which doxycycline and ciprofloxacin had the most severe ecological effect in the agricultural soils. Antibiotic resistance genes (ARGs), such as tetA, sulI, and qnrS, were detected in 15 analyzed soil samples, and sulI showed significant correlations with quinolones, tetracyclines, copper, and zinc. Further studies on the distribution of other ARGs in agricultural soil at a region-scale are needed for the risk management of extensively used antibiotics and major ARGs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Use of Sentinel Surveillance and Geographic Information Systems to Monitor Trends in HIV Prevalence, Incidence, and Related Risk Behavior among Women Undergoing Syphilis Screening in a Jail Setting

PubMed Central

Kim, Andrea A.; Klausner, Jeffrey D.; Goldenson, Joe; Kent, Charlotte; Liska, Sally; McFarland, Willi

2008-01-01

Innovative methods are needed to systematically track the HIV epidemic and appropriately target prevention and care programs in vulnerable populations of women. We conducted sentinel surveillance among women entering the jail system of San Francisco from 1999 to 2001 to track trends in HIV incidence, HIV prevalence, and related risk behavior. Using geographic information software (GIS), we triangulated findings to examine the spatial distribution of risk and disease. A total of 1,577 female arrestees voluntarily screened for sexually transmitted diseases at intake were included. HIV incidence, estimated using the serologic testing algorithm for recent HIV seroconversion (STARHS), was 0.4% per year (95% confidence interval [95%CI] = 0.1–2.1). HIV prevalence was 1.8% (95%CI = 1.1–2.4). HIV infection was independently associated with age 30 to 39 years compared to all other ages, African-American race/ethnicity vs. non-African-American, and recent injection drug use. Maps showed that the communities in which arrested women reside are also those with the highest concentrations of newly detected female HIV cases, AIDS cases, and clients of substance use programs. The combined strategy of using sentinel surveillance in the jail setting and GIS to map the spatial distribution of disease provides a useful tool to identify patterns of risk in hard-to-reach, vulnerable populations of women. PMID:18785013

[GIS Spatial Distribution and Ecological Risk Assessment of Heavy Metals in Surface Sediments of Shallow Lakes in Jiangsu Province].

PubMed

Li, Ying-jie; Zhang, Lie-yu; Wu, Yi-wen; Li, Cao-le; Yang, Tian-xue; Tang, Jun

2016-04-15

To understand pollution of heavy metals in surface sediments of shallow lakes, surface sediments samples of 11 lakes in Jiangsu province were collected to determine the content of six heavy metals including As, Cr, Cu, Pb, Zn and Ni. GIS was used to analyze the spatial distribution of heavy metals, and geological accumulation index (Igeo), modified contamination index (mCd) pollution load index (PLI) and potential ecological risk index (RI) were used to evaluate heavy metal contamination in the sediments. The results showed that: in the lakes' surface sediments, the average content of As, Cu, Zn, Cr, Pb, Ni in multiples of soil background of Jiangsu province were 1.74-3.85, 0.65-2.66, 0.48-3.56, 0.43-1.52, 0.02-1.49 and 0.12-1.42. According to the evaluation results of Igeo and RI, As, which had high degree of enrichment and great potential ecological risk, was the main pollutant, followed by Cu, and pollution of the rest of heavy metals was relatively light. Combining the results of several evaluation methods, in surface sediments of Sanjiu Lake, Gaoyou Lake and Shaobo Lake, these heavy metals had the most serious pollution, the maximum pollution loading and moderate potential ecological risk; in surface sediments of Gehu Lake, Baima Lake and Hongze Lake, some regions were polluted by certain metals, the overall trend of pollution was aggravating, the pollution loading was large, and the potential ecological risk reached moderate; in the other 5 lakes, the risk of sediments polluted by heavy metals, as well as the pollution loading, was small, and the overall was not polluted.

Climate Risk and Vulnerability in the Caribbean and Gulf of Mexico Region: Interactions with Spatial Population and Land Cover Change

NASA Astrophysics Data System (ADS)

Chen, R. S.; Levy, M.; Baptista, S.; Adamo, S.

2010-12-01

Vulnerability to climate variability and change will depend on dynamic interactions between different aspects of climate, land-use change, and socioeconomic trends. Measurements and projections of these changes are difficult at the local scale but necessary for effective planning. New data sources and methods make it possible to assess land-use and socioeconomic changes that may affect future patterns of climate vulnerability. In this paper we report on new time series data sets that reveal trends in the spatial patterns of climate vulnerability in the Caribbean/Gulf of Mexico Region. Specifically, we examine spatial time series data for human population over the period 1990-2000, time series data on land use and land cover over 2000-2009, and infant mortality rates as a proxy for poverty for 2000-2008. We compare the spatial trends for these measures to the distribution of climate-related natural disaster risk hotspots (cyclones, floods, landslides, and droughts) in terms of frequency, mortality, and economic losses. We use these data to identify areas where climate vulnerability appears to be increasing and where it may be decreasing. Regions where trends and patterns are especially worrisome include coastal areas of Guatemala and Honduras.

Spatial analysis of alcohol-related motor vehicle crash injuries in southeastern Michigan.

PubMed

Meliker, Jaymie R; Maio, Ronald F; Zimmerman, Marc A; Kim, Hyungjin Myra; Smith, Sarah C; Wilson, Mark L

2004-11-01

Temporal, behavioral and social risk factors that affect injuries resulting from alcohol-related motor vehicle crashes have been characterized in previous research. Much less is known about spatial patterns and environmental associations of alcohol-related motor vehicle crashes. The aim of this study was to evaluate geographic patterns of alcohol-related motor vehicle crashes and to determine if locations of alcohol outlets are associated with those crashes. In addition, we sought to demonstrate the value of integrating spatial and traditional statistical techniques in the analysis of this preventable public health risk. The study design was a cross-sectional analysis of individual-level blood alcohol content, traffic report information, census block group data, and alcohol distribution outlets. Besag and Newell's spatial analysis and traditional logistic regression both indicated that areas of low population density had more alcohol-related motor vehicle crashes than expected (P < 0.05). There was no significant association between alcohol outlets and alcohol-related motor vehicle crashes using distance analyses, logistic regression, and Chi-square. Differences in environmental or behavioral factors characteristic of areas of low population density may be responsible for the higher proportion of alcohol-related crashes occurring in these areas.

Spatial distribution of single-nucleotide polymorphisms related to fungicide resistance and implications for sampling.

PubMed

Van der Heyden, H; Dutilleul, P; Brodeur, L; Carisse, O

2014-06-01

Spatial distribution of single-nucleotide polymorphisms (SNPs) related to fungicide resistance was studied for Botrytis cinerea populations in vineyards and for B. squamosa populations in onion fields. Heterogeneity in this distribution was characterized by performing geostatistical analyses based on semivariograms and through the fitting of discrete probability distributions. Two SNPs known to be responsible for boscalid resistance (H272R and H272Y), both located on the B subunit of the succinate dehydrogenase gene, and one SNP known to be responsible for dicarboximide resistance (I365S) were chosen for B. cinerea in grape. For B. squamosa in onion, one SNP responsible for dicarboximide resistance (I365S homologous) was chosen. One onion field was sampled in 2009 and another one was sampled in 2010 for B. squamosa, and two vineyards were sampled in 2011 for B. cinerea, for a total of four sampled sites. Cluster sampling was carried on a 10-by-10 grid, each of the 100 nodes being the center of a 10-by-10-m quadrat. In each quadrat, 10 samples were collected and analyzed by restriction fragment length polymorphism polymerase chain reaction (PCR) or allele specific PCR. Mean SNP incidence varied from 16 to 68%, with an overall mean incidence of 43%. In the geostatistical analyses, omnidirectional variograms showed spatial autocorrelation characterized by ranges of 21 to 1 m. Various levels of anisotropy were detected, however, with variograms computed in four directions (at 0°, 45°, 90°, and 135° from the within-row direction used as reference), indicating that spatial autocorrelation was prevalent or characterized by a longer range in one direction. For all eight data sets, the β-binomial distribution was found to fit the data better than the binomial distribution. This indicates local aggregation of fungicide resistance among sampling units, as supported by estimates of the parameter θ of the β-binomial distribution of 0.09 to 0.23 (overall median value = 0.20). On the basis of the observed spatial distribution patterns of SNP incidence, sampling curves were computed for different levels of reliability, emphasizing the importance of sample size for the detection of mutation incidence below the risk threshold for control failure.

Making Energy-Water Nexus Scenarios more Fit-for-Purpose through Better Characterization of Extremes

NASA Astrophysics Data System (ADS)

Yetman, G.; Levy, M. A.; Chen, R. S.; Schnarr, E.

2017-12-01

Often quantitative scenarios of future trends exhibit less variability than the historic data upon which the models that generate them are based. The problem of dampened variability, which typically also entails dampened extremes, manifests both temporally and spatially. As a result, risk assessments that rely on such scenarios are in danger of producing misleading results. This danger is pronounced in nexus issues, because of the multiple dimensions of change that are relevant. We illustrate the above problem by developing alternative joint distributions of the probability of drought and of human population totals, across U.S. counties over the period 2010-2030. For the dampened-extremes case we use drought frequencies derived from climate models used in the U.S. National Climate Assessment and the Environmental Protection Agency's population and land use projections contained in its Integrated Climate and Land Use Scenarios (ICLUS). For the elevated extremes case we use an alternative spatial drought frequency estimate based on tree-ring data, covering a 555-year period (Ho et al 2017); and we introduce greater temporal and spatial extremes in the ICLUS socioeconomic projections so that they conform to observed extremes in the historical U.S. spatial census data 1790-present (National Historical Geographic Information System). We use spatial and temporal coincidence of high population and extreme drought as a proxy for energy-water nexus risk. We compare the representation of risk in the dampened-extreme and elevated-extreme scenario analysis. We identify areas of the country where using more realistic portrayals of extremes makes the biggest difference in estimate risk and suggest implications for future risk assessments. References: Michelle Ho, Upmanu Lall, Xun Sun, Edward R. Cook. 2017. Multiscale temporal variability and regional patterns in 555 years of conterminous U.S. streamflow. Water Resources Research. . doi: 10.1002/2016WR019632

Neural Processing of Facial Identity and Emotion in Infants at High-Risk for Autism Spectrum Disorders

PubMed Central

Fox, Sharon E.; Wagner, Jennifer B.; Shrock, Christine L.; Tager-Flusberg, Helen; Nelson, Charles A.

2013-01-01

Deficits in face processing and social impairment are core characteristics of autism spectrum disorder. The present work examined 7-month-old infants at high-risk for developing autism and typically developing controls at low-risk, using a face perception task designed to differentiate between the effects of face identity and facial emotions on neural response using functional Near-Infrared Spectroscopy. In addition, we employed independent component analysis, as well as a novel method of condition-related component selection and classification to identify group differences in hemodynamic waveforms and response distributions associated with face and emotion processing. The results indicate similarities of waveforms, but differences in the magnitude, spatial distribution, and timing of responses between groups. These early differences in local cortical regions and the hemodynamic response may, in turn, contribute to differences in patterns of functional connectivity. PMID:23576966

Concise biomarker for spatial-temporal change in three-dimensional ultrasound measurement of carotid vessel wall and plaque thickness based on a graph-based random walk framework: Towards sensitive evaluation of response to therapy.

PubMed

Chiu, Bernard; Chen, Weifu; Cheng, Jieyu

2016-12-01

Rapid progression in total plaque area and volume measured from ultrasound images has been shown to be associated with an elevated risk of cardiovascular events. Since atherosclerosis is focal and predominantly occurring at the bifurcation, biomarkers that are able to quantify the spatial distribution of vessel-wall-plus-plaque thickness (VWT) change may allow for more sensitive detection of treatment effect. The goal of this paper is to develop simple and sensitive biomarkers to quantify the responsiveness to therapies based on the spatial distribution of VWT-Change on the entire 2D carotid standardized map previously described. Point-wise VWT-Changes computed for each patient were reordered lexicographically to a high-dimensional data node in a graph. A graph-based random walk framework was applied with the novel Weighted Cosine (WCos) similarity function introduced, which was tailored for quantification of responsiveness to therapy. The converging probability of each data node to the VWT regression template in the random walk process served as a scalar descriptor for VWT responsiveness to treatment. The WCos-based biomarker was 14 times more sensitive than the mean VWT-Change in discriminating responsive and unresponsive subjects based on the p-values obtained in T-tests. The proposed framework was extended to quantify where VWT-Change occurred by including multiple VWT-Change distribution templates representing focal changes at different regions. Experimental results show that the framework was effective in classifying carotid arteries with focal VWT-Change at different locations and may facilitate future investigations to correlate risk of cardiovascular events with the location where focal VWT-Change occurs. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatial and temporal distribution of polycyclic aromatic hydrocarbons (PAHs) in surface water from Liaohe River Basin, northeast China.

PubMed

Lv, Jiapei; Xu, Jian; Guo, Changsheng; Zhang, Yuan; Bai, Yangwei; Meng, Wei

2014-01-01

Liaohe River Basin is an important region in northeast China, which consists of several main rivers including Liao River, Taizi river, Daliao River, and Hun River. As a highly industrialized region, the basin receives dense waste discharges, causing severe environmental problems. In this study, the spatial and temporal distribution of aqueous polycyclic aromatic hydrocarbons (PAHs) in Liaohe River Basin from 50 sampling sites in both dry (May) and level (October) periods in 2012 was investigated. Sixteen USEPA priority PAHs were quantified by gas chromatography/mass selective detector. The total PAH concentration ranged from 111.8 to 2,931.6 ng/L in the dry period and from 94.8 to 2766.0 ng/L in the level period, respectively. As for the spatial distribution, the mean concentration of PAHs followed the order of Taizi River > Daliao River > Hun River > Liao River, showing higher concentrations close to large cities with dense industries. The composition and possible sources of PAHs in the water samples were also determined. The fractions of low molecular weight PAHs ranged from 58.2 to 93.3 %, indicating the influence of low or moderate temperature combustion process. Diagnostic ratios, principal component analysis, and hierarchical cluster analysis were used to study the possible source categories in the study area, and consistent results were obtained from different techniques, that PAHs in water samples mainly originated from complex sources, i.e., both pyrogenic and petrogenic sources. The benzo[a]pyrene equivalents (EBaP) characterizing the ecological risk of PAHs to the aquatic environment suggested that PAHs in Liaohe River Basin had already caused environmental health risks.

Mapping the spatio-temporal risk of lead exposure in apex species for more effective mitigation

PubMed Central

Mateo-Tomás, Patricia; Olea, Pedro P.; Jiménez-Moreno, María; Camarero, Pablo R.; Sánchez-Barbudo, Inés S.; Rodríguez Martín-Doimeadios, Rosa C.; Mateo, Rafael

2016-01-01

Effective mitigation of the risks posed by environmental contaminants for ecosystem integrity and human health requires knowing their sources and spatio-temporal distribution. We analysed the exposure to lead (Pb) in griffon vulture Gyps fulvus—an apex species valuable as biomonitoring sentinel. We determined vultures' lead exposure and its main sources by combining isotope signatures and modelling analyses of 691 bird blood samples collected over 5 years. We made yearlong spatially explicit predictions of the species risk of lead exposure. Our results highlight elevated lead exposure of griffon vultures (i.e. 44.9% of the studied population, approximately 15% of the European, showed lead blood levels more than 200 ng ml−1) partly owing to environmental lead (e.g. geological sources). These exposures to environmental lead of geological sources increased in those vultures exposed to point sources (e.g. lead-based ammunition). These spatial models and pollutant risk maps are powerful tools that identify areas of wildlife exposure to potentially harmful sources of lead that could affect ecosystem and human health. PMID:27466455

Geospatial assessment of ecological functions and flood-related risks on floodplains along major rivers in the Puget Sound Basin, Washington

USGS Publications Warehouse

Konrad, Christopher P.

