High-Dimensional Bayesian Geostatistics.

PubMed

Banerjee, Sudipto

2017-06-01

With the growing capabilities of Geographic Information Systems (GIS) and user-friendly software, statisticians today routinely encounter geographically referenced data containing observations from a large number of spatial locations and time points. Over the last decade, hierarchical spatiotemporal process models have become widely deployed statistical tools for researchers to better understand the complex nature of spatial and temporal variability. However, fitting hierarchical spatiotemporal models often involves expensive matrix computations with complexity increasing in cubic order for the number of spatial locations and temporal points. This renders such models unfeasible for large data sets. This article offers a focused review of two methods for constructing well-defined highly scalable spatiotemporal stochastic processes. Both these processes can be used as "priors" for spatiotemporal random fields. The first approach constructs a low-rank process operating on a lower-dimensional subspace. The second approach constructs a Nearest-Neighbor Gaussian Process (NNGP) that ensures sparse precision matrices for its finite realizations. Both processes can be exploited as a scalable prior embedded within a rich hierarchical modeling framework to deliver full Bayesian inference. These approaches can be described as model-based solutions for big spatiotemporal datasets. The models ensure that the algorithmic complexity has ~ n floating point operations (flops), where n the number of spatial locations (per iteration). We compare these methods and provide some insight into their methodological underpinnings.

Bayesian geostatistical modelling of soil-transmitted helminth survey data in the People’s Republic of China

PubMed Central

2013-01-01

Background Soil-transmitted helminth infections affect tens of millions of individuals in the People’s Republic of China (P.R. China). There is a need for high-resolution estimates of at-risk areas and number of people infected to enhance spatial targeting of control interventions. However, such information is not yet available for P.R. China. Methods A geo-referenced database compiling surveys pertaining to soil-transmitted helminthiasis, carried out from 2000 onwards in P.R. China, was established. Bayesian geostatistical models relating the observed survey data with potential climatic, environmental and socioeconomic predictors were developed and used to predict at-risk areas at high spatial resolution. Predictors were extracted from remote sensing and other readily accessible open-source databases. Advanced Bayesian variable selection methods were employed to develop a parsimonious model. Results Our results indicate that the prevalence of soil-transmitted helminth infections in P.R. China considerably decreased from 2005 onwards. Yet, some 144 million people were estimated to be infected in 2010. High prevalence (>20%) of the roundworm Ascaris lumbricoides infection was predicted for large areas of Guizhou province, the southern part of Hubei and Sichuan provinces, while the northern part and the south-eastern coastal-line areas of P.R. China had low prevalence (<5%). High infection prevalence (>20%) with hookworm was found in Hainan, the eastern part of Sichuan and the southern part of Yunnan provinces. High infection prevalence (>20%) with the whipworm Trichuris trichiura was found in a few small areas of south P.R. China. Very low prevalence (<0.1%) of hookworm and whipworm infections were predicted for the northern parts of P.R. China. Conclusions We present the first model-based estimates for soil-transmitted helminth infections throughout P.R. China at high spatial resolution. Our prediction maps provide useful information for the spatial targeting of

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

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

Introduction to Geostatistics

NASA Astrophysics Data System (ADS)

Kitanidis, P. K.

1997-05-01

Introduction to Geostatistics presents practical techniques for engineers and earth scientists who routinely encounter interpolation and estimation problems when analyzing data from field observations. Requiring no background in statistics, and with a unique approach that synthesizes classic and geostatistical methods, this book offers linear estimation methods for practitioners and advanced students. Well illustrated with exercises and worked examples, Introduction to Geostatistics is designed for graduate-level courses in earth sciences and environmental engineering.

APPLICATION OF BAYESIAN AND GEOSTATISTICAL MODELING TO THE ENVIRONMENTAL MONITORING OF CS-137 AT THE IDAHO NATIONAL LABORATORY

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

Kara G. Eby

2010-08-01

At the Idaho National Laboratory (INL) Cs-137 concentrations above the U.S. Environmental Protection Agency risk-based threshold of 0.23 pCi/g may increase the risk of human mortality due to cancer. As a leader in nuclear research, the INL has been conducting nuclear activities for decades. Elevated anthropogenic radionuclide levels including Cs-137 are a result of atmospheric weapons testing, the Chernobyl accident, and nuclear activities occurring at the INL site. Therefore environmental monitoring and long-term surveillance of Cs-137 is required to evaluate risk. However, due to the large land area involved, frequent and comprehensive monitoring is limited. Developing a spatial model thatmore » predicts Cs-137 concentrations at unsampled locations will enhance the spatial characterization of Cs-137 in surface soils, provide guidance for an efficient monitoring program, and pinpoint areas requiring mitigation strategies. The predictive model presented herein is based on applied geostatistics using a Bayesian analysis of environmental characteristics across the INL site, which provides kriging spatial maps of both Cs-137 estimates and prediction errors. Comparisons are presented of two different kriging methods, showing that the use of secondary information (i.e., environmental characteristics) can provide improved prediction performance in some areas of the INL site.« less

Geostatistics and petroleum geology

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

Hohn, M.E.

1988-01-01

This book examines purpose and use of geostatistics in exploration and development of oil and gas with an emphasis on appropriate and pertinent case studies. It present an overview of geostatistics. Topics covered include: The semivariogram; Linear estimation; Multivariate geostatistics; Nonlinear estimation; From indicator variables to nonparametric estimation; and More detail, less certainty; conditional simulation.

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.

Quantifying natural delta variability using a multiple-point geostatistics prior uncertainty model

NASA Astrophysics Data System (ADS)

Scheidt, Céline; Fernandes, Anjali M.; Paola, Chris; Caers, Jef

2016-10-01

We address the question of quantifying uncertainty associated with autogenic pattern variability in a channelized transport system by means of a modern geostatistical method. This question has considerable relevance for practical subsurface applications as well, particularly those related to uncertainty quantification relying on Bayesian approaches. Specifically, we show how the autogenic variability in a laboratory experiment can be represented and reproduced by a multiple-point geostatistical prior uncertainty model. The latter geostatistical method requires selection of a limited set of training images from which a possibly infinite set of geostatistical model realizations, mimicking the training image patterns, can be generated. To that end, we investigate two methods to determine how many training images and what training images should be provided to reproduce natural autogenic variability. The first method relies on distance-based clustering of overhead snapshots of the experiment; the second method relies on a rate of change quantification by means of a computer vision algorithm termed the demon algorithm. We show quantitatively that with either training image selection method, we can statistically reproduce the natural variability of the delta formed in the experiment. In addition, we study the nature of the patterns represented in the set of training images as a representation of the "eigenpatterns" of the natural system. The eigenpattern in the training image sets display patterns consistent with previous physical interpretations of the fundamental modes of this type of delta system: a highly channelized, incisional mode; a poorly channelized, depositional mode; and an intermediate mode between the two.

Risk mapping of clonorchiasis in the People’s Republic of China: A systematic review and Bayesian geostatistical analysis

PubMed Central

Lai, Ying-Si; Zhou, Xiao-Nong; Pan, Zhi-Heng; Utzinger, Jürg; Vounatsou, Penelope

2017-01-01

Background Clonorchiasis, one of the most important food-borne trematodiases, affects more than 12 million people in the People’s Republic of China (P.R. China). Spatially explicit risk estimates of Clonorchis sinensis infection are needed in order to target control interventions. Methodology Georeferenced survey data pertaining to infection prevalence of C. sinensis in P.R. China from 2000 onwards were obtained via a systematic review in PubMed, ISI Web of Science, Chinese National Knowledge Internet, and Wanfang Data from January 1, 2000 until January 10, 2016, with no restriction of language or study design. Additional disease data were provided by the National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention in Shanghai. Environmental and socioeconomic proxies were extracted from remote-sensing and other data sources. Bayesian variable selection was carried out to identify the most important predictors of C. sinensis risk. Geostatistical models were applied to quantify the association between infection risk and the predictors of the disease, and to predict the risk of infection across P.R. China at high spatial resolution (over a grid with grid cell size of 5×5 km). Principal findings We obtained clonorchiasis survey data at 633 unique locations in P.R. China. We observed that the risk of C. sinensis infection increased over time, particularly from 2005 onwards. We estimate that around 14.8 million (95% Bayesian credible interval 13.8–15.8 million) people in P.R. China were infected with C. sinensis in 2010. Highly endemic areas (≥ 20%) were concentrated in southern and northeastern parts of the country. The provinces with the highest risk of infection and the largest number of infected people were Guangdong, Guangxi, and Heilongjiang. Conclusions/Significance Our results provide spatially relevant information for guiding clonorchiasis control interventions in P.R. China. The trend toward higher risk of C. sinensis

Geostatistical applications in environmental remediation

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

Stewart, R.N.; Purucker, S.T.; Lyon, B.F.

1995-02-01

Geostatistical analysis refers to a collection of statistical methods for addressing data that vary in space. By incorporating spatial information into the analysis, geostatistics has advantages over traditional statistical analysis for problems with a spatial context. Geostatistics has a history of success in earth science applications, and its popularity is increasing in other areas, including environmental remediation. Due to recent advances in computer technology, geostatistical algorithms can be executed at a speed comparable to many standard statistical software packages. When used responsibly, geostatistics is a systematic and defensible tool can be used in various decision frameworks, such as the Datamore » Quality Objectives (DQO) process. At every point in the site, geostatistics can estimate both the concentration level and the probability or risk of exceeding a given value. Using these probability maps can assist in identifying clean-up zones. Given any decision threshold and an acceptable level of risk, the probability maps identify those areas that are estimated to be above or below the acceptable risk. Those areas that are above the threshold are of the most concern with regard to remediation. In addition to estimating clean-up zones, geostatistics can assist in designing cost-effective secondary sampling schemes. Those areas of the probability map with high levels of estimated uncertainty are areas where more secondary sampling should occur. In addition, geostatistics has the ability to incorporate soft data directly into the analysis. These data include historical records, a highly correlated secondary contaminant, or expert judgment. The role of geostatistics in environmental remediation is a tool that in conjunction with other methods can provide a common forum for building consensus.« less

Zambia.

PubMed

1988-08-01

Attention in this discussion of Zambia is directed to the following: geography; the people; history; government; the economy; foreign relations; defense; and relations between Zambia and the US. In 1986, the population totaled 7 million with an annual growth rate of 3.7%. The infant mortality rate is 87/1000 with a life expectancy of 51 years. Zambia, located in south-central Africa, is bordered by Zaire, Tanzania, Malawi, Mozambique, Zimbabwe, Botswana, Angola, and Namibia. The population is made up of over 70 Bantu-speaking tribes. Expatriates, mostly British (15,000 in 1986) or South African, live primarily in Lusaka where they are employed in mines and related activities. Some ancestors of present-day Zambians most likely arrived about 2000 years ago and eventually displaced or absorbed indigenous stone age hunters and gatherers. The major waves of Bantu-speaking immigrants began in the 15th century; the greatest influx occurred in the late 17th to the early 19th centuries. After the mid-19th century, the area was penetrated by Western explorers. In 1888, Northern and Southern Rhodesia (now Zambia and Zimbabwe) were proclaimed a British sphere of influence. Southern Rhodesia was annexed formally and granted self-government in 1923. Independence was realized on October 24, 1964. Zambia was the 1st British territory to become a republic immediately upon realizing independence. The constitution promulgated on August 25, 1973, abrogated the original 1964 constitution, and this new constitution and the national elections that followed in December 1973 were the final steps in achieving what is termed a "1-party participatory democracy." President Kenneth Kaunda is the major figure in the country's politics. He has wide popular support and traditionally has bridged the rivalries among the country's various regions and ethnic groups. The economy of Zambia is based primarily on its majority state-owned copper industry, which is the only significant source of foreign

Constraining geostatistical models with hydrological data to improve prediction realism

NASA Astrophysics Data System (ADS)

Demyanov, V.; Rojas, T.; Christie, M.; Arnold, D.

2012-04-01

Geostatistical models reproduce spatial correlation based on the available on site data and more general concepts about the modelled patters, e.g. training images. One of the problem of modelling natural systems with geostatistics is in maintaining realism spatial features and so they agree with the physical processes in nature. Tuning the model parameters to the data may lead to geostatistical realisations with unrealistic spatial patterns, which would still honour the data. Such model would result in poor predictions, even though although fit the available data well. Conditioning the model to a wider range of relevant data provide a remedy that avoid producing unrealistic features in spatial models. For instance, there are vast amounts of information about the geometries of river channels that can be used in describing fluvial environment. Relations between the geometrical channel characteristics (width, depth, wave length, amplitude, etc.) are complex and non-parametric and are exhibit a great deal of uncertainty, which is important to propagate rigorously into the predictive model. These relations can be described within a Bayesian approach as multi-dimensional prior probability distributions. We propose a way to constrain multi-point statistics models with intelligent priors obtained from analysing a vast collection of contemporary river patterns based on previously published works. We applied machine learning techniques, namely neural networks and support vector machines, to extract multivariate non-parametric relations between geometrical characteristics of fluvial channels from the available data. An example demonstrates how ensuring geological realism helps to deliver more reliable prediction of a subsurface oil reservoir in a fluvial depositional environment.

Using geostatistics to evaluate cleanup goals

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

Marcon, M.F.; Hopkins, L.P.

1995-12-01

Geostatistical analysis is a powerful predictive tool typically used to define spatial variability in environmental data. The information from a geostatistical analysis using kriging, a geostatistical. tool, can be taken a step further to optimize sampling location and frequency and help quantify sampling uncertainty in both the remedial investigation and remedial design at a hazardous waste site. Geostatistics were used to quantify sampling uncertainty in attainment of a risk-based cleanup goal and determine the optimal sampling frequency necessary to delineate the horizontal extent of impacted soils at a Gulf Coast waste site.

Application of geostatistics to risk assessment.

PubMed

Thayer, William C; Griffith, Daniel A; Goodrum, Philip E; Diamond, Gary L; Hassett, James M

2003-10-01

Geostatistics offers two fundamental contributions to environmental contaminant exposure assessment: (1) a group of methods to quantitatively describe the spatial distribution of a pollutant and (2) the ability to improve estimates of the exposure point concentration by exploiting the geospatial information present in the data. The second contribution is particularly valuable when exposure estimates must be derived from small data sets, which is often the case in environmental risk assessment. This article addresses two topics related to the use of geostatistics in human and ecological risk assessments performed at hazardous waste sites: (1) the importance of assessing model assumptions when using geostatistics and (2) the use of geostatistics to improve estimates of the exposure point concentration (EPC) in the limited data scenario. The latter topic is approached here by comparing design-based estimators that are familiar to environmental risk assessors (e.g., Land's method) with geostatistics, a model-based estimator. In this report, we summarize the basics of spatial weighting of sample data, kriging, and geostatistical simulation. We then explore the two topics identified above in a case study, using soil lead concentration data from a Superfund site (a skeet and trap range). We also describe several areas where research is needed to advance the use of geostatistics in environmental risk assessment.

A practical primer on geostatistics

USGS Publications Warehouse

Olea, Ricardo A.

2009-01-01

The Challenge—Most geological phenomena are extraordinarily complex in their interrelationships and vast in their geographical extension. Ordinarily, engineers and geoscientists are faced with corporate or scientific requirements to properly prepare geological models with measurements involving a small fraction of the entire area or volume of interest. Exact description of a system such as an oil reservoir is neither feasible nor economically possible. The results are necessarily uncertain. Note that the uncertainty is not an intrinsic property of the systems; it is the result of incomplete knowledge by the observer.The Aim of Geostatistics—The main objective of geostatistics is the characterization of spatial systems that are incompletely known, systems that are common in geology. A key difference from classical statistics is that geostatistics uses the sampling location of every measurement. Unless the measurements show spatial correlation, the application of geostatistics is pointless. Ordinarily the need for additional knowledge goes beyond a few points, which explains the display of results graphically as fishnet plots, block diagrams, and maps.Geostatistical Methods—Geostatistics is a collection of numerical techniques for the characterization of spatial attributes using primarily two tools: probabilistic models, which are used for spatial data in a manner similar to the way in which time-series analysis characterizes temporal data, or pattern recognition techniques. The probabilistic models are used as a way to handle uncertainty in results away from sampling locations, making a radical departure from alternative approaches like inverse distance estimation methods.Differences with Time Series—On dealing with time-series analysis, users frequently concentrate their attention on extrapolations for making forecasts. Although users of geostatistics may be interested in extrapolation, the methods work at their best interpolating. This simple difference

Geostatistics and petroleum geology

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

Hohn, M.E.

1988-01-01

The book reviewed is designed as a practical guide to geostatistics or kriging for the petroleum geologists. The author's aim in the book is to explain geostatistics as a working tool for petroleum geologists through extensive use of case-study material mostly drawn from his own research in gas potential evaluation in West Virginia. Theory and mathematics are pared down to immediate needs.

Reservoir property grids improve with geostatistics

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

Vogt, J.

1993-09-01

Visualization software, reservoir simulators and many other E and P software applications need reservoir property grids as input. Using geostatistics, as compared to other gridding methods, to produce these grids leads to the best output from the software programs. For the purpose stated herein, geostatistics is simply two types of gridding methods. Mathematically, these methods are based on minimizing or duplicating certain statistical properties of the input data. One geostatical method, called kriging, is used when the highest possible point-by-point accuracy is desired. The other method, called conditional simulation, is used when one wants statistics and texture of the resultingmore » grid to be the same as for the input data. In the following discussion, each method is explained, compared to other gridding methods, and illustrated through example applications. Proper use of geostatistical data in flow simulations, use of geostatistical data for history matching, and situations where geostatistics has no significant advantage over other methods, also will be covered.« less

The Republic of Zambia.

PubMed

Hakkert, R; Wieringa, R

1986-05-01

In 1964, at independence, Zambia's economic future looked brighter than that of most other developing countries. Its copper production accounted for 8% of total world production, and only neighboring Zaire outpaced it in the production of cobalt. Its Central Province around Kabwe held rich deposits of both zinc and lead; uranium deposits also had been found, but their projected yield remained undetermined. Since 1974, the decline in the price of copper and the increase in the price of oil have played havoc with Zambia's balance of payments. Copper, which accounted for 40% of the gross national product (GNP) and 98% of all foreign exchange in 1964, shrank to 12% of the GNP in 1978 while still generating most of the foreign exchange. As a result, imports were cut back markedly from $1.5 billion in 1973 to $690 million in 1983. Although this trend is beginning to make a U-turn, Zambia's economic situation is grave. In 1984 the GNP continued to register negative growth and inflation stood at 25%. With its urbanization rate doubling from 21% in 1964 to 43% in 1985, Zambia is now the most urbanized country south of the Sahara. Zambia's 1985 population is estimated to be 6.8 million. Between 1963 and 1969, the average annual population growth rate was 2.5: it was 3.1% between 1969-80. The current birthrate of about 48/1000 is expected to decline only marginally in the next 15 years, but the death rate is declining more rapidly -- from 19/1000 in the late 1960s to 15/1000 in 1985. Life expectancy is expected to rise from the current 51 years to about 58 years. As a result of the high growth rate, Zambia's population is young, with a median age of about 16.3 years. Traditional African values stress the importance of large families. Zambia's total fertility rate was 6.9 in 1985. According to the World Bank, only 1% of married women of childbearing age in 1982 used contraceptives. Although tribal links are weakening, Zambia still counts 73 officially recognized tribes

GEOSTATISTICS FOR WASTE MANAGEMENT: A USER'S MANUAL FOR THE GEOPACK (VERSION 1.0) GEOSTATISTICAL SOFTWARE SYSTEM

EPA Science Inventory

GEOPACK, a comprehensive user-friendly geostatistical software system, was developed to help in the analysis of spatially correlated data. The software system was developed to be used by scientists, engineers, regulators, etc., with little experience in geostatistical techniques...

GEOSTATISTICS FOR WASTE MANAGEMENT: A USER'S MANUEL FOR THE GEOPACK (VERSION 1.0) GEOSTATISTICAL SOFTWARE SYSTEM

EPA Science Inventory

A comprehensive, user-friendly geostatistical software system called GEOPACk has been developed. The purpose of this software is to make available the programs necessary to undertake a geostatistical analysis of spatially correlated data. The programs were written so that they ...

Imprecise (fuzzy) information in geostatistics

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

Bardossy, A.; Bogardi, I.; Kelly, W.E.

1988-05-01

A methodology based on fuzzy set theory for the utilization of imprecise data in geostatistics is presented. A common problem preventing a broader use of geostatistics has been the insufficient amount of accurate measurement data. In certain cases, additional but uncertain (soft) information is available and can be encoded as subjective probabilities, and then the soft kriging method can be applied (Journal, 1986). In other cases, a fuzzy encoding of soft information may be more realistic and simplify the numerical calculations. Imprecise (fuzzy) spatial information on the possible variogram is integrated into a single variogram which is used in amore » fuzzy kriging procedure. The overall uncertainty of prediction is represented by the estimation variance and the calculated membership function for each kriged point. The methodology is applied to the permeability prediction of a soil liner for hazardous waste containment. The available number of hard measurement data (20) was not enough for a classical geostatistical analysis. An additional 20 soft data made it possible to prepare kriged contour maps using the fuzzy geostatistical procedure.« less

Catholic Schools in Zambia: 1891-1924.

ERIC Educational Resources Information Center

Carmody, Brendan

1999-01-01

Retraces the contribution of the Catholic Church to schooling in Northern Rhodesia (currently Zambia) from 1891-1924. Provides background on the development of the Church in Zambia. Discusses Catholic and government perspectives on schooling and conversion, Catholic schooling in Zambia, and the African response to Catholic schooling. (CMK)

Multiobjective design of aquifer monitoring networks for optimal spatial prediction and geostatistical parameter estimation

NASA Astrophysics Data System (ADS)

Alzraiee, Ayman H.; Bau, Domenico A.; Garcia, Luis A.

2013-06-01

Effective sampling of hydrogeological systems is essential in guiding groundwater management practices. Optimal sampling of groundwater systems has previously been formulated based on the assumption that heterogeneous subsurface properties can be modeled using a geostatistical approach. Therefore, the monitoring schemes have been developed to concurrently minimize the uncertainty in the spatial distribution of systems' states and parameters, such as the hydraulic conductivity K and the hydraulic head H, and the uncertainty in the geostatistical model of system parameters using a single objective function that aggregates all objectives. However, it has been shown that the aggregation of possibly conflicting objective functions is sensitive to the adopted aggregation scheme and may lead to distorted results. In addition, the uncertainties in geostatistical parameters affect the uncertainty in the spatial prediction of K and H according to a complex nonlinear relationship, which has often been ineffectively evaluated using a first-order approximation. In this study, we propose a multiobjective optimization framework to assist the design of monitoring networks of K and H with the goal of optimizing their spatial predictions and estimating the geostatistical parameters of the K field. The framework stems from the combination of a data assimilation (DA) algorithm and a multiobjective evolutionary algorithm (MOEA). The DA algorithm is based on the ensemble Kalman filter, a Monte-Carlo-based Bayesian update scheme for nonlinear systems, which is employed to approximate the posterior uncertainty in K, H, and the geostatistical parameters of K obtained by collecting new measurements. Multiple MOEA experiments are used to investigate the trade-off among design objectives and identify the corresponding monitoring schemes. The methodology is applied to design a sampling network for a shallow unconfined groundwater system located in Rocky Ford, Colorado. Results indicate that

Bayesian Geostatistical Model-Based Estimates of Soil-Transmitted Helminth Infection in Nigeria, Including Annual Deworming Requirements

PubMed Central

Oluwole, Akinola S.; Ekpo, Uwem F.; Karagiannis-Voules, Dimitrios-Alexios; Abe, Eniola M.; Olamiju, Francisca O.; Isiyaku, Sunday; Okoronkwo, Chukwu; Saka, Yisa; Nebe, Obiageli J.; Braide, Eka I.; Mafiana, Chiedu F.; Utzinger, Jürg; Vounatsou, Penelope

2015-01-01

Background The acceleration of the control of soil-transmitted helminth (STH) infections in Nigeria, emphasizing preventive chemotherapy, has become imperative in light of the global fight against neglected tropical diseases. Predictive risk maps are an important tool to guide and support control activities. Methodology STH infection prevalence data were obtained from surveys carried out in 2011 using standard protocols. Data were geo-referenced and collated in a nationwide, geographic information system database. Bayesian geostatistical models with remotely sensed environmental covariates and variable selection procedures were utilized to predict the spatial distribution of STH infections in Nigeria. Principal Findings We found that hookworm, Ascaris lumbricoides, and Trichuris trichiura infections are endemic in 482 (86.8%), 305 (55.0%), and 55 (9.9%) locations, respectively. Hookworm and A. lumbricoides infection co-exist in 16 states, while the three species are co-endemic in 12 states. Overall, STHs are endemic in 20 of the 36 states of Nigeria, including the Federal Capital Territory of Abuja. The observed prevalence at endemic locations ranged from 1.7% to 51.7% for hookworm, from 1.6% to 77.8% for A. lumbricoides, and from 1.0% to 25.5% for T. trichiura. Model-based predictions ranged from 0.7% to 51.0% for hookworm, from 0.1% to 82.6% for A. lumbricoides, and from 0.0% to 18.5% for T. trichiura. Our models suggest that day land surface temperature and dense vegetation are important predictors of the spatial distribution of STH infection in Nigeria. In 2011, a total of 5.7 million (13.8%) school-aged children were predicted to be infected with STHs in Nigeria. Mass treatment at the local government area level for annual or bi-annual treatment of the school-aged population in Nigeria in 2011, based on World Health Organization prevalence thresholds, were estimated at 10.2 million tablets. Conclusions/Significance The predictive risk maps and estimated

Bayesian geostatistical model-based estimates of soil-transmitted helminth infection in Nigeria, including annual deworming requirements.

PubMed

Oluwole, Akinola S; Ekpo, Uwem F; Karagiannis-Voules, Dimitrios-Alexios; Abe, Eniola M; Olamiju, Francisca O; Isiyaku, Sunday; Okoronkwo, Chukwu; Saka, Yisa; Nebe, Obiageli J; Braide, Eka I; Mafiana, Chiedu F; Utzinger, Jürg; Vounatsou, Penelope

2015-04-01

The acceleration of the control of soil-transmitted helminth (STH) infections in Nigeria, emphasizing preventive chemotherapy, has become imperative in light of the global fight against neglected tropical diseases. Predictive risk maps are an important tool to guide and support control activities. STH infection prevalence data were obtained from surveys carried out in 2011 using standard protocols. Data were geo-referenced and collated in a nationwide, geographic information system database. Bayesian geostatistical models with remotely sensed environmental covariates and variable selection procedures were utilized to predict the spatial distribution of STH infections in Nigeria. We found that hookworm, Ascaris lumbricoides, and Trichuris trichiura infections are endemic in 482 (86.8%), 305 (55.0%), and 55 (9.9%) locations, respectively. Hookworm and A. lumbricoides infection co-exist in 16 states, while the three species are co-endemic in 12 states. Overall, STHs are endemic in 20 of the 36 states of Nigeria, including the Federal Capital Territory of Abuja. The observed prevalence at endemic locations ranged from 1.7% to 51.7% for hookworm, from 1.6% to 77.8% for A. lumbricoides, and from 1.0% to 25.5% for T. trichiura. Model-based predictions ranged from 0.7% to 51.0% for hookworm, from 0.1% to 82.6% for A. lumbricoides, and from 0.0% to 18.5% for T. trichiura. Our models suggest that day land surface temperature and dense vegetation are important predictors of the spatial distribution of STH infection in Nigeria. In 2011, a total of 5.7 million (13.8%) school-aged children were predicted to be infected with STHs in Nigeria. Mass treatment at the local government area level for annual or bi-annual treatment of the school-aged population in Nigeria in 2011, based on World Health Organization prevalence thresholds, were estimated at 10.2 million tablets. The predictive risk maps and estimated deworming needs presented here will be helpful for escalating the control

Carbon Tetrachloride Emissions from the US during 2008 - 2012 Derived from Atmospheric Data Using Bayesian and Geostatistical Inversions

NASA Astrophysics Data System (ADS)

Hu, L.; Montzka, S. A.; Miller, B.; Andrews, A. E.; Miller, J. B.; Lehman, S.; Sweeney, C.; Miller, S. M.; Thoning, K. W.; Siso, C.; Atlas, E. L.; Blake, D. R.; De Gouw, J. A.; Gilman, J.; Dutton, G. S.; Elkins, J. W.; Hall, B. D.; Chen, H.; Fischer, M. L.; Mountain, M. E.; Nehrkorn, T.; Biraud, S.; Tans, P. P.

2015-12-01

Global atmospheric observations suggest substantial ongoing emissions of carbon tetrachloride (CCl4) despite a 100% phase-out of production for dispersive uses since 1996 in developed countries and 2010 in other countries. Little progress has been made in understanding the causes of these ongoing emissions or identifying their contributing sources. In this study, we employed multiple inverse modeling techniques (i.e. Bayesian and geostatistical inversions) to assimilate CCl4 mole fractions observed from the National Oceanic and Atmospheric Administration (NOAA) flask-air sampling network over the US, and quantify its national and regional emissions during 2008 - 2012. Average national total emissions of CCl4 between 2008 and 2012 determined from these observations and an ensemble of inversions range between 2.1 and 6.1 Gg yr-1. This emission is substantially larger than the mean of 0.06 Gg/yr reported to the US EPA Toxics Release Inventory over these years, suggesting that under-reported emissions or non-reporting sources make up the bulk of CCl4 emissions from the US. But while the inventory does not account for the magnitude of observationally-derived CCl4 emissions, the regional distribution of derived and inventory emissions is similar. Furthermore, when considered relative to the distribution of uncapped landfills or population, the variability in measured mole fractions was most consistent with the distribution of industrial sources (i.e., those from the Toxics Release Inventory). Our results suggest that emissions from the US only account for a small fraction of the global on-going emissions of CCl4 (30 - 80 Gg yr-1 over this period). Finally, to ascertain the importance of the US emissions relative to the unaccounted global emission rate we considered multiple approaches to extrapolate our results to other countries and the globe.

Geostatistics and Bayesian updating for transmissivity estimation in a multiaquifer system in Manitoba, Canada.

PubMed

Kennedy, Paula L; Woodbury, Allan D

2002-01-01

In ground water flow and transport modeling, the heterogeneous nature of porous media has a considerable effect on the resulting flow and solute transport. Some method of generating the heterogeneous field from a limited dataset of uncertain measurements is required. Bayesian updating is one method that interpolates from an uncertain dataset using the statistics of the underlying probability distribution function. In this paper, Bayesian updating was used to determine the heterogeneous natural log transmissivity field for a carbonate and a sandstone aquifer in southern Manitoba. It was determined that the transmissivity in m2/sec followed a natural log normal distribution for both aquifers with a mean of -7.2 and - 8.0 for the carbonate and sandstone aquifers, respectively. The variograms were calculated using an estimator developed by Li and Lake (1994). Fractal nature was not evident in the variogram from either aquifer. The Bayesian updating heterogeneous field provided good results even in cases where little data was available. A large transmissivity zone in the sandstone aquifer was created by the Bayesian procedure, which is not a reflection of any deterministic consideration, but is a natural outcome of updating a prior probability distribution function with observations. The statistical model returns a result that is very reasonable; that is homogeneous in regions where little or no information is available to alter an initial state. No long range correlation trends or fractal behavior of the log-transmissivity field was observed in either aquifer over a distance of about 300 km.

Systematic evaluation of sequential geostatistical resampling within MCMC for posterior sampling of near-surface geophysical inverse problems

NASA Astrophysics Data System (ADS)

Ruggeri, Paolo; Irving, James; Holliger, Klaus

2015-08-01

We critically examine the performance of sequential geostatistical resampling (SGR) as a model proposal mechanism for Bayesian Markov-chain-Monte-Carlo (MCMC) solutions to near-surface geophysical inverse problems. Focusing on a series of simple yet realistic synthetic crosshole georadar tomographic examples characterized by different numbers of data, levels of data error and degrees of model parameter spatial correlation, we investigate the efficiency of three different resampling strategies with regard to their ability to generate statistically independent realizations from the Bayesian posterior distribution. Quite importantly, our results show that, no matter what resampling strategy is employed, many of the examined test cases require an unreasonably high number of forward model runs to produce independent posterior samples, meaning that the SGR approach as currently implemented will not be computationally feasible for a wide range of problems. Although use of a novel gradual-deformation-based proposal method can help to alleviate these issues, it does not offer a full solution. Further, we find that the nature of the SGR is found to strongly influence MCMC performance; however no clear rule exists as to what set of inversion parameters and/or overall proposal acceptance rate will allow for the most efficient implementation. We conclude that although the SGR methodology is highly attractive as it allows for the consideration of complex geostatistical priors as well as conditioning to hard and soft data, further developments are necessary in the context of novel or hybrid MCMC approaches for it to be considered generally suitable for near-surface geophysical inversions.

The relative contribution of climate variability and vector control coverage to changes in malaria parasite prevalence in Zambia 2006-2012.

PubMed

Bennett, Adam; Yukich, Josh; Miller, John M; Keating, Joseph; Moonga, Hawela; Hamainza, Busiku; Kamuliwo, Mulakwa; Andrade-Pacheco, Ricardo; Vounatsou, Penelope; Steketee, Richard W; Eisele, Thomas P

2016-08-05

Four malaria indicator surveys (MIS) were conducted in Zambia between 2006 and 2012 to evaluate malaria control scale-up. Nationally, coverage of insecticide-treated nets (ITNs) and indoor residual spraying (IRS) increased over this period, while parasite prevalence in children 1-59 months decreased dramatically between 2006 and 2008, but then increased from 2008 to 2010. We assessed the relative effects of vector control coverage and climate variability on malaria parasite prevalence over this period. Nationally-representative MISs were conducted in April-June of 2006, 2008, 2010 and 2012 to collect household-level information on malaria control interventions such as IRS, ITN ownership and use, and child parasite prevalence by microscopic examination of blood smears. We fitted Bayesian geostatistical models to assess the association between IRS and ITN coverage and climate variability and malaria parasite prevalence. We created predictions of the spatial distribution of malaria prevalence at each time point and compared results of varying IRS, ITN, and climate inputs to assess their relative contributions to changes in prevalence. Nationally, the proportion of households owning an ITN increased from 37.8 % in 2006 to 64.3 % in 2010 and 68.1 % in 2012, with substantial heterogeneity sub-nationally. The population-adjusted predicted child malaria parasite prevalence decreased from 19.6 % in 2006 to 10.4 % in 2008, but rose to 15.3 % in 2010 and 13.5 % in 2012. We estimated that the majority of this prevalence increase at the national level between 2008 and 2010 was due to climate effects on transmission, although there was substantial heterogeneity at the provincial level in the relative contribution of changing climate and ITN availability. We predict that if climate factors preceding the 2010 survey were the same as in 2008, the population-adjusted prevalence would have fallen to 9.9 % nationally. These results suggest that a combination of climate factors

Mine planning and emission control strategies using geostatistics

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

Martino, F.; Kim, Y.C.

1983-03-01

This paper reviews the past four years' research efforts performed jointly by the University of Arizona and the Homer City Owners in which geostatistics were applied to solve various problems associated with coal characterization, mine planning, and development of emission control strategies. Because geostatistics is the only technique which can quantify the degree of confidence associated with a given estimate (or prediction), it played an important role throughout the research efforts. Through geostatistics, it was learned that there is an urgent need for closely spaced sample information, if short-term coal quality predictions are to be made for mine planning purposes.

Geostatistics and spatial analysis in biological anthropology.

PubMed

Relethford, John H

2008-05-01

A variety of methods have been used to make evolutionary inferences based on the spatial distribution of biological data, including reconstructing population history and detection of the geographic pattern of natural selection. This article provides an examination of geostatistical analysis, a method used widely in geology but which has not often been applied in biological anthropology. Geostatistical analysis begins with the examination of a variogram, a plot showing the relationship between a biological distance measure and the geographic distance between data points and which provides information on the extent and pattern of spatial correlation. The results of variogram analysis are used for interpolating values of unknown data points in order to construct a contour map, a process known as kriging. The methods of geostatistical analysis and discussion of potential problems are applied to a large data set of anthropometric measures for 197 populations in Ireland. The geostatistical analysis reveals two major sources of spatial variation. One pattern, seen for overall body and craniofacial size, shows an east-west cline most likely reflecting the combined effects of past population dispersal and settlement. The second pattern is seen for craniofacial height and shows an isolation by distance pattern reflecting rapid spatial changes in the midlands region of Ireland, perhaps attributable to the genetic impact of the Vikings. The correspondence of these results with other analyses of these data and the additional insights generated from variogram analysis and kriging illustrate the potential utility of geostatistical analysis in biological anthropology. (c) 2008 Wiley-Liss, Inc.