2015-01-01

Ecological functions and flood-related risks were assessed for floodplains along the 17 major rivers flowing into Puget Sound Basin, Washington. The assessment addresses five ecological functions, five components of flood-related risks at two spatial resolutions—fine and coarse. The fine-resolution assessment compiled spatial attributes of floodplains from existing, publically available sources and integrated the attributes into 10-meter rasters for each function, hazard, or exposure. The raster values generally represent different types of floodplains with regard to each function, hazard, or exposure rather than the degree of function, hazard, or exposure. The coarse-resolution assessment tabulates attributes from the fine-resolution assessment for larger floodplain units, which are floodplains associated with 0.1 to 21-kilometer long segments of major rivers. The coarse-resolution assessment also derives indices that can be used to compare function or risk among different floodplain units and to develop normative (based on observed distributions) standards. The products of the assessment are available online as geospatial datasets (Konrad, 2015; http://dx.doi.org/10.5066/F7DR2SJC).

Prey risk allocation in a grazing ecosystem.

PubMed

Gude, Justin A; Garrott, Robert A; Borkowski, John J; King, Fred

2006-02-01

Understanding the behaviorally mediated indirect effects of predators in ecosystems requires knowledge of predator-prey behavioral interactions. In predator-ungulate-plant systems, empirical research quantifying how predators affect ungulate group sizes and distribution, in the context of other influential variables, is particularly needed. The risk allocation hypothesis proposes that prey behavioral responses to predation risk depend on background frequencies of exposure to risk, and it can be used to make predictions about predator-ungulate-plant interactions. We determined non-predation variables that affect elk (Cervus elaphus) group sizes and distribution on a winter range in the Greater Yellowstone Ecosystem (GYE) using logistic and log-linear regression on surveys of 513 1-km2 areas conducted over two years. Employing model selection techniques, we evaluated risk allocation and other a priori hypotheses of elk group size and distributional responses to wolf (Canis lupus) predation risk while accounting for influential non-wolf-predation variables. We found little evidence that wolves affect elk group sizes, which were strongly influenced by habitat type and hunting by humans. Following predictions from the risk allocation hypothesis, wolves likely created a more dynamic elk distribution in areas that they frequently hunted, as elk tended to move following wolf encounters in those areas. This response should dilute elk foraging pressure on plant communities in areas where they are frequently hunted by wolves. We predict that this should decrease the spatial heterogeneity of elk impacts on grasslands in areas that wolves frequently hunt. We also predict that this should decrease browsing pressure on heavily browsed woody plant stands in certain areas, which is supported by recent research in the GYE.

Resilience of aging populations after devastating earthquake event and its determinants - A case study of the Chi-Chi earthquake in Taiwan

NASA Astrophysics Data System (ADS)

Hung, Chih-Hsuan; Hung, Hung-Chih

2016-04-01

1.Background Major portions of urban areas in Asia are highly exposed and vulnerable to devastating earthquakes. Many studies identify ways to reduce earthquake risk by concentrating more on building resilience for the particularly vulnerable populations. By 2020, as the United Nations' warning, many Asian countries would become 'super-aged societies', such as Taiwan. However, local authorities rarely use resilience approach to frame earthquake disaster risk management and land use strategies. The empirically-based research about the resilience of aging populations has also received relatively little attention. Thus, a challenge arisen for decision-makers is how to enhance resilience of aging populations within the context of risk reduction. This study aims to improve the understanding of the resilience of aging populations and its changes over time in the aftermath of a destructive earthquake at the local level. A novel methodology is proposed to assess the resilience of aging populations and to characterize their changes of spatial distribution patterns, as well as to examine their determinants. 2.Methods and data An indicator-based assessment framework is constructed with the goal of identifying composite indicators (including before, during and after a disaster) that could serve as proxies for attributes of the resilience of aging populations. Using the recovery process of the Chi-Chi earthquake struck central Taiwan in 1999 as a case study, we applied a method combined a geographical information system (GIS)-based spatial statistics technique and cluster analysis to test the extent of which the resilience of aging populations is spatially autocorrelated throughout the central Taiwan, and to explain why clustering of resilient areas occurs in specific locations. Furthermore, to scrutinize the affecting factors of resilience, we develop an aging population resilience model (APRM) based on existing resilience theory. Using the APRM, we applied a multivariate regression analysis to identify and examine how various factors connect to the resilience of aging populations. To illustrate the proposed methodology, the study collected data on the resilience attributes, the disaster impacts and damages due to the Chi-Chi earthquake. The data were offered by the National Science and Technology Center for Disaster Reduction, Taiwan, as well as collected from the National Land Use Investigation, official census statistics and questionnaire surveys. 3.Results Integrating cluster analysis with GIS-based spatial statistical analysis, the resilience of aging populations were divided into five clusters of distribution patterns over the 10 years after the Chi-Chi earthquake. It shows that both population and elderly distributions were highly heterogeneous and spatial correlated across the study areas. We also demonstrated the 'hot spots' areas of the highly concentrated aging population across central Taiwan. Results of regression analysis disclosed the major factors that caused low resilience and changes of aging population distributions over time. These factors included the levels of seismic damage, infrastructure investments, as well as the land-use and socioeconomic attributes associated with the disaster areas. Finally, our findings provide stakeholders and policy-makers with better adaptive options to design and synthesize appropriate patchworks of planning measures for different types of resilience areas to reduce earthquake disaster risk.

Assessment of soil erosion risk in Komering watershed, South Sumatera, using SWAT model

NASA Astrophysics Data System (ADS)

Salsabilla, A.; Kusratmoko, E.

2017-07-01

Changes in land use watershed led to environmental degradation. Estimated loss of soil erosion is often difficult due to some factors such as topography, land use, climate and human activities. This study aims to predict soil erosion hazard and sediment yield using the Soil and Water Assessment Tools (SWAT) hydrological model. The SWAT was chosen because it can simulate the model with limited data. The study area is Komering watershed (806,001 Ha) in South Sumatera Province. There are two factors land management intervention: 1) land with agriculture, and 2) land with cultivation. These factors selected in accordance with the regulations of spatial plan area. Application of the SWAT demonstrated that the model can predict surface runoff, soil erosion loss and sediment yield. The erosion risk for each watershed can be classified and predicted its changes based on the scenarios which arranged. In this paper, we also discussed the relationship between the distribution of erosion risk and watershed's characteristics in a spatial perspective.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors.

PubMed

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H; Gambhir, Manoj; Fu, Joshua S; Liu, Yang; Remais, Justin V

2013-09-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis , the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001-2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057-2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses-including altered phenology-of disease vectors to altered climate.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors

PubMed Central

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H.; Gambhir, Manoj; Fu, Joshua S.; Liu, Yang; Remais, Justin V.

2014-01-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001–2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057–2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses—including altered phenology—of disease vectors to altered climate. PMID:24772388

Evaluation of New Zealand’s High-Seas Bottom Trawl Closures Using Predictive Habitat Models and Quantitative Risk Assessment

PubMed Central

Penney, Andrew J.; Guinotte, John M.

2013-01-01

United Nations General Assembly Resolution 61/105 on sustainable fisheries (UNGA 2007) establishes three difficult questions for participants in high-seas bottom fisheries to answer: 1) Where are vulnerable marine systems (VMEs) likely to occur?; 2) What is the likelihood of fisheries interaction with these VMEs?; and 3) What might qualify as adequate conservation and management measures to prevent significant adverse impacts? This paper develops an approach to answering these questions for bottom trawling activities in the Convention Area of the South Pacific Regional Fisheries Management Organisation (SPRFMO) within a quantitative risk assessment and cost : benefit analysis framework. The predicted distribution of deep-sea corals from habitat suitability models is used to answer the first question. Distribution of historical bottom trawl effort is used to answer the second, with estimates of seabed areas swept by bottom trawlers being used to develop discounting factors for reduced biodiversity in previously fished areas. These are used in a quantitative ecological risk assessment approach to guide spatial protection planning to address the third question. The coral VME likelihood (average, discounted, predicted coral habitat suitability) of existing spatial closures implemented by New Zealand within the SPRFMO area is evaluated. Historical catch is used as a measure of cost to industry in a cost : benefit analysis of alternative spatial closure scenarios. Results indicate that current closures within the New Zealand SPRFMO area bottom trawl footprint are suboptimal for protection of VMEs. Examples of alternative trawl closure scenarios are provided to illustrate how the approach could be used to optimise protection of VMEs under chosen management objectives, balancing protection of VMEs against economic loss to commercial fishers from closure of historically fished areas. PMID:24358162

Geographic information systems and pharmacoepidemiology: using spatial cluster detection to monitor local patterns of prescription opioid abuse.

PubMed

Brownstein, John S; Green, Traci C; Cassidy, Theresa A; Butler, Stephen F

2010-06-01

Understanding the spatial distribution of opioid abuse at the local level may facilitate public health interventions. Using patient-level data from addiction treatment facilities in New Mexico from ASI-MV Connect, we applied geographic information system (GIS) in combination with a spatial scan statistic to generate risk maps of prescription opioid abuse and identify clusters of product- and compound-specific abuse. Prescribed opioid volume data was used to determine whether identified clusters are beyond geographic differences in availability. Data on 24 452 patients residing in New Mexico were collected. Among those patients, 1779 (7.3%) reported abusing any prescription opioid (past 30 days). According to opioid type, 979 patients (4.0%) reported abuse of any hydrocodone, 1007 (4.1%) for any oxycodone, 108 (0.4%) for morphine, 507 (2.1%) for Vicodin or generic equivalent, 390 (1.6%) for OxyContin, and 63 (0.2%) for MS Contin or generic equivalent. Highest rates of abuse were found in the area surrounding Albuquerque with 8.6 patients indicating abuse per 100 interviewed patients. We found clustering of abuse around Albuquerque (P = 0.001; Relative Risk = 1.35, and a radius of 146 km). At the compound level, we found that drug availability was partly responsible for clustering of prescription opioid abuse. After accounting for drug availability, we identified a second foci of Vicodin abuse in the southern rural portion of the state near Las Cruces, NM and El Paso, Texas and bordering Mexico (RR = 2.1; P = 0.001). A better understanding of local risk distribution may have implications for response strategies to future introductions of prescription opioids.

Geographic Informations Systems and Pharmacoepidemiology: Using spatial cluster detection to monitor local patterns of prescription opioid abuse

PubMed Central

Brownstein, John S.; Green, Traci C.; Cassidy, Theresa A.; Butler, Stephen F.

2010-01-01

Purpose Understanding the spatial distribution of opioid abuse at the local level may facilitate public health interventions. Methods Using patient-level data from addiction treatment facilities in New Mexico from ASI-MV® Connect, we applied geographic information system in combination with a spatial scan statistics to generate risk maps of prescription opioid abuse and identify clusters of product- and compound-specific abuse. Prescribed opioid volume data was used to determine whether identified clusters are beyond geographic differences in availability. Results Data on 24,452 patients residing in New Mexico was collected. Among those patients, 1779 (7.3%) reported abusing any prescription opioid (past 30 days). According to opioid type, 979 patients (4.0%) reported abuse of any hydrocodone, 1007 (4.1%) for any oxycodone, 108 (0.4%) for morphine, 507 (2.1%) for Vicodin® or generic equivalent, 390 (1.6%) for OxyContin®, and 63 (0.2%) for MS Contin® or generic equivalent. Highest rates of abuse were found in the area surrounding Albuquerque with 8.6 patients indicating abuse per 100 interviewed patients. We found clustering of abuse around Albuquerque (P=0.001; Relative Risk=1.35 and a radius of 146 km). At the compound level, we found that drug availability was partly responsible for clustering of prescription opioid abuse. After accounting for drug availability, we identified a second foci of Vicodin® abuse in the southern rural portion of the state near Las Cruces, NM and El Paso, Texas and bordering Mexico (RR=2.1; P=0.001). Conclusions A better understanding of local risk distribution may have implications for response strategies to future introductions of prescription opioids. PMID:20535759

Reprint of "Spatial modeling of Cutaneous Leishmaniasis in Iran from 1983 to 2013".

PubMed

Holakouie-Naieni, Kourosh; Mostafavi, Ehsan; Boloorani, Ali Darvishi; Mohebali, Mehdi; Pakzad, Reza

2017-01-01

Cutaneous Leshmaniasis (CL), a parasitic skin infection caused by Leishmania species, is endemic in some regions of Iran. In this study, the effect of location on the incidence and distribution of CL in Iran was studied. We collected datas including the number of Cutaneous Leishmaniasis cases and populations at-risk of disease in Iran's different provinces reported by the Iranian ministry of health and the National Bureau of Statistics, respectively. Spatial modeling was performed using Arc GIS software. Descriptive maps, hotspot analysis, and high/low clustering analysis were used to demonstrate distribution of the cutaneous leishmaniasis, to determine regions at risk of disease's incidence, and to reach the most appropriate method for clustering of disease. The total number of cases of cutaneous leishmaniasis reported through the study period was 589,913. The annual incidence of CL was estimated to be 30.9 per 100,000 in Iranian population. We also demonstrated that Cutaneous leishmaniasis most prominently occurs in regions with dry and desert climates as well as in central parts of Iran. It affected the southwest of Iran between 1983 and 1997, and subsequently developed towards the center and the eastern between 1998 and 2013. Disease hotspots were focused in the provinces of Yazd, Khozestan and Kohgiloyeh-Boyer-Ahmad (p<0.05). No pattern of spatial clustering was observed. Cutaneous leishmaniasis is a major health problem which could be a serious threat for inhabitants who live in high-risk provinces of Iran; much more resources need to be allocated in these areas, to warrant the prevention as well as effectively management of this disease. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatial modeling of cutaneous leishmaniasis in Iran from 1983 to 2013.

PubMed

Holakouie-Naieni, Kourosh; Mostafavi, Ehsan; Boloorani, Ali Darvishi; Mohebali, Mehdi; Pakzad, Reza

2017-02-01

Cutaneous Leshmaniasis (CL), a parasitic skin infection caused by Leishmania species, is endemic in some regions of Iran. In this study, the effect of location on the incidence and distribution of CL in Iran was studied. We collected datas including the number of Cutaneous Leishmaniasis cases and populations at-risk of disease in Iran's different provinces reported by the Iranian ministry of health and the National Bureau of Statistics, respectively. Spatial modeling was performed using Arc GIS software. Descriptive maps, hotspot analysis, and high/low clustering analysis were used to demonstrate distribution of the cutaneous leishmaniasis, to determine regions at risk of disease's incidence, and to reach the most appropriate method for clustering of disease. The total number of cases of cutaneous leishmaniasis reported through the study period was 589,913. The annual incidence of CL was estimated to be 30.9 per 100,000 in Iranian population. We also demonstrated that Cutaneous leishmaniasis most prominently occurs in regions with dry and desert climates as well as in central parts of Iran. It affected the southwest of Iran between 1983 and 1997, and subsequently developed towards the center and the eastern between 1998 and 2013. Disease hotspots were focused in the provinces of Yazd, Khozestan and Kohgiloyeh-Boyer-Ahmad (p<0.05). No pattern of spatial clustering was observed. Cutaneous leishmaniasis is a major health problem which could be a serious threat for inhabitants who live in high-risk provinces of Iran; much more resources need to be allocated in these areas, to warrant the prevention as well as effectively management of this disease. Copyright © 2016 Elsevier B.V. All rights reserved.

Evaluation of New Zealand's high-seas bottom trawl closures using predictive habitat models and quantitative risk assessment.

PubMed

Penney, Andrew J; Guinotte, John M

2013-01-01

United Nations General Assembly Resolution 61/105 on sustainable fisheries (UNGA 2007) establishes three difficult questions for participants in high-seas bottom fisheries to answer: 1) Where are vulnerable marine systems (VMEs) likely to occur?; 2) What is the likelihood of fisheries interaction with these VMEs?; and 3) What might qualify as adequate conservation and management measures to prevent significant adverse impacts? This paper develops an approach to answering these questions for bottom trawling activities in the Convention Area of the South Pacific Regional Fisheries Management Organisation (SPRFMO) within a quantitative risk assessment and cost : benefit analysis framework. The predicted distribution of deep-sea corals from habitat suitability models is used to answer the first question. Distribution of historical bottom trawl effort is used to answer the second, with estimates of seabed areas swept by bottom trawlers being used to develop discounting factors for reduced biodiversity in previously fished areas. These are used in a quantitative ecological risk assessment approach to guide spatial protection planning to address the third question. The coral VME likelihood (average, discounted, predicted coral habitat suitability) of existing spatial closures implemented by New Zealand within the SPRFMO area is evaluated. Historical catch is used as a measure of cost to industry in a cost : benefit analysis of alternative spatial closure scenarios. Results indicate that current closures within the New Zealand SPRFMO area bottom trawl footprint are suboptimal for protection of VMEs. Examples of alternative trawl closure scenarios are provided to illustrate how the approach could be used to optimise protection of VMEs under chosen management objectives, balancing protection of VMEs against economic loss to commercial fishers from closure of historically fished areas.

Occurrence and distribution of antibiotics in surface water impacted by crab culturing: a case study of Lake Guchenghu, China.

PubMed

Wang, Wenxia; Zhou, Lijun; Gu, Xiaohong; Chen, Huihui; Zeng, Qingfei; Mao, Zhigang

2018-05-30

The objective of this study was to evaluate the occurrence, distribution, potential sources, and ecological risk of antibiotics in aqueous phase of Lake Guchenghu, China. Target antibiotics in surface water of Lake Guchenghu, adjacent streams, and crab ponds were detected seasonally. The results showed that erythromycin-H 2 O (1.60-2450 ng/L), sulfadiazine (ND-654 ng/L), and florfenicol (ND-919 ng/L) were the predominant antibiotics in Lake Guchenghu. The concentrations of antibiotics in Lake Guchenghu Basin showed obvious seasonal variation, with the highest concentration in summer. In general, the concentrations of antibiotics in crab ponds and streams were higher than those in the lake and spatial distributions of antibiotics were affected by pollution sources. The types and origins of antibiotics indicated that wastewater from ponds was the main source of antibiotics in the lake. Risk assessment suggested that as individual compound, erythromycin-H 2 O and clarithromycin posed a high risk to algae while other compounds might pose low or no risk. The mixture of antibiotics may pose a high risk to aquatic organisms in Lake Guchenghu. Overall, our study revealed the occurrence and spatiotemporal variation of antibiotics in Lake Guchenghu, which was related with crab culturing.

Spatial Pattern of Attacks of the Invasive Woodwasp Sirex noctilio, at Landscape and Stand Scales.

PubMed

Lantschner, M Victoria; Corley, Juan C

2015-01-01

Invasive insect pests are responsible for important damage to native and plantation forests, when population outbreaks occur. Understanding the spatial pattern of attacks by forest pest populations is essential to improve our understanding of insect population dynamics and for predicting attack risk by invasives or planning pest management strategies. The woodwasp Sirex noctilio is an invasive woodwasp that has become probably the most important pest of pine plantations in the Southern Hemisphere. Our aim was to study the spatial dynamics of S. noctilio populations in Southern Argentina. Specifically we describe: (1) the spatial patterns of S. noctilio outbreaks and their relation with environmental factors at a landscape scale; and (2) characterize the spatial pattern of attacked trees at the stand scale. We surveyed the spatial distribution of S. noctilio outbreaks in three pine plantation landscapes, and we assessed potential associations with topographic variables, habitat characteristics, and distance to other outbreaks. We also looked at the spatial distribution of attacked trees in 20 stands with different levels of infestation, and assessed the relationship of attacks with stand composition and management. We found that the spatial pattern of pine stands with S. noctilio outbreaks at the landscape scale is influenced mainly by the host species present, slope aspect, and distance to other outbreaks. At a stand scale, there is strong aggregation of attacked trees in stands with intermediate infestation levels, and the degree of attacks is influenced by host species and plantation management. We conclude that the pattern of S. noctilio damage at different spatial scales is influenced by a combination of both inherent population dynamics and the underlying patterns of environmental factors. Our results have important implications for the understanding and management of invasive insect outbreaks in forest systems.

Spatial assessment of potential ecological risk of heavy metals in soils from informal e-waste recycling in Ghana.

PubMed

Kyere, Vincent Nartey; Greve, Klaus; Atiemo, Sampson Manukure; Ephraim, James

2017-01-01

The rapidly increasing annual global volume of e-waste, and of its inherently valuable fraction, has created an opportunity for individuals in Agbogbloshie, Accra, Ghana to make a living by using unconventional, uncontrolled, primitive and crude procedures to recycle and recover valuable metals from this waste. The current form of recycling procedures releases hazardous fractions, such as heavy metals, into the soil, posing a significant risk to the environment and human health. Using a handheld global positioning system, 132 soil samples based on 100 m grid intervals were collected and analysed for cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), lead (Pb) and zinc (Zn). Using geostatistical techniques and sediment quality guidelines, this research seeks to assess the potential risk these heavy metals posed to the proposed Korle Ecological Restoration Zone by informal e-waste processing site in Agbogbloshie, Accra, Ghana. Analysis of heavy metals revealed concentrations exceeded the regulatory limits of both Dutch and Canadian soil quality and guidance values, and that the ecological risk posed by the heavy metals extended beyond the main burning and dismantling sites of the informal recyclers to the school, residential, recreational, clinic, farm and worship areas. The heavy metals Cr, Cu, Pb and Zn had normal distribution, spatial variability, and spatial autocorrelation. Further analysis revealed the decreasing order of toxicity, Hg>Cd>Pb> Cu>Zn>Cr, of contributing significantly to the potential ecological risk in the study area.

Spatial assessment of potential ecological risk of heavy metals in soils from informal e-waste recycling in Ghana

PubMed Central

Greve, Klaus; Atiemo, Sampson Manukure

2017-01-01

The rapidly increasing annual global volume of e-waste, and of its inherently valuable fraction, has created an opportunity for individuals in Agbogbloshie, Accra, Ghana to make a living by using unconventional, uncontrolled, primitive and crude procedures to recycle and recover valuable metals from this waste. The current form of recycling procedures releases hazardous fractions, such as heavy metals, into the soil, posing a significant risk to the environment and human health. Using a handheld global positioning system, 132 soil samples based on 100 m grid intervals were collected and analysed for cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), lead (Pb) and zinc (Zn). Using geostatistical techniques and sediment quality guidelines, this research seeks to assess the potential risk these heavy metals posed to the proposed Korle Ecological Restoration Zone by informal e-waste processing site in Agbogbloshie, Accra, Ghana. Analysis of heavy metals revealed concentrations exceeded the regulatory limits of both Dutch and Canadian soil quality and guidance values, and that the ecological risk posed by the heavy metals extended beyond the main burning and dismantling sites of the informal recyclers to the school, residential, recreational, clinic, farm and worship areas. The heavy metals Cr, Cu, Pb and Zn had normal distribution, spatial variability, and spatial autocorrelation. Further analysis revealed the decreasing order of toxicity, Hg>Cd>Pb> Cu>Zn>Cr, of contributing significantly to the potential ecological risk in the study area. PMID:29056034

Identifying areas at risk of low birth weight using spatial epidemiology: A small area surveillance study.

PubMed

Insaf, Tabassum Z; Talbot, Thomas

2016-07-01

To assess the geographic distribution of Low Birth Weight (LBW) in New York State among singleton births using a spatial regression approach in order to identify priority areas for public health actions. LBW was defined as birth weight less than 2500g. Geocoded data from 562,586 birth certificates in New York State (years 2008-2012) were merged with 2010 census data at the tract level. To provide stable estimates and maintain confidentiality, data were aggregated to yield 1268 areas of analysis. LBW prevalence among singleton births was related with area-level behavioral, socioeconomic and demographic characteristics using a Poisson mixed effects spatial error regression model. Observed low birth weight showed statistically significant auto-correlation in our study area (Moran's I 0.16 p value 0.0005). After over-dispersion correction and accounting for fixed effects for selected social determinants, spatial autocorrelation was fully accounted for (Moran's I-0.007 p value 0.241). The proportion of LBW was higher in areas with larger Hispanic or Black populations and high smoking prevalence. Smoothed maps with predicted prevalence were developed to identify areas at high risk of LBW. Spatial patterns of residual variation were analyzed to identify unique risk factors. Neighborhood racial composition contributes to disparities in LBW prevalence beyond differences in behavioral and socioeconomic factors. Small-area analyses of LBW can identify areas for targeted interventions and display unique local patterns that should be accounted for in prevention strategies. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Spatial-temporal pattern and risk factor analysis of bacillary dysentery in the Beijing-Tianjin-Tangshan urban region of China.

PubMed

Xiao, Gexin; Xu, Chengdong; Wang, Jinfeng; Yang, Dongyang; Wang, Li

2014-09-25

Bacillary dysentery remains a major public health concern in China. The Beijing-Tianjin-Tangshan urban region is one of the most heavily infected areas in the country. This study aimed to analyze epidemiological features of bacillary dysentery, detect spatial-temporal clusters of the disease, and analyze risk factors that may affect bacillary dysentery incidence in the region. Bacillary dysentery case data from January 2011 to December 2011 in Beijing-Tianjin-Tangshan were used in this study. The epidemiological features of cases were characterized, then scan statistics were performed to detect spatial temporal clusters of bacillary dysentery. A spatial panel model was used to identify potential risk factors. There were a total of 28,765 cases of bacillary dysentery in 2011. The results of the analysis indicated that compared with other age groups, the highest incidence (473.75/105) occurred in individuals <5 years of age. The incidence in males (530.57/105) was higher compared with females (409.06/105). On a temporal basis, incidence increased rapidly starting in April. Peak incidence occurred in August (571.10/105). Analysis of the spatial distribution model revealed that factors such as population density, temperature, precipitation, and sunshine hours were positively associated with incidence rate. Per capita gross domestic product was negatively associated with disease incidence. Meteorological and socio-economic factors have affected the transmission of bacillary dysentery in the urban Beijing-Tianjin-Tangshan region of China. The success of bacillary dysentery prevention and control department strategies would benefit from giving more consideration to climate variations and local socio-economic conditions.

Distribution of RF energy emitted by mobile phones in anatomical structures of the brain

NASA Astrophysics Data System (ADS)

Cardis, E.; Deltour, I.; Mann, S.; Moissonnier, M.; Taki, M.; Varsier, N.; Wake, K.; Wiart, J.

2008-06-01

The rapid worldwide increase in mobile phone use in the last decade has generated considerable interest in possible carcinogenic effects of radio frequency (RF). Because exposure to RF from phones is localized, if a risk exists it is likely to be greatest for tumours in regions with greatest energy absorption. The objective of the current paper was to characterize the spatial distribution of RF energy in the brain, using results of measurements made in two laboratories on 110 phones used in Europe or Japan. Most (97-99% depending on frequency) appears to be absorbed in the brain hemisphere on the side where the phone is used, mainly (50-60%) in the temporal lobe. The average relative SARSAR is the specific energy absorption rate i.e. energy absorption rate per unit mass (measured in W kg-1). is highest in the temporal lobe (6-15%, depending on frequency, of the spatial peak SAR in the most exposed region of the brain) and the cerebellum (2-10%) and decreases very rapidly with increasing depth, particularly at higher frequencies. The SAR distribution appears to be fairly similar across phone models, between older and newer phones and between phones with different antenna types and positions. Analyses of risk by location of tumour are therefore important for the interpretation of results of studies of brain tumours in relation to mobile phone use.

A spatial Bayesian network model to assess the benefits of early warning for urban flood risk to people

NASA Astrophysics Data System (ADS)

Balbi, Stefano; Villa, Ferdinando; Mojtahed, Vahid; Hegetschweiler, Karin Tessa; Giupponi, Carlo

2016-06-01

This article presents a novel methodology to assess flood risk to people by integrating people's vulnerability and ability to cushion hazards through coping and adapting. The proposed approach extends traditional risk assessments beyond material damages; complements quantitative and semi-quantitative data with subjective and local knowledge, improving the use of commonly available information; and produces estimates of model uncertainty by providing probability distributions for all of its outputs. Flood risk to people is modeled using a spatially explicit Bayesian network model calibrated on expert opinion. Risk is assessed in terms of (1) likelihood of non-fatal physical injury, (2) likelihood of post-traumatic stress disorder and (3) likelihood of death. The study area covers the lower part of the Sihl valley (Switzerland) including the city of Zurich. The model is used to estimate the effect of improving an existing early warning system, taking into account the reliability, lead time and scope (i.e., coverage of people reached by the warning). Model results indicate that the potential benefits of an improved early warning in terms of avoided human impacts are particularly relevant in case of a major flood event.

Evaluation of socio-spatial vulnerability of citydwellers and analysis of risk perception: industrial and seismic risks in Mulhouse

NASA Astrophysics Data System (ADS)

Glatron, S.; Beck, E.

2008-10-01

Social vulnerability has been studied for years with sociological, psychological and economical approaches. Our proposition focuses on perception and cognitive representations of risks by city dwellers living in a medium size urban area, namely Mulhouse (France). Perception, being part of the social vulnerability and resilience of the society to disasters, influences the potential damage; for example it leads to adequate or inadequate behaviour in the case of an emergency. As geographers, we assume that the spatial relationship to danger or hazard can be an important factor of vulnerability and we feel that the spatial dimension is a challenging question either for better knowledge or for operational reasons (e.g. management of preventive information). We interviewed 491 people, inhabitants and workers, regularly distributed within the urban area to get to know their opinion on hazards and security measures better. We designed and mapped a vulnerability index on the basis of their answers. The results show that the social vulnerability depends on the type of hazard, and that the distance to the source of danger influences the vulnerability, especially for hazards with a precise location (industrial for example). Moreover, the effectiveness of the information campaigns is doubtful, as the people living close to hazardous industries (target of specific preventive information) are surprisingly more vulnerable and less aware of industrial risk.

Contamination potential of nitrogen compounds in the heterogeneous aquifers of the Choushui River alluvial fan, Taiwan

NASA Astrophysics Data System (ADS)

Jang, Cheng-Shin; Liu, Chen-Wuing

2005-10-01

This study aimed to analyze the contamination potential associated with the reactive transport of nitrate-N and ammonium-N in the Choushui River alluvial fan, Taiwan and to evaluate a risk region in developing a groundwater protection policy in 2021. In this area, an aquifer redox sequence provided a good understanding of the spatial distributions of nitrate-N and ammonium-N and of aerobic and anaerobic environments. Equiprobable hydraulic conductivity ( K) fields reproduced by geostatistical methods characterized the spatial uncertainty of contaminant transport in the heterogeneous aquifer. Nitrogen contamination potential fronts for high and low threshold concentrations based on a 95% risk probability were used to assess different levels of risk. The simulated result reveals that the spatial uncertainty of highly heterogeneous K fields governs the contamination potential assessment of the nitrogen compounds along the regional flow directions. The contamination potential of nitrate-N is more uncertain than that for ammonium-N. The high nitrate-N concentrations (≧ 3 mg/L) are prevalent in the aerobic environment. The low concentration nitrate-N plumes (0.5-3 mg/L) gradually migrate to the mid-fan area and to a maximum distance of 15 km from the aerobic region. The nitrate-N plumes pose a potential human health risk in the aerobic and anaerobic environments. The ammonium-N plumes remain stably confined to the distal-fan and partial mid-fan areas.

Geostatistical risk estimation at waste disposal sites in the presence of hot spots.