Leprosy trends in Zambia 1991-2009.

PubMed

Kapata, Nathan; Chanda-Kapata, Pascalina; Grobusch, Martin Peter; O'Grady, Justin; Bates, Matthew; Mwaba, Peter; Zumla, Alimuddin

2012-10-01

To document leprosy trends in Zambia over the past two decades to ascertain the importance of leprosy as a health problem in Zambia. Retrospective study covering the period 1991-2009 of routine national leprosy surveillance data, published national programme review reports and desk reviews of in-country TB reports. Data reports were available for all the years under study apart from years 2001, 2002 and 2006. The Leprosy case notification rates (CNR) declined from 2.73/10 000 population in 1991 to 0.43/10 000 population in 2009. The general leprosy burden showed a downward trend for both adults and children. Leprosy case burden dropped from approximately 18 000 cases in 1980 to only about 1000 cases in 1996, and by the year 2000, the prevalence rates had fallen to 0.67/10 000 population. There were more multibacillary cases of leprosy than pauci-bacillary cases. Several major gaps in data recording, entry and surveillance were identified. Data on disaggregation by gender, HIV status or geographical origin were not available. Whilst Zambia has achieved WHO targets for leprosy control, leprosy prevalence data from Zambia may not reflect real situation because of poor data recording and surveillance. Greater investment into infrastructure and training are required for more accurate surveillance of leprosy in Zambia. © 2012 Blackwell Publishing Ltd.

G STL: the geostatistical template library in C++

NASA Astrophysics Data System (ADS)

Remy, Nicolas; Shtuka, Arben; Levy, Bruno; Caers, Jef

2002-10-01

The development of geostatistics has been mostly accomplished by application-oriented engineers in the past 20 years. The focus on concrete applications gave birth to many algorithms and computer programs designed to address different issues, such as estimating or simulating a variable while possibly accounting for secondary information such as seismic data, or integrating geological and geometrical data. At the core of any geostatistical data integration methodology is a well-designed algorithm. Yet, despite their obvious differences, all these algorithms share many commonalities on which to build a geostatistics programming library, lest the resulting library is poorly reusable and difficult to expand. Building on this observation, we design a comprehensive, yet flexible and easily reusable library of geostatistics algorithms in C++. The recent advent of the generic programming paradigm allows us elegantly to express the commonalities of the geostatistical algorithms into computer code. Generic programming, also referred to as "programming with concepts", provides a high level of abstraction without loss of efficiency. This last point is a major gain over object-oriented programming which often trades efficiency for abstraction. It is not enough for a numerical library to be reusable, it also has to be fast. Because generic programming is "programming with concepts", the essential step in the library design is the careful identification and thorough definition of these concepts shared by most geostatistical algorithms. Building on these definitions, a generic and expandable code can be developed. To show the advantages of such a generic library, we use G STL to build two sequential simulation programs working on two different types of grids—a surface with faults and an unstructured grid—without requiring any change to the G STL code.

Mental illness--stigma and discrimination in Zambia.

PubMed

Kapungwe, A; Cooper, S; Mwanza, J; Mwape, L; Sikwese, A; Kakuma, R; Lund, C; Flisher, A J

2010-07-01

The aim of this qualitative study was to explore the presence, causes and means of addressing individual and systemic stigma and discrimination against people with mental illness in Zambia. This is to facilitate the development of tailor-made antistigma initiatives that are culturally sensitive for Zambia and other low-income African countries. This is the first in-depth study on mental illness stigma in Zambia. Fifty semi-structured interviews and 6 focus group discussions were conducted with key stakeholders drawn from 3 districts in Zambia (Lusaka, Kabwe and Sinazongwe). Transcripts were analyzed using a grounded theory approach. Mental illness stigma and discrimination is pervasive across Zambian society, prevailing within the general community, amongst family members, amid general and mental health care providers, and at the level of government. Such stigma appears to be fuelled by misunderstandings of mental illness aetiology; fears of contagion and the perceived dangerousness of people with mental illness; and associations between HIV/AIDS and mental illness. Strategies suggested for reducing stigma and discrimination in Zambia included education campaigns, the transformation of mental health policy and legislation and expanding the social and economic opportunities of the mentally ill. In Zambia, as in many other low-income African countries, very little attention is devoted to addressing the negative beliefs and behaviours surrounding mental illness, despite the devastating costs that ensue. The results from this study underscore the need for greater commitment from governments and policy-makers in African countries to start prioritizing mental illness stigma as a major public health and development issue.

Reservoir studies with geostatistics to forecast performance

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

Tang, R.W.; Behrens, R.A.; Emanuel, A.S.

1991-05-01

In this paper example geostatistics and streamtube applications are presented for waterflood and CO{sub 2} flood in two low-permeability sandstone reservoirs. Thy hybrid approach of combining fine vertical resolution in cross-sectional models with streamtubes resulted in models that showed water channeling and provided realistic performance estimates. Results indicate that the combination of detailed geostatistical cross sections and fine-grid streamtube models offers a systematic approach for realistic performance forecasts.

Distribution and phenology of ixodid ticks in southern Zambia.

PubMed

Speybroeck, N; Madder, M; Van Den Bossche, P; Mtambo, J; Berkvens, N; Chaka, G; Mulumba, M; Brandt, J; Tirry, L; Berkvens, D

2002-12-01

Distribution data for epidemiologically important ticks (Acari: Ixodidae) in the Southern Province of Zambia, one of the main cattle areas of the country, are presented. Boophilus microplus (Canestrini) was not recorded in southern Zambia, whereas Boophilus decoloratus (Koch) is present throughout the area. New distribution patterns for less economically important ixodid ticks are also discussed. Southern Zambia is a transition zone because it is the most northern area in Africa where mixed Rhipicephalus appendiculatus Neumann and Rhipicephalus zambeziensis Walker, Norval & Corwin populations were reported. Although a second generation of adult R. appendiculatus/R. zamnbeziensis was encountered, simulations indicated that this phenomenon is very rare in southern Zambia, mainly because of the colder temperatures during the early dry season and lower rainfall. These simulations were supported by a development trial under experimental conditions. Tick body size measurements showed that southern Zambian ticks are larger than eastern Zambian R. appendiculatus. It is hypothesized that body size is related to diapausing intensity in this species. The epidemiological consequences are that a different approach to control Theileria parva (Theiler) (Piroplasmida: Theileriidae) and other tick-borne diseases is needed in southern Zambia, compared to the one adopted in eastern Zambia.

Random vectors and spatial analysis by geostatistics for geotechnical applications

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

Young, D.S.

1987-08-01

Geostatistics is extended to the spatial analysis of vector variables by defining the estimation variance and vector variogram in terms of the magnitude of difference vectors. Many random variables in geotechnology are in vectorial terms rather than scalars, and its structural analysis requires those sample variable interpolations to construct and characterize structural models. A better local estimator will result in greater quality of input models; geostatistics can provide such estimators; kriging estimators. The efficiency of geostatistics for vector variables is demonstrated in a case study of rock joint orientations in geological formations. The positive cross-validation encourages application of geostatistics tomore » spatial analysis of random vectors in geoscience as well as various geotechnical fields including optimum site characterization, rock mechanics for mining and civil structures, cavability analysis of block cavings, petroleum engineering, and hydrologic and hydraulic modelings.« less

Gstat: a program for geostatistical modelling, prediction and simulation

NASA Astrophysics Data System (ADS)

Pebesma, Edzer J.; Wesseling, Cees G.

1998-01-01

Gstat is a computer program for variogram modelling, and geostatistical prediction and simulation. It provides a generic implementation of the multivariable linear model with trends modelled as a linear function of coordinate polynomials or of user-defined base functions, and independent or dependent, geostatistically modelled, residuals. Simulation in gstat comprises conditional or unconditional (multi-) Gaussian sequential simulation of point values or block averages, or (multi-) indicator sequential simulation. Besides many of the popular options found in other geostatistical software packages, gstat offers the unique combination of (i) an interactive user interface for modelling variograms and generalized covariances (residual variograms), that uses the device-independent plotting program gnuplot for graphical display, (ii) support for several ascii and binary data and map file formats for input and output, (iii) a concise, intuitive and flexible command language, (iv) user customization of program defaults, (v) no built-in limits, and (vi) free, portable ANSI-C source code. This paper describes the class of problems gstat can solve, and addresses aspects of efficiency and implementation, managing geostatistical projects, and relevant technical details.

Geostatistics applied to gas reservoirs

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

Meunier, G.; Coulomb, C.; Laille, J.P.

1989-09-01

The spatial distribution of many of the physical parameters connected with a gas reservoir is of primary interest to both engineers and geologists throughout the study, development, and operation of a field. It is therefore desirable for the distribution to be capable of statistical interpretation, to have a simple graphical representation, and to allow data to be entered from either two- or three-dimensional grids. To satisfy these needs while dealing with the geographical variables, new methods have been developed under the name geostatistics. This paper describes briefly the theory of geostatistics and its most recent improvements for the specific problemmore » of subsurface description. The external-drift technique has been emphasized in particular, and in addition, four case studies related to gas reservoirs are presented.« less

Application of geostatistics to coal-resource characterization and mine planning. Final report

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

Kauffman, P.W.; Walton, D.R.; Martuneac, L.

1981-12-01

Geostatistics is a proven method of ore reserve estimation in many non-coal mining areas but little has been published concerning its application to coal resources. This report presents the case for using geostatistics for coal mining applications and describes how a coal mining concern can best utilize geostatistical techniques for coal resource characterization and mine planning. An overview of the theory of geostatistics is also presented. Many of the applications discussed are documented in case studies that are a part of the report. The results of an exhaustive literature search are presented and recommendations are made for needed future researchmore » and demonstration projects.« less

Applications of Geostatistics in Plant Nematology

PubMed Central

Wallace, M. K.; Hawkins, D. M.

1994-01-01

The application of geostatistics to plant nematology was made by evaluating soil and nematode data acquired from 200 soil samples collected from the Ap horizon of a reed canary-grass field in northern Minnesota. Geostatistical concepts relevant to nematology include semi-variogram modelling, kriging, and change of support calculations. Soil and nematode data generally followed a spherical semi-variogram model, with little random variability associated with soil data and large inherent variability for nematode data. Block kriging of soil and nematode data provided useful contour maps of the data. Change of snpport calculations indicated that most of the random variation in nematode data was due to short-range spatial variability in the nematode population densities. PMID:19279938

Applications of geostatistics in plant nematology.

PubMed

Wallace, M K; Hawkins, D M

1994-12-01

The application of geostatistics to plant nematology was made by evaluating soil and nematode data acquired from 200 soil samples collected from the A(p) horizon of a reed canary-grass field in northern Minnesota. Geostatistical concepts relevant to nematology include semi-variogram modelling, kriging, and change of support calculations. Soil and nematode data generally followed a spherical semi-variogram model, with little random variability associated with soil data and large inherent variability for nematode data. Block kriging of soil and nematode data provided useful contour maps of the data. Change of snpport calculations indicated that most of the random variation in nematode data was due to short-range spatial variability in the nematode population densities.

Addressing HIV in Zambia through traditional games.

PubMed

Njelesani, Janet; Njelesani, Donald

2018-05-18

There has been a proliferation of organizations in Zambia touting the mobilization of traditional games as a tool to prevent HIV. However, there is a dearth of evidence on how culturally important activities like traditional games are being incorporated into programing. The purpose of this study was to explore how traditional games are used as a strategy to prevent HIV in Zambia. This qualitative study generated data from 17 case studies of HIV programs operating in Lusaka, Zambia. Observations of the programs were conducted and 44 interviews with program staff were completed. Participants believed that traditional games can engage youth while helping them learn about HIV. However, when traditional games were implemented, they were oversimplified and taught via regimented practices that did not foster critical thinking. This kind of implementation comes at the expense of the development of skills needed to retain and act on information essential for HIV prevention. The results of the study also reveal that due to the increase in cultural pride that has welcomed the revival of traditional games, there are opportunities to encourage government and political support for their systematic integration to address HIV in Zambia.

Restricted spatial regression in practice: Geostatistical models, confounding, and robustness under model misspecification

USGS Publications Warehouse

Hanks, Ephraim M.; Schliep, Erin M.; Hooten, Mevin B.; Hoeting, Jennifer A.

2015-01-01

In spatial generalized linear mixed models (SGLMMs), covariates that are spatially smooth are often collinear with spatially smooth random effects. This phenomenon is known as spatial confounding and has been studied primarily in the case where the spatial support of the process being studied is discrete (e.g., areal spatial data). In this case, the most common approach suggested is restricted spatial regression (RSR) in which the spatial random effects are constrained to be orthogonal to the fixed effects. We consider spatial confounding and RSR in the geostatistical (continuous spatial support) setting. We show that RSR provides computational benefits relative to the confounded SGLMM, but that Bayesian credible intervals under RSR can be inappropriately narrow under model misspecification. We propose a posterior predictive approach to alleviating this potential problem and discuss the appropriateness of RSR in a variety of situations. We illustrate RSR and SGLMM approaches through simulation studies and an analysis of malaria frequencies in The Gambia, Africa.

Incorporating reservoir heterogeneity with geostatistics to investigate waterflood recoveries

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

Wolcott, D.S.; Chopra, A.K.

1993-03-01

This paper presents an investigation of infill drilling performance and reservoir continuity with geostatistics and a reservoir simulator. The geostatistical technique provides many possible realizations and realistic descriptions of reservoir heterogeneity. Correlation between recovery efficiency and thickness of individual sand subunits is shown. Additional recovery from infill drilling results from thin, discontinuous subunits. The technique may be applied to variations in continuity for other sandstone reservoirs.

Peace Corps/Zambia PST 1995 Special Lessons. Nyanja.

ERIC Educational Resources Information Center

Peace Corps (Zambia).

This guide is designed for language teachers training Peace Corps volunteers in Nyanja for service in Zambia, and focuses on daily communication skills in that context. It consists of a language "survival kit" of useful phrases and vocabulary, conjugation of the verb "to be," the Zambia national anthem, extensive notes on verb…

A MS-lesion pattern discrimination plot based on geostatistics.

PubMed

Marschallinger, Robert; Schmidt, Paul; Hofmann, Peter; Zimmer, Claus; Atkinson, Peter M; Sellner, Johann; Trinka, Eugen; Mühlau, Mark

2016-03-01

A geostatistical approach to characterize MS-lesion patterns based on their geometrical properties is presented. A dataset of 259 binary MS-lesion masks in MNI space was subjected to directional variography. A model function was fit to express the observed spatial variability in x, y, z directions by the geostatistical parameters Range and Sill. Parameters Range and Sill correlate with MS-lesion pattern surface complexity and total lesion volume. A scatter plot of ln(Range) versus ln(Sill), classified by pattern anisotropy, enables a consistent and clearly arranged presentation of MS-lesion patterns based on geometry: the so-called MS-Lesion Pattern Discrimination Plot. The geostatistical approach and the graphical representation of results are considered efficient exploratory data analysis tools for cross-sectional, follow-up, and medication impact analysis.

Geostatistics and GIS: tools for characterizing environmental contamination.

PubMed

Henshaw, Shannon L; Curriero, Frank C; Shields, Timothy M; Glass, Gregory E; Strickland, Paul T; Breysse, Patrick N

2004-08-01

Geostatistics is a set of statistical techniques used in the analysis of georeferenced data that can be applied to environmental contamination and remediation studies. In this study, the 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE) contamination at a Superfund site in western Maryland is evaluated. Concern about the site and its future clean up has triggered interest within the community because residential development surrounds the area. Spatial statistical methods, of which geostatistics is a subset, are becoming increasingly popular, in part due to the availability of geographic information system (GIS) software in a variety of application packages. In this article, the joint use of ArcGIS software and the R statistical computing environment are demonstrated as an approach for comprehensive geostatistical analyses. The spatial regression method, kriging, is used to provide predictions of DDE levels at unsampled locations both within the site and the surrounding areas where residential development is ongoing.

Nontuberculous Mycobacteria, Zambia

PubMed Central

van der Sande, Marianne A.B.; de Graaff, Cas S.; Parkinson, Shelagh; Verbrugh, Henri A.; Petit, Pieter L.C.; van Soolingen, Dick

2009-01-01

Clinical relevance of nontuberculous mycobacteria (NTM) isolated from 180 chronically ill patients and 385 healthy controls in Zambia was evaluated to examine the contribution of these isolates to tuberculosis (TB)–like disease. The proportion of NTM-positive sputum samples was significantly higher in the patient group than in controls; 11% and 6%, respectively (p<0.05). NTM-associated lung disease was diagnosed for 1 patient, and a probable diagnosis was made for 3 patients. NTM-positive patients and controls were more likely to report vomiting and diarrhea and were more frequently underweight than the NTM-negative patients and controls. Chest radiographs of NTM-positive patients showed deviations consistent with TB more frequently than those of controls. The most frequently isolated NTM was Mycobacterium avium complex. Multiple, not previously identified mycobacteria (55 of 171 NTM) were isolated from both groups. NTM probably play an important role in the etiology of TB-like diseases in Zambia. PMID:19193268

The institutional context of tobacco production in Zambia.

PubMed

Labonté, Ronald; Lencucha, Raphael; Drope, Jeffrey; Packer, Corinne; Goma, Fastone M; Zulu, Richard

2018-01-16

Tobacco production is said to be an important contributor to Zambia's economy in terms of labour and revenue generation. In light of Zambia's obligations under the WHO Framework Convention of Tobacco Control (FCTC) we examined the institutional actors in Zambia's tobacco sector to better understand their roles and determine the institutional context that supports tobacco production in Zambia. Findings from 26 qualitative, semi-structured individual or small-group interviews with key informants from governmental, intergovernmental and non-governmental organisations were analysed, along with data and information from published literature. Although Zambia is obligated under the FCTC to take steps to reduce tobacco production, the country's weak economy and strong tobacco interests make it difficult to achieve this goal. Respondents uniformly acknowledged that growing the country's economy and ensuring employment for its citizens are the government's top priorities. Lacklustre coordination and collaboration between the institutional actors, both within and outside government, contributes to an environment that helps sustain tobacco production in the country. A Tobacco Products Control Bill has been under review for a number of years, but with no supply measures included, and with no indication of when or whether it will be passed. As with other low-income countries involved in tobacco production, there is inconsistency between Zambia's economic policy to strengthen the country's economy and its FCTC commitment to regulate and control tobacco production. The absence of a whole-of-government approach towards tobacco control has created an institutional context of duelling objectives, with some government ministries working at cross-purposes and tobacco interests left unchecked. With no ultimate coordinating authority, this industry risks being run according to the desire and demands of multinational tobacco companies, with few, if any, checks against them.

Three-Dimensional Bayesian Geostatistical Aquifer Characterization at the Hanford 300 Area using Tracer Test Data

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

Chen, Xingyuan; Murakami, Haruko; Hahn, Melanie S.

2012-06-01

Tracer testing under natural or forced gradient flow holds the potential to provide useful information for characterizing subsurface properties, through monitoring, modeling and interpretation of the tracer plume migration in an aquifer. Non-reactive tracer experiments were conducted at the Hanford 300 Area, along with constant-rate injection tests and electromagnetic borehole flowmeter (EBF) profiling. A Bayesian data assimilation technique, the method of anchored distributions (MAD) [Rubin et al., 2010], was applied to assimilate the experimental tracer test data with the other types of data and to infer the three-dimensional heterogeneous structure of the hydraulic conductivity in the saturated zone of themore » Hanford formation. In this study, the Bayesian prior information on the underlying random hydraulic conductivity field was obtained from previous field characterization efforts using the constant-rate injection tests and the EBF data. The posterior distribution of the conductivity field was obtained by further conditioning the field on the temporal moments of tracer breakthrough curves at various observation wells. MAD was implemented with the massively-parallel three-dimensional flow and transport code PFLOTRAN to cope with the highly transient flow boundary conditions at the site and to meet the computational demands of MAD. A synthetic study proved that the proposed method could effectively invert tracer test data to capture the essential spatial heterogeneity of the three-dimensional hydraulic conductivity field. Application of MAD to actual field data shows that the hydrogeological model, when conditioned on the tracer test data, can reproduce the tracer transport behavior better than the field characterized without the tracer test data. This study successfully demonstrates that MAD can sequentially assimilate multi-scale multi-type field data through a consistent Bayesian framework.« less

Geostatistical regularization operators for geophysical inverse problems on irregular meshes

NASA Astrophysics Data System (ADS)

Jordi, C.; Doetsch, J.; Günther, T.; Schmelzbach, C.; Robertsson, J. OA

2018-05-01

Irregular meshes allow to include complicated subsurface structures into geophysical modelling and inverse problems. The non-uniqueness of these inverse problems requires appropriate regularization that can incorporate a priori information. However, defining regularization operators for irregular discretizations is not trivial. Different schemes for calculating smoothness operators on irregular meshes have been proposed. In contrast to classical regularization constraints that are only defined using the nearest neighbours of a cell, geostatistical operators include a larger neighbourhood around a particular cell. A correlation model defines the extent of the neighbourhood and allows to incorporate information about geological structures. We propose an approach to calculate geostatistical operators for inverse problems on irregular meshes by eigendecomposition of a covariance matrix that contains the a priori geological information. Using our approach, the calculation of the operator matrix becomes tractable for 3-D inverse problems on irregular meshes. We tested the performance of the geostatistical regularization operators and compared them against the results of anisotropic smoothing in inversions of 2-D surface synthetic electrical resistivity tomography (ERT) data as well as in the inversion of a realistic 3-D cross-well synthetic ERT scenario. The inversions of 2-D ERT and seismic traveltime field data with geostatistical regularization provide results that are in good accordance with the expected geology and thus facilitate their interpretation. In particular, for layered structures the geostatistical regularization provides geologically more plausible results compared to the anisotropic smoothness constraints.

Cigarette Price and Other Factors Associated with Brand Choice and Brand Loyalty in Zambia: Findings from the ITC Zambia Survey

PubMed Central

Salloum, Ramzi G.; Goma, Fastone; Chelwa, Grieve; Cheng, Xi; Zulu, Richard; Kaai, Susan C.; Quah, Anne C.K.; Thrasher, James F.; Fong, Geoffrey T.

2015-01-01

Objectives Little is known about cigarette pricing and brand loyalty in sub-Saharan Africa. This study examines these issues in Zambia, analyzing data from the International Tobacco Control (ITC) Zambia Survey. Methods Data from Wave 1 of the ITC Zambia Survey (2012) were analyzed for current smokers of factory-made (FM) cigarettes compared to those who smoked both FM and roll-your-own (RYO) cigarettes, using multivariate logistic regression models to identify the predictors of brand loyalty and reasons for brand choice. Results 75% of FM-only smokers and 64% of FM+RYO smokers reported having a regular brand. Compared with FM-only smokers, FM+RYO smokers were, on average, older (28% vs. 20% ≥ 40 years), low income (64% vs. 43%), and had lower education (76% vs. 44% < secondary). Mean price across FM brands was ZMW0.50 (USD0.08) per stick. Smokers were significantly less likely to be brand-loyal (>1 year) if they were aged 15-17 years (vs. 40-54 years) and if they had moderate (vs. low) income. Brand choice was predicted mostly by friends, taste, and brand popularity. Price was more likely to be a reason for brand loyalty among FM+RYO smokers, among ≥55 year old smokers, and among those who reported being more addicted to cigarettes. Conclusions These results in Zambia document the high levels of brand loyalty in a market where price variation is fairly small across cigarette brands. Future research is needed on longitudinal trends to evaluate the effect of tobacco control policies in Zambia. PMID:25631482

Perceptions of and Attitudes towards Ageing in Zambia

ERIC Educational Resources Information Center

Mapoma, Christopher C.; Masaiti, Gift

2012-01-01

This paper reflects part of the wider outlook on ageing in general in Zambia and was intended to investigate perceptions of and attitudes towards the aged and ageing in Zambia by members of the community who, by definition and chronologically are not classified as aged i.e. not yet 60 years and over. Focus Group Discussions (FGD) were used to…

Attitudes toward abortion in Zambia.

PubMed

Geary, Cynthia Waszak; Gebreselassie, Hailemichael; Awah, Paschal; Pearson, Erin

2012-09-01

Despite Zambia's relatively progressive abortion law, women continue to seek unsafe, illegal abortions. Four domains of abortion attitudes - support for legalization, immorality, rights, and access to services - were measured in 4 communities. A total of 668 people were interviewed. Associations among the 4 domains were inconsistent with expectations. The belief that abortion is immoral was widespread, but was not associated with lack of support for legalization. Instead, it was associated with belief that women need access to safe services. These findings suggest that increasing awareness about abortion law in Zambia may be important for encouraging more favorable attitudes. Copyright © 2012 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Acquisition of Scientific Literature in Developing Countries. 4: Zambia.

ERIC Educational Resources Information Center

Lundu, Maurice C.; Lungu, Charles B. M.

1989-01-01

Description of selected science and technical libraries and information services in Zambia focuses on collection development and acquisition policies. The problems of transferring technology through the transfer of information are discussed, the future of information transfer in Zambia is explored, and proposals for future action are presented.…

Geostatistical applications in ground-water modeling in south-central Kansas

USGS Publications Warehouse

Ma, T.-S.; Sophocleous, M.; Yu, Y.-S.

1999-01-01

This paper emphasizes the supportive role of geostatistics in applying ground-water models. Field data of 1994 ground-water level, bedrock, and saltwater-freshwater interface elevations in south-central Kansas were collected and analyzed using the geostatistical approach. Ordinary kriging was adopted to estimate initial conditions for ground-water levels and topography of the Permian bedrock at the nodes of a finite difference grid used in a three-dimensional numerical model. Cokriging was used to estimate initial conditions for the saltwater-freshwater interface. An assessment of uncertainties in the estimated data is presented. The kriged and cokriged estimation variances were analyzed to evaluate the adequacy of data employed in the modeling. Although water levels and bedrock elevations are well described by spherical semivariogram models, additional data are required for better cokriging estimation of the interface data. The geostatistically analyzed data were employed in a numerical model of the Siefkes site in the project area. Results indicate that the computed chloride concentrations and ground-water drawdowns reproduced the observed data satisfactorily.This paper emphasizes the supportive role of geostatistics in applying ground-water models. Field data of 1994 ground-water level, bedrock, and saltwater-freshwater interface elevations in south-central Kansas were collected and analyzed using the geostatistical approach. Ordinary kriging was adopted to estimate initial conditions for ground-water levels and topography of the Permian bedrock at the nodes of a finite difference grid used in a three-dimensional numerical model. Cokriging was used to estimate initial conditions for the saltwater-freshwater interface. An assessment of uncertainties in the estimated data is presented. The kriged and cokriged estimation variances were analyzed to evaluate the adequacy of data employed in the modeling. Although water levels and bedrock elevations are well described

Hydrogeologic unit flow characterization using transition probability geostatistics.

PubMed

Jones, Norman L; Walker, Justin R; Carle, Steven F

2005-01-01

This paper describes a technique for applying the transition probability geostatistics method for stochastic simulation to a MODFLOW model. Transition probability geostatistics has some advantages over traditional indicator kriging methods including a simpler and more intuitive framework for interpreting geologic relationships and the ability to simulate juxtapositional tendencies such as fining upward sequences. The indicator arrays generated by the transition probability simulation are converted to layer elevation and thickness arrays for use with the new Hydrogeologic Unit Flow package in MODFLOW 2000. This makes it possible to preserve complex heterogeneity while using reasonably sized grids and/or grids with nonuniform cell thicknesses.

ON THE GEOSTATISTICAL APPROACH TO THE INVERSE PROBLEM. (R825689C037)

EPA Science Inventory

Abstract

The geostatistical approach to the inverse problem is discussed with emphasis on the importance of structural analysis. Although the geostatistical approach is occasionally misconstrued as mere cokriging, in fact it consists of two steps: estimation of statist...

Using river distance and existing hydrography data can improve the geostatistical estimation of fish tissue mercury at unsampled locations.

PubMed

Money, Eric S; Sackett, Dana K; Aday, D Derek; Serre, Marc L

2011-09-15

Mercury in fish tissue is a major human health concern. Consumption of mercury-contaminated fish poses risks to the general population, including potentially serious developmental defects and neurological damage in young children. Therefore, it is important to accurately identify areas that have the potential for high levels of bioaccumulated mercury. However, due to time and resource constraints, it is difficult to adequately assess fish tissue mercury on a basin wide scale. We hypothesized that, given the nature of fish movement along streams, an analytical approach that takes into account distance traveled along these streams would improve the estimation accuracy for fish tissue mercury in unsampled streams. Therefore, we used a river-based Bayesian Maximum Entropy framework (river-BME) for modern space/time geostatistics to estimate fish tissue mercury at unsampled locations in the Cape Fear and Lumber Basins in eastern North Carolina. We also compared the space/time geostatistical estimation using river-BME to the more traditional Euclidean-based BME approach, with and without the inclusion of a secondary variable. Results showed that this river-based approach reduced the estimation error of fish tissue mercury by more than 13% and that the median estimate of fish tissue mercury exceeded the EPA action level of 0.3 ppm in more than 90% of river miles for the study domain.

Integrated geostatistics for modeling fluid contacts and shales in Prudhoe Bay

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

Perez, G.; Chopra, A.K.; Severson, C.D.

1997-12-01

Geostatistics techniques are being used increasingly to model reservoir heterogeneity at a wide range of scales. A variety of techniques is now available with differing underlying assumptions, complexity, and applications. This paper introduces a novel method of geostatistics to model dynamic gas-oil contacts and shales in the Prudhoe Bay reservoir. The method integrates reservoir description and surveillance data within the same geostatistical framework. Surveillance logs and shale data are transformed to indicator variables. These variables are used to evaluate vertical and horizontal spatial correlation and cross-correlation of gas and shale at different times and to develop variogram models. Conditional simulationmore » techniques are used to generate multiple three-dimensional (3D) descriptions of gas and shales that provide a measure of uncertainty. These techniques capture the complex 3D distribution of gas-oil contacts through time. The authors compare results of the geostatistical method with conventional techniques as well as with infill wells drilled after the study. Predicted gas-oil contacts and shale distributions are in close agreement with gas-oil contacts observed at infill wells.« less

Applications of geostatistics and Markov models for logo recognition

NASA Astrophysics Data System (ADS)

Pham, Tuan

2003-01-01

Spatial covariances based on geostatistics are extracted as representative features of logo or trademark images. These spatial covariances are different from other statistical features for image analysis in that the structural information of an image is independent of the pixel locations and represented in terms of spatial series. We then design a classifier in the sense of hidden Markov models to make use of these geostatistical sequential data to recognize the logos. High recognition rates are obtained from testing the method against a public-domain logo database.

Cigarette price and other factors associated with brand choice and brand loyalty in Zambia: findings from the ITC Zambia Survey.

PubMed

Salloum, Ramzi G; Goma, Fastone; Chelwa, Grieve; Cheng, Xi; Zulu, Richard; Kaai, Susan C; Quah, Anne C K; Thrasher, James F; Fong, Geoffrey T

2015-07-01

Little is known about cigarette pricing and brand loyalty in sub-Saharan Africa. This study examines these issues in Zambia, analysing data from the International Tobacco Control (ITC) Zambia Survey. Data from Wave 1 of the ITC Zambia Survey (2012) were analysed for current smokers of factory-made (FM) cigarettes compared with those who smoked both FM and roll-your-own (RYO) cigarettes, using multivariate logistic regression models to identify the predictors of brand loyalty and reasons for brand choice. 75% of FM-only smokers and 64% of FM+RYO smokers reported having a regular brand. Compared with FM-only smokers, FM+RYO smokers were, on average, older (28% vs 20% ≥40 years), low income (64% vs 43%) and had lower education (76% vs 44% < secondary). Mean price across FM brands was ZMW0.50 (US$0.08) per stick. Smokers were significantly less likely to be brand loyal (>1 year) if they were aged 15-17 years (vs 40-54 years) and if they had moderate (vs low) income. Brand choice was predicted mostly by friends, taste and brand popularity. Price was more likely to be a reason for brand loyalty among FM+RYO smokers, among ≥55-year-old smokers and among those who reported being more addicted to cigarettes. These results in Zambia document the high levels of brand loyalty in a market where price variation is fairly small across cigarette brands. Future research is needed on longitudinal trends to evaluate the effect of tobacco control policies in Zambia. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Theileriosis in Zambia: etiology, epidemiology and control measures.

PubMed

Nambota, A; Samui, K; Sugimoto, C; Kakuta, T; Onuma, M

1994-06-01

In Zambia, theileriosis manifests itself in the form of Corridor disease (CD), caused by Theileria parva lawrencei, and East Coast fever (ECF), caused by T. parva parva. Of the approximately 3 million cattle in Zambia, 1.4 million are at risk to theileriosis. ECF is found in the Northern and Eastern provinces of the country, while CD appears in Southern, Central, Lusaka and Copperbelt provinces. Theileriosis is a major constraint to the development of the livestock industry in Zambia, with losses of about 10,000 cattle per annum. The disease is spreading at a very fast rate, over-flowing its original borders. The epidemiology is complicated by, among other factors, the wide distribution of the tick vector, Rhipicephalus appendiculatus, which is found all over the country. The current strategy of relying on tick control and therapeutic drugs as a way of controlling the disease is becoming increasingly difficult for Zambia. This is because both curative drugs and acaricides are very costly. Immunization against theileriosis using the infection and treatment method as a way of controlling the disease is becoming increasingly accepted, provided local Theileria stocks are used. This paper reviews the incidence of theileriosis in the last 2 years, 1991 and 1992. It also gives a historical perspective of the disease, epidemiology and control measures presently in use.

TiConverter: A training image converting tool for multiple-point geostatistics

NASA Astrophysics Data System (ADS)

Fadlelmula F., Mohamed M.; Killough, John; Fraim, Michael

2016-11-01

TiConverter is a tool developed to ease the application of multiple-point geostatistics whether by the open source Stanford Geostatistical Modeling Software (SGeMS) or other available commercial software. TiConverter has a user-friendly interface and it allows the conversion of 2D training images into numerical representations in four different file formats without the need for additional code writing. These are the ASCII (.txt), the geostatistical software library (GSLIB) (.txt), the Isatis (.dat), and the VTK formats. It performs the conversion based on the RGB color system. In addition, TiConverter offers several useful tools including image resizing, smoothing, and segmenting tools. The purpose of this study is to introduce the TiConverter, and to demonstrate its application and advantages with several examples from the literature.

Can family planning outreach bridge the urban-rural divide in Zambia?

PubMed

White, Justin S; Speizer, Ilene S

2007-09-05

Zambia experienced declining aggregate fertility and increasing aggregate contraceptive use from 1990 to 2000. Yet, in rural Zambia, progress in family planning has lagged far behind the advances made in Zambia's urban areas. The contraceptive prevalence rate in Lusaka and other urban areas outstripped the rate in rural Zambia by nearly 25 percentage points (41.2 percent versus 16.6 percent) in 2001. The total fertility rate varied between urban and rural areas by 2.5 children (4.3 versus 6.9 children). This paper considers the urban-rural differentials in Zambia and assesses family planning outreach as a tool to narrow this divide. This study uses the Zambia Demographic and Health Survey (DHS) data, collected between 2001 and 2002. Logistic regression techniques were employed to examine factors associated with contraceptive use. The first analysis tested modern contraceptive use versus traditional method use and no use. In addition, separate models were run for samples stratified by type of residence (rural or urban) to determine if different factors were associated with use by residence. A simulation determined the effect of all women receiving at least one household visit from a health worker if all other variables were held constant. Differences in modern contraceptive use between urban and rural areas persist (OR: 1.56, 95 percent CI: 1.24-1.96) even after adjusting for a number of demographic, socioeconomic, cognitive, and attitudinal factors. Household visits by a community health worker significantly increased the likelihood of modern contraceptive use among rural women (OR: 1.83; 95 percent CI: 1.29-2.58). If all rural women received at least one outreach visit per year, the prevalence rate for modern contraceptive methods would be expected to increase for this group by 5.9 percentage points, a marked increase but less than one-quarter of the total urban-rural differential. Outreach in the form of health worker visits can improve access to family planning

Bayesian assessment of the expected data impact on prediction confidence in optimal sampling design

NASA Astrophysics Data System (ADS)

Leube, P. C.; Geiges, A.; Nowak, W.