PubMed

Komnitsas, Kostas; Modis, Kostas

2009-05-30

The present paper aims to estimate risk by using geostatistics at the wider coal mining/waste disposal site of Belkovskaya, Tula region, in Russia. In this area the presence of hot spots causes a spatial trend in the mean value of the random field and a non-Gaussian data distribution. Prior to application of geostatistics, subtraction of trend and appropriate smoothing and transformation of the data into a Gaussian form were carried out; risk maps were then generated for the wider study area in order to assess the probability of exceeding risk thresholds. Finally, the present paper discusses the need for homogenization of soil risk thresholds regarding hazardous elements that will enhance reliability of risk estimation and enable application of appropriate rehabilitation actions in contaminated areas.

SPATIAL-TEMPORAL DISTRIBUTION OF WATERBORNE INFECTIOUS DISEASE RISK USING THE HYDRAULIC MODEL AND OUTPATIENT DATA

NASA Astrophysics Data System (ADS)

Amano, Ayako; Sakuma, Taisuke; Kazama, So

This study evaluated waterborne infectious diseases risk and incidence rate around Phonm Penh in Cambodia. We use the hydraulic flood simulation, coliform bacterium diffusion model, dose-response model and outpatient data for quantitative analysis. The results obtained are as follows; 1. The incidence (incidence rate) of diarrhea as water borne diseases risk is 0.14 million people (9%) in the inundation area. 2. The residents in the inundation area are exposed up to 4 times as high risk as daily mean calculated by the integrated model combined in the regional scale. 3.The infectious disease risk due to floods and inundation indicated is effective as an element to explain the risk. The scenario explains 34% number of patient estimated by the outpatient data.

Chagas disease risk in Texas.

PubMed

Sarkar, Sahotra; Strutz, Stavana E; Frank, David M; Rivaldi, Chissa-Louise; Sissel, Blake; Sánchez-Cordero, Victor

2010-10-05

Chagas disease, caused by Trypanosoma cruzi, remains a serious public health concern in many areas of Latin America, including México. It is also endemic in Texas with an autochthonous canine cycle, abundant vectors (Triatoma species) in many counties, and established domestic and peridomestic cycles which make competent reservoirs available throughout the state. Yet, Chagas disease is not reportable in Texas, blood donor screening is not mandatory, and the serological profiles of human and canine populations remain unknown. The purpose of this analysis was to provide a formal risk assessment, including risk maps, which recommends the removal of these lacunae. The spatial relative risk of the establishment of autochthonous Chagas disease cycles in Texas was assessed using a five-stage analysis. 1. Ecological risk for Chagas disease was established at a fine spatial resolution using a maximum entropy algorithm that takes as input occurrence points of vectors and environmental layers. The analysis was restricted to triatomine vector species for which new data were generated through field collection and through collation of post-1960 museum records in both México and the United States with sufficiently low georeferenced error to be admissible given the spatial resolution of the analysis (1 arc-minute). The new data extended the distribution of vector species to 10 new Texas counties. The models predicted that Triatoma gerstaeckeri has a large region of contiguous suitable habitat in the southern United States and México, T. lecticularia has a diffuse suitable habitat distribution along both coasts of the same region, and T. sanguisuga has a disjoint suitable habitat distribution along the coasts of the United States. The ecological risk is highest in south Texas. 2. Incidence-based relative risk was computed at the county level using the Bayesian Besag-York-Mollié model and post-1960 T. cruzi incidence data. This risk is concentrated in south Texas. 3. The ecological and incidence-based risks were analyzed together in a multi-criteria dominance analysis of all counties and those counties in which there were as yet no reports of parasite incidence. Both analyses picked out counties in south Texas as those at highest risk. 4. As an alternative to the multi-criteria analysis, the ecological and incidence-based risks were compounded in a multiplicative composite risk model. Counties in south Texas emerged as those with the highest risk. 5. Risk as the relative expected exposure rate was computed using a multiplicative model for the composite risk and a scaled population county map for Texas. Counties with highest risk were those in south Texas and a few counties with high human populations in north, east, and central Texas showing that, though Chagas disease risk is concentrated in south Texas, it is not restricted to it. For all of Texas, Chagas disease should be designated as reportable, as it is in Arizona and Massachusetts. At least for south Texas, lower than N, blood donor screening should be mandatory, and the serological profiles of human and canine populations should be established. It is also recommended that a joint initiative be undertaken by the United States and México to combat Chagas disease in the trans-border region. The methodology developed for this analysis can be easily exported to other geographical and disease contexts in which risk assessment is of potential value.

Toxic releases and risk disparity: a spatiotemporal model of industrial ecology and social empowerment.

PubMed

Aoyagi, Hannah; Ogunseitan, Oladele A

2015-06-02

Information-based regulations (IBRs) are founded on the theoretical premise that public participation in accomplishing policy goals is empowered by open access to information. Since its inception in 1988, the Toxics Release Inventory (TRI) has provided the framework and regulatory impetus for the compilation and distribution of data on toxic releases associated with industrial development, following the tenets of IBR. As TRI emissions are reputed to disproportionately affect low-income communities, we investigated how demographic characteristics are related to change in TRI emissions and toxicity risks between 1989 and 2002, and we sought to identify factors that predict these changes. We used local indicators of spatial association (LISA) maps and spatial regression techniques to study risk disparity in the Los Angeles urban area. We also surveyed 203 individuals in eight communities in the same region to measure the levels of awareness of TRI, attitudes towards air pollution, and general environmental risk. We discovered, through spatial lag models, that changes in gross and toxic emissions are related to community ethnic composition, poverty level, home ownership, and base 1989 emissions (R-square=0.034-0.083). We generated a structural equation model to explain the determinants of social empowerment to act on the basis of environmental information. Hierarchical confirmatory factor analysis (HCFA) supports the theoretical model that individual empowerment is predicted by risk perception, worry, and awareness (Chi-square=63.315, p=0.022, df=42). This study provides strong evidence that spatiotemporal changes in regional-scale environmental risks are influenced by individual-scale empowerment mediated by IBRs.

Toxic Releases and Risk Disparity: A Spatiotemporal Model of Industrial Ecology and Social Empowerment

PubMed Central

Aoyagi, Hannah; Ogunseitan, Oladele A.

2015-01-01

Information-based regulations (IBRs) are founded on the theoretical premise that public participation in accomplishing policy goals is empowered by open access to information. Since its inception in 1988, the Toxics Release Inventory (TRI) has provided the framework and regulatory impetus for the compilation and distribution of data on toxic releases associated with industrial development, following the tenets of IBR. As TRI emissions are reputed to disproportionately affect low-income communities, we investigated how demographic characteristics are related to change in TRI emissions and toxicity risks between 1989 and 2002, and we sought to identify factors that predict these changes. We used local indicators of spatial association (LISA) maps and spatial regression techniques to study risk disparity in the Los Angeles urban area. We also surveyed 203 individuals in eight communities in the same region to measure the levels of awareness of TRI, attitudes towards air pollution, and general environmental risk. We discovered, through spatial lag models, that changes in gross and toxic emissions are related to community ethnic composition, poverty level, home ownership, and base 1989 emissions (R-square = 0.034–0.083). We generated a structural equation model to explain the determinants of social empowerment to act on the basis of environmental information. Hierarchical confirmatory factor analysis (HCFA) supports the theoretical model that individual empowerment is predicted by risk perception, worry, and awareness (Chi-square = 63.315, p = 0.022, df = 42). This study provides strong evidence that spatiotemporal changes in regional-scale environmental risks are influenced by individual-scale empowerment mediated by IBRs. PMID:26042368

Assessing habitat risk from human activities to inform coastal and marine spatial planning: a demonstration in Belize

NASA Astrophysics Data System (ADS)

Arkema, Katie K.; Verutes, Gregory; Bernhardt, Joanna R.; Clarke, Chantalle; Rosado, Samir; Canto, Maritza; Wood, Spencer A.; Ruckelshaus, Mary; Rosenthal, Amy; McField, Melanie; de Zegher, Joann

2014-11-01

Integrated coastal and ocean management requires transparent and accessible approaches for understanding the influence of human activities on marine environments. Here we introduce a model for assessing the combined risk to habitats from multiple ocean uses. We apply the model to coral reefs, mangrove forests and seagrass beds in Belize to inform the design of the country’s first Integrated Coastal Zone Management (ICZM) Plan. Based on extensive stakeholder engagement, review of existing legislation and data collected from diverse sources, we map the current distribution of coastal and ocean activities and develop three scenarios for zoning these activities in the future. We then estimate ecosystem risk under the current and three future scenarios. Current levels of risk vary spatially among the nine coastal planning regions in Belize. Empirical tests of the model are strong—three-quarters of the measured data for coral reef health lie within the 95% confidence interval of interpolated model data and 79% of the predicted mangrove occurrences are associated with observed responses. The future scenario that harmonizes conservation and development goals results in a 20% reduction in the area of high-risk habitat compared to the current scenario, while increasing the extent of several ocean uses. Our results are a component of the ICZM Plan for Belize that will undergo review by the national legislature in 2015. This application of our model to marine spatial planning in Belize illustrates an approach that can be used broadly by coastal and ocean planners to assess risk to habitats under current and future management scenarios.

Polycyclic aromatic hydrocarbons in surface sediment of typical estuaries and the spatial distribution in Haihe river basin.

PubMed

Liu, Jing L; Zhang, Jing; Liu, Feng; Zhang, Lu L

2014-05-01

Polycyclic aromatic hydrocarbons (PAHs) with carcinogenic and mutagenic characteristics have been detected in many estuaries and bays around the world. To detect the contaminated level in typical estuaries in Haihe river basin, China, a comprehensive survey of 16 PAHs in surface sediment has been conducted and an ecological risk assessment has been taken. It showed that Haihe river estuary had the highest concentration, ranging from 92.91 to 15886.00 ng g(-1). And Luan river estuary has the lowest polluted level, ranging from 39.55 to 328.10 ng g(-1). PAHs in sediment were dominated by low and mid molecular weight PAHs in all the sampling sites. Most of the sampling sites in all sampling seasons indicated a rarely happened ecological risk of ΣPAHs, while the S6 in Haihe river estuary was in an occasionally anticipated risk. To illustrate the spatial distribution pattern of PAHs in surface sediment in Haihe river basin, the results were compared with previous research of the research team. Based on data of the comparison, it had been revealed that Haihe river had the most serious PAHs pollution, with an average concentration of 5884.86 ng g(-1), and showed the highest contamination level in all four ecological units. The ΣPAHs concentration showed in a rank of reservoir > estuary > rural area > city.

Assessment of the distribution, bioavailability and ecological risks of heavy metals in the lake water and surface sediments of the Caohai plateau wetland, China.

PubMed

Hu, Jing; Zhou, Shaoqi; Wu, Pan; Qu, Kunjie

2017-01-01

In this study, selected heavy metals (Hg, As, Cd, Pb, Cr, Cu and Zn) in the lake water and sediments from the Caohai wetland, which is a valuable state reserve for migrant birds in China, were investigated to assess the spatial distribution, sources, bioavailability and ecological risks. The results suggested that most of the higher concentrations were found in the eastern region of the lakeshore. The concentration factor (CF) revealed that Hg, Cd and Zn were present from moderate risk levels to considerable risk levels in this study; thus, based on the high pollution load index (PLI) values, the Caohai wetland can be considered polluted. According to the associated effects-range classification, Cd may present substantial environmental hazards. An investigation of the chemical speciation suggested that Cd and Zn were unstable across most of the sites, which implied a higher risk of quick desorption and release. Principal component analysis (PCA) indicated that the heavy metal contamination originated from both natural and anthropogenic sources.

Assessment of the distribution, bioavailability and ecological risks of heavy metals in the lake water and surface sediments of the Caohai plateau wetland, China

PubMed Central

Hu, Jing; Zhou, Shaoqi; Wu, Pan; Qu, Kunjie

2017-01-01

In this study, selected heavy metals (Hg, As, Cd, Pb, Cr, Cu and Zn) in the lake water and sediments from the Caohai wetland, which is a valuable state reserve for migrant birds in China, were investigated to assess the spatial distribution, sources, bioavailability and ecological risks. The results suggested that most of the higher concentrations were found in the eastern region of the lakeshore. The concentration factor (CF) revealed that Hg, Cd and Zn were present from moderate risk levels to considerable risk levels in this study; thus, based on the high pollution load index (PLI) values, the Caohai wetland can be considered polluted. According to the associated effects-range classification, Cd may present substantial environmental hazards. An investigation of the chemical speciation suggested that Cd and Zn were unstable across most of the sites, which implied a higher risk of quick desorption and release. Principal component analysis (PCA) indicated that the heavy metal contamination originated from both natural and anthropogenic sources. PMID:29253896

Mapping wildland fuels and forest structure for land management: a comparison of nearest neighbor imputation and other methods

Treesearch

Kenneth B. Pierce; Janet L. Ohmann; Michael C. Wimberly; Matthew J. Gregory; Jeremy S. Fried

2009-01-01

Land managers need consistent information about the geographic distribution of wildland fuels and forest structure over large areas to evaluate fire risk and plan fuel treatments. We compared spatial predictions for 12 fuel and forest structure variables across three regions in the western United States using gradient nearest neighbor (GNN) imputation, linear models (...

Study on association between spatial distribution of metal mines and disease mortality: a case study in Suxian District, South China.

PubMed

Song, Daping; Jiang, Dong; Wang, Yong; Chen, Wei; Huang, Yaohuan; Zhuang, Dafang

2013-10-16

Metal mines release toxic substances into the environment and can therefore negatively impact the health of residents in nearby regions. This paper sought to investigate whether there was excess disease mortality in populations in the vicinity of the mining area in Suxian District, South China. The spatial distribution of metal mining and related activities from 1985 to 2012, which was derived from remote sensing imagery, was overlapped with disease mortality data. Three hotspot areas with high disease mortality were identified around the Shizhuyuan mine sites, i.e., the Dengjiatang metal smelting sites, and the Xianxichong mine sites. Disease mortality decreased with the distance to the mining and smelting areas. Population exposure to pollution was estimated on the basis of distance from town of residence to pollution source. The risk of dying according to disease mortality rates was analyzed within 7-25 km buffers. The results suggested that there was a close relationship between the risk of disease mortality and proximity to the Suxian District mining industries. These associations were dependent on the type and scale of mining activities, the area influenced by mining and so on.

Study on Association between Spatial Distribution of Metal Mines and Disease Mortality: A Case Study in Suxian District, South China

PubMed Central

Song, Daping; Jiang, Dong; Wang, Yong; Chen, Wei; Huang, Yaohuan; Zhuang, Dafang

2013-01-01

Metal mines release toxic substances into the environment and can therefore negatively impact the health of residents in nearby regions. This paper sought to investigate whether there was excess disease mortality in populations in the vicinity of the mining area in Suxian District, South China. The spatial distribution of metal mining and related activities from 1985 to 2012, which was derived from remote sensing imagery, was overlapped with disease mortality data. Three hotspot areas with high disease mortality were identified around the Shizhuyuan mine sites, i.e., the Dengjiatang metal smelting sites, and the Xianxichong mine sites. Disease mortality decreased with the distance to the mining and smelting areas. Population exposure to pollution was estimated on the basis of distance from town of residence to pollution source. The risk of dying according to disease mortality rates was analyzed within 7–25 km buffers. The results suggested that there was a close relationship between the risk of disease mortality and proximity to the Suxian District mining industries. These associations were dependent on the type and scale of mining activities, the area influenced by mining and so on. PMID:24135822

Intrinsic and specific vulnerability of groundwater in central Spain: the risk of nitrate pollution

NASA Astrophysics Data System (ADS)

Martínez-Bastida, Juan J.; Arauzo, Mercedes; Valladolid, Maria

2010-05-01

The intrinsic vulnerability of groundwater in the Comunidad de Madrid (central Spain) was evaluated using the DRASTIC and GOD indexes. Groundwater vulnerability to nitrate pollution was also assessed using the composite DRASTIC (CD) and nitrate vulnerability (NV) indexes. The utility of these methods was tested by analyzing the spatial distribution of nitrate concentrations in the different aquifers located in the study area: the Tertiary Detrital Aquifer, the Moor Limestone Aquifer, the Cretaceous Limestone Aquifer and the Quaternary Aquifer. Vulnerability maps based on these four indexes showed very similar results, identifying the Quaternary Aquifer and the lower sub-unit of the Moor Limestone Aquifer as deposits subjected to a high risk of nitrate pollution due to intensive agriculture. As far as the spatial distribution of groundwater nitrate concentrations is concerned, the NV index showed the greatest statistical significance ( p < 0.01). This new type of multiplicative model offers greater accuracy in estimations of specific vulnerability with respect to the real impact of each type of land use. The results of this study provide a basis on which to guide the designation of nitrate vulnerable zones in the Comunidad de Madrid, in line with European Union Directive 91/676/EEC.