2012-02-01

Incorporating hydro(geo)logical data, such as head and tracer data, into stochastic models of (subsurface) flow and transport helps to reduce prediction uncertainty. Because of financial limitations for investigation campaigns, information needs toward modeling or prediction goals should be satisfied efficiently and rationally. Optimal design techniques find the best one among a set of investigation strategies. They optimize the expected impact of data on prediction confidence or related objectives prior to data collection. We introduce a new optimal design method, called PreDIA(gnosis) (Preposterior Data Impact Assessor). PreDIA derives the relevant probability distributions and measures of data utility within a fully Bayesian, generalized, flexible, and accurate framework. It extends the bootstrap filter (BF) and related frameworks to optimal design by marginalizing utility measures over the yet unknown data values. PreDIA is a strictly formal information-processing scheme free of linearizations. It works with arbitrary simulation tools, provides full flexibility concerning measurement types (linear, nonlinear, direct, indirect), allows for any desired task-driven formulations, and can account for various sources of uncertainty (e.g., heterogeneity, geostatistical assumptions, boundary conditions, measurement values, model structure uncertainty, a large class of model errors) via Bayesian geostatistics and model averaging. Existing methods fail to simultaneously provide these crucial advantages, which our method buys at relatively higher-computational costs. We demonstrate the applicability and advantages of PreDIA over conventional linearized methods in a synthetic example of subsurface transport. In the example, we show that informative data is often invisible for linearized methods that confuse zero correlation with statistical independence. Hence, PreDIA will often lead to substantially better sampling designs. Finally, we extend our example to specifically

Recasting Postcolonial Citizenship through Civic Education: Critical Perspectives on Zambia

ERIC Educational Resources Information Center

Abdi, Ali A.; Shizha, Edward; Bwalya, Ignatio

2006-01-01

Since the early 1990s and, perhaps, as one effect of the emergence of the uni-polar world, there have been a lot of "democratizing" activities in the Sub-Saharan context, with Zambia, a central African country of about 10 million, at the forefront of these processes. While democracy, in one form or another, has come to Zambia,…

GEOSTATISTICAL SAMPLING DESIGNS FOR HAZARDOUS WASTE SITES

EPA Science Inventory

This chapter discusses field sampling design for environmental sites and hazardous waste sites with respect to random variable sampling theory, Gy's sampling theory, and geostatistical (kriging) sampling theory. The literature often presents these sampling methods as an adversari...

Hydrogeologic Unit Flow Characterization Using Transition Probability Geostatistics

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

Jones, N L; Walker, J R; Carle, S F

2003-11-21

This paper describes a technique for applying the transition probability geostatistics method for stochastic simulation to a MODFLOW model. Transition probability geostatistics has several advantages over traditional indicator kriging methods including a simpler and more intuitive framework for interpreting geologic relationships and the ability to simulate juxtapositional tendencies such as fining upwards sequences. The indicator arrays generated by the transition probability simulation are converted to layer elevation and thickness arrays for use with the new Hydrogeologic Unit Flow (HUF) package in MODFLOW 2000. This makes it possible to preserve complex heterogeneity while using reasonably sized grids. An application of themore » technique involving probabilistic capture zone delineation for the Aberjona Aquifer in Woburn, Ma. is included.« less

Consultancy Report: Assessment of the Zambia College of Distance Education (ZACODE)

ERIC Educational Resources Information Center

Ellis, Justin

2009-01-01

This study was carried out at the request of the Ministry of Education, Zambia. The Commonwealth of Learning contracted Turning Points Consultancy CC, a Namibian company, who provided the services of the author, to "carry out an evaluation of the Zambia College of Distance Education (ZACODE) and submit recommendations to the Ministry of…

77 FR 60966 - Executive-Led Trade Mission to South Africa and Zambia

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-05

... Africa and Zambia AGENCY: International Trade Administration, Department of Commerce. ACTION: Notice...- Led Trade Mission to South Africa and Zambia scheduled for November 26- 30, 2012, to revise the dates... and scheduling constraints permit), interested U.S. agriculture, mining, transportation, water, energy...

Integrating Address Geocoding, Land Use Regression, and Spatiotemporal Geostatistical Estimation for Groundwater Tetrachloroethylene

PubMed Central

Messier, Kyle P.; Akita, Yasuyuki; Serre, Marc L.

2012-01-01

Geographic Information Systems (GIS) based techniques are cost-effective and efficient methods used by state agencies and epidemiology researchers for estimating concentration and exposure. However, budget limitations have made statewide assessments of contamination difficult, especially in groundwater media. Many studies have implemented address geocoding, land use regression, and geostatistics independently, but this is the first to examine the benefits of integrating these GIS techniques to address the need of statewide exposure assessments. A novel framework for concentration exposure is introduced that integrates address geocoding, land use regression (LUR), below detect data modeling, and Bayesian Maximum Entropy (BME). A LUR model was developed for Tetrachloroethylene that accounts for point sources and flow direction. We then integrate the LUR model into the BME method as a mean trend while also modeling below detects data as a truncated Gaussian probability distribution function. We increase available PCE data 4.7 times from previously available databases through multistage geocoding. The LUR model shows significant influence of dry cleaners at short ranges. The integration of the LUR model as mean trend in BME results in a 7.5% decrease in cross validation mean square error compared to BME with a constant mean trend. PMID:22264162

Integrating address geocoding, land use regression, and spatiotemporal geostatistical estimation for groundwater tetrachloroethylene.

PubMed

Messier, Kyle P; Akita, Yasuyuki; Serre, Marc L

2012-03-06

Geographic information systems (GIS) based techniques are cost-effective and efficient methods used by state agencies and epidemiology researchers for estimating concentration and exposure. However, budget limitations have made statewide assessments of contamination difficult, especially in groundwater media. Many studies have implemented address geocoding, land use regression, and geostatistics independently, but this is the first to examine the benefits of integrating these GIS techniques to address the need of statewide exposure assessments. A novel framework for concentration exposure is introduced that integrates address geocoding, land use regression (LUR), below detect data modeling, and Bayesian Maximum Entropy (BME). A LUR model was developed for tetrachloroethylene that accounts for point sources and flow direction. We then integrate the LUR model into the BME method as a mean trend while also modeling below detects data as a truncated Gaussian probability distribution function. We increase available PCE data 4.7 times from previously available databases through multistage geocoding. The LUR model shows significant influence of dry cleaners at short ranges. The integration of the LUR model as mean trend in BME results in a 7.5% decrease in cross validation mean square error compared to BME with a constant mean trend.

Three-dimensional Bayesian geostatistical aquifer characterization at the Hanford 300 Area using tracer test data

NASA Astrophysics Data System (ADS)

Chen, Xingyuan; Murakami, Haruko; Hahn, Melanie S.; Hammond, Glenn E.; Rockhold, Mark L.; Zachara, John M.; Rubin, Yoram

2012-06-01

Tracer tests performed under natural or forced gradient flow conditions can provide useful information for characterizing subsurface properties, through monitoring, modeling, and interpretation of the tracer plume migration in an aquifer. Nonreactive tracer experiments were conducted at the Hanford 300 Area, along with constant-rate injection tests and electromagnetic borehole flowmeter tests. A Bayesian data assimilation technique, the method of anchored distributions (MAD) (Rubin et al., 2010), was applied to assimilate the experimental tracer test data with the other types of data and to infer the three-dimensional heterogeneous structure of the hydraulic conductivity in the saturated zone of the Hanford formation.In this study, the Bayesian prior information on the underlying random hydraulic conductivity field was obtained from previous field characterization efforts using constant-rate injection and borehole flowmeter test data. The posterior distribution of the conductivity field was obtained by further conditioning the field on the temporal moments of tracer breakthrough curves at various observation wells. MAD was implemented with the massively parallel three-dimensional flow and transport code PFLOTRAN to cope with the highly transient flow boundary conditions at the site and to meet the computational demands of MAD. A synthetic study proved that the proposed method could effectively invert tracer test data to capture the essential spatial heterogeneity of the three-dimensional hydraulic conductivity field. Application of MAD to actual field tracer data at the Hanford 300 Area demonstrates that inverting for spatial heterogeneity of hydraulic conductivity under transient flow conditions is challenging and more work is needed.

Geostatistics for environmental and geotechnical applications

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

Rouhani, S.; Srivastava, R.M.; Desbarats, A.J.

1996-12-31

This conference was held January 26--27, 1995 in Phoenix, Arizona. The purpose of this conference was to provide a multidisciplinary forum for exchange of state-of-the-art information on the technology of geostatistics and its applicability for environmental studies, especially site characterization. Individual papers have been processed separately for inclusion in the appropriate data bases.

Combining geostatistics with Moran's I analysis for mapping soil heavy metals in Beijing, China.

PubMed

Huo, Xiao-Ni; Li, Hong; Sun, Dan-Feng; Zhou, Lian-Di; Li, Bao-Guo

2012-03-01

Production of high quality interpolation maps of heavy metals is important for risk assessment of environmental pollution. In this paper, the spatial correlation characteristics information obtained from Moran's I analysis was used to supplement the traditional geostatistics. According to Moran's I analysis, four characteristics distances were obtained and used as the active lag distance to calculate the semivariance. Validation of the optimality of semivariance demonstrated that using the two distances where the Moran's I and the standardized Moran's I, Z(I) reached a maximum as the active lag distance can improve the fitting accuracy of semivariance. Then, spatial interpolation was produced based on the two distances and their nested model. The comparative analysis of estimation accuracy and the measured and predicted pollution status showed that the method combining geostatistics with Moran's I analysis was better than traditional geostatistics. Thus, Moran's I analysis is a useful complement for geostatistics to improve the spatial interpolation accuracy of heavy metals.

Geostatistical noise filtering of geophysical images : application to unexploded ordnance (UXO) sites.

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

Saito, Hirotaka; McKenna, Sean Andrew; Coburn, Timothy C.

2004-07-01

Geostatistical and non-geostatistical noise filtering methodologies, factorial kriging and a low-pass filter, and a region growing method are applied to analytic signal magnetometer images at two UXO contaminated sites to delineate UXO target areas. Overall delineation performance is improved by removing background noise. Factorial kriging slightly outperforms the low-pass filter but there is no distinct difference between them in terms of finding anomalies of interest.

Use of geostatistics for remediation planning to transcend urban political boundaries.

PubMed

Milillo, Tammy M; Sinha, Gaurav; Gardella, Joseph A

2012-11-01

Soil remediation plans are often dictated by areas of jurisdiction or property lines instead of scientific information. This study exemplifies how geostatistically interpolated surfaces can substantially improve remediation planning. Ordinary kriging, ordinary co-kriging, and inverse distance weighting spatial interpolation methods were compared for analyzing surface and sub-surface soil sample data originally collected by the US EPA and researchers at the University at Buffalo in Hickory Woods, an industrial-residential neighborhood in Buffalo, NY, where both lead and arsenic contamination is present. Past clean-up efforts estimated contamination levels from point samples, but parcel and agency jurisdiction boundaries were used to define remediation sites, rather than geostatistical models estimating the spatial behavior of the contaminants in the soil. Residents were understandably dissatisfied with the arbitrariness of the remediation plan. In this study we show how geostatistical mapping and participatory assessment can make soil remediation scientifically defensible, socially acceptable, and economically feasible. Copyright © 2012 Elsevier Ltd. All rights reserved.

Estimation of Fine Particulate Matter in Taipei Using Landuse Regression and Bayesian Maximum Entropy Methods

PubMed Central

Yu, Hwa-Lung; Wang, Chih-Hsih; Liu, Ming-Che; Kuo, Yi-Ming

2011-01-01

Fine airborne particulate matter (PM2.5) has adverse effects on human health. Assessing the long-term effects of PM2.5 exposure on human health and ecology is often limited by a lack of reliable PM2.5 measurements. In Taipei, PM2.5 levels were not systematically measured until August, 2005. Due to the popularity of geographic information systems (GIS), the landuse regression method has been widely used in the spatial estimation of PM concentrations. This method accounts for the potential contributing factors of the local environment, such as traffic volume. Geostatistical methods, on other hand, account for the spatiotemporal dependence among the observations of ambient pollutants. This study assesses the performance of the landuse regression model for the spatiotemporal estimation of PM2.5 in the Taipei area. Specifically, this study integrates the landuse regression model with the geostatistical approach within the framework of the Bayesian maximum entropy (BME) method. The resulting epistemic framework can assimilate knowledge bases including: (a) empirical-based spatial trends of PM concentration based on landuse regression, (b) the spatio-temporal dependence among PM observation information, and (c) site-specific PM observations. The proposed approach performs the spatiotemporal estimation of PM2.5 levels in the Taipei area (Taiwan) from 2005–2007. PMID:21776223

Estimation of fine particulate matter in Taipei using landuse regression and bayesian maximum entropy methods.

PubMed

Yu, Hwa-Lung; Wang, Chih-Hsih; Liu, Ming-Che; Kuo, Yi-Ming

2011-06-01

Fine airborne particulate matter (PM2.5) has adverse effects on human health. Assessing the long-term effects of PM2.5 exposure on human health and ecology is often limited by a lack of reliable PM2.5 measurements. In Taipei, PM2.5 levels were not systematically measured until August, 2005. Due to the popularity of geographic information systems (GIS), the landuse regression method has been widely used in the spatial estimation of PM concentrations. This method accounts for the potential contributing factors of the local environment, such as traffic volume. Geostatistical methods, on other hand, account for the spatiotemporal dependence among the observations of ambient pollutants. This study assesses the performance of the landuse regression model for the spatiotemporal estimation of PM2.5 in the Taipei area. Specifically, this study integrates the landuse regression model with the geostatistical approach within the framework of the Bayesian maximum entropy (BME) method. The resulting epistemic framework can assimilate knowledge bases including: (a) empirical-based spatial trends of PM concentration based on landuse regression, (b) the spatio-temporal dependence among PM observation information, and (c) site-specific PM observations. The proposed approach performs the spatiotemporal estimation of PM2.5 levels in the Taipei area (Taiwan) from 2005-2007.

Model-Based Geostatistical Mapping of the Prevalence of Onchocerca volvulus in West Africa

PubMed Central

O’Hanlon, Simon J.; Slater, Hannah C.; Cheke, Robert A.; Boatin, Boakye A.; Coffeng, Luc E.; Pion, Sébastien D. S.; Boussinesq, Michel; Zouré, Honorat G. M.; Stolk, Wilma A.; Basáñez, María-Gloria

2016-01-01

Background The initial endemicity (pre-control prevalence) of onchocerciasis has been shown to be an important determinant of the feasibility of elimination by mass ivermectin distribution. We present the first geostatistical map of microfilarial prevalence in the former Onchocerciasis Control Programme in West Africa (OCP) before commencement of antivectorial and antiparasitic interventions. Methods and Findings Pre-control microfilarial prevalence data from 737 villages across the 11 constituent countries in the OCP epidemiological database were used as ground-truth data. These 737 data points, plus a set of statistically selected environmental covariates, were used in a Bayesian model-based geostatistical (B-MBG) approach to generate a continuous surface (at pixel resolution of 5 km x 5km) of microfilarial prevalence in West Africa prior to the commencement of the OCP. Uncertainty in model predictions was measured using a suite of validation statistics, performed on bootstrap samples of held-out validation data. The mean Pearson’s correlation between observed and estimated prevalence at validation locations was 0.693; the mean prediction error (average difference between observed and estimated values) was 0.77%, and the mean absolute prediction error (average magnitude of difference between observed and estimated values) was 12.2%. Within OCP boundaries, 17.8 million people were deemed to have been at risk, 7.55 million to have been infected, and mean microfilarial prevalence to have been 45% (range: 2–90%) in 1975. Conclusions and Significance This is the first map of initial onchocerciasis prevalence in West Africa using B-MBG. Important environmental predictors of infection prevalence were identified and used in a model out-performing those without spatial random effects or environmental covariates. Results may be compared with recent epidemiological mapping efforts to find areas of persisting transmission. These methods may be extended to areas where

Structural adjustment and drought in Zambia.

PubMed

Mulwanda, M

1995-06-01

While drought is not uncommon in Zambia, the country is now facing the worst drought in history. The monetary and social costs will be enormous. Although it is too early to measure the economic and social costs of the drought on Zambia, it is obvious that the impact is catastrophic on a country whose economy is under pressure. The drought will affect the structural adjustment programme (SAP) unveiled by the new government which has embraced the market economy. The country has imported, and will continue to import, large quantities of maize and other foodstuffs, a situation likely to strain the balance of payments. Earlier targets with regard to export earnings, reductions in the budget deficit, and GDP growth as contained in the Policy Framework Paper (PFP) are no longer attainable due to the effects of the drought.

Estimation of geotechnical parameters on the basis of geophysical methods and geostatistics

NASA Astrophysics Data System (ADS)

Brom, Aleksander; Natonik, Adrianna

2017-12-01

The paper presents possible implementation of ordinary cokriging and geophysical investigation on humidity data acquired in geotechnical studies. The Author describes concept of geostatistics, terminology of geostatistical modelling, spatial correlation functions, principles of solving cokriging systems, advantages of (co-)kriging in comparison with other interpolation methods, obstacles in this type of attempt. Cross validation and discussion of results was performed with an indication of prospect of applying similar procedures in various researches..

Geostatistical estimation of forest biomass in interior Alaska combining Landsat-derived tree cover, sampled airborne lidar and field observations

NASA Astrophysics Data System (ADS)

Babcock, Chad; Finley, Andrew O.; Andersen, Hans-Erik; Pattison, Robert; Cook, Bruce D.; Morton, Douglas C.; Alonzo, Michael; Nelson, Ross; Gregoire, Timothy; Ene, Liviu; Gobakken, Terje; Næsset, Erik

2018-06-01

The goal of this research was to develop and examine the performance of a geostatistical coregionalization modeling approach for combining field inventory measurements, strip samples of airborne lidar and Landsat-based remote sensing data products to predict aboveground biomass (AGB) in interior Alaska's Tanana Valley. The proposed modeling strategy facilitates pixel-level mapping of AGB density predictions across the entire spatial domain. Additionally, the coregionalization framework allows for statistically sound estimation of total AGB for arbitrary areal units within the study area---a key advance to support diverse management objectives in interior Alaska. This research focuses on appropriate characterization of prediction uncertainty in the form of posterior predictive coverage intervals and standard deviations. Using the framework detailed here, it is possible to quantify estimation uncertainty for any spatial extent, ranging from pixel-level predictions of AGB density to estimates of AGB stocks for the full domain. The lidar-informed coregionalization models consistently outperformed their counterpart lidar-free models in terms of point-level predictive performance and total AGB precision. Additionally, the inclusion of Landsat-derived forest cover as a covariate further improved estimation precision in regions with lower lidar sampling intensity. Our findings also demonstrate that model-based approaches that do not explicitly account for residual spatial dependence can grossly underestimate uncertainty, resulting in falsely precise estimates of AGB. On the other hand, in a geostatistical setting, residual spatial structure can be modeled within a Bayesian hierarchical framework to obtain statistically defensible assessments of uncertainty for AGB estimates.

Zambia: Multi-Faith Religious Education?

ERIC Educational Resources Information Center

Carmody, Brendan

2006-01-01

As countries' populations become more religiously diverse, a need to review the religious education syllabus that operates is often perceived. One such country is Zambia, which was not only traditionally religiously diverse but has become even more so with the advent of Christianity, Islam and Hinduism and other non-African faiths. This article…

[Spatial distribution pattern of Chilo suppressalis analyzed by classical method and geostatistics].

PubMed

Yuan, Zheming; Fu, Wei; Li, Fangyi

2004-04-01

Two original samples of Chilo suppressalis and their grid, random and sequence samples were analyzed by classical method and geostatistics to characterize the spatial distribution pattern of C. suppressalis. The limitations of spatial distribution analysis with classical method, especially influenced by the original position of grid, were summarized rather completely. On the contrary, geostatistics characterized well the spatial distribution pattern, congregation intensity and spatial heterogeneity of C. suppressalis. According to geostatistics, the population was up to Poisson distribution in low density. As for higher density population, its distribution was up to aggregative, and the aggregation intensity and dependence range were 0.1056 and 193 cm, respectively. Spatial heterogeneity was also found in the higher density population. Its spatial correlativity in line direction was more closely than that in row direction, and the dependence ranges in line and row direction were 115 and 264 cm, respectively.

Urbanization in Zambia. An International Urbanization Survey Report to the Ford Foundation.

ERIC Educational Resources Information Center

Simmance, Alan J. F.

This report reviews the "Seers Report," which contained policy guidelines for modern development planning in Zambia, and compares its findings to recent findings during the period 1963-1970. The Seers Report found that Zambia was the most urbanized country in Africa south of the Sahara (excluding South Africa). This report finds that…

A flexible Bayesian assessment for the expected impact of data on prediction confidence for optimal sampling designs

NASA Astrophysics Data System (ADS)

Leube, Philipp; Geiges, Andreas; Nowak, Wolfgang

2010-05-01

Incorporating hydrogeological data, such as head and tracer data, into stochastic models of subsurface flow and transport helps to reduce prediction uncertainty. Considering limited financial resources available for the data acquisition campaign, information needs towards the prediction goal should be satisfied in a efficient and task-specific manner. For finding the best one among a set of design candidates, an objective function is commonly evaluated, which measures the expected impact of data on prediction confidence, prior to their collection. An appropriate approach to this task should be stochastically rigorous, master non-linear dependencies between data, parameters and model predictions, and allow for a wide variety of different data types. Existing methods fail to fulfill all these requirements simultaneously. For this reason, we introduce a new method, denoted as CLUE (Cross-bred Likelihood Uncertainty Estimator), that derives the essential distributions and measures of data utility within a generalized, flexible and accurate framework. The method makes use of Bayesian GLUE (Generalized Likelihood Uncertainty Estimator) and extends it to an optimal design method by marginalizing over the yet unknown data values. Operating in a purely Bayesian Monte-Carlo framework, CLUE is a strictly formal information processing scheme free of linearizations. It provides full flexibility associated with the type of measurements (linear, non-linear, direct, indirect) and accounts for almost arbitrary sources of uncertainty (e.g. heterogeneity, geostatistical assumptions, boundary conditions, model concepts) via stochastic simulation and Bayesian model averaging. This helps to minimize the strength and impact of possible subjective prior assumptions, that would be hard to defend prior to data collection. Our study focuses on evaluating two different uncertainty measures: (i) expected conditional variance and (ii) expected relative entropy of a given prediction goal. The

Combining Geostatistics with Moran’s I Analysis for Mapping Soil Heavy Metals in Beijing, China

PubMed Central

Huo, Xiao-Ni; Li, Hong; Sun, Dan-Feng; Zhou, Lian-Di; Li, Bao-Guo

2012-01-01

Production of high quality interpolation maps of heavy metals is important for risk assessment of environmental pollution. In this paper, the spatial correlation characteristics information obtained from Moran’s I analysis was used to supplement the traditional geostatistics. According to Moran’s I analysis, four characteristics distances were obtained and used as the active lag distance to calculate the semivariance. Validation of the optimality of semivariance demonstrated that using the two distances where the Moran’s I and the standardized Moran’s I, Z(I) reached a maximum as the active lag distance can improve the fitting accuracy of semivariance. Then, spatial interpolation was produced based on the two distances and their nested model. The comparative analysis of estimation accuracy and the measured and predicted pollution status showed that the method combining geostatistics with Moran’s I analysis was better than traditional geostatistics. Thus, Moran’s I analysis is a useful complement for geostatistics to improve the spatial interpolation accuracy of heavy metals. PMID:22690179

Assessment and modeling of the groundwater hydrogeochemical quality parameters via geostatistical approaches

NASA Astrophysics Data System (ADS)

Karami, Shawgar; Madani, Hassan; Katibeh, Homayoon; Fatehi Marj, Ahmad

2018-03-01

Geostatistical methods are one of the advanced techniques used for interpolation of groundwater quality data. The results obtained from geostatistics will be useful for decision makers to adopt suitable remedial measures to protect the quality of groundwater sources. Data used in this study were collected from 78 wells in Varamin plain aquifer located in southeast of Tehran, Iran, in 2013. Ordinary kriging method was used in this study to evaluate groundwater quality parameters. According to what has been mentioned in this paper, seven main quality parameters (i.e. total dissolved solids (TDS), sodium adsorption ratio (SAR), electrical conductivity (EC), sodium (Na+), total hardness (TH), chloride (Cl-) and sulfate (SO4 2-)), have been analyzed and interpreted by statistical and geostatistical methods. After data normalization by Nscore method in WinGslib software, variography as a geostatistical tool to define spatial regression was compiled and experimental variograms were plotted by GS+ software. Then, the best theoretical model was fitted to each variogram based on the minimum RSS. Cross validation method was used to determine the accuracy of the estimated data. Eventually, estimation maps of groundwater quality were prepared in WinGslib software and estimation variance map and estimation error map were presented to evaluate the quality of estimation in each estimated point. Results showed that kriging method is more accurate than the traditional interpolation methods.

Three-Dimensional Bayesian Geostatistical Aquifer Characterization at the Hanford 300 Area using Tracer Test Data

NASA Astrophysics Data System (ADS)

Chen, X.; Murakami, H.; Hahn, M. S.; Hammond, G. E.; Rockhold, M. L.; Rubin, Y.

2010-12-01

Tracer testing under natural or forced gradient flow provides useful information for characterizing subsurface properties, by monitoring and modeling the tracer plume migration in a heterogeneous aquifer. At the Hanford 300 Area, non-reactive tracer experiments, in addition to constant-rate injection tests and electromagnetic borehole flowmeter (EBF) profiling, were conducted to characterize the heterogeneous hydraulic conductivity field. A Bayesian data assimilation technique, method of anchored distributions (MAD), is applied to assimilate the experimental tracer test data and to infer the three-dimensional heterogeneous structure of the hydraulic conductivity in the saturated zone of the Hanford formation. In this study, the prior information of the underlying random hydraulic conductivity field was obtained from previous field characterization efforts using the constant-rate injection tests and the EBF data. The posterior distribution of the random field is obtained by further conditioning the field on the temporal moments of tracer breakthrough curves at various observation wells. The parallel three-dimensional flow and transport code PFLOTRAN is implemented to cope with the highly transient flow boundary conditions at the site and to meet the computational demand of the proposed method. The validation results show that the field conditioned on the tracer test data better reproduces the tracer transport behavior compared to the field characterized previously without the tracer test data. A synthetic study proves that the proposed method can effectively assimilate tracer test data to capture the essential spatial heterogeneity of the three-dimensional hydraulic conductivity field. These characterization results will improve conceptual models developed for the site, including reactive transport models. The study successfully demonstrates the capability of MAD to assimilate multi-scale multi-type field data within a consistent Bayesian framework. The MAD

"Lazy men", time-use, and rural development in Zambia.

PubMed

Whitehead, A

1999-11-01

This paper examines how work and the labor in agriculture in rural sub-Saharan Africa is measured. Section 1 presents a historical example of colonial discourses of the "lazy" African (the Lamba in Zambia). Section 2 analyzes a study carried out in rural Zambia to illustrate the relationship between stereotypes held by many Europeans, particular aspects of the colonial project, and the social relations brought about by colonialism. Section 3 examines the ways in which present work and labor approaches in sub-Saharan Africa embody value judgements which leads to distorted documentation of the division of labor between opposite genders. Sections 4 through 7 look at a time-use study conducted in Zambia and argue that studies of such nature create value judgement on what comprises work, and about how researchers and planners classify this. Overall, this article has demonstrated that time-use surveys may provide inadequate understanding of women and men's work in the absence of an understanding of the local context in which the work is undertaken, and of labor markets.

Breast carcinoma, intratumour heterogeneity and histological grading, using geostatistics.

PubMed

Sharifi-Salamatian, V; de Roquancourt, A; Rigaut, J P

2000-01-01

Tumour progression is currently believed to result from genetic instability. Chromosomal patterns specific of a type of cancer are frequent even though phenotypic spatial heterogeneity is omnipresent. The latter is the usual cause of histological grading imprecision, a well documented problem, without any fully satisfactory solution up to now. The present article addresses this problem in breast carcinoma. The assessment of a genetic marker for human tumours requires quantifiable measures of intratumoral heterogeneity. If any invariance paradigm representing a stochastic or geostatistic function could be discovered, this might help in solving the grading problem. A novel methodological approach using geostatistics to measure heterogeneity is used. Twenty tumours from the three usual (Scarff-Bloom and Richardson) grades were obtained and paraffin sections stained by MIB-1 (Ki-67) and peroxidase staining. Whole two-dimensional sections were sampled. Morphometric grids of variable sizes allowed a simple and fast recording of positions of epithelial nuclei, marked or not by MIB-1. The geostatistical method is based here upon the asymptotic behaviour of dispersion variance. Measure of asymptotic exponent of dispersion variance shows an increase from grade 1 to grade 3. Preliminary results are encouraging: grades 1 and 3 on one hand and 2 and 3 on the other hand are totally separated. The final proof of an improved grading using this measure will of course require a confrontation with the results of survival studies.

200 junior doctors sacked in Zambia.

PubMed

Ahmad, K

2000-07-29

Since December 1999 junior doctors in Zambia have been on strike, demanding from the government better working conditions, better pay, and improvements in hospital services. However, on June 20, 2000, around 200 junior doctors were dismissed by the Zambian government, who asserts that the action was taken in the public¿s interest. Nevertheless, the doctors argue that the move came at a time when the country is struggling with a critical shortage of doctors and with an HIV/AIDS crisis. In addition, health policy experts say that the dismissal could further undermine the alarming conditions of Zambia's health care system. It is noted that there are only 800 doctors registered with the Zambian Medical Council, but WHO estimates that the country needs 1500 clinicians. To meet such a shortage, the government has hired Cuban and Chinese doctors. They are paid more and given more benefits than the Zambian doctors, generating complaints from the president of the junior doctors' representative body.

Assessment of geostatistical features for object-based image classification of contrasted landscape vegetation cover

NASA Astrophysics Data System (ADS)

de Oliveira Silveira, Eduarda Martiniano; de Menezes, Michele Duarte; Acerbi Júnior, Fausto Weimar; Castro Nunes Santos Terra, Marcela; de Mello, José Márcio

2017-07-01

Accurate mapping and monitoring of savanna and semiarid woodland biomes are needed to support the selection of areas of conservation, to provide sustainable land use, and to improve the understanding of vegetation. The potential of geostatistical features, derived from medium spatial resolution satellite imagery, to characterize contrasted landscape vegetation cover and improve object-based image classification is studied. The study site in Brazil includes cerrado sensu stricto, deciduous forest, and palm swamp vegetation cover. Sentinel 2 and Landsat 8 images were acquired and divided into objects, for each of which a semivariogram was calculated using near-infrared (NIR) and normalized difference vegetation index (NDVI) to extract the set of geostatistical features. The features selected by principal component analysis were used as input data to train a random forest algorithm. Tests were conducted, combining spectral and geostatistical features. Change detection evaluation was performed using a confusion matrix and its accuracies. The semivariogram curves were efficient to characterize spatial heterogeneity, with similar results using NIR and NDVI from Sentinel 2 and Landsat 8. Accuracy was significantly greater when combining geostatistical features with spectral data, suggesting that this method can improve image classification results.

Bismarck in the Bush: Year 12 Write Zambia's History for Zambian Students

ERIC Educational Resources Information Center

Gray, Peter

2011-01-01

Peter Gray explains how his Year 12 students came to research and write a resource on the history of Zambia, for history teachers "in" Zambia. The construction of the resource stretched the Year 12 students in new ways: the Internet was useless and there were no easy digests in A-Level textbooks to get them started. They would have to…

7 CFR 319.56-43 - Baby corn and baby carrots from Zambia.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 5 2011-01-01 2011-01-01 false Baby corn and baby carrots from Zambia. 319.56-43... § 319.56-43 Baby corn and baby carrots from Zambia. (a) Immature, dehusked “baby” sweet corn (Zea mays L..., which is a field, where the corn has been grown must have been inspected at least once during the...

Strategies for Living with the Challenges of HIV and Antiretroviral Use in Zambia

ERIC Educational Resources Information Center

Jones, Deborah; Zulu, Isaac; Mumbi, Miriam; Chitalu, Ndashi; Vamos, Szonja; Gomez, Jacqueline; Weiss, Stephen M.

2009-01-01

This study sought to identify strategies for living with the challenges of HIV and antiretroviral (ARV) use among new medication users in urban Zambia. Participants (n = 160) were recruited from urban Lusaka, Zambia. Qualitative Data was drawn from monthly ARV treatment education intervention groups addressing HIV and antiretroviral use. Themes…

Introduction to This Special Issue on Geostatistics and Geospatial Techniques in Remote Sensing

NASA Technical Reports Server (NTRS)

Atkinson, Peter; Quattrochi, Dale A.; Goodman, H. Michael (Technical Monitor)

2000-01-01

The germination of this special Computers & Geosciences (C&G) issue began at the Royal Geographical Society (with the Institute of British Geographers) (RGS-IBG) annual meeting in January 1997 held at the University of Exeter, UK. The snow and cold of the English winter were tempered greatly by warm and cordial discussion of how to stimulate and enhance cooperation on geostatistical and geospatial research in remote sensing 'across the big pond' between UK and US researchers. It was decided that one way forward would be to hold parallel sessions in 1998 on geostatistical and geospatial research in remote sensing at appropriate venues in both the UK and the US. Selected papers given at these sessions would be published as special issues of C&G on the UK side and Photogrammetric Engineering and Remote Sensing (PE&RS) on the US side. These issues would highlight the commonality in research on geostatistical and geospatial research in remote sensing on both sides of the Atlantic Ocean. As a consequence, a session on "Geostatistics and Geospatial Techniques for Remote Sensing of Land Surface Processes" was held at the RGS-IBG annual meeting in Guildford, Surrey, UK in January 1998, organized by the Modeling and Advanced Techniques Special Interest Group (MAT SIG) of the Remote Sensing Society (RSS). A similar session was held at the Association of American Geographers (AAG) annual meeting in Boston, Massachusetts in March 1998, sponsored by the AAG's Remote Sensing Specialty Group (RSSG). The 10 papers that make up this issue of C&G, comprise 7 papers from the UK and 3 papers from the LIS. We are both co-editors of each of the journal special issues, with the lead editor of each journal issue being from their respective side of the Atlantic. The special issue of PE&RS (vol. 65) that constitutes the other half of this co-edited journal series was published in early 1999, comprising 6 papers by US authors. We are indebted to the International Association for Mathematical

Mwabu: Interactive Education in Zambia

ERIC Educational Resources Information Center

Gordon, Jenny; Postlewhite, Kerry

2017-01-01

Africa has more people younger than 20 years old than anywhere in the world, and the continent's population is set to double to two billion by 2050. Asking whether that is a challenge or an opportunity isn't really the right question because it is both. For Mwabu, an education technology company born and bred in Zambia, the more important question…

The Zambia Children's KS-HHV8 Study: Rationale, Study Design, and Study Methods

PubMed Central

Minhas, Veenu; Crabtree, Kay L.; Chao, Ann; Wojcicki, Janet M.; Sifuniso, Adrian M.; Nkonde, Catherine; Kankasa, Chipepo; Mitchell, Charles D.; Wood, Charles

2011-01-01

The epidemic of human immunodeficiency virus in Zambia has led to a dramatic rise in the incidence of human herpesvirus-8 (HHV-8)–associated Kaposi's sarcoma in both adults and children. However, there is a paucity of knowledge about the routes of HHV-8 transmission to young children. The Zambia Children's KS-HHV8 Study, a large, prospective cohort study in Lusaka, Zambia, was launched in 2004 to investigate the role of household members as a source of HHV-8 infection in young children and social behaviors that may modify the risk of HHV-8 acquisition. This cohort is distinct from other epidemiologic studies designed to investigate HHV-8 incidence and transmission because it recruited and followed complete households in the urban central African context. Between July 2004 and March 2007, 1,600 households were screened; 368 households comprising 464 children and 1,335 caregivers and household members were enrolled. Follow-up of this population continued for 48 months postrecruitment, affording a unique opportunity to study horizontal transmission of HHV-8 and understand the routes and sources of transmission to young children in Zambia. The authors describe the study rationale, design, execution, and characteristics of this cohort, which provides critical data on the epidemiology and transmission of HHV-8 to young children in Zambia. PMID:21447476

Aspergillus section Flavi community structure in Zambia influences aflatoxin contamination of maize and groundnut.