Using remote sensing and machine learning for the spatial modelling of a bluetongue virus vector

NASA Astrophysics Data System (ADS)

Van doninck, J.; Peters, J.; De Baets, B.; Ducheyne, E.; Verhoest, N. E. C.

2012-04-01

Bluetongue is a viral vector-borne disease transmitted between hosts, mostly cattle and small ruminants, by some species of Culicoides midges. Within the Mediterranean basin, C. imicola is the main vector of the bluetongue virus. The spatial distribution of this species is limited by a number of environmental factors, including temperature, soil properties and land cover. The identification of zones at risk of bluetongue outbreaks thus requires detailed information on these environmental factors, as well as appropriate epidemiological modelling techniques. We here give an overview of the environmental factors assumed to be constraining the spatial distribution of C. imicola, as identified in different studies. Subsequently, remote sensing products that can be used as proxies for these environmental constraints are presented. Remote sensing data are then used together with species occurrence data from the Spanish Bluetongue National Surveillance Programme to calibrate a supervised learning model, based on Random Forests, to model the probability of occurrence of the C. imicola midge. The model will then be applied for a pixel-based prediction over the Iberian peninsula using remote sensing products for habitat characterization.

Effects of geometrical structure on spatial distribution of thermal energy in two-dimensional triangular lattices

NASA Astrophysics Data System (ADS)

Liu, Yong-Yang; Xu, Yu-Liang; Liu, Zhong-Qiang; Li, Jing; Wang, Chun-Yang; Kong, Xiang-Mu

2018-07-01

Employing the correlation matrix technique, the spatial distribution of thermal energy in two-dimensional triangular lattices in equilibrium, interacting with linear springs, is studied. It is found that the spatial distribution of thermal energy varies with the included angle of the springs. In addition, the average thermal energy of the longer springs is lower. Springs with different included angle and length will lead to an inhomogeneous spatial distribution of thermal energy. This suggests that the spatial distribution of thermal energy is affected by the geometrical structure of the system: the more asymmetric the geometrical structure of the system is, the more inhomogeneous is the spatial distribution of thermal energy.

Logistical constraints lead to an intermediate optimum in outbreak response vaccination

PubMed Central

Shea, Katriona; Ferrari, Matthew

2018-01-01

Dynamic models in disease ecology have historically evaluated vaccination strategies under the assumption that they are implemented homogeneously in space and time. However, this approach fails to formally account for operational and logistical constraints inherent in the distribution of vaccination to the population at risk. Thus, feedback between the dynamic processes of vaccine distribution and transmission might be overlooked. Here, we present a spatially explicit, stochastic Susceptible-Infected-Recovered-Vaccinated model that highlights the density-dependence and spatial constraints of various diffusive strategies of vaccination during an outbreak. The model integrates an agent-based process of disease spread with a partial differential process of vaccination deployment. We characterize the vaccination response in terms of a diffusion rate that describes the distribution of vaccination to the population at risk from a central location. This generates an explicit trade-off between slow diffusion, which concentrates effort near the central location, and fast diffusion, which spreads a fixed vaccination effort thinly over a large area. We use stochastic simulation to identify the optimum vaccination diffusion rate as a function of population density, interaction scale, transmissibility, and vaccine intensity. Our results show that, conditional on a timely response, the optimal strategy for minimizing outbreak size is to distribute vaccination resource at an intermediate rate: fast enough to outpace the epidemic, but slow enough to achieve local herd immunity. If the response is delayed, however, the optimal strategy for minimizing outbreak size changes to a rapidly diffusive distribution of vaccination effort. The latter may also result in significantly larger outbreaks, thus suggesting a benefit of allocating resources to timely outbreak detection and response. PMID:29791432

The Historical Distribution of Main Malaria Foci in Spain as Related to Water Bodies

PubMed Central

Sousa, Arturo; García-Barrón, Leoncio; Vetter, Mark; Morales, Julia

2014-01-01

The possible connectivity between the spatial distribution of water bodies suitable for vectors of malaria and endemic malaria foci in Southern Europe is still not well known. Spain was one of the last countries in Western Europe to be declared free of malaria by the World Health Organization (WHO) in 1964. This study combines, by means of a spatial-temporal analysis, the historical data of patients and deceased with the distribution of water bodies where the disease-transmitting mosquitos proliferate. Therefore, data from historical archives with a Geographic Information System (GIS), using the Inverse Distance Weighted (IDW) interpolation method, was analyzed with the aim of identifying regional differences in the distribution of malaria in Spain. The reasons, why the risk of transmission is concentrated in specific regions, are related to worse socioeconomic conditions (Extremadura), the presence of another vector (Anopheles labranchiae) besides A. atroparvus (Levante) or large areas of water bodies in conditions to reproduce theses vectors (La Mancha and Western Andalusia). In the particular case of Western Andalusia, in 1913, the relatively high percentage of 4.73% of the surface, equal to 202362 ha, corresponds to wetlands and other unhealthy water bodies. These wetlands have been reduced as a result of desiccation policies and climate change such as the Little Ice Age and Global Climate Change. The comprehension of the main factors of these wetland changes in the past can help us interpret accurately the future risk of malaria re-emergence in temperate latitudes, since it reveals the crucial role of unhealthy water bodies on the distribution, endemicity and eradication of malaria in southern Europe. PMID:25101771

The historical distribution of main malaria foci in Spain as related to water bodies.

PubMed

Sousa, Arturo; García-Barrón, Leoncio; Vetter, Mark; Morales, Julia

2014-08-06

The possible connectivity between the spatial distribution of water bodies suitable for vectors of malaria and endemic malaria foci in Southern Europe is still not well known. Spain was one of the last countries in Western Europe to be declared free of malaria by the World Health Organization (WHO) in 1964. This study combines, by means of a spatial-temporal analysis, the historical data of patients and deceased with the distribution of water bodies where the disease-transmitting mosquitos proliferate. Therefore, data from historical archives with a Geographic Information System (GIS), using the Inverse Distance Weighted (IDW) interpolation method, was analyzed with the aim of identifying regional differences in the distribution of malaria in Spain. The reasons, why the risk of transmission is concentrated in specific regions, are related to worse socioeconomic conditions (Extremadura), the presence of another vector (Anopheles labranchiae) besides A. atroparvus (Levante) or large areas of water bodies in conditions to reproduce theses vectors (La Mancha and Western Andalusia). In the particular case of Western Andalusia, in 1913, the relatively high percentage of 4.73% of the surface, equal to 202362 ha, corresponds to wetlands and other unhealthy water bodies. These wetlands have been reduced as a result of desiccation policies and climate change such as the Little Ice Age and Global Climate Change. The comprehension of the main factors of these wetland changes in the past can help us interpret accurately the future risk of malaria re-emergence in temperate latitudes, since it reveals the crucial role of unhealthy water bodies on the distribution, endemicity and eradication of malaria in southern Europe.

Spatially explicit assessment of heat health risk by using multi-sensor remote sensing images and socioeconomic data in Yangtze River Delta, China.

PubMed

Chen, Qian; Ding, Mingjun; Yang, Xuchao; Hu, Kejia; Qi, Jiaguo

2018-05-25

The increase in the frequency and intensity of extreme heat events, which are potentially associated with climate change in the near future, highlights the importance of heat health risk assessment, a significant reference for heat-related death reduction and intervention. However, a spatiotemporal mismatch exists between gridded heat hazard and human exposure in risk assessment, which hinders the identification of high-risk areas at finer scales. A human settlement index integrated by nighttime light images, enhanced vegetation index, and digital elevation model data was utilized to assess the human exposure at high spatial resolution. Heat hazard and vulnerability index were generated by land surface temperature and demographic and socioeconomic census data, respectively. Spatially explicit assessment of heat health risk and its driving factors was conducted in the Yangtze River Delta (YRD), east China at 250 m pixel level. High-risk areas were mainly distributed in the urbanized areas of YRD, which were mostly driven by high human exposure and heat hazard index. In some less-urbanized cities and suburban and rural areas of mega-cities, the heat health risks are in second priority. The risks in some less-developed areas were high despite the low human exposure index because of high heat hazard and vulnerability index. This study illustrated a methodology for identifying high-risk areas by combining freely available multi-source data. Highly urbanized areas were considered hotspots of high heat health risks, which were largely driven by the increasing urban heat island effects and population density in urban areas. Repercussions of overheating were weakened due to the low social vulnerability in some central areas benefitting from the low proportion of sensitive population or the high level of socioeconomic development. By contrast, high social vulnerability intensifies heat health risks in some less-urbanized cities and suburban areas of mega-cities.

Present and Future of Dengue Fever in Nepal: Mapping Climatic Suitability by Ecological Niche Model

PubMed Central

Cao, Chunxiang; Xu, Min; Pandit, Shreejana

2018-01-01

Both the number of cases of dengue fever and the areas of outbreaks within Nepal have increased significantly in recent years. Further expansion and range shift is expected in the future due to global climate change and other associated factors. However, due to limited spatially-explicit research in Nepal, there is poor understanding about the present spatial distribution patterns of dengue risk areas and the potential range shift due to future climate change. In this context, it is crucial to assess and map dengue fever risk areas in Nepal. Here, we used reported dengue cases and a set of bioclimatic variables on the MaxEnt ecological niche modeling approach to model the climatic niche and map present and future (2050s and 2070s) climatically suitable areas under different representative concentration pathways (RCP2.6, RCP6.0 and RCP8.5). Simulation-based estimates suggest that climatically suitable areas for dengue fever are presently distributed throughout the lowland Tarai from east to west and in river valleys at lower elevations. Under the different climate change scenarios, these areas will be slightly shifted towards higher elevation with varied magnitude and spatial patterns. Population exposed to climatically suitable areas of dengue fever in Nepal is anticipated to further increase in both 2050s and 2070s on all the assumed emission scenarios. These findings could be instrumental to plan and execute the strategic interventions for controlling dengue fever in Nepal. PMID:29360797

Spatial distribution of mumps in South Korea, 2001-2015: identifying clusters and population risk factors.

PubMed

Choe, Y-J; Min, K; Cho, S-I

2017-07-01

In South Korea, the resurgence of mumps was noted primarily among school-aged children and adolescents since 2000. We analyzed spatial patterns in mumps incidence to give an indication to the geographical risk. We used National Notifiable Disease Surveillance System data from 2001 to 2015, classifying into three periods according to the level of endemicity. A geographic-weighted regression analysis was performed to find demographic predictors of mumps incidence according to district level. We assessed the association between the total population size, population density, percentage of children (age 0-19 years), timely vaccination rate of measles-mumps-rubella vaccines and the higher incidence rate of mumps. During low endemic periods, there were sporadic regional distributions of outbreak in the central and northern part of the country. During intermediate endemic periods, the increase of incidence was noted across the country. During high endemic period, a nationwide high incidence of mumps was noted especially concentrated in southwestern regions. A clear pattern for the mumps cluster shown through global spatial autocorrelation analysis from 2004 to 2015. The 'non-timely vaccination coverage' (P = 0·002), and 'proportion of children population' (P < 0·001) were the predictors for high mumps incidence in district levels. Our study indicates that the rate of mumps incidence according to geographic regions vary by population proportion and neighboring regions, and timeliness of vaccination, suggesting the importance of community-level surveillance and improving of timely vaccination.

Spatial trends and pollution assessment for mercury in the surface soils of the Nansi Lake catchment, China.

PubMed

Ren, Ming-Yi; Yang, Li-Yuan; Wang, Long-Feng; Han, Xue-Mei; Dai, Jie-Rui; Pang, Xu-Gui

2018-01-01

Surface soil samples collected from Nansi Lake catchment were analyzed for mercury (Hg) to determine its spatial trends and environmental impacts. Results showed that the average soil Hg contents were 0.043 mg kg -1 . A positive correlation was shown between TOC and soil Hg contents. The main type of soil with higher TOC contents and lower pH values showed higher soil Hg contents. Soil TOC contents and CV values were both higher in the eastern catchment. The eastern part of the catchment, where the industry is developed, had relatively high soil Hg contents and a banding distribution of high Hg contents was corresponded with the southwest-northeast economic belt. Urban soils had higher Hg contents than rural soils. The urbanization pattern that soil Hg contents presented a decreasing trend from city center to suburb was shown clearly especially in the three cities. Soil Hg contents in Jining City showed a good consistency with the urban land expansion. The spatial trends of soil Hg contents in the catchment indicated that the type and the intensity of human activities have a strong influence on the distribution of Hg in soils. Calculated risk indices showed that the western part of the catchment presented moderately polluted condition and the eastern part of the catchment showed moderate to strong pollution level. The area with high ecological risk appeared mainly along the economic belt.

Spatial distribution of environmental risk associated to a uranium abandoned mine (Central Portugal)

NASA Astrophysics Data System (ADS)

Antunes, I. M.; Ribeiro, A. F.

2012-04-01

The abandoned uranium mine of Canto do Lagar is located at Arcozelo da Serra, central Portugal. The mine was exploited in an open pit and produced about 12430Kg of uranium oxide (U3O8), between 1987 and 1988. The dominant geological unit is the porphyritic coarse-grained two-mica granite, with biotite>muscovite. The uranium deposit consists of two gaps crushing, parallel to the coarse-grained porphyritic granite, with average direction N30°E, silicified, sericitized and reddish jasperized, with a width of approximately 10 meters. These gaps are accompanied by two thin veins of white quartz, 70°-80° WNW, ferruginous and jasperized with chalcedony, red jasper and opal. These veins are about 6 meters away from each other. They contain secondary U-phosphates phases such as autunite and torbernite. Rejected materials (1000000ton) were deposited on two dumps and a lake was formed in the open pit. To assess the environmental risk of the abandoned uranium mine of Canto do Lagar, were collected and analysed 70 samples on stream sediments, soils and mine tailings materials. The relation between samples composition were tested using the Principal Components Analysis (PCA) (multivariate analysis) and spatial distribution using Kriging Indicator. The spatial distribution of stream sediments shows that the probability of expression for principal component 1 (explaining Y, Zr, Nb, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Hf, Th and U contents), decreases along SE-NW direction. This component is explained by the samples located inside mine influence. The probability of expression for principal component 2 (explaining Be, Na, Al, Si, P, K, Ca, Ti, Mn, Fe, Co, Ni, Cu, As, Rb, Sr, Mo, Cs, Ba, Tl and Bi contents), increases to middle stream line. This component is explained by the samples located outside mine influence. The spatial distribution of soils, shows that the probability of expression for principal component 1 (explaining Mg, P, Ca, Ge, Sr, Y, Zr, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, Hf, W, Th and U contents) decreases along SE direction and increases along NE and SW directions. The probability of expression for principal component 2 (explaining pH, K, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Sr and Pb contents), decreases from central points (inside mine influence) to peripheral points (outside mine influence) and gradually increases along N and SW directions. The spatial distribution of tailing materials did not allowed a consistent spatial distribution. In general, the stream sediments are classified as unpolluted and not polluted or moderately polluted, according to geoaccumulation Müller index with exception of local samples, located inside mine influence. The soils cannot be used for public, private or residential uses according to the Canadian soil legislation. However, almost samples can be used for commercial or industrial occupation. According to the target values and intervention values for soils remediation, these soils need intervention. Tailing materials samples are much polluted in thorium (Th) and uranium (U) and they cannot be used for public, private or residential uses.

National spatial and temporal patterns of notified dengue cases, Colombia 2007-2010.

PubMed

Restrepo, Angela Cadavid; Baker, Peter; Clements, Archie C A

2014-07-01

To explore the variation in the spatial distribution of notified dengue cases in Colombia from January 2007 to December 2010 and examine associations between the disease and selected environmental risk factors. Data on the number of notified dengue cases in Colombia were obtained from the National Institute of Health (Instituto Nacional de Salud - INS) for the period 1 January 2007 through 31 December 2010. Data on environmental factors were collected from the Worldclim website. A Bayesian spatio-temporal conditional autoregressive model was used to quantify the relationship between monthly dengue cases and temperature, precipitation and elevation. Monthly dengue counts decreased by 18% (95% credible interval (CrI): 17-19%) in 2008 and increased by 30% (95% CrI: 28-31%) and 326% (95% CrI: 322-331%) in 2009 and 2010, respectively, compared to 2007. Additionally, there was a significant, nonlinear effect of monthly average precipitation. The results highlight the role of environmental risk factors in determining the spatial of dengue and show how these factors can be used to develop and refine preventive approaches for dengue in Colombia. © 2014 John Wiley & Sons Ltd.

Identification of a potential toxic hot spot associated with AVS spatial and seasonal variation.

PubMed

Campana, O; Rodríguez, A; Blasco, J

2009-04-01

In risk assessment of aquatic sediments, much attention is paid to the difference between acid-volatile sulfide (AVS) and simultaneously extracted metals (SEMs) as indicators of metal availability. Ten representative sampling sites were selected along the estuary of the Guadalete River. Surficial sediments were sampled in winter and summer to better understand SEM and AVS spatial and seasonal distributions and to establish priority risk areas. Total SEM concentration (SigmaSEM) ranged from 0.3 to 4.7 micromol g(-1). It was not significantly different between seasons, however, it showed a significant difference between sampling stations. AVS concentrations were much more variable, showing significant spatial and temporal variations. The values ranged from 0.8 to 22.4 micromol g(-1). The SEM/AVS ratio was found to be <1 at all except one station located near the mouth of the estuary. The results provided information on a potential pollution source near the mouth of the estuary, probably associated with vessel-related activities carried out in a local harbor area located near the station.

Time-dependent landslide probability mapping

USGS Publications Warehouse

Campbell, Russell H.; Bernknopf, Richard L.; ,

1993-01-01

Case studies where time of failure is known for rainfall-triggered debris flows can be used to estimate the parameters of a hazard model in which the probability of failure is a function of time. As an example, a time-dependent function for the conditional probability of a soil slip is estimated from independent variables representing hillside morphology, approximations of material properties, and the duration and rate of rainfall. If probabilities are calculated in a GIS (geomorphic information system ) environment, the spatial distribution of the result for any given hour can be displayed on a map. Although the probability levels in this example are uncalibrated, the method offers a potential for evaluating different physical models and different earth-science variables by comparing the map distribution of predicted probabilities with inventory maps for different areas and different storms. If linked with spatial and temporal socio-economic variables, this method could be used for short-term risk assessment.

Spatial modelling of arsenic distribution and human health effects in Lake Victoria basin, Tanzania

NASA Astrophysics Data System (ADS)

Ijumulana, Julian; Mtalo, Felix; Bhattacharya, Prosun

2016-04-01

Increasing incidences of naturally occurring geogenic pollutants in drinking water sources and associated human health risks are the two major challenges requiring detailed knowledge to support decision making process at various levels. The presence, location and extent of environmental contamination is needed towards developing mitigation measures to achieve required standards. In this study we are developing a GIS-based model to detect and predict drinking water pollutants at the identified hotspots and monitor its variation in space. In addition, the mobility of pollutants within the affected region needs to be evaluated using topographic and hydrogeological data. Based on these geospatial data on contaminant distribution, spatial relationship of As and F contamination and reported human health effects such as dental caries, dental fluorosis, skeletal fluorosis and bone crippling, skin and other cancers etc. can be modeled for potential interventions for safe drinking water supplies.

Surveillance of the colorectal cancer disparities among demographic subgroups: a spatial analysis.

PubMed

Hsu, Chiehwen Ed; Mas, Francisco Soto; Hickey, Jessica M; Miller, Jerry A; Lai, Dejian

2006-09-01

The literature suggests that colorectal cancer mortality in Texas is distributed inhomogeneously among specific demographic subgroups and in certain geographic regions over an extended period. To understand the extent of the demographic and geographic disparities, the present study examined colorectal cancer mortality in 15 demographic groups in Texas counties between 1990 and 2001. The Spatial Scan Statistic was used to assess the standardized mortality ratio, duration and age-adjusted rates of excess mortality, and their respective p-values for testing the null hypothesis of homogeneity of geographic and temporal distribution. The study confirmed the excess mortality in some Texas counties found in the literature, identified 13 additional excess mortality regions, and found 4 health regions with persistent excess mortality involving several population subgroups. Health disparities of colorectal cancer mortality continue to exist in Texas demographic subpopulations. Health education and intervention programs should be directed to the at-risk subpopulations in the identified regions.

Enrichment, spatial distribution of potential ecological and human health risk assessment via toxic metals in soil and surface water ingestion in the vicinity of Sewakht mines, district Chitral, Northern Pakistan.

PubMed

Rehman, Inayat Ur; Ishaq, Muhammad; Ali, Liaqat; Khan, Sardar; Ahmad, Imtiaz; Din, Imran Ud; Ullah, Hameed

2018-06-15

This study focuses on enrichment, spatial distribution, potential ecological risk index (PERI) and human health risk of various toxic metals taken via soil and surface water in the vicinity of Sewakht mines, Pakistan. The samples of soils (n = 54) of different fields and surface water (n = 38) were analyzed for toxic metals including cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), lead (Pb), nickel (Ni), zinc (Zn) and molybdenum (Mo). Soil pollution level was evaluated using pollution indices including geo-accumulation index (Igeo), contamination factor (CF), degree of contamination (CD), enrichment factor (EF) and PERI. CF showed moderate contamination of soil with Cd, Co, Fe and Mo, while Igeo values indicated moderate accumulation of Cu. For Cd, EF> 1.5 was found in agricultural soils of the study area. PERI findings presented a very high ecological risk (PERI > 380) at two sites (4%), considerable ecological risk at four sites (7.4%). Non-carcinogenic risk from exposure to Fe in soil was higher than limit (HI > 1) for both children and adults. Moreover, carcinogenic risk postured by soil contaminants i.e. Cd, Cr, Co and Ni in children was higher than their limits (except Pb), while in adults only Co posed higher risk of cancer than the limit (10 -4 ) through soil exposure. Non-carcinogenic risks in children due to Cd, Co, Mo via surface water intake were higher than their safe limits (HQ > 1), while in adults the risk order was Cr > Cd > Cu > Pb > Co > Mo. Moreover, carcinogenic risk exposure due to Co > Cd > Cr > Ni from surface water (except Pb) was higher than the tolerable limit (1 × 10 -4 ) both for children and adults. However, Pb concentrations in both soil and surface water exposure were not likely to cause cancer risk in the local population. Copyright © 2018 Elsevier Inc. All rights reserved.

Analysis of Dynamic Characteristics of the 21st Century Maritime Silk Road

NASA Astrophysics Data System (ADS)

Zhang, Xudong; Zhang, Jie; Fan, Chenqing; Meng, Junmin; Wang, Jing; Wan, Yong

2018-06-01

The 21st century Maritime Silk Road (MSR) proposed by China strongly promotes the maritime industry. In this paper, we use wind and ocean wave datasets from 1979 to 2014 to analyze the spatial and temporal distributions of the wind speed, significant wave height (SWH), mean wave direction (MWD), and mean wave period (MWP) in the MSR. The analysis results indicate that the Luzon Strait and Gulf of Aden have the most obvious seasonal variations and that the central Indian Ocean is relatively stable. We analyzed the distributions of the maximum wind speed and SWH in the MSR over this 36-year period. The results show that the distribution of the monthly average frequency for SWH exceeds 4 m (huge waves) and that of the corresponding wind speed exceeds 13.9 m s-1 (high wind speed). The occurrence frequencies of huge waves and high winds in regions east of the Gulf of Aden are as high as 56% and 80%, respectively. We also assessed the wave and wind energies in different seasons. Based on our analyses, we propose a risk factor (RF) for determining navigation safety levels, based on the wind speed and SWH. We determine the spatial and temporal RF distributions for different seasons and analyze the corresponding impact on four major sea routes. Finally, we determine the spatial distribution of tropical cyclones from 2000 to 2015 and analyze the corresponding impact on the four sea routes. The analysis of the dynamic characteristics of the MSR provides references for ship navigation as well as ocean engineering.

Failure-probability driven dose painting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vogelius, Ivan R.; Håkansson, Katrin; Due, Anne K.

Purpose: To demonstrate a data-driven dose-painting strategy based on the spatial distribution of recurrences in previously treated patients. The result is a quantitative way to define a dose prescription function, optimizing the predicted local control at constant treatment intensity. A dose planning study using the optimized dose prescription in 20 patients is performed.Methods: Patients treated at our center have five tumor subvolumes from the center of the tumor (PET positive volume) and out delineated. The spatial distribution of 48 failures in patients with complete clinical response after (chemo)radiation is used to derive a model for tumor control probability (TCP). Themore » total TCP is fixed to the clinically observed 70% actuarial TCP at five years. Additionally, the authors match the distribution of failures between the five subvolumes to the observed distribution. The steepness of the dose–response is extracted from the literature and the authors assume 30% and 20% risk of subclinical involvement in the elective volumes. The result is a five-compartment dose response model matching the observed distribution of failures. The model is used to optimize the distribution of dose in individual patients, while keeping the treatment intensity constant and the maximum prescribed dose below 85 Gy.Results: The vast majority of failures occur centrally despite the small volumes of the central regions. Thus, optimizing the dose prescription yields higher doses to the central target volumes and lower doses to the elective volumes. The dose planning study shows that the modified prescription is clinically feasible. The optimized TCP is 89% (range: 82%–91%) as compared to the observed TCP of 70%.Conclusions: The observed distribution of locoregional failures was used to derive an objective, data-driven dose prescription function. The optimized dose is predicted to result in a substantial increase in local control without increasing the predicted risk of toxicity.« less

Tree cover at fine and coarse spatial grains interacts with shade tolerance to shape plant species distributions across the Alps

PubMed Central

Nieto-Lugilde, Diego; Lenoir, Jonathan; Abdulhak, Sylvain; Aeschimann, David; Dullinger, Stefan; Gégout, Jean-Claude; Guisan, Antoine; Pauli, Harald; Renaud, Julien; Theurillat, Jean-Paul; Thuiller, Wilfried; Van Es, Jérémie; Vittoz, Pascal; Willner, Wolfgang; Wohlgemuth, Thomas; Zimmermann, Niklaus E.; Svenning, Jens-Christian

2015-01-01

The role of competition for light among plants has long been recognised at local scales, but its importance for plant species distributions at larger spatial scales has generally been ignored. Tree cover modifies the local abiotic conditions below the canopy, notably by reducing light availability, and thus, also the performance of species that are not adapted to low-light conditions. However, this local effect may propagate to coarser spatial grains, by affecting colonisation probabilities and local extinction risks of herbs and shrubs. To assess the effect of tree cover at both the plot- and landscape-grain sizes (approximately 10-m and 1-km), we fit Generalised Linear Models (GLMs) for the plot-level distributions of 960 species of herbs and shrubs using 6,935 vegetation plots across the European Alps. We ran four models with different combinations of variables (climate, soil and tree cover) at both spatial grains for each species. We used partial regressions to evaluate the independent effects of plot- and landscape-grain tree cover on plot-level plant communities. Finally, the effects on species-specific elevational range limits were assessed by simulating a removal experiment comparing the species distributions under high and low tree cover. Accounting for tree cover improved the model performance, with the probability of the presence of shade-tolerant species increasing with increasing tree cover, whereas shade-intolerant species showed the opposite pattern. The tree cover effect occurred consistently at both the plot and landscape spatial grains, albeit most strongly at the former. Importantly, tree cover at the two grain sizes had partially independent effects on plot-level plant communities. With high tree cover, shade-intolerant species exhibited narrower elevational ranges than with low tree cover whereas shade-tolerant species showed wider elevational ranges at both limits. These findings suggest that forecasts of climate-related range shifts for herb and shrub species may be modified by tree cover dynamics. PMID:26290621

Meteorological risks as drivers of innovation for agroecosystem management

NASA Astrophysics Data System (ADS)

Gobin, Anne; Van de Vyver, Hans; Zamani, Sepideh; Curnel, Yannick; Planchon, Viviane; Verspecht, Ann; Van Huylenbroeck, Guido

2015-04-01

Devastating weather-related events recorded in recent years have captured the interest of the general public in Belgium. The MERINOVA project research hypothesis is that meteorological risks act as drivers of environmental innovation in agro-ecosystem management which is being tested using a "chain of risk" approach. The major objectives are to (1) assess the probability of extreme meteorological events by means of probability density functions; (2) analyse the extreme events impact of on agro-ecosystems using process-based bio-physical modelling methods; (3) identify the most vulnerable agro-ecosystems using fuzzy multi-criteria and spatial analysis; (4) uncover innovative risk management and adaptation options using actor-network theory and economic modelling; and, (5) communicate to research, policy and practitioner communities using web-based techniques. Generalized Extreme Value (GEV) theory was used to model annual rainfall maxima based on location-, scale- and shape-parameters that determine the centre of the distribution, the deviation of the location-parameter and the upper tail decay, respectively. Likewise the distributions of consecutive rainy days, rainfall deficits and extreme 24-hour rainfall were modelled. Spatial interpolation of GEV-derived return levels resulted in maps of extreme precipitation, precipitation deficits and wet periods. The degree of temporal overlap between extreme weather conditions and sensitive periods in the agro-ecosystem was determined using a bio-physically based modelling framework that couples phenological models, a soil water balance, crop growth and environmental models. 20-year return values were derived for frost, heat stress, drought, waterlogging and field access during different sensitive stages for different arable crops. Extreme yield values were detected from detrended long term arable yields and relationships were found with soil moisture conditions, heat stress or other meteorological variables during the season. A methodology for identifying agro-ecosystem vulnerability was developed using spatially explicit information and was tested for arable crop production in Belgium. The different components of vulnerability for a region include spatial information on meteorology, soil available water content, soil erosion, the degree of waterlogging, crop share and the diversity of potato varieties. The level of vulnerability and resilience of an agro-ecosystem is also determined by risk management. The types of agricultural risk and their relative importance differ across sectors and farm types. Risk types are further distinguished according to production, market, institutional, financial and liability risks. Strategies are often combined in the risk management strategy of a farmer and include reduction and prevention, mitigation, coping and impact reduction. Based on an extensive literature review, a portfolio of potential strategies was identified at farm, market and policy level. Research hypotheses were tested using an on-line questionnaire on knowledge of agricultural risk, measuring the general risk aversion of the farmer and risk management strategies. The "chain of risk" approach adopted as a research methodology allows for investigating the hypothesis that meteorological risks act as drivers for agricultural innovation. Risks related to extreme weather events in Belgium are mainly caused by heat, frost, excess rainfall, drought and storms, and their impact is predominantly felt by arable, horticultural and extensive dairy farmers. Quantification of the risk is evaluated in terms of probability of occurrence, magnitude, frequency and extent of impact on several agro-ecosystems services. The spatial extent of vulnerability is developed by integrating different layers of geo-information, while risk management is analysed using questionnaires and economic modelling methods. Future work will concentrate on the further development and testing of the currently developed modelling methodologies. https://merinova.vito.be The research is funded by the Belgian Science Policy Organisation (Belspo) under contract nr SD/RI/03A.