PubMed

Kachapulula, Paul W; Akello, Juliet; Bandyopadhyay, Ranajit; Cotty, Peter J

2017-11-16

Aflatoxins are cancer-causing, immuno-suppressive mycotoxins that frequently contaminate important staples in Zambia including maize and groundnut. Several species within Aspergillus section Flavi have been implicated as causal agents of aflatoxin contamination in Africa. However, Aspergillus populations associated with aflatoxin contamination in Zambia have not been adequately detailed. Most of Zambia's arable land is non-cultivated and Aspergillus communities in crops may originate in non-cultivated soil. However, relationships between Aspergillus populations on crops and those resident in non-cultivated soils have not been explored. Because characterization of similar fungal populations outside of Zambia have resulted in strategies to prevent aflatoxins, the current study sought to improve understanding of fungal communities in cultivated and non-cultivated soils and in crops. Crops (n=412) and soils from cultivated (n=160) and non-cultivated land (n=60) were assayed for Aspergillus section Flavi from 2012 to 2016. The L-strain morphotype of Aspergillus flavus and A. parasiticus were dominant on maize and groundnut (60% and 42% of Aspergillus section Flavi, respectively). Incidences of A. flavus L-morphotype were negatively correlated with aflatoxin in groundnut (log y=2.4990935-0.09966x, R 2 =0.79, P=0.001) but not in maize. Incidences of A. parasiticus partially explained groundnut aflatoxin concentrations in all agroecologies and maize aflatoxin in agroecology III (log y=0.1956034+0.510379x, R 2 =0.57, P<0.001) supporting A. parasiticus as the dominant etiologic agent of aflatoxin contamination in Zambia. Communities in both non-cultivated and cultivated soils were dominated by A. parasiticus (69% and 58%, respectively). Aspergillus parasiticus from cultivated and non-cultivated land produced statistically similar concentrations of aflatoxins. Aflatoxin-producers causing contamination of crops in Zambia may be native and, originate from non-cultivated areas

Improving paediatric asthma care in Zambia

PubMed Central

Jumbe-Marsden, Emilia; Mateyo, Kondwelani; Senkwe, Mutale Nsakashalo; Sotomayor-Ruiz, Maria; Musuku, John; Soriano, Joan B; Ancochea, Julio; Fishman, Mark C

2015-01-01

Abstract Problem In 2008, the prevalence of paediatric asthma in Zambia was unknown and the national treatment guideline was outdated. Approach We created an international partnership between Zambian clinicians, the Zambian Government and a pharmaceutical company to address shortcomings in asthma treatment. We did two studies, one to estimate prevalence in the capital of Lusaka and one to assess attitudes and practices of patients. Based on the information obtained, we educated health workers and the public. The information from the studies was also used to modernize government policy for paediatric asthma management. Local setting The health-care system in Zambia is primarily focused on acute care delivery with a focus on infectious diseases. Comprehensive services for noncommunicable diseases are lacking. Asthma management relies on treatment of acute exacerbations instead of disease control. Relevant changes Seven percent of children surveyed had asthma (255/3911). Of the 120 patients interviewed, most (82/120, 68%) used oral short-acting β2-agonists for symptom control; almost half (59/120, 49%) did not think the symptoms were preventable and 43% (52/120) thought inhalers were addictive. These misconceptions informed broad-based educational programmes. We used a train-the-trainer model to educate health-care workers and ran public awareness campaigns. Access to inhalers was increased and the Zambian standard treatment guideline for paediatric asthma was revised to include steroid inhalers as a control treatment. Lessons learnt Joint activities were required to change paediatric asthma care in Zambia. Success will depend on local sustainability, and it may be necessary to shift resources to mirror the disease burden. PMID:26600616

Benchmarking a geostatistical procedure for the homogenisation of annual precipitation series

NASA Astrophysics Data System (ADS)

Caineta, Júlio; Ribeiro, Sara; Henriques, Roberto; Soares, Amílcar; Costa, Ana Cristina

2014-05-01

The European project COST Action ES0601, Advances in homogenisation methods of climate series: an integrated approach (HOME), has brought to attention the importance of establishing reliable homogenisation methods for climate data. In order to achieve that, a benchmark data set, containing monthly and daily temperature and precipitation data, was created to be used as a comparison basis for the effectiveness of those methods. Several contributions were submitted and evaluated by a number of performance metrics, validating the results against realistic inhomogeneous data. HOME also led to the development of new homogenisation software packages, which included feedback and lessons learned during the project. Preliminary studies have suggested a geostatistical stochastic approach, which uses Direct Sequential Simulation (DSS), as a promising methodology for the homogenisation of precipitation data series. Based on the spatial and temporal correlation between the neighbouring stations, DSS calculates local probability density functions at a candidate station to detect inhomogeneities. The purpose of the current study is to test and compare this geostatistical approach with the methods previously presented in the HOME project, using surrogate precipitation series from the HOME benchmark data set. The benchmark data set contains monthly precipitation surrogate series, from which annual precipitation data series were derived. These annual precipitation series were subject to exploratory analysis and to a thorough variography study. The geostatistical approach was then applied to the data set, based on different scenarios for the spatial continuity. Implementing this procedure also promoted the development of a computer program that aims to assist on the homogenisation of climate data, while minimising user interaction. Finally, in order to compare the effectiveness of this methodology with the homogenisation methods submitted during the HOME project, the obtained results

Breast Carcinoma, Intratumour Heterogeneity and Histological Grading, Using Geostatistics

PubMed Central

Sharifi‐Salamatian, Vénus; de Roquancourt, Anne; Rigaut, Jean Paul

2000-01-01

Tumour progression is currently believed to result from genetic instability. Chromosomal patterns specific of a type of cancer are frequent even though phenotypic spatial heterogeneity is omnipresent. The latter is the usual cause of histological grading imprecision, a well documented problem, without any fully satisfactory solution up to now. The present article addresses this problem in breast carcinoma. The assessment of a genetic marker for human tumours requires quantifiable measures of intratumoral heterogeneity. If any invariance paradigm representing a stochastic or geostatistic function could be discovered, this might help in solving the grading problem. A novel methodological approach using geostatistics to measure heterogeneity is used. Twenty tumours from the three usual (Scarff‐Bloom and Richardson) grades were obtained and paraffin sections stained by MIB‐1 (Ki‐67) and peroxidase staining. Whole two‐dimensional sections were sampled. Morphometric grids of variable sizes allowed a simple and fast recording of positions of epithelial nuclei, marked or not by MIB‐1. The geostatistical method is based here upon the asymptotic behaviour of dispersion variance. Measure of asymptotic exponent of dispersion variance shows an increase from grade 1 to grade 3. Preliminary results are encouraging: grades 1 and 3 on one hand and 2 and 3 on the other hand are totally separated. The final proof of an improved grading using this measure will of course require a confrontation with the results of survival studies. PMID:11153611

The Role of Open and Distance Learning in the Implementation of the Right to Education in Zambia

ERIC Educational Resources Information Center

Siaciwena, Richard; Lubinda, Foster

2008-01-01

As a member of the United Nations, Zambia is committed to the observance of human rights enshrined in the Universal Declaration of Human Rights of 1948. This is evidenced, among others, by the fact that Zambia is a signatory to the Convention on the Rights of the Child and the African Charter on the Rights and Welfare of the Child. Zambia has a…

Insecticide-treated nets mass distribution campaign: benefits and lessons in Zambia.

PubMed

Masaninga, Freddie; Mukumbuta, Nawa; Ndhlovu, Ketty; Hamainza, Busiku; Wamulume, Pauline; Chanda, Emmanuel; Banda, John; Mwanza-Ingwe, Mercy; Miller, John M; Ameneshewa, Birkinesh; Mnzava, Abraham; Kawesha-Chizema, Elizabeth

2018-04-24

Zambia was an early adopter of insecticide-treated nets strategy in 2001, and policy for mass distribution with long-lasting insecticidal nets (LLINs) in 2005. Since then, the country has implemented mass distribution supplemented with routine delivery through antenatal care and under five clinics in health facilities. The national targets of universal (100%) coverage and 80% utilization of LLINs have not been attained. Free mass LLIN distribution campaign in Zambia offers important lessons to inform future campaigns in the African region. This study reviewed LLIN free mass distribution campaign information derived from Zambia's national and World Health Organization Global Malaria Programme annual reports and strategic plans published between 2001 and 2016. In 2014, a nationwide mass distribution campaign in Zambia delivered all the 6.0 million LLINs in 6 out of 10 provinces in 4 months between June and September before the onset of the rainy season. Compared with 235,800 LLINs and 2.9 million LLINs distributed on a rolling basis in 2008 and 2013, respectively, the 2014 mass campaign, which distributed 6 million LLINs represented the largest one-time-nationwide LLIN distribution in Zambia. The province (Luapula) with highest malaria transmission, mostly with rural settings recorded 98-100% sleeping spaces in homes covered with LLINs. The percentage of households owning at least 1 LLIN increased from 50.9% in 2006 to 77.7% in 2015. The 2014 mass campaign involved a coordinated response with substantial investments into macro (central) and micro (district) level planning, capacity building, tracking and logistics management supported by a new non-health sector partnership landscape. Coordination of LLIN distribution and logistics benefited from the mobile phone technology to transmit "real time" data on commodity tracking that facilitated timely delivery to districts. Free mass distribution of LLINs policy was adopted in 2005 in Zambia. Consistently implemented

A Nonparametric Geostatistical Method For Estimating Species Importance

Treesearch

Andrew J. Lister; Rachel Riemann; Michael Hoppus

2001-01-01

Parametric statistical methods are not always appropriate for conducting spatial analyses of forest inventory data. Parametric geostatistical methods such as variography and kriging are essentially averaging procedures, and thus can be affected by extreme values. Furthermore, non normal distributions violate the assumptions of analyses in which test statistics are...

Restructuring of labor markets in the Philippines and Zambia: the gender dimension.

PubMed

Floro, M S; Schaefer, K

1998-01-01

This paper critically examines labor market changes accompanying the process of structural adjustment in the Philippines and Zambia and, in particular, the resulting impact on women's economic participation. The changes in the labor market occurring during the process of economic restructuring in Zambia and the Philippines are similar in some respects but very different in others. Zambia's economic performance has not been sufficient to generate wide-based employment and has been characterized by rising unemployment. The Philippines has also unfortunately been characterized by a growth in joblessness, specifically with regard to skilled and semiskilled employment. Global integration of labor markets in the Philippines give some employment opportunity to workers who are willing to seek jobs overseas but not to those in Zambia. Both in the Philippines and Zambia, the informal sector has shifted its agricultural reforms to female labor toward agricultural wage work (which is seasonal and low paid). In the Philippines, specifically in urban areas, certain export-oriented industries have created some jobs, predominantly for young women, but only a small proportion of total females are employed. Much of the female job growth has occurred in sales and service sectors, including sex work, domestic service, and petty trade. International labor migration in the Philippines has become more feminized, because a majority of overseas contract workers are women, who are employed in the service sector as entertainers and domestic helpers. Access to paid work in some cases may empower women, yet in other cases their power may be diminished. Both the specific character of labor market development and the nature of the accompanying economic reform alter the ability of the women and men to take advantage of the opportunity. Reform shifts patterns of production organization and location of employment and can either reinforce the prevailing distribution of power or provide tension

Patterns of Rift Valley fever activity in Zambia.

PubMed Central

Davies, F. G.; Kilelu, E.; Linthicum, K. J.; Pegram, R. G.

1992-01-01

An hypothesis that there was an annual emergence of Rift Valley fever virus in Zambia, during or after the seasonal rains, was examined with the aid of sentinel cattle. Serum samples taken during 1974 and 1978 showed evidence of epizootic Rift Valley fever in Zambia, with more than 80% positive. A sentinel herd exposed from 1982 to 1986 showed that some Rift Valley fever occurred each year. This was usually at a low level, with 3-8% of the susceptible cattle seroconverting. In 1985-6 more than 20% of the animals seroconverted, and this greater activity was associated with vegetational changes--which could be detected by remote-sensing satellite imagery--which have also been associated with greater virus activity in Kenya. PMID:1547835

Geostatistics: a new tool for describing spatially-varied surface conditions from timber harvested and burned hillslopes

Treesearch

Peter R. Robichaud

1997-01-01

Geostatistics provides a method to describe the spatial continuity of many natural phenomena. Spatial models are based upon the concept of scaling, kriging and conditional simulation. These techniques were used to describe the spatially-varied surface conditions on timber harvest and burned hillslopes. Geostatistical techniques provided estimates of the ground cover (...

OUTLINE OF VOCATIONAL TRAINING IN ZAMBIA.

ERIC Educational Resources Information Center

Australian Dept. of Labour and National Service, Perth.

THE 1963 POPULATION OF ZAMBIA WAS APPROXIMATELY 3.5 MILLION. THE 8-YEAR PRIMARY EDUCATION PROGRAM IS FOLLOWED BY SECONDARY, SECONDARY TECHNICAL, AND TRADE SCHOOL OPTIONS. THERE IS AN INCREASE IN ADULT EDUCATION AT THE PRIMARY AND SECONDARY LEVELS. CRAFT AND TECHNICIAN LEVEL PROGRAMS ARE CONDUCTED AT NORTHERN TECHNICAL COLLEGE AND ITS ANCILLARY…

Aflatoxin contamination of groundnut and maize in Zambia: observed and potential concentrations.

PubMed

Kachapulula, P W; Akello, J; Bandyopadhyay, R; Cotty, P J

2017-06-01

The aims of the study were to quantify aflatoxins, the potent carcinogens associated with stunting and immune suppression, in maize and groundnut across Zambia's three agroecologies and to determine the vulnerability to aflatoxin increases after purchase. Aflatoxin concentrations were determined for 334 maize and groundnut samples from 27 districts using lateral-flow immunochromatography. Seventeen per cent of crops from markets contained aflatoxin concentrations above allowable levels in Zambia (10 μg kg -1 ). Proportions of crops unsafe for human consumption differed significantly (P < 0·001) among agroecologies with more contamination (38%) in the warmest (Agroecology I) and the least (8%) in cool, wet Agroecology III. Aflatoxin in groundnut (39 μg kg -1 ) and maize (16 μg kg -1 ) differed (P = 0·032). Poor storage (31°C, 100% RH, 1 week) increased aflatoxin in safe crops by over 1000-fold in both maize and groundnut. The L morphotype of Aspergillus flavus was negatively correlated with postharvest increases in groundnut. Aflatoxins are common in Zambia's food staples with proportions of unsafe crops dependent on agroecology. Fungal community structure influences contamination suggesting Zambia would benefit from biocontrol with atoxigenic A. flavus. Aflatoxin contamination across the three agroecologies of Zambia is detailed and the case for aflatoxin management with atoxigenic biocontrol agents provided. The first method for evaluating the potential for aflatoxin increase after purchase is presented. Published 2017. This article is a U.S. Government work and is in the public domain in the USA. Journal of Applied Microbiology published by John Wiley & Sons Ltd on behalf of The Society for Applied Microbiology.

The Use of Geostatistics in the Study of Floral Phenology of Vulpia geniculata (L.) Link

PubMed Central

León Ruiz, Eduardo J.; García Mozo, Herminia; Domínguez Vilches, Eugenio; Galán, Carmen

2012-01-01

Traditionally phenology studies have been focused on changes through time, but there exist many instances in ecological research where it is necessary to interpolate among spatially stratified samples. The combined use of Geographical Information Systems (GIS) and Geostatistics can be an essential tool for spatial analysis in phenological studies. Geostatistics are a family of statistics that describe correlations through space/time and they can be used for both quantifying spatial correlation and interpolating unsampled points. In the present work, estimations based upon Geostatistics and GIS mapping have enabled the construction of spatial models that reflect phenological evolution of Vulpia geniculata (L.) Link throughout the study area during sampling season. Ten sampling points, scattered troughout the city and low mountains in the “Sierra de Córdoba” were chosen to carry out the weekly phenological monitoring during flowering season. The phenological data were interpolated by applying the traditional geostatitical method of Kriging, which was used to ellaborate weekly estimations of V. geniculata phenology in unsampled areas. Finally, the application of Geostatistics and GIS to create phenological maps could be an essential complement in pollen aerobiological studies, given the increased interest in obtaining automatic aerobiological forecasting maps. PMID:22629169

The use of geostatistics in the study of floral phenology of Vulpia geniculata (L.) link.

PubMed

León Ruiz, Eduardo J; García Mozo, Herminia; Domínguez Vilches, Eugenio; Galán, Carmen

2012-01-01

Traditionally phenology studies have been focused on changes through time, but there exist many instances in ecological research where it is necessary to interpolate among spatially stratified samples. The combined use of Geographical Information Systems (GIS) and Geostatistics can be an essential tool for spatial analysis in phenological studies. Geostatistics are a family of statistics that describe correlations through space/time and they can be used for both quantifying spatial correlation and interpolating unsampled points. In the present work, estimations based upon Geostatistics and GIS mapping have enabled the construction of spatial models that reflect phenological evolution of Vulpia geniculata (L.) Link throughout the study area during sampling season. Ten sampling points, scattered throughout the city and low mountains in the "Sierra de Córdoba" were chosen to carry out the weekly phenological monitoring during flowering season. The phenological data were interpolated by applying the traditional geostatitical method of Kriging, which was used to elaborate weekly estimations of V. geniculata phenology in unsampled areas. Finally, the application of Geostatistics and GIS to create phenological maps could be an essential complement in pollen aerobiological studies, given the increased interest in obtaining automatic aerobiological forecasting maps.

Assessing the resolution-dependent utility of tomograms for geostatistics

USGS Publications Warehouse

Day-Lewis, F. D.; Lane, J.W.

2004-01-01

Geophysical tomograms are used increasingly as auxiliary data for geostatistical modeling of aquifer and reservoir properties. The correlation between tomographic estimates and hydrogeologic properties is commonly based on laboratory measurements, co-located measurements at boreholes, or petrophysical models. The inferred correlation is assumed uniform throughout the interwell region; however, tomographic resolution varies spatially due to acquisition geometry, regularization, data error, and the physics underlying the geophysical measurements. Blurring and inversion artifacts are expected in regions traversed by few or only low-angle raypaths. In the context of radar traveltime tomography, we derive analytical models for (1) the variance of tomographic estimates, (2) the spatially variable correlation with a hydrologic parameter of interest, and (3) the spatial covariance of tomographic estimates. Synthetic examples demonstrate that tomograms of qualitative value may have limited utility for geostatistics; moreover, the imprint of regularization may preclude inference of meaningful spatial statistics from tomograms.

AIDS education for a low literate audience in Zambia.

PubMed

Msimuko, A K

1988-04-01

A workshop funded by the USA Program for Appropriate Technology in Health (PATH) was an effort by Zambia toward prevention and control of AIDS. The lack of educational materials about AIDS for a low-literate audience was the major problem addressed by the workshop. Other problems include the lack of collaborative effort in the development of materials on AIDS, and the lack of skills needed in the development of such materials in Zambia. 1 of the objectives of the workshop was to launch the Planned Parenthood Association of Zambia's (PPAZ) materials development project. The scope of this project includes the production of educational materials on AIDS for low-literate audiences and a counseling handbook for family planning workers. Print materials should be simply written, using words, idioms, and graphics that are familiar to the target audience. Other workshop objectives included the establishment of collaborative relationships between organizations involved in existing AIDS educational activities in Zambia, and the development of practical skills needed to produce print materials. Education was identified as the most important strategy for the prevention and control of AIDS, and PPAZ should be the executing agency of the print materials project. Audience research, using focus group techniques, focus group discussions, behavioral messages, and pretesting of messages, should be the most effective means of reaching targeted audiences. PPAZ is contracted by PATH to begin development of educational materials, and 2 committees have formed to implement the project and to establish interagency collaboration. Audience research was begun between January and March of 1988, focusing on people's beliefs, practices, and ideas about AIDS. The final phase of the project will be the printing, distribution, and use of the AIDS materials and the training of family planning field workers in the proper use of these materials.

Co-circulation of multiple genotypes of African swine fever viruses among domestic pigs in Zambia (2013-2015).

PubMed

Simulundu, E; Chambaro, H M; Sinkala, Y; Kajihara, M; Ogawa, H; Mori, A; Ndebe, J; Dautu, G; Mataa, L; Lubaba, C H; Simuntala, C; Fandamu, P; Simuunza, M; Pandey, G S; Samui, K L; Misinzo, G; Takada, A; Mweene, A S

2018-02-01

During 2013-2015, several and severe outbreaks of African swine fever (ASF) affected domestic pigs in six provinces of Zambia. Genetic characterization of ASF viruses (ASFVs) using standardized genotyping procedures revealed that genotypes I, II and XIV were associated with these outbreaks. Molecular and epidemiological data suggest that genotype II ASFV (Georgia 2007/1-like) detected in Northern Province of Zambia may have been introduced from neighbouring Tanzania. Also, a genotype II virus detected in Eastern Province of Zambia showed a p54 phylogenetic relationship that was inconsistent with that of p72, underscoring the genetic variability of ASFVs. While it appears genotype II viruses detected in Zambia arose from a domestic pig cycle, genotypes I and XIV possibly emerged from a sylvatic cycle. Overall, this study demonstrates the co-circulation of multiple genotypes of ASFVs, involvement of both the sylvatic and domestic pig cycle in ASF outbreaks in Zambia and possible trans-boundary spread of the disease in south-eastern Africa. Indeed, while there is need for regional or international concerted efforts in the control of ASF, understanding pig marketing practices, pig population dynamics, pig housing and rearing systems and community engagement will be important considerations when designing future prevention and control strategies of this disease in Zambia. © 2017 Blackwell Verlag GmbH.

Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices

USGS Publications Warehouse

Ji, Lei; Zhang, Li; Rover, Jennifer R.; Wylie, Bruce K.; Chen, Xuexia

2014-01-01

In the past 40 years, many spectral vegetation indices have been developed to quantify vegetation biophysical parameters. An ideal vegetation index should contain the maximum level of signal related to specific biophysical characteristics and the minimum level of noise such as background soil influences and atmospheric effects. However, accurate quantification of signal and noise in a vegetation index remains a challenge, because it requires a large number of field measurements or laboratory experiments. In this study, we applied a geostatistical method to estimate signal-to-noise ratio (S/N) for spectral vegetation indices. Based on the sample semivariogram of vegetation index images, we used the standardized noise to quantify the noise component of vegetation indices. In a case study in the grasslands and shrublands of the western United States, we demonstrated the geostatistical method for evaluating S/N for a series of soil-adjusted vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The soil-adjusted vegetation indices were found to have higher S/N values than the traditional normalized difference vegetation index (NDVI) and simple ratio (SR) in the sparsely vegetated areas. This study shows that the proposed geostatistical analysis can constitute an efficient technique for estimating signal and noise components in vegetation indices.

Analysis of Feature Intervisibility and Cumulative Visibility Using GIS, Bayesian and Spatial Statistics: A Study from the Mandara Mountains, Northern Cameroon

PubMed Central

Wright, David K.; MacEachern, Scott; Lee, Jaeyong

2014-01-01

The locations of diy-geδ-bay (DGB) sites in the Mandara Mountains, northern Cameroon are hypothesized to occur as a function of their ability to see and be seen from points on the surrounding landscape. A series of geostatistical, two-way and Bayesian logistic regression analyses were performed to test two hypotheses related to the intervisibility of the sites to one another and their visual prominence on the landscape. We determine that the intervisibility of the sites to one another is highly statistically significant when compared to 10 stratified-random permutations of DGB sites. Bayesian logistic regression additionally demonstrates that the visibility of the sites to points on the surrounding landscape is statistically significant. The location of sites appears to have also been selected on the basis of lower slope than random permutations of sites. Using statistical measures, many of which are not commonly employed in archaeological research, to evaluate aspects of visibility on the landscape, we conclude that the placement of DGB sites improved their conspicuousness for enhanced ritual, social cooperation and/or competition purposes. PMID:25383883

Personal and Environmental Predictors of the Intention to Use Maternal Healthcare Services in Kalomo, Zambia

ERIC Educational Resources Information Center

Sialubanje, Cephas; Massar, Karlijn; Hamer, Davidson H.; Ruiter, Robert A. C.

2014-01-01

Low maternal healthcare service utilization contributes to poor maternal and new born health outcomes in rural Zambia. The purpose of this study was to identify important factors influencing women's intention to use these services in Kalomo, Zambia. An interviewer-administered questionnaire was used to collect data from 1007 women of reproductive…

Geostatistical enhancement of european hydrological predictions

NASA Astrophysics Data System (ADS)

Pugliese, Alessio; Castellarin, Attilio; Parajka, Juraj; Arheimer, Berit; Bagli, Stefano; Mazzoli, Paolo; Montanari, Alberto; Blöschl, Günter

2016-04-01

Geostatistical Enhancement of European Hydrological Prediction (GEEHP) is a research experiment developed within the EU funded SWITCH-ON project, which proposes to conduct comparative experiments in a virtual laboratory in order to share water-related information and tackle changes in the hydrosphere for operational needs (http://www.water-switch-on.eu). The main objective of GEEHP deals with the prediction of streamflow indices and signatures in ungauged basins at different spatial scales. In particular, among several possible hydrological signatures we focus in our experiment on the prediction of flow-duration curves (FDCs) along the stream-network, which has attracted an increasing scientific attention in the last decades due to the large number of practical and technical applications of the curves (e.g. hydropower potential estimation, riverine habitat suitability and ecological assessments, etc.). We apply a geostatistical procedure based on Top-kriging, which has been recently shown to be particularly reliable and easy-to-use regionalization approach, employing two different type of streamflow data: pan-European E-HYPE simulations (http://hypeweb.smhi.se/europehype) and observed daily streamflow series collected in two pilot study regions, i.e. Tyrol (merging data from Austrian and Italian stream gauging networks) and Sweden. The merger of the two study regions results in a rather large area (~450000 km2) and might be considered as a proxy for a pan-European application of the approach. In a first phase, we implement a bidirectional validation, i.e. E-HYPE catchments are set as training sites to predict FDCs at the same sites where observed data are available, and vice-versa. Such a validation procedure reveals (1) the usability of the proposed approach for predicting the FDCs over the entire river network of interest using alternatively observed data and E-HYPE simulations and (2) the accuracy of E-HYPE-based predictions of FDCs in ungauged sites. In a

Fire management assessment of Eastern Province, Zambia

Treesearch

L. T. Hollingsworth; D. Johnson; G. Sikaundi; S. Siame

2015-01-01

The mission that produced this assessment was prompted by requests from Forestry Department personnel in Zambia to the United States Agency for International Development (USAID) for formal fire management training. USAID contacted the United States Forest Service's (USFS) International Programs (IP) with the training request. Together, USFS, USAID, and Zambian...

Non-prescription sale and dispensing of antibiotics in community pharmacies in Zambia.

PubMed

Kalungia, Aubrey Chichonyi; Burger, Johanita; Godman, Brian; Costa, Juliana de Oliveira; Simuwelu, Chimwemwe

2016-12-01

In Zambia, antibiotics are categorized as prescription-only medicines. Antibiotics dispensed without a prescription pose a public health threat, which is a concern. Consequently, the aim is to ascertain the extent of non-prescription sales and dispensing of antibiotics in community pharmacies in Zambia. The practice of non-prescription sale and dispensing were assessed in 73 randomly selected community retail pharmacies, using a structured interviewer-administered questionnaire with simulated case scenarios. Majority (97%) stated that clients frequently requested non-prescribed antibiotics. Interviewees usually asked clients' indications (94%), counselled on dosing (96%) and suggested changes to antibiotic choices (97%). All (100%) dispensed non-prescribed antibiotics. Commonly dispensed antibiotics included amoxicillin (52%), cotrimoxazole (25%) and metronidazole (23%). Non-prescription sale and dispensing of antibiotics was significantly associated with interviewees' professional qualification in four out of five simulations. Non-prescription sale and dispensing of antibiotics is widespread in Zambia. Concerted public and professional interventions are needed coupled with stronger regulatory enforcement to reduce this.

Lusaka, Zambia, during SAFARI-2000: Convergence of local and imported ozone pollution

NASA Astrophysics Data System (ADS)

Thompson, Anne M.; Witte, Jacquelyn C.; Freiman, M. Tal; Phahlane, N. Agnes; Coetzee, Gert J. R.

2002-10-01

In August and September, throughout south central Africa, seasonal clearing of dry vegetation and other fire-related activities lead to intense smoke haze and ozone formation. The first ozone soundings in the heart of the southern African burning region were taken at Lusaka, Zambia (15.5S, 28E) in early September 2000. Maximum surface ozone was over 90 ppbv and column tropospheric ozone exceeded 50 DU. These values are higher than concurrent measurements over Nairobi (1S, 38E) and Irene (25S, 28E, near Pretoria). At least 30% of Lusaka surface ozone appears to be from local sources. A layer at 800-500 hPa has ozone >120 ppbv and originates from trans-boundary recirculation. Starting out over Zambia, Angola, and Namibia, ozone-rich air travels east to the Indian Ocean, before heading back toward Mozambique, Zimbabwe and Zambia. Thus, Lusaka collects local and imported pollution, consistent with its location within the southern African gyre.

Topsoil moisture mapping using geostatistical techniques under different Mediterranean climatic conditions.

PubMed

Martínez-Murillo, J F; Hueso-González, P; Ruiz-Sinoga, J D

2017-10-01

Soil mapping has been considered as an important factor in the widening of Soil Science and giving response to many different environmental questions. Geostatistical techniques, through kriging and co-kriging techniques, have made possible to improve the understanding of eco-geomorphologic variables, e.g., soil moisture. This study is focused on mapping of topsoil moisture using geostatistical techniques under different Mediterranean climatic conditions (humid, dry and semiarid) in three small watersheds and considering topography and soil properties as key factors. A Digital Elevation Model (DEM) with a resolution of 1×1m was derived from a topographical survey as well as soils were sampled to analyzed soil properties controlling topsoil moisture, which was measured during 4-years. Afterwards, some topography attributes were derived from the DEM, the soil properties analyzed in laboratory, and the topsoil moisture was modeled for the entire watersheds applying three geostatistical techniques: i) ordinary kriging; ii) co-kriging considering as co-variate topography attributes; and iii) co-kriging ta considering as co-variates topography attributes and gravel content. The results indicated topsoil moisture was more accurately mapped in the dry and semiarid watersheds when co-kriging procedure was performed. The study is a contribution to improve the efficiency and accuracy of studies about the Mediterranean eco-geomorphologic system and soil hydrology in field conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Exploring prediction uncertainty of spatial data in geostatistical and machine learning Approaches

NASA Astrophysics Data System (ADS)

Klump, J. F.; Fouedjio, F.

2017-12-01

Geostatistical methods such as kriging with external drift as well as machine learning techniques such as quantile regression forest have been intensively used for modelling spatial data. In addition to providing predictions for target variables, both approaches are able to deliver a quantification of the uncertainty associated with the prediction at a target location. Geostatistical approaches are, by essence, adequate for providing such prediction uncertainties and their behaviour is well understood. However, they often require significant data pre-processing and rely on assumptions that are rarely met in practice. Machine learning algorithms such as random forest regression, on the other hand, require less data pre-processing and are non-parametric. This makes the application of machine learning algorithms to geostatistical problems an attractive proposition. The objective of this study is to compare kriging with external drift and quantile regression forest with respect to their ability to deliver reliable prediction uncertainties of spatial data. In our comparison we use both simulated and real world datasets. Apart from classical performance indicators, comparisons make use of accuracy plots, probability interval width plots, and the visual examinations of the uncertainty maps provided by the two approaches. By comparing random forest regression to kriging we found that both methods produced comparable maps of estimated values for our variables of interest. However, the measure of uncertainty provided by random forest seems to be quite different to the measure of uncertainty provided by kriging. In particular, the lack of spatial context can give misleading results in areas without ground truth data. These preliminary results raise questions about assessing the risks associated with decisions based on the predictions from geostatistical and machine learning algorithms in a spatial context, e.g. mineral exploration.

Geostatistical mapping of effluent-affected sediment distribution on the Palos Verdes shelf

USGS Publications Warehouse

Murray, C.J.; Lee, H.J.; Hampton, M.A.

2002-01-01

Geostatistical techniques were used to study the spatial continuity of the thickness of effluent-affected sediment in the offshore Palos Verdes Margin area. The thickness data were measured directly from cores and indirectly from high-frequency subbottom profiles collected over the Palos Verdes Margin. Strong spatial continuity of the sediment thickness data was identified, with a maximum range of correlation in excess of 1.4 km. The spatial correlation showed a marked anisotropy, and was more than twice as continuous in the alongshore direction as in the cross-shelf direction. Sequential indicator simulation employing models fit to the thickness data variograms was used to map the distribution of the sediment, and to quantify the uncertainty in those estimates. A strong correlation between sediment thickness data and measurements of the mass of the contaminant p,p???-DDE per unit area was identified. A calibration based on the bivariate distribution of the thickness and p,p???-DDE data was applied using Markov-Bayes indicator simulation to extend the geostatistical study and map the contamination levels in the sediment. Integrating the map grids produced by the geostatistical study of the two variables indicated that 7.8 million m3 of effluent-affected sediment exist in the map area, containing approximately 61-72 Mg (metric tons) of p,p???-DDE. Most of the contaminated sediment (about 85% of the sediment and 89% of the p,p???-DDE) occurs in water depths < 100 m. The geostatistical study also indicated that the samples available for mapping are well distributed and the uncertainty of the estimates of the thickness and contamination level of the sediments is lowest in areas where the contaminated sediment is most prevalent. ?? 2002 Elsevier Science Ltd. All rights reserved.

Inequalities in public health care delivery in Zambia

PubMed Central

2014-01-01

Background Access to adequate health services that is of acceptable quality is important in the move towards universal health coverage. However, previous studies have revealed inequities in health care utilisation in the favour of the rich. Further, those with the greatest need for health services are not getting a fair share. In Zambia, though equity in access is extolled in government documents, there is evidence suggesting that those needing health services are not receiving their fair share. This study seeks therefore, to assess if socioeconomic related inequalities/inequities in public health service utilisation in Zambia still persist. Methods The 2010 nationally representative Zambia Living Conditions and Monitoring Survey data are used. Inequality is assessed using concentration curves and concentrations indices while inequity is assessed using a horizontal equity index: an index of inequity across socioeconomic status groups, based on standardizing health service utilisation for health care need. Public health services considered include public health post visits, public clinic visits, public hospital visits and total public facility visits. Results There is evidence of pro-poor inequality in public primary health care utilisation but a pro-rich inequality in hospital visits. The concentration indices for public health post visits and public clinic visits are −0.28 and −0.09 respectively while that of public hospitals is 0.06. After controlling for need, the pro-poor distribution is maintained at primary facilities and with a pro-rich distribution at hospitals. The horizontal equity indices for health post and clinic are estimated at −0.23 and −0.04 respectively while that of public hospitals is estimated at 0.11. A pro-rich inequity is observed when all the public facilities are combined (horizontal equity index = 0.01) though statistically insignificant. Conclusion The results of the paper point to areas of focus in ensuring equitable access

Spatial analysis of hazardous waste data using geostatistics

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

Zirschky, J.H.

1984-01-01

The objective of this investigation was to determine if geostatistics could be a useful tool for evaluating hazardous waste sites. Three sites contaminated by dioxin (2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)) were investigated. The first site evaluated was a creek into which TCDD-contaminated soil had eroded. The second site was a town in which TCDD-contaminated wastes had been sprayed onto the streets. Finally, the third site was a highway of which the shoulders were contaminated by dust deposition from a nearby hazardous waste site. The distribution of TCDD at the first and third sites were investigated using kriging, an optimal estimation technique. By usingmore » kriging, the areas of both sites requiring cleanup were successfully identified. At the second site, the town, satisfactory results were not obtained. The distribution of contamination in this town is believed to be very heterogeneous; thus, reasonable estimates could not be obtained. Additional sampling was therefore recommended at this site. Based upon this research, geostatistics appears to be a very useful tool for evaluating a hazardous waste site if the distribution of contaminants at the site is homogeneous, or can be divided into homogeneous areas.« less

Assessing income redistributive effect of health financing in Zambia.

PubMed

Mulenga, Arnold; Ataguba, John Ele-Ojo

2017-09-01

Ensuring an equitable health financing system is a major concern particularly in many developing countries. Internationally, there is a strong debate to move away from excessive reliance on direct out-of-pocket (OOP) spending towards a system that incorporates a greater element of risk pooling and thus affords greater protection for the poor. This is a major focus of the move towards universal health coverage (UHC). Currently, Zambia with high levels of poverty and income inequality is implementing health sector reforms for UHC through a social health insurance scheme. However, the way to identify the health financing mechanisms that are best suited to achieving this goal is to conduct empirical analysis and consider international evidence on funding universal health systems. This study assesses, for the first time, the progressivity of health financing and how it impacts on income inequality in Zambia. Three broad health financing mechanisms (general tax, a health levy and OOP spending) were considered. Data come from the 2010 nationally representative Zambian Living Conditions and Monitoring Survey with a sample size of 19,397 households. Applying standard methodologies, the findings show that total health financing in Zambia is progressive. It also leads to a statistically significant reduction in income inequality (i.e. a pro-poor redistributive effect estimated at 0.0110 (p < 0.01)). Similar significant pro-poor redistribution was reported for general taxes (0.0101 (p < 0.01)) and a health levy (0.0002 (p < 0.01)). However, the redistributive effect was not significant for OOP spending (0.0006). These results further imply that health financing redistributes income from the rich to the poor with a greater potential via general taxes. This points to areas where government policy may focus in attempting to reduce the high level of income inequality and to improve equity in health financing towards UHC in Zambia. Copyright © 2017 Elsevier Ltd. All rights

Three-dimensional geostatistical inversion of flowmeter and pumping test data.

PubMed

Li, Wei; Englert, Andreas; Cirpka, Olaf A; Vereecken, Harry

2008-01-01

We jointly invert field data of flowmeter and multiple pumping tests in fully screened wells to estimate hydraulic conductivity using a geostatistical method. We use the steady-state drawdowns of pumping tests and the discharge profiles of flowmeter tests as our data in the inference. The discharge profiles need not be converted to absolute hydraulic conductivities. Consequently, we do not need measurements of depth-averaged hydraulic conductivity at well locations. The flowmeter profiles contain information about relative vertical distributions of hydraulic conductivity, while drawdown measurements of pumping tests provide information about horizontal fluctuation of the depth-averaged hydraulic conductivity. We apply the method to data obtained at the Krauthausen test site of the Forschungszentrum Jülich, Germany. The resulting estimate of our joint three-dimensional (3D) geostatistical inversion shows an improved 3D structure in comparison to the inversion of pumping test data only.

Health worker shortages in Zambia: an assessment of government responses.

PubMed

Gow, Jeff; George, Gavin; Mutinta, Given; Mwamba, Sylvia; Ingombe, Lutungu

2011-11-01

A dire health worker shortage in Zambia's national health programs is adversely impacting the quantity and quality of health care and posing a serious barrier to achieving Millennium Development Goals to improve population health. In 2005, Zambia's Ministry of Health developed a 10-year strategic plan for human resources for health to address the crisis through improved training, hiring, and retention. The plan has neither arrested nor reduced the shortage. We review the causes of the shortage, present results from a health worker survey showing that safe work conditions, manageable workloads, and career advancement opportunities matter more to respondents than financial compensation. We comment on the adequacy of government efforts to address the health worker shortage.

Cholera Epidemic - Lusaka, Zambia, October 2017-May 2018.

PubMed

Sinyange, Nyambe; Brunkard, Joan M; Kapata, Nathan; Mazaba, Mazyanga Lucy; Musonda, Kunda G; Hamoonga, Raymond; Kapina, Muzala; Kapaya, Fred; Mutale, Lwito; Kateule, Ernest; Nanzaluka, Francis; Zulu, James; Musyani, Chileshe Lukwesa; Winstead, Alison V; Davis, William W; N'cho, Hammad S; Mulambya, Nelia L; Sakubita, Patrick; Chewe, Orbie; Nyimbili, Sulani; Onwuekwe, Ezinne V C; Adrien, Nedghie; Blackstock, Anna J; Brown, Travis W; Derado, Gordana; Garrett, Nancy; Kim, Sunkyung; Hubbard, Sydney; Kahler, Amy M; Malambo, Warren; Mintz, Eric; Murphy, Jennifer; Narra, Rupa; Rao, Gouthami G; Riggs, Margaret A; Weber, Nicole; Yard, Ellen; Zyambo, Khozya D; Bakyaita, Nathan; Monze, Namani; Malama, Kennedy; Mulwanda, Jabbin; Mukonka, Victor M

2018-05-18

On October 6, 2017, an outbreak of cholera was declared in Zambia after laboratory confirmation of Vibrio cholerae O1, biotype El Tor, serotype Ogawa, from stool specimens from two patients with acute watery diarrhea. The two patients had gone to a clinic in Lusaka, the capital city, on October 4. Cholera cases increased rapidly, from several hundred cases in early December 2017 to approximately 2,000 by early January 2018 (Figure). In collaboration with partners, the Zambia Ministry of Health (MoH) launched a multifaceted public health response that included increased chlorination of the Lusaka municipal water supply, provision of emergency water supplies, water quality monitoring and testing, enhanced surveillance, epidemiologic investigations, a cholera vaccination campaign, aggressive case management and health care worker training, and laboratory testing of clinical samples. In late December 2017, a number of water-related preventive actions were initiated, including increasing chlorine levels throughout the city's water distribution system and placing emergency tanks of chlorinated water in the most affected neighborhoods; cholera cases declined sharply in January 2018. During January 10-February 14, 2018, approximately 2 million doses of oral cholera vaccine were administered to Lusaka residents aged ≥1 year. However, in mid-March, heavy flooding and widespread water shortages occurred, leading to a resurgence of cholera. As of May 12, 2018, the outbreak had affected seven of the 10 provinces in Zambia, with 5,905 suspected cases and a case fatality rate (CFR) of 1.9%. Among the suspected cases, 5,414 (91.7%), including 98 deaths (CFR = 1.8%), occurred in Lusaka residents.

Assessment of spatial distribution of fallout radionuclides through geostatistics concept.

PubMed

Mabit, L; Bernard, C

2007-01-01

After introducing geostatistics concept and its utility in environmental science and especially in Fallout Radionuclide (FRN) spatialisation, a case study for cesium-137 ((137)Cs) redistribution at the field scale using geostatistics is presented. On a Canadian agricultural field, geostatistics coupled with a Geographic Information System (GIS) was used to test three different techniques of interpolation [Ordinary Kriging (OK), Inverse Distance Weighting power one (IDW1) and two (IDW2)] to create a (137)Cs map and to establish a radioisotope budget. Following the optimization of variographic parameters, an experimental semivariogram was developed to determine the spatial dependence of (137)Cs. It was adjusted to a spherical isotropic model with a range of 30 m and a very small nugget effect. This (137)Cs semivariogram showed a good autocorrelation (R(2)=0.91) and was well structured ('nugget-to-sill' ratio of 4%). It also revealed that the sampling strategy was adequate to reveal the spatial correlation of (137)Cs. The spatial redistribution of (137)Cs was estimated by Ordinary Kriging and IDW to produce contour maps. A radioisotope budget was established for the 2.16 ha agricultural field under investigation. It was estimated that around 2 x 10(7)Bq of (137)Cs were missing (around 30% of the total initial fallout) and were exported by physical processes (runoff and erosion processes) from the area under investigation. The cross-validation analysis showed that in the case of spatially structured data, OK is a better interpolation method than IDW1 or IDW2 for the assessment of potential radioactive contamination and/or pollution.

Geospatial interpolation and mapping of tropospheric ozone pollution using geostatistics.

PubMed

Kethireddy, Swatantra R; Tchounwou, Paul B; Ahmad, Hafiz A; Yerramilli, Anjaneyulu; Young, John H

2014-01-10

Tropospheric ozone (O3) pollution is a major problem worldwide, including in the United States of America (USA), particularly during the summer months. Ozone oxidative capacity and its impact on human health have attracted the attention of the scientific community. In the USA, sparse spatial observations for O3 may not provide a reliable source of data over a geo-environmental region. Geostatistical Analyst in ArcGIS has the capability to interpolate values in unmonitored geo-spaces of interest. In this study of eastern Texas O3 pollution, hourly episodes for spring and summer 2012 were selectively identified. To visualize the O3 distribution, geostatistical techniques were employed in ArcMap. Using ordinary Kriging, geostatistical layers of O3 for all the studied hours were predicted and mapped at a spatial resolution of 1 kilometer. A decent level of prediction accuracy was achieved and was confirmed from cross-validation results. The mean prediction error was close to 0, the root mean-standardized-prediction error was close to 1, and the root mean square and average standard errors were small. O3 pollution map data can be further used in analysis and modeling studies. Kriging results and O3 decadal trends indicate that the populace in Houston-Sugar Land-Baytown, Dallas-Fort Worth-Arlington, Beaumont-Port Arthur, San Antonio, and Longview are repeatedly exposed to high levels of O3-related pollution, and are prone to the corresponding respiratory and cardiovascular health effects. Optimization of the monitoring network proves to be an added advantage for the accurate prediction of exposure levels.

SRS 2010 Vegetation Inventory GeoStatistical Mapping Results for Custom Reaction Intensity and Total Dead Fuels.

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

Edwards, Lloyd A.; Paresol, Bernard

This report of the geostatistical analysis results of the fire fuels response variables, custom reaction intensity and total dead fuels is but a part of an SRS 2010 vegetation inventory project. For detailed description of project, theory and background including sample design, methods, and results please refer to USDA Forest Service Savannah River Site internal report “SRS 2010 Vegetation Inventory GeoStatistical Mapping Report”, (Edwards & Parresol 2013).

Examining the Role of Couples' Characteristics in Contraceptive use in Nigeria and Zambia.

PubMed

Ntoimo, Lorretta Favour C; Chirwa-Banda, Pamela

2017-12-01

Relationship-related characteristics influence diverse health and demographic outcomes. This study examined the role of couples' characteristics in contraceptive use. Data were obtained from 2013 Nigeria and 2013-14 Zambia Demographic and Health Surveys. The study population consisted of couples in monogamous union (married or living together) who had at least one live birth and the wife was not pregnant at the time of the survey. Prevalence of contraceptive use among couples in Nigeria was 27% and 63% in Zambia. Couples' educational attainment, religious affiliation, the frequency of listening to the radio, reported number of children, fertility preference, region of residence and household wealth index were significant predictors of contraceptive use among couples in Nigeria and Zambia. Given the significant role of couples' characteristics in the uptake of contraceptives, there is the need to encourage interventions that target couples, particularly those of poor socioeconomic status.

Validating spatial structure in canopy water content using geostatistics

NASA Technical Reports Server (NTRS)

Sanderson, E. W.; Zhang, M. H.; Ustin, S. L.; Rejmankova, E.; Haxo, R. S.

1995-01-01

Heterogeneity in ecological phenomena are scale dependent and affect the hierarchical structure of image data. AVIRIS pixels average reflectance produced by complex absorption and scattering interactions between biogeochemical composition, canopy architecture, view and illumination angles, species distributions, and plant cover as well as other factors. These scales affect validation of pixel reflectance, typically performed by relating pixel spectra to ground measurements acquired at scales of 1m(exp 2) or less (e.g., field spectra, foilage and soil samples, etc.). As image analysis becomes more sophisticated, such as those for detection of canopy chemistry, better validation becomes a critical problem. This paper presents a methodology for bridging between point measurements and pixels using geostatistics. Geostatistics have been extensively used in geological or hydrogeolocial studies but have received little application in ecological studies. The key criteria for kriging estimation is that the phenomena varies in space and that an underlying controlling process produces spatial correlation between the measured data points. Ecological variation meets this requirement because communities vary along environmental gradients like soil moisture, nutrient availability, or topography.

Priorities for Antiretroviral Therapy Research in Sub-Saharan Africa: A 2002 Consensus Conference in Zambia

PubMed Central

Zulu, Isaac; Schuman, Paula; Musonda, Rosemary; Chomba, Elwyn; Mwinga, Kasonde; Sinkala, Moses; Chisembele, Maureen; Mwaba, Peter; Kasonde, Dorothy; Vermund, Sten H.

2009-01-01

Background A consensus conference was held to discuss priorities for antiretroviral therapy (ART) research in Zambia, one of the world’s most heavily HIV-afflicted nations. Zambia, like other resource-limited settings, has increasing access to highly active antiretroviral therapy (HAART) because of declining drug costs, use of government-purchased generic medications, and increased global donations. For sustained delivery of care with HAART in a resource-constrained medical and public health context, operational research is required and clinical trials are desirable. The priority areas for research are most relevant today given the increasing availability of HAART. Methods A conference was held in Lusaka, Zambia, in January 2002 to discuss priority areas for ART research in Zambia, with participants drawn from a broad cross section of Zambian society. State-of-the-art reviews and 6 intensive small group discussions helped to formulate a suggested research agenda. Results Conference participants believed that the most urgent research priorities were to assess how therapeutic resources could be applied for the greatest overall benefit and to minimize the impact of nonadherence and viral resistance. Identified research priorities were as follows: To determine when to initiate HAART in relation to CD4+ cell count To assess whether HIV/AIDS can be managed well without the use of costly frequent viral load measurements and CD4+ cell count monitoring To assess whether HIV/AIDS can be managed in the same fashion in patients coinfected with opportunistic infections such as tuberculosis and HIV-related chronic diarrhea, taking into consideration complications that may occur in tuberculosis such as immune reconstitution syndrome and medication malabsorption in the presence of diarrhea To carefully assess and characterize toxicities, adverse effects, and viral resistance patterns in Zambia, including studies of mothers exposed to prepartum single-dose nevirapine To conduct

Estimating Solar PV Output Using Modern Space/Time Geostatistics (Presentation)

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

Lee, S. J.; George, R.; Bush, B.

2009-04-29

This presentation describes a project that uses mapping techniques to predict solar output at subhourly resolution at any spatial point, develop a methodology that is applicable to natural resources in general, and demonstrate capability of geostatistical techniques to predict the output of a potential solar plant.

Geostatistical Borehole Image-Based Mapping of Karst-Carbonate Aquifer Pores.

PubMed

Sukop, Michael C; Cunningham, Kevin J

2016-03-01

Quantification of the character and spatial distribution of porosity in carbonate aquifers is important as input into computer models used in the calculation of intrinsic permeability and for next-generation, high-resolution groundwater flow simulations. Digital, optical, borehole-wall image data from three closely spaced boreholes in the karst-carbonate Biscayne aquifer in southeastern Florida are used in geostatistical experiments to assess the capabilities of various methods to create realistic two-dimensional models of vuggy megaporosity and matrix-porosity distribution in the limestone that composes the aquifer. When the borehole image data alone were used as the model training image, multiple-point geostatistics failed to detect the known spatial autocorrelation of vuggy megaporosity and matrix porosity among the three boreholes, which were only 10 m apart. Variogram analysis and subsequent Gaussian simulation produced results that showed a realistic conceptualization of horizontal continuity of strata dominated by vuggy megaporosity and matrix porosity among the three boreholes. © 2015, National Ground Water Association.

Geostatistical borehole image-based mapping of karst-carbonate aquifer pores

USGS Publications Warehouse

Michael Sukop,; Cunningham, Kevin J.

2016-01-01

Quantification of the character and spatial distribution of porosity in carbonate aquifers is important as input into computer models used in the calculation of intrinsic permeability and for next-generation, high-resolution groundwater flow simulations. Digital, optical, borehole-wall image data from three closely spaced boreholes in the karst-carbonate Biscayne aquifer in southeastern Florida are used in geostatistical experiments to assess the capabilities of various methods to create realistic two-dimensional models of vuggy megaporosity and matrix-porosity distribution in the limestone that composes the aquifer. When the borehole image data alone were used as the model training image, multiple-point geostatistics failed to detect the known spatial autocorrelation of vuggy megaporosity and matrix porosity among the three boreholes, which were only 10 m apart. Variogram analysis and subsequent Gaussian simulation produced results that showed a realistic conceptualization of horizontal continuity of strata dominated by vuggy megaporosity and matrix porosity among the three boreholes.

Predicting polycyclic aromatic hydrocarbons using a mass fraction approach in a geostatistical framework across North Carolina.

PubMed

Reyes, Jeanette M; Hubbard, Heidi F; Stiegel, Matthew A; Pleil, Joachim D; Serre, Marc L

2018-01-09

Currently in the United States there are no regulatory standards for ambient concentrations of polycyclic aromatic hydrocarbons (PAHs), a class of organic compounds with known carcinogenic species. As such, monitoring data are not routinely collected resulting in limited exposure mapping and epidemiologic studies. This work develops the log-mass fraction (LMF) Bayesian maximum entropy (BME) geostatistical prediction method used to predict the concentration of nine particle-bound PAHs across the US state of North Carolina. The LMF method develops a relationship between a relatively small number of collocated PAH and fine Particulate Matter (PM2.5) samples collected in 2005 and applies that relationship to a larger number of locations where PM2.5 is routinely monitored to more broadly estimate PAH concentrations across the state. Cross validation and mapping results indicate that by incorporating both PAH and PM2.5 data, the LMF BME method reduces mean squared error by 28.4% and produces more realistic spatial gradients compared to the traditional kriging approach based solely on observed PAH data. The LMF BME method efficiently creates PAH predictions in a PAH data sparse and PM2.5 data rich setting, opening the door for more expansive epidemiologic exposure assessments of ambient PAH.

Cost of abortions in Zambia: A comparison of safe abortion and post abortion care.

PubMed

Parmar, Divya; Leone, Tiziana; Coast, Ernestina; Murray, Susan Fairley; Hukin, Eleanor; Vwalika, Bellington

2017-02-01

Unsafe abortion is a significant but preventable cause of maternal mortality. Although induced abortion has been legal in Zambia since 1972, many women still face logistical, financial, social, and legal obstacles to access safe abortion services, and undergo unsafe abortion instead. This study provides the first estimates of costs of post abortion care (PAC) after an unsafe abortion and the cost of safe abortion in Zambia. In the absence of routinely collected data on abortions, we used multiple data sources: key informant interviews, medical records and hospital logbooks. We estimated the costs of providing safe abortion and PAC services at the University Teaching Hospital, Lusaka and then projected these costs to generate indicative cost estimates for Zambia. Due to unavailability of data on the actual number of safe abortions and PAC cases in Zambia, we used estimates from previous studies and from other similar countries, and checked the robustness of our estimates with sensitivity analyses. We found that PAC following an unsafe abortion can cost 2.5 times more than safe abortion care. The Zambian health system could save as much as US$0.4 million annually if those women currently treated for an unsafe abortion instead had a safe abortion.

A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling: GEOSTATISTICAL SENSITIVITY ANALYSIS

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

Dai, Heng; Chen, Xingyuan; Ye, Ming

Sensitivity analysis is an important tool for quantifying uncertainty in the outputs of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study we developed a hierarchical sensitivity analysis method that (1) constructs an uncertainty hierarchy by analyzing the input uncertainty sources, and (2) accounts for the spatial correlation among parameters at each level ofmore » the hierarchy using geostatistical tools. The contribution of uncertainty source at each hierarchy level is measured by sensitivity indices calculated using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport in model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally as driven by the dynamic interaction between groundwater and river water at the site. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially-distributed parameters.« less

Trends of selected cattle diseases in eastern Zambia between 1988 and 2008.

PubMed

Mubamba, Chrisborn; Sitali, Joseph; Gummow, Bruce

2011-09-01

Livestock diseases have long been a challenge to livestock production and public health in sub-Saharan Africa and Zambia in particular. The Eastern Province of Zambia is one area in Zambia that is not spared by this challenge. Among various livestock diseases affecting cattle in this region, the most prominent are East Coast Fever (ECF) and African Animal Trypanasomiasis (AAT). Since little has been published on the epidemiological trends of these diseases in eastern Zambia, a retrospective epidemiological study was carried out using reports that were submitted to the provincial veterinary office over the past 20 years. This paper assists in evaluating the impact of some of these aid programmes. Data was analysed using Excel(©), SPSS(®), Epi Info(©), and Epi Map(©) software. Apparent prevalence of AAT in cattle had decreased in the study period from estimates as high as 50% in Katete and Petauke district in 1990 and 1992 respectively to just below 3% (Petauke and Katete) in 2008, thereby, reducing the provincial apparent prevalence from 20% in 1992 to just below 3% in 2008. AAT apparent prevalence dropped from estimates as high as 17% in Chadiza district and 6% in Chipata district in 1990 to just below 1% in 2008 thereby reducing the provincial mean prevalence of East Coast Fever from 6% (1990) to 1% (2008). The inclusion of donor assistance in disease control programmes for both AAT and ECF appeared to have a significant impact on the prevalence of both diseases. Copyright © 2011 Elsevier B.V. All rights reserved.

Observation of the total solar eclipse on 21 June 2001 in Zambia

NASA Astrophysics Data System (ADS)

Takahashi, Noritsugu; Yumoto, Kiyohumi; Ichimoto, Kiyoshi

2002-04-01

On 21 June 2001, path of totality in Angola, Zambia, Zimbabwe, Mozambique, and Madagascar in Africa. The Japan Scientific Observation Team, consisting primarily of the members of the Solar Eclipse Subcommittee of the Committee for International Collaboration in Astronomy of the Science Council of JAPAN, visited Lusaka in Zambia to observe the total solar eclipse. Blessed with fine weather, the observation was successful. The outline of the influence of solar eclipse on the terrestrial magnetism, polarization of the flash spectrum, and other observation data, as well as the way educational activities were carried out, are reported.

Geostatistics as a tool to define various categories of resources

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

Sabourin, R.

1983-02-01

Definition of 'measured' and 'indicated' resources tend to be vague. Yet, the calculation of such categories of resources in a mineral deposit calls for specific technical criteria. The author discusses how a geostatistical methodology provides the technical criteria required to classify reasonably assured resources by levels of assurance of their existence.

A geostatistical approach to predicting sulfur content in the Pittsburgh coal bed

USGS Publications Warehouse

Watson, W.D.; Ruppert, L.F.; Bragg, L.J.; Tewalt, S.J.

2001-01-01

The US Geological Survey (USGS) is completing a national assessment of coal resources in the five top coal-producing regions in the US. Point-located data provide measurements on coal thickness and sulfur content. The sample data and their geologic interpretation represent the most regionally complete and up-to-date assessment of what is known about top-producing US coal beds. The sample data are analyzed using a combination of geologic and Geographic Information System (GIS) models to estimate tonnages and qualities of the coal beds. Traditionally, GIS practitioners use contouring to represent geographical patterns of "similar" data values. The tonnage and grade of coal resources are then assessed by using the contour lines as references for interpolation. An assessment taken to this point is only indicative of resource quantity and quality. Data users may benefit from a statistical approach that would allow them to better understand the uncertainty and limitations of the sample data. To develop a quantitative approach, geostatistics were applied to the data on coal sulfur content from samples taken in the Pittsburgh coal bed (located in the eastern US, in the southwestern part of the state of Pennsylvania, and in adjoining areas in the states of Ohio and West Virginia). Geostatistical methods that account for regional and local trends were applied to blocks 2.7 mi (4.3 km) on a side. The data and geostatistics support conclusions concerning the average sulfur content and its degree of reliability at regional- and economic-block scale over the large, contiguous part of the Pittsburgh outcrop, but not to a mine scale. To validate the method, a comparison was made with the sulfur contents in sample data taken from 53 coal mines located in the study area. The comparison showed a high degree of similarity between the sulfur content in the mine samples and the sulfur content represented by the geostatistically derived contours. Published by Elsevier Science B.V.

Bayesian Hierarchical Modeling for Big Data Fusion in Soil Hydrology

NASA Astrophysics Data System (ADS)

Mohanty, B.; Kathuria, D.; Katzfuss, M.

2016-12-01

Soil moisture datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors on the other hand provide observations on a finer spatial scale (meter scale or less) but are sparsely available. Soil moisture is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables. Hydrologic processes usually occur at a scale of 1 km or less and therefore spatially ubiquitous and temporally periodic soil moisture products at this scale are required to aid local decision makers in agriculture, weather prediction and reservoir operations. Past literature has largely focused on downscaling RS soil moisture for a small extent of a field or a watershed and hence the applicability of such products has been limited. The present study employs a spatial Bayesian Hierarchical Model (BHM) to derive soil moisture products at a spatial scale of 1 km for the state of Oklahoma by fusing point scale Mesonet data and coarse scale RS data for soil moisture and its auxiliary covariates such as precipitation, topography, soil texture and vegetation. It is seen that the BHM model handles change of support problems easily while performing accurate uncertainty quantification arising from measurement errors and imperfect retrieval algorithms. The computational challenge arising due to the large number of measurements is tackled by utilizing basis function approaches and likelihood approximations. The BHM model can be considered as a complex Bayesian extension of traditional geostatistical prediction methods (such as Kriging) for large datasets in the presence of uncertainties.

Schistosomiasis in Zambia: a systematic review of past and present experiences.

PubMed

Kalinda, Chester; Chimbari, Moses J; Mukaratirwa, Samson

2018-04-30

The speedy rate of change in the environmental and socio-economics factors may increase the incidence, prevalence and risk of schistosomiasis infections in Zambia. However, available information does not provide a comprehensive understanding of the biogeography and distribution of the disease, ecology and population dynamics of intermediate host snails. The current study used an information-theoretical approach to understand the biogeography and prevalence schistosomiasis and identified knowledge gaps that would be useful to improve policy towards surveillance and eradication of intermediate hosts snails in Zambia. To summarise the existing knowledge and build on past and present experiences of schistosomiasis epidemiology for effective disease control in Zambia, a systematic search of literature for the period 2000-2017 was done on PubMed, Google Scholar and EBSCOhost. Using the key words: 'Schistosomiasis', 'Biomphalaria', 'Bulinus', 'Schistosoma mansoni', 'Schistosoma haematobium', and 'Zambia', in combination with Booleans terms 'AND' and 'OR', published reports/papers were obtained and reviewed independently for inclusion. Thirteen papers published in English that fulfilled the inclusion criteria were selected for the final review. The papers suggest that the risk of infection has increased over the years and this has been attributed to environmental, socio-economic and demographic factors. Furthermore, schistosomiasis is endemic in many parts of the country with infection due to Schistosoma haematobium being more prevalent than that due to S. mansoni. This review also found that S. haematobium was linked to genital lesions, thus increasing risks of contracting other diseases such as HIV and cervical cancer. For both S. haematobium and S. mansoni, environmental, socio-economic, and demographic factors were influential in the transmission and prevalence of the disease and highlight the need for detailed knowledge on ecological modelling and mapping the

The reach and impact of social marketing and reproductive health communication campaigns in Zambia

PubMed Central

Van Rossem, Ronan; Meekers, Dominique

2007-01-01

Background Like many sub-Saharan African countries, Zambia is dealing with major health issues, including HIV/AIDS, family planning, and reproductive health. To address reproductive health problems and the HIV/AIDS epidemic in Zambia, several social marketing and health communication programs focusing on reproductive and HIV/AIDS prevention programs are being implemented. This paper describes the reach of these programs and assesses their impact on condom use. Methods This paper assesses the reach of selected radio and television programs about family planning and HIV/AIDS and of communications about the socially marketed Maximum condoms in Zambia, as well as their impact on condom use, using data from the 2001–2002 Zambia Demographic and Health Survey. To control for self-selection and endogeneity, we use a two-stage regression model to estimate the effect of program exposure on the behavioural outcomes. Results Those who were exposed to radio and television programs about family planning and HIV/AIDS were more likely to have ever used a condom (OR = 1.16 for men and 1.06 for women). Men highly exposed to Maximum condoms social marketing communication were more likely than those with low exposure to the program to have ever used a condom (OR = 1.48), and to have used a condom at their last sexual intercourse (OR = 1.23). Conclusion Findings suggest that the reproductive health and social marketing campaigns in Zambia reached a large portion of the population and had a significant impact on condom use. The results suggest that future reproductive health communication campaigns that invest in radio programming may be more effective than those investing in television programming, and that future campaigns should seek to increase their impact among women, perhaps by focusing on the specific constrains that prevent females from using condoms. PMID:18088437

The reach and impact of social marketing and reproductive health communication campaigns in Zambia.

PubMed

Van Rossem, Ronan; Meekers, Dominique

2007-12-18

Like many sub-Saharan African countries, Zambia is dealing with major health issues, including HIV/AIDS, family planning, and reproductive health. To address reproductive health problems and the HIV/AIDS epidemic in Zambia, several social marketing and health communication programs focusing on reproductive and HIV/AIDS prevention programs are being implemented. This paper describes the reach of these programs and assesses their impact on condom use. This paper assesses the reach of selected radio and television programs about family planning and HIV/AIDS and of communications about the socially marketed Maximum condoms in Zambia, as well as their impact on condom use, using data from the 2001-2002 Zambia Demographic and Health Survey. To control for self-selection and endogeneity, we use a two-stage regression model to estimate the effect of program exposure on the behavioural outcomes. Those who were exposed to radio and television programs about family planning and HIV/AIDS were more likely to have ever used a condom (OR = 1.16 for men and 1.06 for women). Men highly exposed to Maximum condoms social marketing communication were more likely than those with low exposure to the program to have ever used a condom (OR = 1.48), and to have used a condom at their last sexual intercourse (OR = 1.23). Findings suggest that the reproductive health and social marketing campaigns in Zambia reached a large portion of the population and had a significant impact on condom use. The results suggest that future reproductive health communication campaigns that invest in radio programming may be more effective than those investing in television programming, and that future campaigns should seek to increase their impact among women, perhaps by focusing on the specific constrains that prevent females from using condoms.

Developing a community driven sustainable model of maternity waiting homes for rural Zambia.

PubMed

Lori, Jody R; Munro-Kramer, Michelle L; Mdluli, Eden Ahmed; Musonda Mrs, Gertrude K; Boyd, Carol J

2016-10-01

maternity waiting homes (MWHs) are residential dwellings located near health facilities where women in the late stages of pregnancy stay to await childbirth and receive immediate postpartum services. These shelters help overcome distance and transportation barriers that prevent women from receiving timely skilled obstetric care. the purpose of this study was to explore Zambian stakeholders' beliefs regarding the acceptability, feasibility, and sustainability of maternity waiting homes (MWHs) to inform a model for rural Zambia. a qualitative design using a semi-structured interview guide for data collection was used. two rural districts in the Eastern province of Zambia. individual interviews were conducted with community leaders (n=46). Focus groups were held with Safe Motherhood Action Groups, husbands, and women of childbearing age in two rural districts in Zambia (n=500). latent content analysis was used to analyze the data. participants were overwhelmingly in support of MWHs as a way to improve access to facility-based childbirth and address the barrier of distance. Data suggest that participants can describe features of high quality care, and the type of care they expect from a MWH. Stakeholders acknowledged the need to contribute to the maintenance of the MWH, and that community involvement was crucial to MWH sustainability. access to facility childbirth remains particularly challenging in rural Zambia and delays in seeking care exist. Maternity waiting homes offer a feasible and acceptable intervention to reduce delays in seeking care, thereby holding the potential to improve maternal outcomes. this study joins a growing literature on the acceptability, feasibility, and sustainability of MWHs. It is believed that MWHs, by addressing the distance and transportation barriers, will increase the use of skilled birth attendants, thereby reducing maternal and neonatal morbidity and mortality in rural, low resource areas of Zambia. We recommend that any initiative

Investment incentives and the implementation of the Framework Convention on Tobacco Control: evidence from Zambia.

PubMed

Lencucha, Raphael; Drope, Jeffrey; Labonte, Ronald; Zulu, Richard; Goma, Fastone

2016-07-01

Policy misalignment across different sectors of government serves as one of the pivotal barriers to WHO Framework Convention on Tobacco Control (FCTC) implementation. This paper examines the logic used by government officials to justify investment incentives to increase tobacco processing and manufacturing in the context of FCTC implementation in Zambia. We conducted qualitative semistructured interviews with key informants from government, civil society and intergovernmental economic organisations (n=23). We supplemented the interview data with an analysis of public documents pertaining to the policy of economic development in Zambia. We found gross misalignments between the policies of the economic sector and efforts to implement the provisions of the FCTC. Our interviews uncovered the rationale used by officials in the economic sector to justify providing economic incentives to bolster tobacco processing and manufacturing in Zambia: (1) tobacco is not consumed by Zambians/tobacco is an export commodity, (2) economic benefits outweigh health costs and (3) tobacco consumption is a personal choice. Much of the struggle Zambia has experienced in implementing the FCTC can be attributed to misalignments between the economic and health sectors. Zambia's development agenda seeks to bolster agricultural processing and manufacturing. Tobacco control proponents must recognise and work within this context in order to foster productive strategies with those working on tobacco supply issues. These findings are broadly applicable to the global context. It is important that the Ministry of Health monitors the tobacco policy of and engages with these sectors to find ways of harmonising FCTC implementation. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Price, tax and tobacco product substitution in Zambia.

PubMed

Stoklosa, Michal; Goma, Fastone; Nargis, Nigar; Drope, Jeffrey; Chelwa, Grieve; Chisha, Zunda; Fong, Geoffrey T

2018-03-24

In Zambia, the number of cigarette users is growing, and the lack of strong tax policies is likely an important cause. When adjusted for inflation, levels of tobacco tax have not changed since 2007. Moreover, roll-your-own (RYO) tobacco, a less-costly alternative to factory-made (FM) cigarettes, is highly prevalent. We modelled the probability of FM and RYO cigarette smoking using individual-level data obtained from the 2012 and 2014 waves of the International Tobacco Control (ITC) Zambia Survey. We used two estimation methods: the standard estimation method involving separate random effects probit models and a method involving a system of equations (incorporating bivariate seemingly unrelated random effects probit) to estimate price elasticities of FM and RYO cigarettes and their cross-price elasticities. The estimated price elasticities of smoking prevalence are -0.20 and -0.03 for FM and RYO cigarettes, respectively. FM and RYO are substitutes; that is, when the price of one of the products goes up, some smokers switch to the other product. The effects are stronger for substitution from FM to RYO than vice versa. This study affirms that increasing cigarette tax with corresponding price increases could significantly reduce cigarette use in Zambia. Furthermore, reducing between-product price differences would reduce substitution from FM to RYO. Since RYO use is associated with lower socioeconomic status, efforts to decrease RYO use, including through tax/price approaches and cessation assistance, would decrease health inequalities in Zambian society and reduce the negative economic consequences of tobacco use experienced by the poor. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

The prevalence and distribution of schistosomiasis in Zambia.

PubMed

Boatin, B A; Wurapa, F K; Ulrich, A M

1985-09-01

This paper attempts to approach an accurate report of prevalence of schistosomiasis in Zambia by bringing together several reports. A review of some early prevalence studies in Zambia shows the prevalence of S. hematobium infection to be (14-40%) and that for S. mansoni to range from (0-7%), in the Northern and Luapula Provinces. The areas around Lakes Kariba in the south, and Bangweulu in the north had prevalence rates of (3-35%) for S. hematobium and (2-6%) for S. mansoni. A nationwide survey found the overall prevalence of S. hematobium to be about 16%. The Gwembe Valley in the South had the highest prevalence of 57.9% for S. hematobium; S. mansoni with a prevalence of (45-77%) in the Northern Province from more recent studies is not very widespread. A comprehensive study performed between 1969-73 covered almost the entire rural population and found an overall prevalence of 16.8%, varying greatly between ecozones. The 5-14 year age group showed the highest prevalence. A 1976-82 study of rural primary school children in several provinces found high prevalence rates. Specimen gathering and analysis is described for most studies analyzed, revealing some inconsistencies threatening the reliability of data. Available data do show the spotty and local nature of the prevalence rates between areas. There have not been many studies of S. mansoni prevalence, possibly due to the difficulties involved with the collection of stool specimens, but prevalence (especially seasonal) has been shown to be high in certain areas (although low generally). The areas around the 2 major lakes show considerable prevalence of both parasites, and further study is needed on the health impact of man-made lakes in Zambia and elsewhere.