Spatial distribution of traffic in a cellular mobile data network

NASA Astrophysics Data System (ADS)

Linnartz, J. P. M. G.

1987-02-01

The use of integral transforms of the probability density function for the received power to analyze the relation between the spatial distributions of offered and throughout packet traffic in a mobile radio network with Rayleigh fading channels and ALOHA multiple access was assessed. A method to obtain the spatial distribution of throughput traffic from a prescribed spatial distribution of offered traffic is presented. Incoherent and coherent addition of interference signals is considered. The channel behavior for heavy traffic loads is studied. In both the incoherent and coherent case, the spatial distribution of offered traffic required to ensure a prescribed spatially uniform throughput is synthesized numerically.

Childhood cancer in small geographical areas and proximity to air-polluting industries.

PubMed

Ortega-García, Juan A; López-Hernández, Fernando A; Cárceles-Álvarez, Alberto; Fuster-Soler, José L; Sotomayor, Diana I; Ramis, Rebeca

2017-07-01

Pediatric cancer has been associated with exposure to certain environmental carcinogens. The purpose of this work is to analyse the relationship between environmental pollution and pediatric cancer risk. We analysed all incidences of pediatric cancer (<15) diagnosed in a Spanish region during the period 1998-2015. The place of residence of each patient and the exact geographical coordinates of main industrial facilities was codified in order to analyse the spatial distribution of cases of cancer in relation to industrial areas. Focal tests and focused Scan methodology were used for the identification of high-incidence-rate spatial clusters around the main industrial pollution foci. The crude rate for the period was 148.0 cases per 1,000,0000 children. The incidence of pediatric cancer increased significantly along the period of study. With respect to spatial distribution, results showed significant high incidence around some industrial pollution foci group and the Scan methodology identify spatial clustering. We observe a global major incidence of non Hodgkin lymphomas (NHL) considering all foci, and high incidence of Sympathetic Nervous System Tumour (SNST) around Energy and Electric and organic and inorganic chemical industries foci group. In the analysis foci to foci, the focused Scan test identifies several significant spatial clusters. Particularly, three significant clusters were identified: the first of SNST was around energy-generating chemical industries (2 cases versus the expected 0.26), another of NHL was around residue-valorisation plants (5 cases versus the expected 0.91) and finally one cluster of Hodgkin lymphoma around building materials (3 cases versus the expected 2.2) CONCLUSION: Results suggest a possible association between proximity to certain industries and pediatric cancer risk. More evidences are necessary before establishing the relationship between industrial pollution and pediatric cancer incidence. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Risk assessment of salinity and turbidity in Victoria (Australia) to stream insects' community structure does not always protect functional traits.

PubMed

Kefford, Ben J; Schäfer, Ralf B; Metzeling, Leon

2012-01-15

Ecological risk assessments mostly consider measures of community composition (structure) across large spatial scales. These assessments, using species sensitivity distributions (SSDs) or the relative species retention (RSR), may not be protective of ecosystem functions and services at smaller spatial scales. Here we examine how changes in biological traits, as proxy for ecosystem functions/services, at a fine spatial scale relate to larger scale assessment of structure. We use functional traits of stream insect species in south-east Australia in two habitats (riffle and edge/pool). We find that the protection of community structure in terms of 95% of species over multiple sites against adverse effects of salinity (as electrical conductivity) and turbidity will mostly, but not always, protect traits at smaller scales. Considering different combinations of trait modalities, contaminants and habitat, a mean of 17.5% (range 0%-36.8) of cases would result in under-protection of trait modalities despite protecting species composition (in terms of Jaccard's Index). This under-protection of trait modalities is only because of the different spatial scales that community structure and the traits were considered. We recommend that where the protection of biological traits, ecosystem functions or ecosystem services from stressors is a management goal, protective targets should not be solely set using measures of community structure such as SSDs or RSR. To protect both structural and functional attributes separate risk assessments should be done. Copyright © 2011 Elsevier B.V. All rights reserved.

Spatial Analysis of Feline Immunodeficiency Virus Infection in Cougars

PubMed Central

Wheeler, David C.; Waller, Lance A.; Biek, Roman

2010-01-01

The cougar (Puma concolor) is a large predatory feline found widely in the Americas that is susceptible to feline immunodeficiency virus (FIV), a fast-evolving lentivirus found in wild feline species that is analogous to simian immunodeficiency viruses in wild primates and belongs to the same family of viruses as human immunodeficiency virus. FIV infection in cougars can lead to a weakened immune system that creates opportunities for other infecting agents. FIV prevalence and lineages have been studied previously in several areas in the western United States, but typically without spatially explicit statistical techniques. To describe the distribution of FIV in a sample of cougars located in the northern Rocky Mountain region of North America, we first used kernel density ratio estimation to map the log relative risk of FIV. The risk surface showed a significant cluster of FIV in northwestern Montana. We also used Bayesian cluster models for genetic data to investigate the spatial structure of the feline immunodeficiency virus with virus genetic sequence data. A result of the models was two spatially distinct FIV lineages that aligned considerably with an interstate highway in Montana. Our results suggest that the use of spatial information and models adds novel insight when investigating an infectious animal disease. The results also suggest that the influence of landscape features likely plays an important role in the spatiotemporal spread of an infectious disease within wildlife populations. PMID:21197421

Spatial analysis of feline immunodeficiency virus infection in cougars.

PubMed

Wheeler, David C; Waller, Lance A; Biek, Roman

2010-07-01

The cougar (Puma concolor) is a large predatory feline found widely in the Americas that is susceptible to feline immunodeficiency virus (FIV), a fast-evolving lentivirus found in wild feline species that is analogous to simian immunodeficiency viruses in wild primates and belongs to the same family of viruses as human immunodeficiency virus. FIV infection in cougars can lead to a weakened immune system that creates opportunities for other infecting agents. FIV prevalence and lineages have been studied previously in several areas in the western United States, but typically without spatially explicit statistical techniques. To describe the distribution of FIV in a sample of cougars located in the northern Rocky Mountain region of North America, we first used kernel density ratio estimation to map the log relative risk of FIV. The risk surface showed a significant cluster of FIV in northwestern Montana. We also used Bayesian cluster models for genetic data to investigate the spatial structure of the feline immunodeficiency virus with virus genetic sequence data. A result of the models was two spatially distinct FIV lineages that aligned considerably with an interstate highway in Montana. Our results suggest that the use of spatial information and models adds novel insight when investigating an infectious animal disease. The results also suggest that the influence of landscape features likely plays an important role in the spatiotemporal spread of an infectious disease within wildlife populations.

Unmanned Aircraft Systems for Studying Spatial Abundance of Ungulates: Relevance to Spatial Epidemiology

PubMed Central

Barasona, José A.; Mulero-Pázmány, Margarita; Acevedo, Pelayo; Negro, Juan J.; Torres, María J.; Gortázar, Christian; Vicente, Joaquín

2014-01-01

Complex ecological and epidemiological systems require multidisciplinary and innovative research. Low cost unmanned aircraft systems (UAS) can provide information on the spatial pattern of hosts’ distribution and abundance, which is crucial as regards modelling the determinants of disease transmission and persistence on a fine spatial scale. In this context we have studied the spatial epidemiology of tuberculosis (TB) in the ungulate community of Doñana National Park (South-western Spain) by modelling species host (red deer, fallow deer and cattle) abundance at fine spatial scale. The use of UAS high-resolution images has allowed us to collect data to model the environmental determinants of host abundance, and in a further step to evaluate their relationships with the spatial risk of TB throughout the ungulate community. We discuss the ecological, epidemiological and logistic conditions under which UAS may contribute to study the wildlife/livestock sanitary interface, where the spatial aggregation of hosts becomes crucial. These findings are relevant for planning and implementing research, fundamentally when managing disease in multi-host systems, and focusing on risky areas. Therefore, managers should prioritize the implementation of control strategies to reduce disease of conservation, economic and social relevance. PMID:25551673

Spatial-Temporal Dynamics of Urban Fire Incidents: a Case Study of Nanjing, China

NASA Astrophysics Data System (ADS)

Yao, J.; Zhang, X.

2016-06-01

Fire and rescue service is one of the fundamental public services provided by government in order to protect people, properties and environment from fires and other disasters, and thus promote a safer living environment. Well understanding spatial-temporal dynamics of fire incidents can offer insights for potential determinants of various fire events and enable better fire risk estimation, assisting future allocation of prevention resources and strategic planning of mitigation programs. Using a 12-year (2002-2013) dataset containing the urban fire events in Nanjing, China, this research explores the spatial-temporal dynamics of urban fire incidents. A range of exploratory spatial data analysis (ESDA) approaches and tools, such as spatial kernel density and co-maps, are employed to examine the spatial, temporal and spatial-temporal variations of the fire events. Particular attention has been paid to two types of fire incidents: residential properties and local facilities, due to their relatively higher occurrence frequencies. The results demonstrated that the amount of urban fire has greatly increased in the last decade and spatial-temporal distribution of fire events vary among different incident types, which implies varying impact of potential influencing factors for further investigation.

Cellular burdens and biological effects on tissue level caused by inhaled radon progenies.

PubMed

Madas, B G; Balásházy, I; Farkas, Á; Szoke, I

2011-02-01

In the case of radon exposure, the spatial distribution of deposited radioactive particles is highly inhomogeneous in the central airways. The object of this research is to investigate the consequences of this heterogeneity regarding cellular burdens in the bronchial epithelium and to study the possible biological effects at tissue level. Applying computational fluid and particle dynamics techniques, the deposition distribution of inhaled radon daughters has been determined in a bronchial airway model for 23 min of work in the New Mexico uranium mine corresponding to 0.0129 WLM exposure. A numerical epithelium model based on experimental data has been utilised in order to quantify cellular hits and doses. Finally, a carcinogenesis model considering cell death-induced cell-cycle shortening has been applied to assess the biological responses. Present computations reveal that cellular dose may reach 1.5 Gy, which is several orders of magnitude higher than tissue dose. The results are in agreement with the histological finding that the uneven deposition distribution of radon progenies may lead to inhomogeneous spatial distribution of tumours in the bronchial airways. In addition, at the macroscopic level, the relationship between cancer risk and radiation burden seems to be non-linear.

Accuracy and uncertainty analysis of soil Bbf spatial distribution estimation at a coking plant-contaminated site based on normalization geostatistical technologies.

PubMed

Liu, Geng; Niu, Junjie; Zhang, Chao; Guo, Guanlin

2015-12-01

Data distribution is usually skewed severely by the presence of hot spots in contaminated sites. This causes difficulties for accurate geostatistical data transformation. Three types of typical normal distribution transformation methods termed the normal score, Johnson, and Box-Cox transformations were applied to compare the effects of spatial interpolation with normal distribution transformation data of benzo(b)fluoranthene in a large-scale coking plant-contaminated site in north China. Three normal transformation methods decreased the skewness and kurtosis of the benzo(b)fluoranthene, and all the transformed data passed the Kolmogorov-Smirnov test threshold. Cross validation showed that Johnson ordinary kriging has a minimum root-mean-square error of 1.17 and a mean error of 0.19, which was more accurate than the other two models. The area with fewer sampling points and that with high levels of contamination showed the largest prediction standard errors based on the Johnson ordinary kriging prediction map. We introduce an ideal normal transformation method prior to geostatistical estimation for severely skewed data, which enhances the reliability of risk estimation and improves the accuracy for determination of remediation boundaries.

Novel Microbiological and Spatial Statistical Methods to Improve Strength of Epidemiological Evidence in a Community-Wide Waterborne Outbreak

PubMed Central

Jalava, Katri; Rintala, Hanna; Ollgren, Jukka; Maunula, Leena; Gomez-Alvarez, Vicente; Revez, Joana; Palander, Marja; Antikainen, Jenni; Kauppinen, Ari; Räsänen, Pia; Siponen, Sallamaari; Nyholm, Outi; Kyyhkynen, Aino; Hakkarainen, Sirpa; Merentie, Juhani; Pärnänen, Martti; Loginov, Raisa; Ryu, Hodon; Kuusi, Markku; Siitonen, Anja; Miettinen, Ilkka; Santo Domingo, Jorge W.; Hänninen, Marja-Liisa; Pitkänen, Tarja

2014-01-01

Failures in the drinking water distribution system cause gastrointestinal outbreaks with multiple pathogens. A water distribution pipe breakage caused a community-wide waterborne outbreak in Vuorela, Finland, July 2012. We investigated this outbreak with advanced epidemiological and microbiological methods. A total of 473/2931 inhabitants (16%) responded to a web-based questionnaire. Water and patient samples were subjected to analysis of multiple microbial targets, molecular typing and microbial community analysis. Spatial analysis on the water distribution network was done and we applied a spatial logistic regression model. The course of the illness was mild. Drinking untreated tap water from the defined outbreak area was significantly associated with illness (RR 5.6, 95% CI 1.9–16.4) increasing in a dose response manner. The closer a person lived to the water distribution breakage point, the higher the risk of becoming ill. Sapovirus, enterovirus, single Campylobacter jejuni and EHEC O157:H7 findings as well as virulence genes for EPEC, EAEC and EHEC pathogroups were detected by molecular or culture methods from the faecal samples of the patients. EPEC, EAEC and EHEC virulence genes and faecal indicator bacteria were also detected in water samples. Microbial community sequencing of contaminated tap water revealed abundance of Arcobacter species. The polyphasic approach improved the understanding of the source of the infections, and aided to define the extent and magnitude of this outbreak. PMID:25147923

Distribution, abundance and habitat use of deep diving cetaceans in the North-East Atlantic

NASA Astrophysics Data System (ADS)

Rogan, Emer; Cañadas, Ana; Macleod, Kelly; Santos, M. Begoña; Mikkelsen, Bjarni; Uriarte, Ainhize; Van Canneyt, Olivier; Vázquez, José Antonio; Hammond, Philip S.

2017-07-01

In spite of their oceanic habitat, deep diving cetacean species have been found to be affected by anthropogenic activities, with potential population impacts of high intensity sounds generated by naval research and oil prospecting receiving the most attention. Improving the knowledge of the distribution and abundance of this poorly known group is an essential prerequisite to inform mitigation strategies seeking to minimize their spatial and temporal overlap with human activities. We provide for the first time abundance estimates for five deep diving cetacean species (sperm whale, long-finned pilot whale, northern bottlenose whale, Cuvier's beaked whale and Sowerby's beaked whale) using data from three dedicated cetacean sighting surveys that covered the oceanic and shelf waters of the North-East Atlantic. Density surface modelling was used to obtain model-based estimates of abundance and to explore the physical and biological characteristics of the habitat used by these species. Distribution of all species was found to be significantly related to depth, distance from the 2000m depth contour, the contour index (a measure of variability in the seabed) and sea surface temperature. Predicted distribution maps also suggest that there is little spatial overlap between these species. Our results represent the best abundance estimates for deep-diving whales in the North-East Atlantic, predict areas of high density during summer and constitute important baseline information to guide future risk assessments of human activities on these species, evaluate potential spatial and temporal trends and inform EU Directives and future conservation efforts.

Exploring Spatial and Temporal Distribution of Cutaneous Leishmaniasis in the Americas, 2001-2011.