Socio-cultural factors surrounding mental distress during the perinatal period in Zambia: a qualitative investigation

PubMed Central

2012-01-01

Background The presence of mental distress during pregnancy and after childbirth imposes detrimental developmental and health consequences for families in all nations. In Zambia, the Ministry of Health (MoH) has proposed a more comprehensive approach towards mental health care, recognizing the importance of the mental health of women during the perinatal period. Aim The study explores factors contributing to mental distress during the perinatal period of motherhood in Zambia. Methods A qualitative study was conducted in Lusaka, Zambia with nineteen focus groups comprising 149 women and men from primary health facilities and schools respectively. Findings There are high levels of mental distress in four domains: worry about HIV status and testing; uncertainty about survival from childbirth; lack of social support; and vulnerability/oppression. Conclusion Identifying mental distress and prompt referral for interventions is critical to improving the mental health of the mother and prevent the effects of mental distress on the baby. Recommendation Strategies should be put in place to ensure pregnant women are screened for possible perinatal mental health problems during their visit to antenatal clinic and referral made to qualified mental health professionals. In addition further research is recommended in order to facilitate evidence based mental health policy formulation and implementation in Zambia. PMID:22954173

Overview and technical and practical aspects for use of geostatistics in hazardous-, toxic-, and radioactive-waste-site investigations

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

Bossong, C.R.; Karlinger, M.R.; Troutman, B.M.

1999-10-01

Technical and practical aspects of applying geostatistics are developed for individuals involved in investigation at hazardous-, toxic-, and radioactive-waste sites. Important geostatistical concepts, such as variograms and ordinary, universal, and indicator kriging, are described in general terms for introductory purposes and in more detail for practical applications. Variogram modeling using measured ground-water elevation data is described in detail to illustrate principles of stationarity, anisotropy, transformations, and cross validation. Several examples of kriging applications are described using ground-water-level elevations, bedrock elevations, and ground-water-quality data. A review of contemporary literature and selected public domain software associated with geostatistics also is provided, asmore » is a discussion of alternative methods for spatial modeling, including inverse distance weighting, triangulation, splines, trend-surface analysis, and simulation.« less

An application of geostatistics and fractal geometry for reservoir characterization

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

Aasum, Y.; Kelkar, M.G.; Gupta, S.P.

1991-03-01

This paper presents an application of geostatistics and fractal geometry concepts for 2D characterization of rock properties (k and {phi}) in a dolomitic, layered-cake reservoir. The results indicate that lack of closely spaced data yield effectively random distributions of properties. Further, incorporation of geology reduces uncertainties in fractal interpolation of wellbore properties.

Infant-mother and infant-sibling attachment in Zambia.

PubMed

Mooya, Haatembo; Sichimba, Francis; Bakermans-Kranenburg, Marian

2016-12-01

This study, the first in Zambia using the Strange Situation Procedure (SSP) to observe attachment relationships and the "very first" observational study of infant-sibling attachment, examined patterns of infant-mother and infant-sibling attachment, and tested their association. We included siblings who were substantially involved in caregiving activities with their younger siblings. We hypothesized that infants would develop attachment relationships to both mothers and siblings; the majority of infants would be classified as securely attached to both caregivers, and infant-mother and infant-sibling attachment would be unrelated. The sample included 88 low-income families in Lusaka, Zambia (average of 3.5 children; SD = 1.5). The SSP distributions (infant-mother) were 59% secure, 24% avoidant and 17% resistant, and 46% secure, 20% avoidant, 5% resistant and 29% disorganized for three- and four-way classifications, respectively. The infant-sibling classifications were 42% secure, 23% avoidant and 35% resistant, and 35% secure, 23% avoidant, 9% resistant and 33% disorganized for three- and four-way classifications, respectively. Infant-mother and infant-sibling attachment relationships were not associated.

Hierarchical Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets.

PubMed

Datta, Abhirup; Banerjee, Sudipto; Finley, Andrew O; Gelfand, Alan E

2016-01-01

Spatial process models for analyzing geostatistical data entail computations that become prohibitive as the number of spatial locations become large. This article develops a class of highly scalable nearest-neighbor Gaussian process (NNGP) models to provide fully model-based inference for large geostatistical datasets. We establish that the NNGP is a well-defined spatial process providing legitimate finite-dimensional Gaussian densities with sparse precision matrices. We embed the NNGP as a sparsity-inducing prior within a rich hierarchical modeling framework and outline how computationally efficient Markov chain Monte Carlo (MCMC) algorithms can be executed without storing or decomposing large matrices. The floating point operations (flops) per iteration of this algorithm is linear in the number of spatial locations, thereby rendering substantial scalability. We illustrate the computational and inferential benefits of the NNGP over competing methods using simulation studies and also analyze forest biomass from a massive U.S. Forest Inventory dataset at a scale that precludes alternative dimension-reducing methods. Supplementary materials for this article are available online.

Hierarchical Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets

PubMed Central

Datta, Abhirup; Banerjee, Sudipto; Finley, Andrew O.; Gelfand, Alan E.

2018-01-01

Spatial process models for analyzing geostatistical data entail computations that become prohibitive as the number of spatial locations become large. This article develops a class of highly scalable nearest-neighbor Gaussian process (NNGP) models to provide fully model-based inference for large geostatistical datasets. We establish that the NNGP is a well-defined spatial process providing legitimate finite-dimensional Gaussian densities with sparse precision matrices. We embed the NNGP as a sparsity-inducing prior within a rich hierarchical modeling framework and outline how computationally efficient Markov chain Monte Carlo (MCMC) algorithms can be executed without storing or decomposing large matrices. The floating point operations (flops) per iteration of this algorithm is linear in the number of spatial locations, thereby rendering substantial scalability. We illustrate the computational and inferential benefits of the NNGP over competing methods using simulation studies and also analyze forest biomass from a massive U.S. Forest Inventory dataset at a scale that precludes alternative dimension-reducing methods. Supplementary materials for this article are available online. PMID:29720777

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.

Mycobacterium bovis infection at the interface between domestic and wild animals in Zambia.

PubMed

Hang'ombe, Mudenda B; Munyeme, Musso; Nakajima, Chie; Fukushima, Yukari; Suzuki, Haruka; Matandiko, Wigganson; Ishii, Akihiro; Mweene, Aaron S; Suzuki, Yasuhiko

2012-11-14

In Zambia, the presence of bovine tuberculosis in both wild and domestic animals has long been acknowledged and mutual transmission between them has been predicted without any direct evidence. Elucidation of the circulating Mycobacterium bovis strains at wild and domestic animals interphase area in Zambia, where bovine tuberculosis was diagnosed in wildlife seemed to be important. A PCR identified 15 and 37 M. bovis isolates from lechwe and cattle, respectively. Spoligotype analysis revealed that M. bovis strains from lechwe and cattle in Kafue basin clustered into a major node SB0120, where isolates outside the Kafue basin clustered into different nodes of SB0131 and SB0948. The comparatively higher variety of strains in cattle compared to lechwe elucidated by Mycobacterial Interspersed Repetitive Units-Variable Number Tandem Repeats analyses are consistent with cattle being the probable source of M. bovis in wild and domestic animals interphase area in Zambia. These results provide strong evidence of M. bovis strains transfer between cattle and lechwe, with the latter having developed into a sylvatic reservoir host.

Mycobacterium bovis infection at the interface between domestic and wild animals in Zambia

PubMed Central

2012-01-01

Background In Zambia, the presence of bovine tuberculosis in both wild and domestic animals has long been acknowledged and mutual transmission between them has been predicted without any direct evidence. Elucidation of the circulating Mycobacterium bovis strains at wild and domestic animals interphase area in Zambia, where bovine tuberculosis was diagnosed in wildlife seemed to be important. Results A PCR identified 15 and 37 M. bovis isolates from lechwe and cattle, respectively. Spoligotype analysis revealed that M. bovis strains from lechwe and cattle in Kafue basin clustered into a major node SB0120, where isolates outside the Kafue basin clustered into different nodes of SB0131 and SB0948. The comparatively higher variety of strains in cattle compared to lechwe elucidated by Mycobacterial Interspersed Repetitive Units–Variable Number Tandem Repeats analyses are consistent with cattle being the probable source of M. bovis in wild and domestic animals interphase area in Zambia. Conclusions These results provide strong evidence of M. bovis strains transfer between cattle and lechwe, with the latter having developed into a sylvatic reservoir host. PMID:23151267

Mapping, Bayesian Geostatistical Analysis and Spatial Prediction of Lymphatic Filariasis Prevalence in Africa

PubMed Central

Slater, Hannah; Michael, Edwin

2013-01-01

There is increasing interest to control or eradicate the major neglected tropical diseases. Accurate modelling of the geographic distributions of parasitic infections will be crucial to this endeavour. We used 664 community level infection prevalence data collated from the published literature in conjunction with eight environmental variables, altitude and population density, and a multivariate Bayesian generalized linear spatial model that allows explicit accounting for spatial autocorrelation and incorporation of uncertainty in input data and model parameters, to construct the first spatially-explicit map describing LF prevalence distribution in Africa. We also ran the best-fit model against predictions made by the HADCM3 and CCCMA climate models for 2050 to predict the likely distributions of LF under future climate and population changes. We show that LF prevalence is strongly influenced by spatial autocorrelation between locations but is only weakly associated with environmental covariates. Infection prevalence, however, is found to be related to variations in population density. All associations with key environmental/demographic variables appear to be complex and non-linear. LF prevalence is predicted to be highly heterogenous across Africa, with high prevalences (>20%) estimated to occur primarily along coastal West and East Africa, and lowest prevalences predicted for the central part of the continent. Error maps, however, indicate a need for further surveys to overcome problems with data scarcity in the latter and other regions. Analysis of future changes in prevalence indicates that population growth rather than climate change per se will represent the dominant factor in the predicted increase/decrease and spread of LF on the continent. We indicate that these results could play an important role in aiding the development of strategies that are best able to achieve the goals of parasite elimination locally and globally in a manner that may also account

Catholic Education in Zambia: Mission Integrity and Politics

ERIC Educational Resources Information Center

Carmody, Brendan

2016-01-01

This article provides the history of Catholic state-aided schooling in Zambia for over a century. It notes how the Catholic Church came to view its school to be a pivotal means of church development. By cooperation with the state it entered more fully into the nation's future by offering high-quality state-sponsored schooling. This proved to…

Spatial interpolation of forest conditions using co-conditional geostatistical simulation

Treesearch

H. Todd Mowrer

2000-01-01

In recent work the author used the geostatistical Monte Carlo technique of sequential Gaussian simulation (s.G.s.) to investigate uncertainty in a GIS analysis of potential old-growth forest areas. The current study compares this earlier technique to that of co-conditional simulation, wherein the spatial cross-correlations between variables are included. As in the...

Developing a new Bayesian Risk Index for risk evaluation of soil contamination.

PubMed

Albuquerque, M T D; Gerassis, S; Sierra, C; Taboada, J; Martín, J E; Antunes, I M H R; Gallego, J R

2017-12-15

Industrial and agricultural activities heavily constrain soil quality. Potentially Toxic Elements (PTEs) are a threat to public health and the environment alike. In this regard, the identification of areas that require remediation is crucial. In the herein research a geochemical dataset (230 samples) comprising 14 elements (Cu, Pb, Zn, Ag, Ni, Mn, Fe, As, Cd, V, Cr, Ti, Al and S) was gathered throughout eight different zones distinguished by their main activity, namely, recreational, agriculture/livestock and heavy industry in the Avilés Estuary (North of Spain). Then a stratified systematic sampling method was used at short, medium, and long distances from each zone to obtain a representative picture of the total variability of the selected attributes. The information was then combined in four risk classes (Low, Moderate, High, Remediation) following reference values from several sediment quality guidelines (SQGs). A Bayesian analysis, inferred for each zone, allowed the characterization of PTEs correlations, the unsupervised learning network technique proving to be the best fit. Based on the Bayesian network structure obtained, Pb, As and Mn were selected as key contamination parameters. For these 3 elements, the conditional probability obtained was allocated to each observed point, and a simple, direct index (Bayesian Risk Index-BRI) was constructed as a linear rating of the pre-defined risk classes weighted by the previously obtained probability. Finally, the BRI underwent geostatistical modeling. One hundred Sequential Gaussian Simulations (SGS) were computed. The Mean Image and the Standard Deviation maps were obtained, allowing the definition of High/Low risk clusters (Local G clustering) and the computation of spatial uncertainty. High-risk clusters are mainly distributed within the area with the highest altitude (agriculture/livestock) showing an associated low spatial uncertainty, clearly indicating the need for remediation. Atmospheric emissions, mainly

New Agricultural Settlement, Meheba River, Zambia, Africa

NASA Technical Reports Server (NTRS)

1990-01-01

This infra-red view of a new settlement along the Meheba River, Zambia, Africa (12.5S, 26.0E) resembles the resettlement clusters in the Amazon basin of Brazil. However, this settlement is on savanna land not a tropical forest region, so relatively little land clearing was required. The familiar pattern of small single family plots, no large commercial fields, along the branches of a herringbone road network is evident.

Usability and potential of geostatistics for spatial discrimination of multiple sclerosis lesion patterns.

PubMed

Marschallinger, Robert; Golaszewski, Stefan M; Kunz, Alexander B; Kronbichler, Martin; Ladurner, Gunther; Hofmann, Peter; Trinka, Eugen; McCoy, Mark; Kraus, Jörg

2014-01-01

In multiple sclerosis (MS) the individual disease courses are very heterogeneous among patients and biomarkers for setting the diagnosis and the estimation of the prognosis for individual patients would be very helpful. For this purpose, we are developing a multidisciplinary method and workflow for the quantitative, spatial, and spatiotemporal analysis and characterization of MS lesion patterns from MRI with geostatistics. We worked on a small data set involving three synthetic and three real-world MS lesion patterns, covering a wide range of possible MS lesion configurations. After brain normalization, MS lesions were extracted and the resulting binary 3-dimensional models of MS lesion patterns were subject to geostatistical indicator variography in three orthogonal directions. By applying geostatistical indicator variography, we were able to describe the 3-dimensional spatial structure of MS lesion patterns in a standardized manner. Fitting a model function to the empirical variograms, spatial characteristics of the MS lesion patterns could be expressed and quantified by two parameters. An orthogonal plot of these parameters enabled a well-arranged comparison of the involved MS lesion patterns. This method in development is a promising candidate to complement standard image-based statistics by incorporating spatial quantification. The work flow is generic and not limited to analyzing MS lesion patterns. It can be completely automated for the screening of radiological archives. Copyright © 2013 by the American Society of Neuroimaging.

Adapting geostatistics to analyze spatial and temporal trends in weed populations

USDA-ARS?s Scientific Manuscript database

Geostatistics were originally developed in mining to estimate the location, abundance and quality of ore over large areas from soil samples to optimize future mining efforts. Here, some of these methods were adapted to weeds to account for a limited distribution area (i.e., inside a field), variatio...

Identification of high-permeability subsurface structures with multiple point geostatistics and normal score ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Zovi, Francesco; Camporese, Matteo; Hendricks Franssen, Harrie-Jan; Huisman, Johan Alexander; Salandin, Paolo

2017-05-01

Alluvial aquifers are often characterized by the presence of braided high-permeable paleo-riverbeds, which constitute an interconnected preferential flow network whose localization is of fundamental importance to predict flow and transport dynamics. Classic geostatistical approaches based on two-point correlation (i.e., the variogram) cannot describe such particular shapes. In contrast, multiple point geostatistics can describe almost any kind of shape using the empirical probability distribution derived from a training image. However, even with a correct training image the exact positions of the channels are uncertain. State information like groundwater levels can constrain the channel positions using inverse modeling or data assimilation, but the method should be able to handle non-Gaussianity of the parameter distribution. Here the normal score ensemble Kalman filter (NS-EnKF) was chosen as the inverse conditioning algorithm to tackle this issue. Multiple point geostatistics and NS-EnKF have already been tested in synthetic examples, but in this study they are used for the first time in a real-world case study. The test site is an alluvial unconfined aquifer in northeastern Italy with an extension of approximately 3 km2. A satellite training image showing the braid shapes of the nearby river and electrical resistivity tomography (ERT) images were used as conditioning data to provide information on channel shape, size, and position. Measured groundwater levels were assimilated with the NS-EnKF to update the spatially distributed groundwater parameters (hydraulic conductivity and storage coefficients). Results from the study show that the inversion based on multiple point geostatistics does not outperform the one with a multiGaussian model and that the information from the ERT images did not improve site characterization. These results were further evaluated with a synthetic study that mimics the experimental site. The synthetic results showed that only for a much

Mercury emissions from coal combustion in Silesia, analysis using geostatistics

NASA Astrophysics Data System (ADS)

Zasina, Damian; Zawadzki, Jaroslaw

2015-04-01

Data provided by the UNEP's report on mercury [1] shows that solid fuel combustion in significant source of mercury emission to air. Silesia, located in southwestern Poland, is notably affected by mercury emission due to being one of the most industrialized Polish regions: the place of coal mining, production of metals, stone mining, mineral quarrying and chemical industry. Moreover, Silesia is the region with high population density. People are exposed to severe risk of mercury emitted from both: industrial and domestic sources (i.e. small household furnaces). Small sources have significant contribution to total emission of mercury. Official and statistical analysis, including prepared for international purposes [2] did not provide data about spatial distribution of the mercury emitted to air, however number of analysis on Polish public power and energy sector had been prepared so far [3; 4]. The distribution of locations exposed for mercury emission from small domestic sources is interesting matter merging information from various sources: statistical, economical and environmental. This paper presents geostatistical approach to distibution of mercury emission from coal combustion. Analysed data organized in 2 independent levels: individual, bottom-up approach derived from national emission reporting system [5; 6] and top down - regional data calculated basing on official statistics [7]. Analysis, that will be presented, will include comparison of spatial distributions of mercury emission using data derived from sources mentioned above. Investigation will include three voivodeships of Poland: Lower Silesian, Opole (voivodeship) and Silesian using selected geostatistical methodologies including ordinary kriging [8]. References [1] UNEP. Global Mercury Assessment 2013: Sources, Emissions, Releases and Environmental Transport. UNEP Chemicals Branch, Geneva, Switzerland, 2013. [2] NCEM. Poland's Informative Inventory Report 2014. NCEM at the IEP-NRI, 2014. http

Bayesian Regression with Network Prior: Optimal Bayesian Filtering Perspective

PubMed Central

Qian, Xiaoning; Dougherty, Edward R.

2017-01-01

The recently introduced intrinsically Bayesian robust filter (IBRF) provides fully optimal filtering relative to a prior distribution over an uncertainty class ofjoint random process models, whereas formerly the theory was limited to model-constrained Bayesian robust filters, for which optimization was limited to the filters that are optimal for models in the uncertainty class. This paper extends the IBRF theory to the situation where there are both a prior on the uncertainty class and sample data. The result is optimal Bayesian filtering (OBF), where optimality is relative to the posterior distribution derived from the prior and the data. The IBRF theories for effective characteristics and canonical expansions extend to the OBF setting. A salient focus of the present work is to demonstrate the advantages of Bayesian regression within the OBF setting over the classical Bayesian approach in the context otlinear Gaussian models. PMID:28824268

Ethnoveterinary treatments for common cattle diseases in four districts of the Southern Province, Zambia.

PubMed

Syakalima, Michelo; Simuunza, Martin; Zulu, Victor Chisha

2018-02-01

Ethno veterinary knowledge has rarely been recorded, and no or limited effort has been made to exploit this knowledge despite its widespread use in Zambia. This study documented the types of plants used to treat important animal diseases in rural Zambia as a way of initiating their sustained documentation and scientific validation. The study was done in selected districts of the Southern Zambia, Africa. The research was a participatory epidemiological study conducted in two phases. The first phase was a pre-study exploratory rapid rural appraisal conducted to familiarize the researchers with the study areas, and the second phase was a participatory rural appraisal to help gather the data. The frequency index was used to rank the commonly mentioned treatments. A number of diseases and traditional treatments were listed with the help of local veterinarians. Diseases included: Corridor disease (Theileriosis), foot and mouth disease, blackleg, bloody diarrhea, lumpy skin disease, fainting, mange, blindness, coughing, bloat, worms, cobra snakebite, hemorrhagic septicemia, and transmissible venereal tumors. The plant preparations were in most diseases given to the livestock orally (as a drench). Leaves, barks, and roots were generally used depending on the plant type. Ethno veterinary medicine is still widespread among the rural farmers in the province and in Zambia in general. Some medicines are commonly used across diseases probably because they have a wide spectrum of action. These medicines should, therefore, be validated for use in conventional livestock healthcare systems in the country to reduce the cost of treatments.

A rapid assessment of avoidable blindness in Southern Zambia.

PubMed

Lindfield, Robert; Griffiths, Ulla; Bozzani, Fiammetta; Mumba, Musonda; Munsanje, Joseph

2012-01-01

A rapid assessment of avoidable blindness (RAAB) was conducted in Southern Zambia to establish the prevalence and causes of blindness in order to plan effective services and advocate for support for eye care to achieve the goals of VISION 2020: the right to sight. Cluster randomisation was used to select villages in the survey area. These were further subdivided into segments. One segment was selected randomly and a survey team moved from house to house examining everyone over the age of 50 years. Each individual received a visual acuity assessment and simple ocular examination. Data was recorded on a standard proforma and entered into an established software programme for analysis. 2.29% of people over the age of 50 were found to be blind (VA <3/60 in the better eye with available correction). The major cause of blindness was cataract (47.2%) with posterior segment disease being the next main cause (18.8%). 113 eyes had received cataract surgery with 30.1% having a poor outcome (VA <6/60) following surgery. Cataract surgical coverage showed that men (72%) received more surgery than women (65%). The results from the RAAB survey in Zambia were very similar to the results from a similar survey in Malawi, where the main cause of blindness was cataract but posterior segment disease was also a significant contributor. Blindness in this part of Zambia is mainly avoidable and there is a need for comprehensive eye care services that can address both cataract and posterior segment disease in the population if the aim of VISION 2020 is to be achieved. Services should focus on quality and gender equity of cataract surgery.

Modelling Geomechanical Heterogeneity of Rock Masses Using Direct and Indirect Geostatistical Conditional Simulation Methods

NASA Astrophysics Data System (ADS)

Eivazy, Hesameddin; Esmaieli, Kamran; Jean, Raynald

2017-12-01

An accurate characterization and modelling of rock mass geomechanical heterogeneity can lead to more efficient mine planning and design. Using deterministic approaches and random field methods for modelling rock mass heterogeneity is known to be limited in simulating the spatial variation and spatial pattern of the geomechanical properties. Although the applications of geostatistical techniques have demonstrated improvements in modelling the heterogeneity of geomechanical properties, geostatistical estimation methods such as Kriging result in estimates of geomechanical variables that are not fully representative of field observations. This paper reports on the development of 3D models for spatial variability of rock mass geomechanical properties using geostatistical conditional simulation method based on sequential Gaussian simulation. A methodology to simulate the heterogeneity of rock mass quality based on the rock mass rating is proposed and applied to a large open-pit mine in Canada. Using geomechanical core logging data collected from the mine site, a direct and an indirect approach were used to model the spatial variability of rock mass quality. The results of the two modelling approaches were validated against collected field data. The study aims to quantify the risks of pit slope failure and provides a measure of uncertainties in spatial variability of rock mass properties in different areas of the pit.

Robust spatialization of soil water content at the scale of an agricultural field using geophysical and geostatistical methods

NASA Astrophysics Data System (ADS)

Henine, Hocine; Tournebize, Julien; Laurent, Gourdol; Christophe, Hissler; Cournede, Paul-Henry; Clement, Remi

2017-04-01

Research on the Critical Zone (CZ) is a prerequisite for undertaking issues related to ecosystemic services that human societies rely on (nutrient cycles, water supply and quality). However, while the upper part of CZ (vegetation, soil, surface water) is readily accessible, knowledge of the subsurface remains limited, due to the point-scale character of conventional direct observations. While the potential for geophysical methods to overcome this limitation is recognized, the translation of the geophysical information into physical properties or states of interest remains a challenge (e.g. the translation of soil electrical resistivity into soil water content). In this study, we propose a geostatistical framework using the Bayesian Maximum Entropy (BME) approach to assimilate geophysical and point-scale data. We especially focus on the prediction of the spatial distribution of soil water content using (1) TDR point-scale measurements of soil water content, which are considered as accurate data, and (2) soil water content data derived from electrical resistivity measurements, which are uncertain data but spatially dense. We used a synthetic dataset obtained with a vertical 2D domain to evaluate the performance of this geostatistical approach. Spatio-temporal simulations of soil water content were carried out using Hydrus-software for different scenarios: homogeneous or heterogeneous hydraulic conductivity distribution, and continuous or punctual infiltration pattern. From the simulations of soil water content, conceptual soil resistivity models were built using a forward modeling approach and point sampling of water content values, vertically ranged, were done. These two datasets are similar to field measurements of soil electrical resistivity (using electrical resistivity tomography, ERT) and soil water content (using TDR probes) obtained at the Boissy-le-Chatel site, in Orgeval catchment (East of Paris, France). We then integrated them into a specialization

Geostatistics, remote sensing and precision farming.

PubMed

Mulla, D J

1997-01-01

Precision farming is possible today because of advances in farming technology, procedures for mapping and interpolating spatial patterns, and geographic information systems for overlaying and interpreting several soil, landscape and crop attributes. The key component of precision farming is the map showing spatial patterns in field characteristics. Obtaining information for this map is often achieved by soil sampling. This approach, however, can be cost-prohibitive for grain crops. Soil sampling strategies can be simplified by use of auxiliary data provided by satellite or aerial photo imagery. This paper describes geostatistical methods for estimating spatial patterns in soil organic matter, soil test phosphorus and wheat grain yield from a combination of Thematic Mapper imaging and soil sampling.

A Rural Implementation of a 52 Node Mixed Wireless Mesh Network in Macha, Zambia

NASA Astrophysics Data System (ADS)

Backens, Jonathan; Mweemba, Gregory; van Stam, Gertjan

In spite of increasing international and academic attention, there remains many challenges facing real world implementations of developing technologies. There has been considerable hype behind Wireless Mesh Networking as the ubiquitous solution for rural ICT in the developing world. In this paper, we present the real world rural mesh network implementation in the village of Macha, Zambia and draw both performance conclusions as well as overall experiential conclusions. The purpose of this paper is to introduce and analyze our low cost solution and extrapolate future trends for rural ICT implementations in Zambia.

Integration of GIS, Geostatistics, and 3-D Technology to Assess the Spatial Distribution of Soil Moisture

NASA Technical Reports Server (NTRS)

Betts, M.; Tsegaye, T.; Tadesse, W.; Coleman, T. L.; Fahsi, A.

1998-01-01

The spatial and temporal distribution of near surface soil moisture is of fundamental importance to many physical, biological, biogeochemical, and hydrological processes. However, knowledge of these space-time dynamics and the processes which control them remains unclear. The integration of geographic information systems (GIS) and geostatistics together promise a simple mechanism to evaluate and display the spatial and temporal distribution of this vital hydrologic and physical variable. Therefore, this research demonstrates the use of geostatistics and GIS to predict and display soil moisture distribution under vegetated and non-vegetated plots. The research was conducted at the Winfred Thomas Agricultural Experiment Station (WTAES), Hazel Green, Alabama. Soil moisture measurement were done on a 10 by 10 m grid from tall fescue grass (GR), alfalfa (AA), bare rough (BR), and bare smooth (BS) plots. Results indicated that variance associated with soil moisture was higher for vegetated plots than non-vegetated plots. The presence of vegetation in general contributed to the spatial variability of soil moisture. Integration of geostatistics and GIS can improve the productivity of farm lands and the precision of farming.

Incorporating geologic information into hydraulic tomography: A general framework based on geostatistical approach

NASA Astrophysics Data System (ADS)

Zha, Yuanyuan; Yeh, Tian-Chyi J.; Illman, Walter A.; Onoe, Hironori; Mok, Chin Man W.; Wen, Jet-Chau; Huang, Shao-Yang; Wang, Wenke

2017-04-01

Hydraulic tomography (HT) has become a mature aquifer test technology over the last two decades. It collects nonredundant information of aquifer heterogeneity by sequentially stressing the aquifer at different wells and collecting aquifer responses at other wells during each stress. The collected information is then interpreted by inverse models. Among these models, the geostatistical approaches, built upon the Bayesian framework, first conceptualize hydraulic properties to be estimated as random fields, which are characterized by means and covariance functions. They then use the spatial statistics as prior information with the aquifer response data to estimate the spatial distribution of the hydraulic properties at a site. Since the spatial statistics describe the generic spatial structures of the geologic media at the site rather than site-specific ones (e.g., known spatial distributions of facies, faults, or paleochannels), the estimates are often not optimal. To improve the estimates, we introduce a general statistical framework, which allows the inclusion of site-specific spatial patterns of geologic features. Subsequently, we test this approach with synthetic numerical experiments. Results show that this approach, using conditional mean and covariance that reflect site-specific large-scale geologic features, indeed improves the HT estimates. Afterward, this approach is applied to HT surveys at a kilometer-scale-fractured granite field site with a distinct fault zone. We find that by including fault information from outcrops and boreholes for HT analysis, the estimated hydraulic properties are improved. The improved estimates subsequently lead to better prediction of flow during a different pumping test at the site.

Cost Sharing in Zambia's Public Universities: Prospects and Challenges

ERIC Educational Resources Information Center

Masaiti, Gift; Shen, Hong

2013-01-01

This research paper explores the concept of "cost sharing" which became more prominent in Zambia education with the advent of democratic form of governance in 1991. As a way of responding to the ever diminishing tax revenues, government through the education policy of 1996, allowed higher education institutions including public…

Enhancing global health and education in Malawi, Zambia, and the United States through an interprofessional global health exchange program.

PubMed

Wilson, Lynda Law; Somerall, D'Ann; Theus, Lisa; Rankin, Sally; Ngoma, Catherine; Chimwaza, Angela

2014-05-01

This article describes participant outcomes of an interprofessional collaboration between health professionals and faculty in Malawi, Zambia, and the United States (US). One strategy critical for improving global health and addressing Millennium Development goals is promotion of interprofessional education and collaboration. Program participants included 25 health professionals from Malawi and Zambia, and 19 faculty/health professionals from Alabama and California. African Fellows participated in a 2 week workshop on Interprofessional Education in Alabama followed by 2 weeks working on individual goals with faculty collaborators/mentors. The US Fellows also spent 2 weeks visiting their counterparts in Malawi and Zambia to develop plans for sustainable partnerships. Program evaluations demonstrated participants' satisfaction with the program and indicated that the program promoted interprofessional and cross-cultural understanding; fostered development of long-term sustainable partnerships between health professionals and educators in Zambia and the US; and created increased awareness and use of resources for global health education. © 2014.

Delineating Hydrofacies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics

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

Song, Xuehang; Chen, Xingyuan; Ye, Ming

2015-07-01

This study develops a new framework of facies-based data assimilation for characterizing spatial distribution of hydrofacies and estimating their associated hydraulic properties. This framework couples ensemble data assimilation with transition probability-based geostatistical model via a parameterization based on a level set function. The nature of ensemble data assimilation makes the framework efficient and flexible to be integrated with various types of observation data. The transition probability-based geostatistical model keeps the updated hydrofacies distributions under geological constrains. The framework is illustrated by using a two-dimensional synthetic study that estimates hydrofacies spatial distribution and permeability in each hydrofacies from transient head data.more » Our results show that the proposed framework can characterize hydrofacies distribution and associated permeability with adequate accuracy even with limited direct measurements of hydrofacies. Our study provides a promising starting point for hydrofacies delineation in complex real problems.« less

Lithostratigraphical correlation of the Neoproterozoic Roan Supergroup from Shaba (Zaire) and Zambia, in the central African copper-cobalt metallogenic province

NASA Astrophysics Data System (ADS)

Cailteux, J.; Binda, P. L.; Katekesha, W. M.; Kampunzu, A. B.; Intiomale, M. M.; Kapenda, D.; Kaunda, C.; Ngongo, K.; Tshiauka, T.; Wendorff, M.

1994-11-01

New data on the lower Katangan sequences in Shaba (Zaire) and Zambia, collected during the 1989 and 1990 UNESCO-sponsored Geotraverses, reveal an important development on friction breccias throughout the Zambian Copperbelt, which still remains poorly documented, and shows that the Zairean and Zambian facies of the Roan Supergroup can be correlated in detail. As in Zaire, the deformation of Katangan terranes during the Lufilian orogeny produced important friction breccias in Zambia. Such breccias occur mostly between the upper part of the Lower Roan Supergroup and the Mwashya Group (R-4): above the shale with grit (RL3) at Konkola and Mindola, or within the Upper Roan Dolomite at Chambishi South, Muliashi and Nchanga. At Mufulira, a typical fragment of Shaba Mines Group was observed within a major heterogeneous tectonic breccia. This situation is similar to that reported at Kipapila (Kimpe) and Lubembe in Zaire, both located on the same tectonic trend as Mufulira. However, a continuous stratigraphical succession can be observed in Zambia from the basal unconformity to the Mwashya Group. Strong lithological similarities were found, formation by formation, between the Roan sequences of Zambia and Zaire. In particular, the complete Mines Group of Zaire (R-2) and the units from the RL6 to the RL4 in Zambia were deposited under comparable conditions of sedimentation and show a similar and correlatable evolution of lithologies. Furthermore, the overlying Dipeta Group (R-3) of Zaire and the RL3, RU2/RU1 of Zambia, are equally comparable. Above the Upper Roan Dolomite, Lower Mwashya dolomitic rocks, identical with the ones of Shaba, have been noted to occur in Zambia in stratigraphical continuity with the typical black shales of the Upper Mwashya. The correlation between the coarse clastics of the Zambian footwall (RL7) and the red dolomitic argillites and sandstones of the Zairean R.A.T. (Roches Argillo Talqueuses: R-1) remains uncertain. However these two sequences show

Changes in sexual behaviour and practice and HIV prevalence indicators among young people aged 15–24 years in Zambia: An in-depth analysis of the 2001–2002 and 2007 Zambia Demographic and Health Surveys

PubMed Central

Kembo, Joshua

2014-01-01

HIV and AIDS still pose a major public health problem to most countries in sub-Saharan Africa, Zambia included. The objective of the paper is to determine changes in selected sexual behaviour and practice and HIV prevalence indicators between 2001–2002 and 2007. We used the Demographic and Health Survey Indicators Database for the computation of the selected indicators. We further used STATA 10.0 to compute significance tests to test for statistical difference in the indicators. The results indicate some changes in sexual behaviour, as indicated by an increase in abstinence, use of condoms and the decrease in multiple partnerships. The overall percentage of abstinence among never-married young men and women aged 15–24 years in Zambia increased significantly by 15.2% (p = .000) and 5.9% (p = .001) respectively, between 2001–2002 and 2007. A statistically significant increase of 6.6% (p = .029) was observed in the percentage of young women who reported having used a condom during the last time they had had premarital sex. A statistically significant decrease of 11.0% (p = .000) and 1.4% (p = .000) was observed among young men and women, respectively, who reported having multiple partners in the preceding 12 months. The factorial decomposition using multivariate analysis reveals that the indicators which contributed to the statistically significant 2.6% decline in HIV prevalence among young women aged 15–24 years in Zambia include proportion reporting condom use during premarital sex (+6.6%), abstinence (+5.9%), sex before age 15 (– 4.5%), premarital sex (– 2.6%), sex before age 18 (– 2.4%) and proportion reporting multiple partnerships (– 1.4%). Remarkable strides have been achieved towards promoting responsible sexual behaviour and practice among young people in Zambia. Further research focusing on factors that predispose young women in Zambia to higher risk of infection from HIV is required. The results from this paper should be useful in the design

Diagnosis and genotyping of African swine fever viruses from 2015 outbreaks in Zambia.

PubMed

Thoromo, Jonas; Simulundu, Edgar; Chambaro, Herman M; Mataa, Liywalii; Lubaba, Caesar H; Pandey, Girja S; Takada, Ayato; Misinzo, Gerald; Mweene, Aaron S

2016-04-29

In early 2015, a highly fatal haemorrhagic disease of domestic pigs resembling African swine fever (ASF) occurred in North Western, Copperbelt, and Lusaka provinces of Zambia. Molecular diagnosis by polymerase chain reaction targeting specific amplification of p72 (B646L) gene of ASF virus (ASFV) was conducted. Fourteen out of 16 domestic pigs from the affected provinces were found to be positive for ASFV. Phylogenetic analyses based on part of the p72 and the complete p54 (E183L) genes revealed that all the ASFVs detected belonged to genotypes I and Id, respectively. Additionally, epidemiological data suggest that the same ASFV spread from Lusaka to other provinces possibly through uncontrolled and/or illegal pig movements. Although the origin of the ASFV that caused outbreaks in domestic pigs in Zambia could not be ascertained, it appears likely that the virus may have emerged from within the country or region, probably from a sylvatic cycle. It is recommended that surveillance of ASF, strict biosecurity, and quarantine measures be imposed in order to prevent further spread and emergence of new ASF outbreaks in Zambia.

Provision of Learning and Teaching Materials for Pupils with Visual Impairment: Results from a National Survey in Zambia

ERIC Educational Resources Information Center

Akakandelwa, Akakandelwa; Munsanje, Joseph

2012-01-01

The aim of this study was to determine the provision of learning and teaching materials for pupils with visual impairment in basic and high schools of Zambia. A survey approach utilizing a questionnaire, interviews and a review of the literature was adopted for the study. The findings demonstrated that most schools in Zambia did not provide…

Adjusting for sampling variability in sparse data: geostatistical approaches to disease mapping

PubMed Central

2011-01-01

Background Disease maps of crude rates from routinely collected health data indexed at a small geographical resolution pose specific statistical problems due to the sparse nature of the data. Spatial smoothers allow areas to borrow strength from neighboring regions to produce a more stable estimate of the areal value. Geostatistical smoothers are able to quantify the uncertainty in smoothed rate estimates without a high computational burden. In this paper, we introduce a uniform model extension of Bayesian Maximum Entropy (UMBME) and compare its performance to that of Poisson kriging in measures of smoothing strength and estimation accuracy as applied to simulated data and the real data example of HIV infection in North Carolina. The aim is to produce more reliable maps of disease rates in small areas to improve identification of spatial trends at the local level. Results In all data environments, Poisson kriging exhibited greater smoothing strength than UMBME. With the simulated data where the true latent rate of infection was known, Poisson kriging resulted in greater estimation accuracy with data that displayed low spatial autocorrelation, while UMBME provided more accurate estimators with data that displayed higher spatial autocorrelation. With the HIV data, UMBME performed slightly better than Poisson kriging in cross-validatory predictive checks, with both models performing better than the observed data model with no smoothing. Conclusions Smoothing methods have different advantages depending upon both internal model assumptions that affect smoothing strength and external data environments, such as spatial correlation of the observed data. Further model comparisons in different data environments are required to provide public health practitioners with guidelines needed in choosing the most appropriate smoothing method for their particular health dataset. PMID:21978359

Adjusting for sampling variability in sparse data: geostatistical approaches to disease mapping.

PubMed

Hampton, Kristen H; Serre, Marc L; Gesink, Dionne C; Pilcher, Christopher D; Miller, William C

2011-10-06

Disease maps of crude rates from routinely collected health data indexed at a small geographical resolution pose specific statistical problems due to the sparse nature of the data. Spatial smoothers allow areas to borrow strength from neighboring regions to produce a more stable estimate of the areal value. Geostatistical smoothers are able to quantify the uncertainty in smoothed rate estimates without a high computational burden. In this paper, we introduce a uniform model extension of Bayesian Maximum Entropy (UMBME) and compare its performance to that of Poisson kriging in measures of smoothing strength and estimation accuracy as applied to simulated data and the real data example of HIV infection in North Carolina. The aim is to produce more reliable maps of disease rates in small areas to improve identification of spatial trends at the local level. In all data environments, Poisson kriging exhibited greater smoothing strength than UMBME. With the simulated data where the true latent rate of infection was known, Poisson kriging resulted in greater estimation accuracy with data that displayed low spatial autocorrelation, while UMBME provided more accurate estimators with data that displayed higher spatial autocorrelation. With the HIV data, UMBME performed slightly better than Poisson kriging in cross-validatory predictive checks, with both models performing better than the observed data model with no smoothing. Smoothing methods have different advantages depending upon both internal model assumptions that affect smoothing strength and external data environments, such as spatial correlation of the observed data. Further model comparisons in different data environments are required to provide public health practitioners with guidelines needed in choosing the most appropriate smoothing method for their particular health dataset.

A geostatistical approach to the change-of-support problem and variable-support data fusion in spatial analysis

NASA Astrophysics Data System (ADS)

Wang, Jun; Wang, Yang; Zeng, Hui

2016-01-01

A key issue to address in synthesizing spatial data with variable-support in spatial analysis and modeling is the change-of-support problem. We present an approach for solving the change-of-support and variable-support data fusion problems. This approach is based on geostatistical inverse modeling that explicitly accounts for differences in spatial support. The inverse model is applied here to produce both the best predictions of a target support and prediction uncertainties, based on one or more measurements, while honoring measurements. Spatial data covering large geographic areas often exhibit spatial nonstationarity and can lead to computational challenge due to the large data size. We developed a local-window geostatistical inverse modeling approach to accommodate these issues of spatial nonstationarity and alleviate computational burden. We conducted experiments using synthetic and real-world raster data. Synthetic data were generated and aggregated to multiple supports and downscaled back to the original support to analyze the accuracy of spatial predictions and the correctness of prediction uncertainties. Similar experiments were conducted for real-world raster data. Real-world data with variable-support were statistically fused to produce single-support predictions and associated uncertainties. The modeling results demonstrate that geostatistical inverse modeling can produce accurate predictions and associated prediction uncertainties. It is shown that the local-window geostatistical inverse modeling approach suggested offers a practical way to solve the well-known change-of-support problem and variable-support data fusion problem in spatial analysis and modeling.

Spatial analysis of groundwater levels using Fuzzy Logic and geostatistical tools

NASA Astrophysics Data System (ADS)

Theodoridou, P. G.; Varouchakis, E. A.; Karatzas, G. P.

2017-12-01

The spatial variability evaluation of the water table of an aquifer provides useful information in water resources management plans. Geostatistical methods are often employed to map the free surface of an aquifer. In geostatistical analysis using Kriging techniques the selection of the optimal variogram is very important for the optimal method performance. This work compares three different criteria to assess the theoretical variogram that fits to the experimental one: the Least Squares Sum method, the Akaike Information Criterion and the Cressie's Indicator. Moreover, variable distance metrics such as the Euclidean, Minkowski, Manhattan, Canberra and Bray-Curtis are applied to calculate the distance between the observation and the prediction points, that affects both the variogram calculation and the Kriging estimator. A Fuzzy Logic System is then applied to define the appropriate neighbors for each estimation point used in the Kriging algorithm. The two criteria used during the Fuzzy Logic process are the distance between observation and estimation points and the groundwater level value at each observation point. The proposed techniques are applied to a data set of 250 hydraulic head measurements distributed over an alluvial aquifer. The analysis showed that the Power-law variogram model and Manhattan distance metric within ordinary kriging provide the best results when the comprehensive geostatistical analysis process is applied. On the other hand, the Fuzzy Logic approach leads to a Gaussian variogram model and significantly improves the estimation performance. The two different variogram models can be explained in terms of a fractional Brownian motion approach and of aquifer behavior at local scale. Finally, maps of hydraulic head spatial variability and of predictions uncertainty are constructed for the area with the two different approaches comparing their advantages and drawbacks.

A geostatistical approach to estimate mining efficiency indicators with flexible meshes

NASA Astrophysics Data System (ADS)

Freixas, Genis; Garriga, David; Fernàndez-Garcia, Daniel; Sanchez-Vila, Xavier

2014-05-01

Geostatistics is a branch of statistics developed originally to predict probability distributions of ore grades for mining operations by considering the attributes of a geological formation at unknown locations as a set of correlated random variables. Mining exploitations typically aim to maintain acceptable mineral laws to produce commercial products based upon demand. In this context, we present a new geostatistical methodology to estimate strategic efficiency maps that incorporate hydraulic test data, the evolution of concentrations with time obtained from chemical analysis (packer tests and production wells) as well as hydraulic head variations. The methodology is applied to a salt basin in South America. The exploitation is based on the extraction of brines through vertical and horizontal wells. Thereafter, brines are precipitated in evaporation ponds to obtain target potassium and magnesium salts of economic interest. Lithium carbonate is obtained as a byproduct of the production of potassium chloride. Aside from providing an assemble of traditional geostatistical methods, the strength of this study falls with the new methodology developed, which focus on finding the best sites to exploit the brines while maintaining efficiency criteria. Thus, some strategic indicator efficiency maps have been developed under the specific criteria imposed by exploitation standards to incorporate new extraction wells in new areas that would allow maintain or improve production. Results show that the uncertainty quantification of the efficiency plays a dominant role and that the use flexible meshes, which properly describe the curvilinear features associated with vertical stratification, provides a more consistent estimation of the geological processes. Moreover, we demonstrate that the vertical correlation structure at the given salt basin is essentially linked to variations in the formation thickness, which calls for flexible meshes and non-stationarity stochastic processes.

Ethnoveterinary treatments for common cattle diseases in four districts of the Southern Province, Zambia

PubMed Central

Syakalima, Michelo; Simuunza, Martin; Zulu, Victor Chisha

2018-01-01

Aim: Ethno veterinary knowledge has rarely been recorded, and no or limited effort has been made to exploit this knowledge despite its widespread use in Zambia. This study documented the types of plants used to treat important animal diseases in rural Zambia as a way of initiating their sustained documentation and scientific validation. Materials and Methods: The study was done in selected districts of the Southern Zambia, Africa. The research was a participatory epidemiological study conducted in two phases. The first phase was a pre-study exploratory rapid rural appraisal conducted to familiarize the researchers with the study areas, and the second phase was a participatory rural appraisal to help gather the data. The frequency index was used to rank the commonly mentioned treatments. Results: A number of diseases and traditional treatments were listed with the help of local veterinarians. Diseases included: Corridor disease (Theileriosis), foot and mouth disease, blackleg, bloody diarrhea, lumpy skin disease, fainting, mange, blindness, coughing, bloat, worms, cobra snakebite, hemorrhagic septicemia, and transmissible venereal tumors. The plant preparations were in most diseases given to the livestock orally (as a drench). Leaves, barks, and roots were generally used depending on the plant type. Conclusion: Ethno veterinary medicine is still widespread among the rural farmers in the province and in Zambia in general. Some medicines are commonly used across diseases probably because they have a wide spectrum of action. These medicines should, therefore, be validated for use in conventional livestock healthcare systems in the country to reduce the cost of treatments. PMID:29657394

Quality of antenatal care in Zambia: a national assessment

PubMed Central

2012-01-01

Background Antenatal care (ANC) is one of the recommended interventions to reduce maternal and neonatal mortality. Yet in most Sub-Saharan African countries, high rates of ANC coverage coexist with high maternal and neonatal mortality. This disconnect has fueled calls to focus on the quality of ANC services. However, little conceptual or empirical work exists on the measurement of ANC quality at health facilities in low-income countries. We developed a classification tool and assessed the level of ANC service provision at health facilities in Zambia on a national scale and compared this to the quality of ANC received by expectant mothers. Methods We analysed two national datasets with detailed antenatal provider and user information, the 2005 Zambia Health Facility Census and the 2007 Zambia Demographic and Health Survey (DHS), to describe the level of ANC service provision at 1,299 antenatal facilities in 2005 and the quality of ANC received by 4,148 mothers between 2002 and 2007. Results We found that only 45 antenatal facilities (3%) fulfilled our developed criteria for optimum ANC service, while 47% of facilities provided adequate service, and the remaining 50% offered inadequate service. Although 94% of mothers reported at least one ANC visit with a skilled health worker and 60% attended at least four visits, only 29% of mothers received good quality ANC, and only 8% of mothers received good quality ANC and attended in the first trimester. Conclusions DHS data can be used to monitor “effective ANC coverage” which can be far below ANC coverage as estimated by current indicators. This “quality gap” indicates missed opportunities at ANC for delivering effective interventions. Evaluating the level of ANC provision at health facilities is an efficient way to detect where deficiencies are located in the system and could serve as a monitoring tool to evaluate country progress. PMID:23237601

Deschooling Language Study in East Africa: The Zambia Plan.

ERIC Educational Resources Information Center

Roberts, David Harrill

The second language learning methods of Southern Baptist missionaries in Zambia are described. Instead of studying the new language in a school setting, the student receives a week of orientation and is then placed in the community and expected to practice communicating with the native speakers at every opportunity. The student follows a course…

Geostatistics for spatial genetic structures: study of wild populations of perennial ryegrass.

PubMed

Monestiez, P; Goulard, M; Charmet, G

1994-04-01

Methods based on geostatistics were applied to quantitative traits of agricultural interest measured on a collection of 547 wild populations of perennial ryegrass in France. The mathematical background of these methods, which resembles spatial autocorrelation analysis, is briefly described. When a single variable is studied, the spatial structure analysis is similar to spatial autocorrelation analysis, and a spatial prediction method, called "kriging", gives a filtered map of the spatial pattern over all the sampled area. When complex interactions of agronomic traits with different evaluation sites define a multivariate structure for the spatial analysis, geostatistical methods allow the spatial variations to be broken down into two main spatial structures with ranges of 120 km and 300 km, respectively. The predicted maps that corresponded to each range were interpreted as a result of the isolation-by-distance model and as a consequence of selection by environmental factors. Practical collecting methodology for breeders may be derived from such spatial structures.

National-scale aboveground biomass geostatistical mapping with FIA inventory and GLAS data: Preparation for sparsely sampled lidar assisted forest inventory

NASA Astrophysics Data System (ADS)

Babcock, C. R.; Finley, A. O.; Andersen, H. E.; Moskal, L. M.; Morton, D. C.; Cook, B.; Nelson, R.

2017-12-01

Upcoming satellite lidar missions, such as GEDI and IceSat-2, are designed to collect laser altimetry data from space for narrow bands along orbital tracts. As a result lidar metric sets derived from these sources will not be of complete spatial coverage. This lack of complete coverage, or sparsity, means traditional regression approaches that consider lidar metrics as explanatory variables (without error) cannot be used to generate wall-to-wall maps of forest inventory variables. We implement a coregionalization framework to jointly model sparsely sampled lidar information and point-referenced forest variable measurements to create wall-to-wall maps with full probabilistic uncertainty quantification of all inputs. We inform the model with USFS Forest Inventory and Analysis (FIA) in-situ forest measurements and GLAS lidar data to spatially predict aboveground forest biomass (AGB) across the contiguous US. We cast our model within a Bayesian hierarchical framework to better model complex space-varying correlation structures among the lidar metrics and FIA data, which yields improved prediction and uncertainty assessment. To circumvent computational difficulties that arise when fitting complex geostatistical models to massive datasets, we use a Nearest Neighbor Gaussian process (NNGP) prior. Results indicate that a coregionalization modeling approach to leveraging sampled lidar data to improve AGB estimation is effective. Further, fitting the coregionalization model within a Bayesian mode of inference allows for AGB quantification across scales ranging from individual pixel estimates of AGB density to total AGB for the continental US with uncertainty. The coregionalization framework examined here is directly applicable to future spaceborne lidar acquisitions from GEDI and IceSat-2. Pairing these lidar sources with the extensive FIA forest monitoring plot network using a joint prediction framework, such as the coregionalization model explored here, offers the

Soil texture and organic carbon fractions predicted from near-infrared spectroscopy and geostatistics

USDA-ARS?s Scientific Manuscript database

Field-specific management could help achieve agricultural sustainability by increasing production and decreasing environmental impacts. Near-infrared spectroscopy (NIRS) and geostatistics are relatively unexplored tools that could reduce time, labor, and costs of soil analysis. Our objective was to ...

Moving Towards Inclusive Education Policies and Practices? Basic Education for AIDS Orphans and Other Vulnerable Children in Zambia

ERIC Educational Resources Information Center

Robson, Sue; Kanyanta, Sylvester Bonaventure

2007-01-01

The global spread of HIV and AIDS has presented a major threat to development, affecting the health of the poor and many aspects of social and economic development. The greatest impact of the epidemic has been felt in sub-Saharan Africa, and Zambia ranks among the worst hit countries. The Free Basic Education Policy in Zambia upholds the right of…

Disease constraints for utilization of the African buffalo (Syncerus caffer) on game ranches in Zambia.

PubMed

Munang'andu, Hetron M; Munag'andu, Hetron M; Siamudaala, Victor M; Nambota, Andrew; Bwalya, John M; Munyeme, Musso; Mweene, Aaron S; Takada, Ayato; Kida, Hiroshi

2006-05-01

Eco-tourism depending on wildlife is becoming increasingly profitable and landowners are beginning to favor game farming and ecotourism. In these areas, large-scale translocation of wildlife involves a diversity of species and large populations. The African buffalo (Syncerus caffer) is one of the major tourist attractions in Zambia. It accounts for 8.7% and 12.4% of the total animal species hunted in the Game Management Areas and the total hunting revenue earned in Zambia, respectively. It is ecologically an important animal species essential for the purpose of habitat control and facilitating the provision of suitable grazing pastures. However, the rearing of the African buffalo on game ranches has been hampered by its carrier state of the Southern Africa Terroritory (SAT) serotypes of foot and mouth disease virus (FMD). The African buffalo is also known to be a carrier of Theileria parva lawrencei, the causative agent of corridor disease (CD) that continues to have devastating effects on the livestock industry in Zambia. In addition, the importation of buffaloes from countries with populations endemic to bovine tuberculosis is highly restricted. Veterinary regulations in Zambia, strongly advocate against the translocation of buffaloes from protected areas to private ranches for disease control purposes thereby mounting a considerable constraint on the economic and ecological viability of the industry. It is hoped that this review will motivate the relevant government authorities in exploiting ways in which this animal species play a central role in eco-tourism.

Facilitators and barriers for HIV-testing in Zambia: A systematic review of multi-level factors.

PubMed

Qiao, Shan; Zhang, Yao; Li, Xiaoming; Menon, J Anitha

2018-01-01

It was estimated that 1.2 million people live with HIV/AIDS in Zambia by 2015. Zambia has developed and implemented diverse programs to reduce the prevalence in the country. HIV-testing is a critical step in HIV treatment and prevention, especially among all the key populations. However, there is no systematic review so far to demonstrate the trend of HIV-testing studies in Zambia since 1990s or synthesis the key factors that associated with HIV-testing practices in the country. Therefore, this study conducted a systematic review to search all English literature published prior to November 2016 in six electronic databases and retrieved 32 articles that meet our inclusion criteria. The results indicated that higher education was a common facilitator of HIV testing, while misconception of HIV testing and the fear of negative consequences were the major barriers for using the testing services. Other factors, such as demographic characteristics, marital dynamics, partner relationship, and relationship with the health care services, also greatly affects the participants' decision making. The findings indicated that 1) individualized strategies and comprehensive services are needed for diverse key population; 2) capacity building for healthcare providers is critical for effectively implementing the task-shifting strategy; 3) HIV testing services need to adapt to the social context of Zambia where HIV-related stigma and discrimination is still persistent and overwhelming; and 4) family-based education and intervention should involving improving gender equity.

Bayesian data analysis for newcomers.

PubMed

Kruschke, John K; Liddell, Torrin M

2018-02-01

This article explains the foundational concepts of Bayesian data analysis using virtually no mathematical notation. Bayesian ideas already match your intuitions from everyday reasoning and from traditional data analysis. Simple examples of Bayesian data analysis are presented that illustrate how the information delivered by a Bayesian analysis can be directly interpreted. Bayesian approaches to null-value assessment are discussed. The article clarifies misconceptions about Bayesian methods that newcomers might have acquired elsewhere. We discuss prior distributions and explain how they are not a liability but an important asset. We discuss the relation of Bayesian data analysis to Bayesian models of mind, and we briefly discuss what methodological problems Bayesian data analysis is not meant to solve. After you have read this article, you should have a clear sense of how Bayesian data analysis works and the sort of information it delivers, and why that information is so intuitive and useful for drawing conclusions from data.

A Qualitative Study of Migrant-related Stressors, Psychosocial Outcomes and HIV Risk Behavior among Truck Drivers in Zambia

PubMed Central

Ncube, Nomagugu; Simona, Simona J.; Kansankala, Brian; Sinkala, Emmanuel; Raidoo, Jasmin

2017-01-01

Truck drivers are part of mobile populations which have been noted as a key population at risk of HIV in Zambia. This study was aimed at 1) determining Potentially Traumatic Events (PTEs), labor migrant-related stressors, psychosocial problems and HIV risk behaviors among truck drivers in Zambia and 2) examining the relationship between PTEs, migrant-related stressors, psychosocial outcomes and HIV sexual risk behavior among truck drivers in Zambia. We conducted fifteen semi-structured interviews with purposively sampled male truck drivers at trucking companies in Lusaka, Zambia. Findings indicate that truck drivers experience multiple stressors and potentially traumatic incidences, including delays and long waiting hours at borders, exposure to crime and violence, poverty, stress related to resisting temptation of sexual interactions with sex workers or migrant women, and job-related safety concerns. Multiple psychosocial problems such as intimate partner violence, loneliness, anxiety and depression-like symptoms were noted. Transactional sex, coupled with inconsistent condom use were identified as HIV sexual risk behaviors. Findings suggest the critical need to develop HIV prevention interventions which account for mobility, potentially traumatic events, psychosocial problems, and the extreme fear of HIV testing among this key population. PMID:27681145

Clustering of Multivariate Geostatistical Data

NASA Astrophysics Data System (ADS)

Fouedjio, Francky

2017-04-01

Multivariate data indexed by geographical coordinates have become omnipresent in the geosciences and pose substantial analysis challenges. One of them is the grouping of data locations into spatially contiguous clusters so that data locations belonging to the same cluster have a certain degree of homogeneity while data locations in the different clusters have to be as different as possible. However, groups of data locations created through classical clustering techniques turn out to show poor spatial contiguity, a feature obviously inconvenient for many geoscience applications. In this work, we develop a clustering method that overcomes this problem by accounting the spatial dependence structure of data; thus reinforcing the spatial contiguity of resulting cluster. The capability of the proposed clustering method to provide spatially contiguous and meaningful clusters of data locations is assessed using both synthetic and real datasets. Keywords: clustering, geostatistics, spatial contiguity, spatial dependence.

Regional flow duration curves: Geostatistical techniques versus multivariate regression

USGS Publications Warehouse

Pugliese, Alessio; Farmer, William H.; Castellarin, Attilio; Archfield, Stacey A.; Vogel, Richard M.

2016-01-01

A period-of-record flow duration curve (FDC) represents the relationship between the magnitude and frequency of daily streamflows. Prediction of FDCs is of great importance for locations characterized by sparse or missing streamflow observations. We present a detailed comparison of two methods which are capable of predicting an FDC at ungauged basins: (1) an adaptation of the geostatistical method, Top-kriging, employing a linear weighted average of dimensionless empirical FDCs, standardised with a reference streamflow value; and (2) regional multiple linear regression of streamflow quantiles, perhaps the most common method for the prediction of FDCs at ungauged sites. In particular, Top-kriging relies on a metric for expressing the similarity between catchments computed as the negative deviation of the FDC from a reference streamflow value, which we termed total negative deviation (TND). Comparisons of these two methods are made in 182 largely unregulated river catchments in the southeastern U.S. using a three-fold cross-validation algorithm. Our results reveal that the two methods perform similarly throughout flow-regimes, with average Nash-Sutcliffe Efficiencies 0.566 and 0.662, (0.883 and 0.829 on log-transformed quantiles) for the geostatistical and the linear regression models, respectively. The differences between the reproduction of FDC's occurred mostly for low flows with exceedance probability (i.e. duration) above 0.98.

Bayesian Probability Theory

NASA Astrophysics Data System (ADS)

von der Linden, Wolfgang; Dose, Volker; von Toussaint, Udo

2014-06-01

Preface; Part I. Introduction: 1. The meaning of probability; 2. Basic definitions; 3. Bayesian inference; 4. Combinatrics; 5. Random walks; 6. Limit theorems; 7. Continuous distributions; 8. The central limit theorem; 9. Poisson processes and waiting times; Part II. Assigning Probabilities: 10. Transformation invariance; 11. Maximum entropy; 12. Qualified maximum entropy; 13. Global smoothness; Part III. Parameter Estimation: 14. Bayesian parameter estimation; 15. Frequentist parameter estimation; 16. The Cramer-Rao inequality; Part IV. Testing Hypotheses: 17. The Bayesian way; 18. The frequentist way; 19. Sampling distributions; 20. Bayesian vs frequentist hypothesis tests; Part V. Real World Applications: 21. Regression; 22. Inconsistent data; 23. Unrecognized signal contributions; 24. Change point problems; 25. Function estimation; 26. Integral equations; 27. Model selection; 28. Bayesian experimental design; Part VI. Probabilistic Numerical Techniques: 29. Numerical integration; 30. Monte Carlo methods; 31. Nested sampling; Appendixes; References; Index.

Geostatistical radar-raingauge combination with nonparametric correlograms: methodological considerations and application in Switzerland

NASA Astrophysics Data System (ADS)

Schiemann, R.; Erdin, R.; Willi, M.; Frei, C.; Berenguer, M.; Sempere-Torres, D.

2011-05-01

Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. Nonetheless, when combined with the sample variance of the spatial field under consideration, they yield an estimate of the semivariogram that is unbiased for small lag distances. This justifies the use of this estimation technique in geostatistical applications. Various formulations of geostatistical combination (Kriging) methods are used here for the construction of hourly precipitation grids for Switzerland based on data from a sparse realtime network of raingauges and from a spatially complete radar composite. Two variants of Ordinary Kriging (OK) are used to interpolate the sparse gauge observations. In both OK variants, the radar data are only used to determine the semivariogram model. One variant relies on a traditional parametric semivariogram estimate, whereas the other variant uses the nonparametric correlogram. The variants are tested for three cases and the impact of the semivariogram model on the Kriging prediction is illustrated. For the three test cases, the method using nonparametric correlograms performs equally well or better than the traditional method, and at the same time offers great practical advantages. Furthermore, two variants of Kriging with external drift (KED) are tested, both of which use the radar data to estimate nonparametric correlograms, and as the external drift variable. The first KED variant has been used previously for geostatistical radar-raingauge merging in Catalonia (Spain). The second variant is newly proposed here and is an extension of the first. Both variants are evaluated for the three test cases as well as an extended evaluation

Geostatistical radar-raingauge combination with nonparametric correlograms: methodological considerations and application in Switzerland

NASA Astrophysics Data System (ADS)

Schiemann, R.; Erdin, R.; Willi, M.; Frei, C.; Berenguer, M.; Sempere-Torres, D.

2010-09-01

Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. Nonetheless, when combined with the sample variance of the spatial field under consideration, they yield an estimate of the semivariogram that is unbiased for small lag distances. This justifies the use of this estimation technique in geostatistical applications. Various formulations of geostatistical combination (Kriging) methods are used here for the construction of hourly precipitation grids for Switzerland based on data from a sparse realtime network of raingauges and from a spatially complete radar composite. Two variants of Ordinary Kriging (OK) are used to interpolate the sparse gauge observations. In both OK variants, the radar data are only used to determine the semivariogram model. One variant relies on a traditional parametric semivariogram estimate, whereas the other variant uses the nonparametric correlogram. The variants are tested for three cases and the impact of the semivariogram model on the Kriging prediction is illustrated. For the three test cases, the method using nonparametric correlograms performs equally well or better than the traditional method, and at the same time offers great practical advantages. Furthermore, two variants of Kriging with external drift (KED) are tested, both of which use the radar data to estimate nonparametric correlograms, and as the external drift variable. The first KED variant has been used previously for geostatistical radar-raingauge merging in Catalonia (Spain). The second variant is newly proposed here and is an extension of the first. Both variants are evaluated for the three test cases as well as an extended evaluation

An Examination of Professionalism in the Zambia Army

DTIC Science & Technology

2014-12-12

corporateness . According to Huntington’s definition, professional officers should never intervene in politics, because officers would lose their...colonial Masters. Therefore, they depicted the African worker as powerless and devoid of self -awareness. This study seeks to put an officer in an African...the Zambia National Broadcasting Corporation radio station that he had taken over the reign of the country in a military coup. The coup was thwarted

Preliminary Investigation of Trypanosomosis in Exotic Dog Breeds from Zambia's Luangwa and Zambezi Valleys Using LAMP

PubMed Central

Namangala, Boniface; Oparaocha, Elizabeth; Kajino, Kiichi; Hayashida, Kyoko; Moonga, Ladslav; Inoue, Noboru; Suzuki, Yasuhiko; Sugimoto, Chihiro

2013-01-01

Canine African trypanosomosis (CAT) is rarely reported in the literature. In this preliminary study, we evaluated the performance of loop-mediated isothermal amplification (LAMP) against microscopy to detect CAT in six exotic dog breeds naturally infected with trypanosomes from Zambia's South Luangwa National Park and Chiawa Game Management Area. To our knowledge, this is the first report of CAT in Zambia. The patients exhibited a variety of aspecific clinical signs. The LAMP did not only confirm all six parasitologically positive CAT cases detected passively between April 2010 and January 2012, but was also critical in trypanosome speciation. According to LAMP, the majority of the dogs had monolytic infections with either Trypanosoma congolense or Trypanosoma brucei rhodesiense. The LAMP is thus a potential simple and cost-effective tool for trypanosome diagnosis in endemic regions. The rare report of zoonotic trypanosomes in dogs in Zambia has public health implications and justifies further investigations of CAT. PMID:23716412

Geostatistical simulations for radon indoor with a nested model including the housing factor.

PubMed

Cafaro, C; Giovani, C; Garavaglia, M

2016-01-01

The radon prone areas definition is matter of many researches in radioecology, since radon is considered a leading cause of lung tumours, therefore the authorities ask for support to develop an appropriate sanitary prevention strategy. In this paper, we use geostatistical tools to elaborate a definition accounting for some of the available information about the dwellings. Co-kriging is the proper interpolator used in geostatistics to refine the predictions by using external covariates. In advance, co-kriging is not guaranteed to improve significantly the results obtained by applying the common lognormal kriging. Here, instead, such multivariate approach leads to reduce the cross-validation residual variance to an extent which is deemed as satisfying. Furthermore, with the application of Monte Carlo simulations, the paradigm provides a more conservative radon prone areas definition than the one previously made by lognormal kriging. Copyright © 2015 Elsevier Ltd. All rights reserved.

An Integrated Hydro-Economic Model for Economy-Wide Climate Change Impact Assessment for Zambia

NASA Astrophysics Data System (ADS)

Zhu, T.; Thurlow, J.; Diao, X.

2008-12-01

Zambia is a landlocked country in Southern Africa, with a total population of about 11 million and a total area of about 752 thousand square kilometers. Agriculture in the country depends heavily on rainfall as the majority of cultivated land is rain-fed. Significant rainfall variability has been a huge challenge for the country to keep a sustainable agricultural growth, which is an important condition for the country to meet the United Nations Millennium Development Goals. The situation is expected to become even more complex as climate change would impose additional impacts on rainwater availability and crop water requirements, among other changes. To understand the impacts of climate variability and change on agricultural production and national economy, a soil hydrology model and a crop water production model are developed to simulate actual crop water uses and yield losses under water stress which provide annual shocks for a recursive dynamic computational general equilibrium (CGE) model developed for Zambia. Observed meteorological data of the past three decades are used in the integrated hydro-economic model for climate variability impact analysis, and as baseline climatology for climate change impact assessment together with several GCM-based climate change scenarios that cover a broad range of climate projections. We found that climate variability can explain a significant portion of the annual variations of agricultural production and GDP of Zambia in the past. Hidden beneath climate variability, climate change is found to have modest impacts on agriculture and national economy of Zambia around 2025 but the impacts would be pronounced in the far future if appropriate adaptations are not implemented. Policy recommendations are provided based on scenario analysis.

Elites, Incrementalism and Educational Policy-Making in Post-Independence Zambia.

ERIC Educational Resources Information Center

Lungu, Gatian F.

1985-01-01

Examines the role of elite groups in Zambia educational policymaking in the postindependence era, using three major attempts at educational reform as illustrations. Concludes that well-to-do groups have dominated educational policy decisions to preserve their own interests and have obtained gradual reforms in spite of offically declared radical…

Regression and Geostatistical Techniques: Considerations and Observations from Experiences in NE-FIA

Treesearch

Rachel Riemann; Andrew Lister

2005-01-01

Maps of forest variables improve our understanding of the forest resource by allowing us to view and analyze it spatially. The USDA Forest Service's Northeastern Forest Inventory and Analysis unit (NE-FIA) has used geostatistical techniques, particularly stochastic simulation, to produce maps and spatial data sets of FIA variables. That work underscores the...

Costs of facility-based HIV testing in Malawi, Zambia and Zimbabwe

PubMed Central

Mwenge, Lawrence; Sande, Linda; Mangenah, Collin; Ahmed, Nurilign; Kanema, Sarah; d’Elbée, Marc; Sibanda, Euphemia; Kalua, Thokozani; Ncube, Gertrude; Johnson, Cheryl C.; Hatzold, Karin; Cowan, Frances M.; Corbett, Elizabeth L.; Ayles, Helen; Maheswaran, Hendramoorthy

2017-01-01

Background Providing HIV testing at health facilities remains the most common approach to ensuring access to HIV treatment and prevention services for the millions of undiagnosed HIV-infected individuals in sub-Saharan Africa. We sought to explore the costs of providing these services across three southern African countries with high HIV burden. Methods Primary costing studies were undertaken in 54 health facilities providing HIV testing services (HTS) in Malawi, Zambia and Zimbabwe. Routinely collected monitoring and evaluation data for the health facilities were extracted to estimate the costs per individual tested and costs per HIV-positive individual identified. Costs are presented in 2016 US dollars. Sensitivity analysis explored key drivers of costs. Results Health facilities were testing on average 2290 individuals annually, albeit with wide variations. The mean cost per individual tested was US$5.03.9 in Malawi, US$4.24 in Zambia and US$8.79 in Zimbabwe. The mean cost per HIV-positive individual identified was US$79.58, US$73.63 and US$178.92 in Malawi, Zambia and Zimbabwe respectively. Both cost estimates were sensitive to scale of testing, facility staffing levels and the costs of HIV test kits. Conclusions Health facility based HIV testing remains an essential service to meet HIV universal access goals. The low costs and potential for economies of scale suggests an opportunity for further scale-up. However low uptake in many settings suggests that demand creation or alternative testing models may be needed to achieve economies of scale and reach populations less willing to attend facility based services. PMID:29036171

Provision and Management of Special Education in Community Schools: A Case of Donata, Malaikha and Shalom Community Schools in Zambia

ERIC Educational Resources Information Center

Mwamba, Mwenya N.

2016-01-01

Community schools appeared in Zambia in 1992 beginning with Lusaka and they quickly spread to other parts of the country. The Ministry of General Education recognizes its obligation to provide education of good quality to all children in response to national and international protocols to which Zambia is a part. The creation of Community Schools…

PCTO-SIM: Multiple-point geostatistical modeling using parallel conditional texture optimization

NASA Astrophysics Data System (ADS)

Pourfard, Mohammadreza; Abdollahifard, Mohammad J.; Faez, Karim; Motamedi, Sayed Ahmad; Hosseinian, Tahmineh

2017-05-01

Multiple-point Geostatistics is a well-known general statistical framework by which complex geological phenomena have been modeled efficiently. Pixel-based and patch-based are two major categories of these methods. In this paper, the optimization-based category is used which has a dual concept in texture synthesis as texture optimization. Our extended version of texture optimization uses the energy concept to model geological phenomena. While honoring the hard point, the minimization of our proposed cost function forces simulation grid pixels to be as similar as possible to training images. Our algorithm has a self-enrichment capability and creates a richer training database from a sparser one through mixing the information of all surrounding patches of the simulation nodes. Therefore, it preserves pattern continuity in both continuous and categorical variables very well. It also shows a fuzzy result in its every realization similar to the expected result of multi realizations of other statistical models. While the main core of most previous Multiple-point Geostatistics methods is sequential, the parallel main core of our algorithm enabled it to use GPU efficiently to reduce the CPU time. One new validation method for MPS has also been proposed in this paper.