PubMed

Maia-Elkhoury, Ana Nilce Silveira; E Yadón, Zaida; Idali Saboyá Díaz, Martha; de Fátima de Araújo Lucena, Francisca; Gerardo Castellanos, Luis; J Sanchez-Vazquez, Manuel

2016-11-01

Cases reported in the period of 2001-2011 from 14/18 CL endemic countries were included in this study by using two spreadsheet to collect the data. Two indicators were analyzed: CL cases and incidence rate. The local regression method was used to analyze case trends and incidence rates for all the studied period, and for 2011 the spatial distribution of each indicator was analyzed by quartile and stratified into four groups. From 2001-2011, 636,683 CL cases were reported by 14 countries and with an increase of 30% of the reported cases. The average incidence rate in the Americas was 15.89/100,000 inhabitants. In 2011, 15 countries reported cases in 180 from a total of 292 units of first subnational level. The global incidence rate for all countries was 17.42 cases per 100,000 inhabitants; while in 180 administrative units at the first subnational level, the average incidence rate was 57.52/100,000 inhabitants. Nicaragua and Panama had the highest incidence but more cases occurred in Brazil and Colombia. Spatial distribution was heterogeneous for each indicator, and when analyzed in different administrative level. The results showed different distribution patterns, illustrating the limitation of the use of individual indicators and the need to classify higher-risk areas in order to prioritize the actions. This study shows the epidemiological patterns using secondary data and the importance of using multiple indicators to define and characterize smaller territorial units for surveillance and control of leishmaniasis.

Epidemiological features and risk factors associated with the spatial and temporal distribution of human brucellosis in China

PubMed Central

2013-01-01

Background Human brucellosis incidence in China has been increasing dramatically since 1999. However, epidemiological features and potential factors underlying the re-emergence of the disease remain less understood. Methods Data on human and animal brucellosis cases at the county scale were collected for the year 2004 to 2010. Also collected were environmental and socioeconomic variables. Epidemiological features including spatial and temporal patterns of the disease were characterized, and the potential factors related to the spatial heterogeneity and the temporal trend of were analysed using Poisson regression analysis, Granger causality analysis, and autoregressive distributed lag (ADL) models, respectively. Results The epidemic showed a significantly higher spatial correlation with the number of sheep and goats than swine and cattle. The disease was most prevalent in grassland areas with elevation between 800–1,600 meters. The ADL models revealed that local epidemics were correlated with comparatively lower temperatures and less sunshine in winter and spring, with a 1–7 month lag before the epidemic peak in May. Conclusions Our findings indicate that human brucellosis tended to occur most commonly in grasslands at moderate elevation where sheep and goats were the predominant livestock, and in years with cooler winter and spring or less sunshine. PMID:24238301

Exploring the impact of climate variability during the Last Glacial Maximum on the pattern of human occupation of Iberia.

PubMed

Burke, Ariane; Levavasseur, Guillaume; James, Patrick M A; Guiducci, Dario; Izquierdo, Manuel Arturo; Bourgeon, Lauriane; Kageyama, Masa; Ramstein, Gilles; Vrac, Mathieu

2014-08-01

The Last Glacial Maximum (LGM) was a global climate event, which had significant repercussions for the spatial distribution and demographic history of prehistoric populations. In Eurasia, the LGM coincides with a potential bottleneck for modern humans and may mark the divergence date for Asian and European populations (Keinan et al., 2007). In this research, the impact of climate variability on human populations in the Iberian Peninsula during the Last Glacial Maximum (LGM) is examined with the aid of downscaled high-resolution (16 × 16 km) numerical climate experiments. Human sensitivity to short time-scale (inter-annual) climate variability during this key time period, which follows the initial modern human colonisation of Eurasia and the extinction of the Neanderthals, is tested using the spatial distribution of archaeological sites. Results indicate that anatomically modern human populations responded to small-scale spatial patterning in climate variability, specifically inter-annual variability in precipitation levels as measured by the standard precipitation index. Climate variability at less than millennial scale, therefore, is shown to be an important component of ecological risk, one that played a role in regulating the spatial behaviour of prehistoric human populations and consequently affected their social networks. Copyright © 2014 Elsevier Ltd. All rights reserved.

Using remote sensing to map larval and adult populations of Anopheles hyrcanus (Diptera: Culicidae) a potential malaria vector in Southern France

PubMed Central

Tran, Annelise; Ponçon, Nicolas; Toty, Céline; Linard, Catherine; Guis, Hélène; Ferré, Jean-Baptiste; Lo Seen, Danny; Roger, François; de la Rocque, Stéphane; Fontenille, Didier; Baldet, Thierry

2008-01-01

Background Although malaria disappeared from southern France more than 60 years ago, suspicions of recent autochthonous transmission in the French Mediterranean coast support the idea that the area could still be subject to malaria transmission. The main potential vector of malaria in the Camargue area, the largest river delta in southern France, is the mosquito Anopheles hyrcanus (Diptera: Culicidae). In the context of recent climatic and landscape changes, the evaluation of the risk of emergence or re-emergence of such a major disease is of great importance in Europe. When assessing the risk of emergence of vector-borne diseases, it is crucial to be able to characterize the arthropod vector's spatial distribution. Given that remote sensing techniques can describe some of the environmental parameters which drive this distribution, satellite imagery or aerial photographs could be used for vector mapping. Results In this study, we propose a method to map larval and adult populations of An. hyrcanus based on environmental indices derived from high spatial resolution imagery. The analysis of the link between entomological field data on An. hyrcanus larvae and environmental indices (biotopes, distance to the nearest main productive breeding sites of this species i.e., rice fields) led to the definition of a larval index, defined as the probability of observing An. hyrcanus larvae in a given site at least once over a year. Independent accuracy assessments showed a good agreement between observed and predicted values (sensitivity and specificity of the logistic regression model being 0.76 and 0.78, respectively). An adult index was derived from the larval index by averaging the larval index within a buffer around the trap location. This index was highly correlated with observed adult abundance values (Pearson r = 0.97, p < 0.05). This allowed us to generate predictive maps of An. hyrcanus larval and adult populations from the landscape indices. Conclusion This work shows that it is possible to use high resolution satellite imagery to map malaria vector spatial distribution. It also confirms the potential of remote sensing to help target risk areas, and constitutes a first essential step in assessing the risk of re-emergence of malaria in southern France. PMID:18302749

Remote Sensing and Modeling of Landslides: Detection, Monitoring and Risk Evaluation

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia; Fukuoka, Hiroshi

2012-01-01

Landslides are one of the most pervasive hazards in the world, resulting in more fatalities and economic damage than is generally recognized_ Occurring over an extensive range of lithologies, morphologies, hydrologies, and climates, mass movements can be triggered by intense or prolonged rainfall, seismicity, freeze/thaw processes, and antbropogertic activities, among other factors. The location, size, and timing of these processes are characteristically difficult to predict and assess because of their localized spatial scales, distribution, and complex interactions between rainfall infiltration, hydromechanical properties of the soil, and the underlying surface composition. However, the increased availability, accessibility, and resolution of remote sensing data offer a new opportunity to explore issues of landslide susceptibility, hazard, and risk over a variety of spatial scales. This special issue presents a series of papers that investigate the sources, behavior, and impacts of different mass movement types using a diverse set of data sources and evaluation methodologies.

Behavioral response races, predator-prey shell games, ecology of fear, and patch use of pumas and their ungulate prey.

PubMed

Laundré, John W

2010-10-01

The predator-prey shell game predicts random movement of prey across the landscape, whereas the behavioral response race and landscape of fear models predict that there should be a negative relationship between the spatial distribution of a predator and its behaviorally active prey. Additionally, prey have imperfect information on the whereabouts of their predator, which the predator should incorporate in its patch use strategy. I used a one-predator-one-prey system, puma (Puma concolor)-mule deer (Odocoileus hemionus) to test the following predictions regarding predator-prey distribution and patch use by the predator. (1) Pumas will spend more time in high prey risk/low prey use habitat types, while deer will spend their time in low-risk habitats. Pumas should (2) select large forage patches more often, (3) remain in large patches longer, and (4) revisit individual large patches more often than individual smaller ones. I tested these predictions with an extensive telemetry data set collected over 16 years in a study area of patchy forested habitat. When active, pumas spent significantly less time in open areas of low intrinsic predation risk than did deer. Pumas used large patches more than expected, revisited individual large patches significantly more often than smaller ones, and stayed significantly longer in larger patches than in smaller ones. The results supported the prediction of a negative relationship in the spatial distribution of a predator and its prey and indicated that the predator is incorporating the prey's imperfect information about its presence. These results indicate a behavioral complexity on the landscape scale that can have far-reaching impacts on predator-prey interactions.

Spatio-temporal modeling of the African swine fever epidemic in the Russian Federation, 2007-2012.

PubMed

Korennoy, F I; Gulenkin, V M; Malone, J B; Mores, C N; Dudnikov, S A; Stevenson, M A

2014-10-01

In 2007 African swine fever (ASF) entered Georgia and in the same year the disease entered the Russian Federation. From 2007 to 2012 ASF spread throughout the southern region of the Russian Federation. At the same time several cases of ASF were detected in the central and northern regions of the Russian Federation, forming a northern cluster of outbreaks in 2011. This northern cluster is of concern because of its proximity to mainland Europe. The aim of this study was to use details of recorded ASF outbreaks and human and swine population details to estimate the spatial distribution of ASF risk in the southern region of the European part of the Russian Federation. Our model of ASF risk was comprised of two components. The first was an estimate of ASF suitability scores calculated using maximum entropy methods. The second was an estimate of ASF risk as a function of Euclidean distance from index cases. An exponential distribution fitted to a frequency histogram of the Euclidean distance between consecutive ASF cases had a mean value of 156 km, a distance greater than the surveillance zone radius of 100-150 km stated in the ASF control regulations for the Russian Federation. We show that the spatial and temporal risk of ASF expansion is related to the suitability of the area of potential expansion, which is in turn a function of socio-economic and geographic variables. We propose that the methodology presented in this paper provides a useful tool to optimize surveillance for ASF in affected areas. Copyright © 2014 Elsevier Ltd. All rights reserved.

Spatio-temporal modeling of the African swine fever epidemic in the Russian Federation, 2007–2012

PubMed Central

Korennoy, F.I.; Gulenkin, V.M.; Malone, J.B.; Mores, C.N.; Dudnikov, S.A.; Stevenson, M.A.

2015-01-01

In 2007 African swine fever (ASF) entered Georgia and in the same year the disease entered the Russian Federation. From 2007 to 2012 ASF spread throughout the southern region of the Russian Federation. At the same time several cases of ASF were detected in the central and northern regions of the Russian Federation, forming a northern cluster of outbreaks in 2011. This northern cluster is of concern because of its proximity to mainland Europe. The aim of this study was to use details of recorded ASF outbreaks and human and swine population details to estimate the spatial distribution of ASF risk in the southern region of the European part of the Russian Federation. Our model of ASF risk was comprised of two components. The first was an estimate of ASF suitability scores calculated using maximum entropy methods. The second was an estimate of ASF risk as a function of Euclidean distance from index cases. An exponential distribution fitted to a frequency histogram of the Euclidean distance between consecutive ASF cases had a mean value of 156 km, a distance greater than the surveillance zone radius of 100–150 km stated in the ASF control regulations for the Russian Federation. We show that the spatial and temporal risk of ASF expansion is related to the suitability of the area of potential expansion, which is in turn a function of socio-economic and geographic variables. We propose that the methodology presented in this paper provides a useful tool to optimize surveillance for ASF in affected areas. PMID:25457602

Evaluating the anthropogenic impacts on fluvial flood risks in a coastal mega-city during its transitional economy (1979-2009): the interaction between land subsidence, urbanization and structural measures

NASA Astrophysics Data System (ADS)

Yu, Dapeng; Yin, Jie

2014-05-01

Flood risk in a specific geographical location is a function of the interaction between various natural (e.g. rainfall, sea-level rise) and anthropogenic processes (e.g. land subsidence and urbanization). These processes, whether a driver or an alleviating factor, often encompass a large degree of spatial and temporal variability. Looking at a specific process in isolation is likely to provide an incomplete picture of the risks. This paper describes a novel approach to the evaluation of anthropogenic impacts on flood risks in coastal mega-cities by incorporating three anthropogenic variables (land subsidence, urbanization and flood defence) within a scenario-based framework where numerical modelling was undertaken to quantify the risks. The evolving risks at four time points (1979, 1990, 2000 and 2009) were assessed for the Huangpu River floodplain where the City of Shanghai is located. Distributed data of land subsidence rate, urbanization rate and flood defence heights were obtained. Scenarios were designed by representing the rate of land subsidence and flood defence height through the modification of DEM. Effect of urbanization is represented by a roughness parameter in the model simulations. A 2D hydrodynamic model (FloodMap-Inertial) was used to estimate the flood risks associated with each scenario. Flood events with various return periods (10-, 100- and 1000-year) were designed based on a one in 50 year flood event occurred in Shanghai in August 1997. Results demonstrate the individual as well as the combined impacts of the three anthropogenic factors on the changing fluvial flood risks in the Huangpu River basin over the last three decades during the city's transitional economy (1979-2009). Land subsidence and urbanization were found to lead to proportionate but non-linear impact on flood risks due to their complex spatial and temporal interaction. The impacts and their sensitivity are the function of the rate & spatial distribution of each evolving factor. They also manifest differently in floods of different magnitude. While the pattern of response to individual anthropogenic variables is largely expected, the combined impacts demonstrate greater spatial and temporal variation. Flood defences offer considerable benefits in reducing the total inundated areas in the Huangpu River basin over the periods considered, for all magnitude floods. This, to a large extent, alleviates the adverse impacts arising from land subsidence and urbanization. However, even with an enclosed and completed defence system in 2009, extensive flood inundation is still expected for a 10-year event, albeit largely restricted to the upstream of the river where urban settlements are limited. The scenario-based approach described herein could be adopted for applications in other urbanized and subsided coastal floodplains, especially in places where the rate of land subsidence is still accelerating, urbanization is still undergoing and the local sea level keeps rising. Risk scenarios that encompass probable future anthropogenic projections may assist decision makers and other concerned stakeholders in better understanding the underlying drivers of changing flood risks, and thus help to design proper adaptation options for sustainable flood risk management and urban planning.

Improving the accuracy of livestock distribution estimates through spatial interpolation.

PubMed

Bryssinckx, Ward; Ducheyne, Els; Muhwezi, Bernard; Godfrey, Sunday; Mintiens, Koen; Leirs, Herwig; Hendrickx, Guy

2012-11-01

Animal distribution maps serve many purposes such as estimating transmission risk of zoonotic pathogens to both animals and humans. The reliability and usability of such maps is highly dependent on the quality of the input data. However, decisions on how to perform livestock surveys are often based on previous work without considering possible consequences. A better understanding of the impact of using different sample designs and processing steps on the accuracy of livestock distribution estimates was acquired through iterative experiments using detailed survey. The importance of sample size, sample design and aggregation is demonstrated and spatial interpolation is presented as a potential way to improve cattle number estimates. As expected, results show that an increasing sample size increased the precision of cattle number estimates but these improvements were mainly seen when the initial sample size was relatively low (e.g. a median relative error decrease of 0.04% per sampled parish for sample sizes below 500 parishes). For higher sample sizes, the added value of further increasing the number of samples declined rapidly (e.g. a median relative error decrease of 0.01% per sampled parish for sample sizes above 500 parishes. When a two-stage stratified sample design was applied to yield more evenly distributed samples, accuracy levels were higher for low sample densities and stabilised at lower sample sizes compared to one-stage stratified sampling. Aggregating the resulting cattle number estimates yielded significantly more accurate results because of averaging under- and over-estimates (e.g. when aggregating cattle number estimates from subcounty to district level, P <0.009 based on a sample of 2,077 parishes using one-stage stratified samples). During aggregation, area-weighted mean values were assigned to higher administrative unit levels. However, when this step is preceded by a spatial interpolation to fill in missing values in non-sampled areas, accuracy is improved remarkably. This counts especially for low sample sizes and spatially even distributed samples (e.g. P <0.001 for a sample of 170 parishes using one-stage stratified sampling and aggregation on district level). Whether the same observations apply on a lower spatial scale should be further investigated.