Monte Carlo Analysis of Reservoir Models Using Seismic Data and Geostatistical Models

NASA Astrophysics Data System (ADS)

Zunino, A.; Mosegaard, K.; Lange, K.; Melnikova, Y.; Hansen, T. M.

2013-12-01

We present a study on the analysis of petroleum reservoir models consistent with seismic data and geostatistical constraints performed on a synthetic reservoir model. Our aim is to invert directly for structure and rock bulk properties of the target reservoir zone. To infer the rock facies, porosity and oil saturation seismology alone is not sufficient but a rock physics model must be taken into account, which links the unknown properties to the elastic parameters. We then combine a rock physics model with a simple convolutional approach for seismic waves to invert the "measured" seismograms. To solve this inverse problem, we employ a Markov chain Monte Carlo (MCMC) method, because it offers the possibility to handle non-linearity, complex and multi-step forward models and provides realistic estimates of uncertainties. However, for large data sets the MCMC method may be impractical because of a very high computational demand. To face this challenge one strategy is to feed the algorithm with realistic models, hence relying on proper prior information. To address this problem, we utilize an algorithm drawn from geostatistics to generate geologically plausible models which represent samples of the prior distribution. The geostatistical algorithm learns the multiple-point statistics from prototype models (in the form of training images), then generates thousands of different models which are accepted or rejected by a Metropolis sampler. To further reduce the computation time we parallelize the software and run it on multi-core machines. The solution of the inverse problem is then represented by a collection of reservoir models in terms of facies, porosity and oil saturation, which constitute samples of the posterior distribution. We are finally able to produce probability maps of the properties we are interested in by performing statistical analysis on the collection of solutions.

A Comparison of Traditional, Step-Path, and Geostatistical Techniques in the Stability Analysis of a Large Open Pit

NASA Astrophysics Data System (ADS)

Mayer, J. M.; Stead, D.

2017-04-01

With the increased drive towards deeper and more complex mine designs, geotechnical engineers are often forced to reconsider traditional deterministic design techniques in favour of probabilistic methods. These alternative techniques allow for the direct quantification of uncertainties within a risk and/or decision analysis framework. However, conventional probabilistic practices typically discretize geological materials into discrete, homogeneous domains, with attributes defined by spatially constant random variables, despite the fact that geological media display inherent heterogeneous spatial characteristics. This research directly simulates this phenomenon using a geostatistical approach, known as sequential Gaussian simulation. The method utilizes the variogram which imposes a degree of controlled spatial heterogeneity on the system. Simulations are constrained using data from the Ok Tedi mine site in Papua New Guinea and designed to randomly vary the geological strength index and uniaxial compressive strength using Monte Carlo techniques. Results suggest that conventional probabilistic techniques have a fundamental limitation compared to geostatistical approaches, as they fail to account for the spatial dependencies inherent to geotechnical datasets. This can result in erroneous model predictions, which are overly conservative when compared to the geostatistical results.

Geostatistics: a common link between medical geography, mathematical geology, and medical geology

PubMed Central

Goovaerts, P.

2015-01-01

Synopsis Since its development in the mining industry, geostatistics has emerged as the primary tool for spatial data analysis in various fields, ranging from earth and atmospheric sciences to agriculture, soil science, remote sensing, and more recently environmental exposure assessment. In the last few years, these tools have been tailored to the field of medical geography or spatial epidemiology, which is concerned with the study of spatial patterns of disease incidence and mortality and the identification of potential ‘causes’ of disease, such as environmental exposure, diet and unhealthy behaviours, economic or socio-demographic factors. On the other hand, medical geology is an emerging interdisciplinary scientific field studying the relationship between natural geological factors and their effects on human and animal health. This paper provides an introduction to the field of medical geology with an overview of geostatistical methods available for the analysis of geological and health data. Key concepts are illustrated using the mapping of groundwater arsenic concentration across eleven Michigan counties and the exploration of its relationship to the incidence of prostate cancer at the township level. PMID:25722963

Geostatistics: a common link between medical geography, mathematical geology, and medical geology.

PubMed

Goovaerts, P

2014-08-01

Since its development in the mining industry, geostatistics has emerged as the primary tool for spatial data analysis in various fields, ranging from earth and atmospheric sciences to agriculture, soil science, remote sensing, and more recently environmental exposure assessment. In the last few years, these tools have been tailored to the field of medical geography or spatial epidemiology, which is concerned with the study of spatial patterns of disease incidence and mortality and the identification of potential 'causes' of disease, such as environmental exposure, diet and unhealthy behaviours, economic or socio-demographic factors. On the other hand, medical geology is an emerging interdisciplinary scientific field studying the relationship between natural geological factors and their effects on human and animal health. This paper provides an introduction to the field of medical geology with an overview of geostatistical methods available for the analysis of geological and health data. Key concepts are illustrated using the mapping of groundwater arsenic concentration across eleven Michigan counties and the exploration of its relationship to the incidence of prostate cancer at the township level.

Liver fibrosis in treatment-naïve HIV-infected and HIV/HBV co-infected patients: Zambia and Switzerland compared.

PubMed

Wandeler, Gilles; Mulenga, Lloyd; Vinikoor, Michael J; Kovari, Helen; Battegay, Manuel; Calmy, Alexandra; Cavassini, Matthias; Bernasconi, Enos; Schmid, Patrick; Bolton-Moore, Carolyn; Sinkala, Edford; Chi, Benjamin H; Egger, Matthias; Rauch, Andri

2016-10-01

To examine the association between hepatitis B virus (HBV) infection and liver fibrosis in HIV-infected patients in Zambia and Switzerland. HIV-infected adults starting antiretroviral therapy in two clinics in Zambia and Switzerland were included. Liver fibrosis was evaluated using the aspartate aminotransferase-to-platelet-ratio index (APRI), with a ratio >1.5 defining significant fibrosis and a ratio >2.0 indicating cirrhosis. The association between hepatitis B surface antigen (HBsAg) positivity, HBV replication, and liver fibrosis was examined using logistic regression. In Zambia, 96 (13.0%) of 739 patients were HBsAg-positive compared to 93 (4.5%) of 2058 in Switzerland. HBsAg-positive patients were more likely to have significant liver fibrosis than HBsAg-negative ones: the adjusted odds ratio (aOR) was 3.25 (95% confidence interval (CI) 1.44-7.33) in Zambia and 2.50 (95% CI 1.19-5.25) in Switzerland. Patients with a high HBV viral load (≥20000 IU/ml) were more likely to have significant liver fibrosis compared to HBsAg-negative patients or patients with an undetectable viral load: aOR 3.85 (95% CI 1.29-11.44) in Zambia and 4.20 (95% CI 1.64-10.76) in Switzerland. In both settings, male sex was a strong risk factor for significant liver fibrosis. Despite the differences in HBV natural history between Sub-Saharan Africa and Europe, the degree of liver fibrosis and the association with important risk factors were similar. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

7 CFR 319.56-43 - Baby corn and baby carrots from Zambia.

Code of Federal Regulations, 2010 CFR

2010-01-01

... § 319.56-43 Baby corn and baby carrots from Zambia. (a) Immature, dehusked “baby” sweet corn (Zea mays L... consignments only. (b) Immature “baby” carrots (Daucus carota L. ssp. sativus) for consumption measuring 10 to...

Agriculture expansion, wood energy and woody encroachment in the Miombo woodlands: striving towards sustainability in Zambia.

NASA Astrophysics Data System (ADS)

Pelletier, J.

2017-12-01

Agricultural expansion is mostly done at the expense of forests and woodlands in the tropics. In Sub-Saharan Africa, forests are also critical as providers of wood energy for domestic consumption with a clear majority of households depending on firewood and charcoal as primary source of energy. Using Zambia as a case study, we look at the link between agricultural expansion, wood energy and the sustainability of forest resources. Zambia has been identified as having one of the highest rates of deforestation in the world, but there is large uncertainty in these estimates. The government of Zambia has identified charcoal production as one of the main of drivers of forest cover loss and is targeting this practice in their national strategy for reducing emissions from deforestation and forest degradation (REDD+). Other assessment however indicate that agricultural expansion is by far the main driver of deforestation and charcoal production is sustainable in Zambia. These competing evaluations call for a better understanding of the drivers of change. Using two national-scale vegetation surveys and remote sensing data, we compare and validate historical forest cover loss estimates to improve their accuracy. We attribute the change and their associated emissions to specific drivers of deforestation. The ecological properties of areas under change are compared to stable areas over time. Our results from national permanent plots indicate a woody encroachment process in Zambia, a potential ecological response to rising CO2 levels. We found that despite large emissions from deforestation, forests and woodlands have been acting as a carbon sink. This research addresses directly the potential feedbacks and responses to competing demands on forests coming from different sectors, including for agriculture and energy, to set the baseline on which to evaluate forest sustainability now and in the future given potentially new ecological conditions. It provides policy relevant

Can Geostatistical Models Represent Nature's Variability? An Analysis Using Flume Experiments

NASA Astrophysics Data System (ADS)

Scheidt, C.; Fernandes, A. M.; Paola, C.; Caers, J.

2015-12-01

The lack of understanding in the Earth's geological and physical processes governing sediment deposition render subsurface modeling subject to large uncertainty. Geostatistics is often used to model uncertainty because of its capability to stochastically generate spatially varying realizations of the subsurface. These methods can generate a range of realizations of a given pattern - but how representative are these of the full natural variability? And how can we identify the minimum set of images that represent this natural variability? Here we use this minimum set to define the geostatistical prior model: a set of training images that represent the range of patterns generated by autogenic variability in the sedimentary environment under study. The proper definition of the prior model is essential in capturing the variability of the depositional patterns. This work starts with a set of overhead images from an experimental basin that showed ongoing autogenic variability. We use the images to analyze the essential characteristics of this suite of patterns. In particular, our goal is to define a prior model (a minimal set of selected training images) such that geostatistical algorithms, when applied to this set, can reproduce the full measured variability. A necessary prerequisite is to define a measure of variability. In this study, we measure variability using a dissimilarity distance between the images. The distance indicates whether two snapshots contain similar depositional patterns. To reproduce the variability in the images, we apply an MPS algorithm to the set of selected snapshots of the sedimentary basin that serve as training images. The training images are chosen from among the initial set by using the distance measure to ensure that only dissimilar images are chosen. Preliminary investigations show that MPS can reproduce fairly accurately the natural variability of the experimental depositional system. Furthermore, the selected training images provide

Qualitative and quantitative comparison of geostatistical techniques of porosity prediction from the seismic and logging data: a case study from the Blackfoot Field, Alberta, Canada

NASA Astrophysics Data System (ADS)

Maurya, S. P.; Singh, K. H.; Singh, N. P.

2018-05-01

In present study, three recently developed geostatistical methods, single attribute analysis, multi-attribute analysis and probabilistic neural network algorithm have been used to predict porosity in inter well region for Blackfoot field, Alberta, Canada, an offshore oil field. These techniques make use of seismic attributes, generated by model based inversion and colored inversion techniques. The principle objective of the study is to find the suitable combination of seismic inversion and geostatistical techniques to predict porosity and identification of prospective zones in 3D seismic volume. The porosity estimated from these geostatistical approaches is corroborated with the well log porosity. The results suggest that all the three implemented geostatistical methods are efficient and reliable to predict the porosity but the multi-attribute and probabilistic neural network analysis provide more accurate and high resolution porosity sections. A low impedance (6000-8000 m/s g/cc) and high porosity (> 15%) zone is interpreted from inverted impedance and porosity sections respectively between 1060 and 1075 ms time interval and is characterized as reservoir. The qualitative and quantitative results demonstrate that of all the employed geostatistical methods, the probabilistic neural network along with model based inversion is the most efficient method for predicting porosity in inter well region.

Model Diagnostics for Bayesian Networks

ERIC Educational Resources Information Center

Sinharay, Sandip

2006-01-01

Bayesian networks are frequently used in educational assessments primarily for learning about students' knowledge and skills. There is a lack of works on assessing fit of Bayesian networks. This article employs the posterior predictive model checking method, a popular Bayesian model checking tool, to assess fit of simple Bayesian networks. A…

Is the Bangweulu Basin in Zambia the Eroded Remnant of a Large, Multiring Impact Crater?

NASA Astrophysics Data System (ADS)

Master, S.

1993-07-01

The Bangweulu Basin (BB) (ca. 29 degrees-31 degrees E, 10 degrees-12 degrees S) is a roughly circular depression, ~150 km in diameter, on the Bangweulu Block of Zambia. The basin, about 1148 m ASL, is occupied by Lakes Bangweulu (~85 km long) and Kampolombo (~20 km long) and the Bangweulu Swamps [1,2]. The basement consists partly of granitoids (~1.8 Ga) together with ~1.1-Ga Katangan cover rocks. To the north, cover rocks of the Mporokoso Group (~1.8-1.3 Ga) form the arcuate Luongo Fold Belt [3], partly defining the perimeter of the outermost ring (R = 125 km) of the Bangweulu structure. Drainage into the BB is centripetal, with one outlet in the south, draining into a tributary of the Luapula River, which then curves in a broad arc toward the north, along the Zambia-Zaire border, before entering Lake Mweru. Rivers entering the BB include the Luansenshi, which rises in the north and flows in an arc to the southeast and south before joining the Chambeshi River, which flows southwest, west, and northwest before entering Lake Bangweulu. There is an arcuate watershed in the west (at R = 100 km), to the west of which rivers drain to the southwest and west into the Luapula River. Several elongate curved sliver-like islands, including Mbawala (~30 x 4 km) and Chisi, are present in Lake Bangweulu. The curvature of the islands follows the arcuate northwest boundary of the lake in a concentric manner. Unlike all the other major lakes in Zambia and surrounding areas (Mweru, Tanganyika, Rukwa, Malawi, and Kariba), which occupy seismically active rift structures [4,5], the Bangweulu Basin is generally aseismic, and is unrelated to rifting. There is a positive aeromagnetic intensity anomaly over the central Bangweulu depression, and there is also a magnetic anomaly density high over the central part of the BB, surrounded by a concentric low [6]. A roughly circular anomaly, outlined by the -140 mgal contour, of the regional Bouguer gravity field is centerd on Lake Bangweulu

The Catholic School in Zambia 1964-2014: Catholic and Catholic?

ERIC Educational Resources Information Center

Carmody, Brendan

2015-01-01

This article sketches the history of the Catholic school in Zambia over a 50-year period noting how for reasons of political acceptability it increasingly became less at home with its religious mission thereby finding itself with an unclear sense of purpose. In order to redeem its identity, this article argues that there is need for the school to…

Aflatoxin contamination of groundnut and maize in Zambia: observed and potential concentrations

USDA-ARS?s Scientific Manuscript database

Maize and groundnut, important staples in Zambia, are susceptible to aflatoxin-producing fungi. Aflatoxins are potent human carcinogens also associated with stunting and immunosuppression. Although health and economic burdens of aflatoxins are well known, patterns of contamination in maize and grou...

Investment Incentives and the Implementation of the Framework Convention on Tobacco Control: Evidence from Zambia

PubMed Central

Drope, Jeffrey; Labonte, Ronald; Zulu, Richard; Goma, Fastone

2016-01-01

Purpose Policy misalignment across different sectors of government serves as one of the pivotal barriers to WHO Framework convention on Tobacco Control (FCTC) implementation. This paper examines the logic used by government officials to justify providing investment incentives to increase tobacco processing and manufacturing in the context of FCTC implementation in Zambia. Methods We conducted qualitative semi-structured interviews with key informants from government, civil society and intergovernmental economic organizations (n=23). We supplemented the interview data with an analysis of public documents pertaining to economic development policy in Zambia. Results We found gross misalignments between the policies of the economic sector and efforts to implement the provisions of the FCTC. Our interviews uncovered the rationale used by officials in the economic sector to justify providing economic incentives to bolster tobacco processing and manufacturing in Zambia: 1) tobacco is not consumed by Zambians/tobacco is an export commodity, 2) economic benefits outweigh health costs, and 3) tobacco consumption is a personal choice. Conclusions Much of the struggle Zambia has experienced implementing the FCTC can be attributed to misalignments between the economic and health sectors. Zambia’s development agenda seeks to bolster agricultural processing and manufacturing. Tobacco control proponents must understand and work within this context of economic development in order to foster productive strategies with those working on tobacco supply issues. These findings are broadly applicable to the global analysis on the barriers and facilitators of FCTC implementation. It is important that the Ministry of Health monitors the tobacco policy of other sectors and engages with these sectors to find ways of harmonizing FCTC implementation across sectors. PMID:26135987

Outbreak of Plague in a High Malaria Endemic Region - Nyimba District, Zambia, March-May 2015.

PubMed

Sinyange, Nyambe; Kumar, Ramya; Inambao, Akatama; Moonde, Loveness; Chama, Jonathan; Banda, Mapopa; Tembo, Elliot; Nsonga, Beron; Mwaba, John; Fwoloshi, Sombo; Musokotwane, Kebby; Chizema, Elizabeth; Kapin'a, Muzala; Hang'ombe, Benard Mudenda; Baggett, Henry C; Hachaambwa, Lottie

2016-08-12

Outbreaks of plague have been recognized in Zambia since 1917 (1). On April 10, 2015, Zambia's Ministry of Health was notified by the Eastern Provincial Medical Office of possible bubonic plague cases in Nyimba District. Eleven patients with acute fever and cervical lymphadenopathy had been evaluated at two rural health centers during March 28-April 9, 2015; three patients died. To confirm the outbreak and develop control measures, the Zambia Ministry of Health's Field Epidemiology Training Program (ZFETP) conducted epidemiologic and laboratory investigations in partnership with the University of Zambia's schools of Medicine and Veterinary Medicine and the provincial and district medical offices. Twenty-one patients with clinically compatible plague were identified, with symptom onset during March 26-May 5, 2015. The median age was 8 years, and all patients were from the same village. Blood specimens or lymph node aspirates from six (29%) patients tested positive for Yersinia pestis by polymerase chain reaction (PCR). There is an urgent need to improve early identification and treatment of plague cases. PCR is a potential complementary tool for identifying plague, especially in areas with limited microbiologic capacity. Twelve (57%) patients, including all six with PCR-positive plague and all three who died, also tested positive for malaria by rapid diagnostic test (RDT). Plague patients coinfected with malaria might be misdiagnosed as solely having malaria, and appropriate antibacterial treatment to combat plague might not be given, increasing risk for mortality. Because patients with malaria might be coinfected with other pathogens, broad spectrum antibiotic treatment to cover other pathogens is recommended for all children with severe malaria, until a bacterial infection is excluded.

Distance to Care, Facility Delivery and Early Neonatal Mortality in Malawi and Zambia

PubMed Central

Lohela, Terhi J.; Campbell, Oona M. R.; Gabrysch, Sabine

2012-01-01

Background Globally, approximately 3 million babies die annually within their first month. Access to adequate care at birth is needed to reduce newborn as well as maternal deaths. We explore the influence of distance to delivery care and of level of care on early neonatal mortality in rural Zambia and Malawi, the influence of distance (and level of care) on facility delivery, and the influence of facility delivery on early neonatal mortality. Methods and Findings National Health Facility Censuses were used to classify the level of obstetric care for 1131 Zambian and 446 Malawian delivery facilities. Straight-line distances to facilities were calculated for 3771 newborns in the 2007 Zambia DHS and 8842 newborns in the 2004 Malawi DHS. There was no association between distance to care and early neonatal mortality in Malawi (OR 0.97, 95%CI 0.58–1.60), while in Zambia, further distance (per 10 km) was associated with lower mortality (OR 0.55, 95%CI 0.35–0.87). The level of care provided in the closest facility showed no association with early neonatal mortality in either Malawi (OR 1.02, 95%CI 0.90–1.16) or Zambia (OR 1.02, 95%CI 0.82–1.26). In both countries, distance to care was strongly associated with facility use for delivery (Malawi: OR 0.35 per 10km, 95%CI 0.26–0.46). All results are adjusted for available confounders. Early neonatal mortality did not differ by frequency of facility delivery in the community. Conclusions While better geographic access and higher level of care were associated with more frequent facility delivery, there was no association with lower early neonatal mortality. This could be due to low quality of care for newborns at health facilities, but differential underreporting of early neonatal deaths in the DHS is an alternative explanation. Improved data sources are needed to monitor progress in the provision of obstetric and newborn care and its impact on mortality. PMID:23300599

Performance prediction using geostatistics and window reservoir simulation

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

Fontanilla, J.P.; Al-Khalawi, A.A.; Johnson, S.G.

1995-11-01

This paper is the first window model study in the northern area of a large carbonate reservoir in Saudi Arabia. It describes window reservoir simulation with geostatistics to model uneven water encroachment in the southwest producing area of the northern portion of the reservoir. In addition, this paper describes performance predictions that investigate the sweep efficiency of the current peripheral waterflood. A 50 x 50 x 549 (240 m. x 260 m. x 0.15 m. average grid block size) geological model was constructed with geostatistics software. Conditional simulation was used to obtain spatial distributions of porosity and volume of dolomite.more » Core data transforms were used to obtain horizontal and vertical permeability distributions. Simple averaging techniques were used to convert the 549-layer geological model to a 50 x 50 x 10 (240 m. x 260 m. x 8 m. average grid block size) window reservoir simulation model. Flux injectors and flux producers were assigned to the outermost grid blocks. Historical boundary flux rates were obtained from a coarsely-ridded full-field model. Pressure distribution, water cuts, GORs, and recent flowmeter data were history matched. Permeability correction factors and numerous parameter adjustments were required to obtain the final history match. The permeability correction factors were based on pressure transient permeability-thickness analyses. The prediction phase of the study evaluated the effects of infill drilling, the use of artificial lifts, workovers, horizontal wells, producing rate constraints, and tight zone development to formulate depletion strategies for the development of this area. The window model will also be used to investigate day-to-day reservoir management problems in this area.« less

The development and evaluation of content validity of the Zambia Spina Bifida Functional Measure: Preliminary studies

PubMed Central

Amosun, Seyi L.; Shilalukey-Ngoma, Mary P.; Kafaar, Zuhayr

2017-01-01

Background Very little is known on outcome measures for children with spina bifida (SB) in Zambia. If rehabilitation professionals managing children with SB in Zambia and other parts of sub-Saharan Africa are to instigate measuring outcomes routinely, a tool has to be made available. The main objective of this study was to develop an appropriate and culturally sensitive instrument for evaluating the impact of the interventions on children with SB in Zambia. Methods A mixed design method was used for the study. Domains were identified retrospectively and confirmation was done through a systematic review study. Items were generated through semi-structured interviews and focus group discussions. Qualitative data were downloaded, translated into English, transcribed verbatim and presented. These were then placed into categories of the main domains of care deductively through the process of manifest content analysis. Descriptive statistics, alpha coefficient and index of content validity were calculated using SPSS. Results Self-care, mobility and social function were identified as main domains, while participation and communication were sub-domains. A total of 100 statements were generated and 78 items were selected deductively. An alpha coefficient of 0.98 was computed and experts judged the items. Conclusions The new functional measure with an acceptable level of content validity titled Zambia Spina Bifida Functional Measure (ZSBFM) was developed. It was designed to evaluate effectiveness of interventions given to children with SB from the age of 6 months to 5 years. Psychometric properties of reliability and construct validity were tested and are reported in another study. PMID:28951850

e-Government for Development Information Exchange (DIE): Zambia

NASA Astrophysics Data System (ADS)

Joseph, Bwalya Kelvin

In most parts of the world, political systems which utilize authoritative rule and mostly employ top-down decision-making processes are slowly transcending towards democratic norms. Information Technology Systems have been identified and adopted as one of the most efficient vehicles for appropriate, transparent and inclusive / participatory decision making. Zambia has shown a higher propensity to indigenous knowledge systems which are full of inefficiencies, a lot of red tape in public service delivery, and prone to corrupt practices. Despite that being the case, it is slowly trying to implement e-government. The adoption of e-government promises a sharp paradigm shift where public institutions will be more responsive and transparent, promote efficient PPP (Public Private Partnerships), and empower citizens by making knowledge and other resources more directly accessible. This paper examines three cases from Zambia where ICT in support of e-government has been implemented for Development Information Exchange (DIE) - knowledge-based decision making. The paper also assesses the challenges, opportunities, and issues together with e-government adoption criteria regarding successful encapsulation of e-government into the Zambian contextual environment. I propose a conceptual model which offers balanced e-government adoption criteria involving a combination of electronic and participatory services. This conceptual e-government adoption model can later be replicated to be used at the Southern African Development Community (SADC) level given the similarity in the contextual environment.

Tobacco Use and Secondhand Smoke Exposure During Pregnancy in Two African Countries: Zambia and the Democratic Republic of the Congo

PubMed Central

Chomba, Elwyn; Tshefu, Antoinette; Onyamboko, Marie; Kaseba - Sata, Christine; Moore, Janet; McClure, Elizabeth M; Moss, Nancy; Goco, Norman; Bloch, Michele; Goldenberg, Robert L

2013-01-01

Objective To study pregnant women’s knowledge, attitudes and behaviors towards tobacco use and secondhand smoke (SHS) exposure, and exposure to advertising for and against tobacco products in Zambia and the Democratic Republic of the Congo (DRC). Design Prospective cross-sectional survey between November 2004 and September 2005. Setting Antenatal care clinics in Lusaka, Zambia and Kinshasa, DRC. Population Pregnant women in Zambia (909) and the DRC (847). Methods Research staff administered a structured questionnaire to pregnant women attending antenatal care clinics. Main Outcome Measures Pregnant women’s use of tobacco, exposure to SHS, knowledge of the harms of tobacco, and exposure to advertising for and against tobacco products. Results Only about 10% of pregnant women reported having ever tried cigarettes (6.6% Zambia; 14.1% DRC). However, in the DRC, 41.8% of pregnant women had ever tried other forms of tobacco, primarily snuff. About 10% of pregnant women and young children were frequently or always exposed to SHS. Pregnant women’s knowledge of the hazards of smoking and SHS exposure was extremely limited. About 13% of pregnant women had seen or heard advertising for tobacco products in the last 30 days. Conclusions Tobacco use and SHS exposure pose serious threats to the health of women, infants, and children. In many African countries, maternal and infant health outcomes are often poor and will likely worsen if maternal tobacco use increases. Our findings suggest that a “window of opportunity” exists to prevent increased tobacco use and SHS exposure of pregnant women in Zambia and the DRC. PMID:20230310

Diabetes mellitus, hypertension and albuminuria in rural Zambia: a hospital-based survey.

PubMed

Rasmussen, Jon B; Thomsen, Jakúp A; Rossing, Peter; Parkinson, Shelagh; Christensen, Dirk L; Bygbjerg, Ib C

2013-09-01

To assess albuminuria in rural Zambia among patients with diabetes mellitus only (DM group), hypertension only (HTN group) and patients with combined DM and HTN (DM/HTN group). A cross-sectional survey was conducted at St. Francis Hospital in the Eastern province of Zambia. Albumin-creatinine ratio in one urine sample was used to assess albuminuria. Other information obtained included age, sex, body mass index (BMI), waist circumference (WC), blood pressure (BP), glycosylated haemoglobin (HbA1c ), random capillary glucose, time since diagnosis, medication and family history of DM or HTN. A total of 193 participants were included (DM group: n = 33; HTN group: n = 92; DM/HTN group: n = 68). The participants in the DM group used insulin more frequently as diabetes medication than the DM/HTN group (P < 0.05). Furthermore, the DM group was younger and had lower BMI, WC and BP than the two other groups. In the DM group, HTN group and DM/HTN group, microalbuminuria was found in 12.1%, 19.6% and 29.4% (P = 0.11), and macroalbuminuria was found in 0.0%, 3.3% and 13.2% (P = 0.014), respectively. The urine albumin (P = 0.014) and albumin-creatinine ratio (P = 0.0006) differed between the three groups. This hospital-based survey in rural Zambia found a lower frequency of albuminuria among the participants than in previous studies of patients with DM or HTN in urban sub-Saharan Africa. © 2013 John Wiley & Sons Ltd.

Robust geostatistical analysis of spatial data

NASA Astrophysics Data System (ADS)

Papritz, Andreas; Künsch, Hans Rudolf; Schwierz, Cornelia; Stahel, Werner A.

2013-04-01

Most of the geostatistical software tools rely on non-robust algorithms. This is unfortunate, because outlying observations are rather the rule than the exception, in particular in environmental data sets. Outliers affect the modelling of the large-scale spatial trend, the estimation of the spatial dependence of the residual variation and the predictions by kriging. Identifying outliers manually is cumbersome and requires expertise because one needs parameter estimates to decide which observation is a potential outlier. Moreover, inference after the rejection of some observations is problematic. A better approach is to use robust algorithms that prevent automatically that outlying observations have undue influence. Former studies on robust geostatistics focused on robust estimation of the sample variogram and ordinary kriging without external drift. Furthermore, Richardson and Welsh (1995) proposed a robustified version of (restricted) maximum likelihood ([RE]ML) estimation for the variance components of a linear mixed model, which was later used by Marchant and Lark (2007) for robust REML estimation of the variogram. We propose here a novel method for robust REML estimation of the variogram of a Gaussian random field that is possibly contaminated by independent errors from a long-tailed distribution. It is based on robustification of estimating equations for the Gaussian REML estimation (Welsh and Richardson, 1997). Besides robust estimates of the parameters of the external drift and of the variogram, the method also provides standard errors for the estimated parameters, robustified kriging predictions at both sampled and non-sampled locations and kriging variances. Apart from presenting our modelling framework, we shall present selected simulation results by which we explored the properties of the new method. This will be complemented by an analysis a data set on heavy metal contamination of the soil in the vicinity of a metal smelter. Marchant, B.P. and Lark, R

Robust geostatistical analysis of spatial data

NASA Astrophysics Data System (ADS)

Papritz, A.; Künsch, H. R.; Schwierz, C.; Stahel, W. A.

2012-04-01

Most of the geostatistical software tools rely on non-robust algorithms. This is unfortunate, because outlying observations are rather the rule than the exception, in particular in environmental data sets. Outlying observations may results from errors (e.g. in data transcription) or from local perturbations in the processes that are responsible for a given pattern of spatial variation. As an example, the spatial distribution of some trace metal in the soils of a region may be distorted by emissions of local anthropogenic sources. Outliers affect the modelling of the large-scale spatial variation, the so-called external drift or trend, the estimation of the spatial dependence of the residual variation and the predictions by kriging. Identifying outliers manually is cumbersome and requires expertise because one needs parameter estimates to decide which observation is a potential outlier. Moreover, inference after the rejection of some observations is problematic. A better approach is to use robust algorithms that prevent automatically that outlying observations have undue influence. Former studies on robust geostatistics focused on robust estimation of the sample variogram and ordinary kriging without external drift. Furthermore, Richardson and Welsh (1995) [2] proposed a robustified version of (restricted) maximum likelihood ([RE]ML) estimation for the variance components of a linear mixed model, which was later used by Marchant and Lark (2007) [1] for robust REML estimation of the variogram. We propose here a novel method for robust REML estimation of the variogram of a Gaussian random field that is possibly contaminated by independent errors from a long-tailed distribution. It is based on robustification of estimating equations for the Gaussian REML estimation. Besides robust estimates of the parameters of the external drift and of the variogram, the method also provides standard errors for the estimated parameters, robustified kriging predictions at both sampled

Geostatistical Prediction of Microbial Water Quality Throughout a Stream Network Using Meteorology, Land Cover, and Spatiotemporal Autocorrelation.

PubMed

Holcomb, David A; Messier, Kyle P; Serre, Marc L; Rowny, Jakob G; Stewart, Jill R

2018-06-25

Predictive modeling is promising as an inexpensive tool to assess water quality. We developed geostatistical predictive models of microbial water quality that empirically modeled spatiotemporal autocorrelation in measured fecal coliform (FC) bacteria concentrations to improve prediction. We compared five geostatistical models featuring different autocorrelation structures, fit to 676 observations from 19 locations in North Carolina's Jordan Lake watershed using meteorological and land cover predictor variables. Though stream distance metrics (with and without flow-weighting) failed to improve prediction over the Euclidean distance metric, incorporating temporal autocorrelation substantially improved prediction over the space-only models. We predicted FC throughout the stream network daily for one year, designating locations "impaired", "unimpaired", or "unassessed" if the probability of exceeding the state standard was ≥90%, ≤10%, or >10% but <90%, respectively. We could assign impairment status to more of the stream network on days any FC were measured, suggesting frequent sample-based monitoring remains necessary, though implementing spatiotemporal predictive models may reduce the number of concurrent sampling locations required to adequately assess water quality. Together, these results suggest that prioritizing sampling at different times and conditions using geographically sparse monitoring networks is adequate to build robust and informative geostatistical models of water quality impairment.

Geostatistical Analysis of Mesoscale Spatial Variability and Error in SeaWiFS and MODIS/Aqua Global Ocean Color Data

NASA Astrophysics Data System (ADS)

Glover, David M.; Doney, Scott C.; Oestreich, William K.; Tullo, Alisdair W.

2018-01-01

Mesoscale (10-300 km, weeks to months) physical variability strongly modulates the structure and dynamics of planktonic marine ecosystems via both turbulent advection and environmental impacts upon biological rates. Using structure function analysis (geostatistics), we quantify the mesoscale biological signals within global 13 year SeaWiFS (1998-2010) and 8 year MODIS/Aqua (2003-2010) chlorophyll a ocean color data (Level-3, 9 km resolution). We present geographical distributions, seasonality, and interannual variability of key geostatistical parameters: unresolved variability or noise, resolved variability, and spatial range. Resolved variability is nearly identical for both instruments, indicating that geostatistical techniques isolate a robust measure of biophysical mesoscale variability largely independent of measurement platform. In contrast, unresolved variability in MODIS/Aqua is substantially lower than in SeaWiFS, especially in oligotrophic waters where previous analysis identified a problem for the SeaWiFS instrument likely due to sensor noise characteristics. Both records exhibit a statistically significant relationship between resolved mesoscale variability and the low-pass filtered chlorophyll field horizontal gradient magnitude, consistent with physical stirring acting on large-scale gradient as an important factor supporting observed mesoscale variability. Comparable horizontal length scales for variability are found from tracer-based scaling arguments and geostatistical decorrelation. Regional variations between these length scales may reflect scale dependence of biological mechanisms that also create variability directly at the mesoscale, for example, enhanced net phytoplankton growth in coastal and frontal upwelling and convective mixing regions. Global estimates of mesoscale biophysical variability provide an improved basis for evaluating higher resolution, coupled ecosystem-ocean general circulation models, and data assimilation.

Insecticide resistance and role in malaria transmission of Anopheles funestus populations from Zambia and Zimbabwe.

PubMed

Choi, Kwang S; Christian, Riann; Nardini, Luisa; Wood, Oliver R; Agubuzo, Eunice; Muleba, Mbanga; Munyati, Shungu; Makuwaza, Aramu; Koekemoer, Lizette L; Brooke, Basil D; Hunt, Richard H; Coetzee, Maureen

2014-10-08

Two mitochondrial DNA clades have been described in Anopheles funestus populations from southern Africa. Clade I is common across the continent while clade II is known only from Mozambique and Madagascar. The specific biological status of these clades is at present unknown. We investigated the possible role that each clade might play in the transmission of Plasmodium falciparum and the insecticide resistance status of An. funestus from Zimbabwe and Zambia. Mosquitoes were collected inside houses from Nchelenge District, Zambia and Honde Valley, Zimbabwe in 2013 and 2014. WHO susceptibility tests, synergist assays and resistance intensity tests were conducted on wild females and progeny of wild females. ELISA was used to detect Plasmodium falciparum circumsporozoite protein. Specimens were identified to species and mtDNA clades using standard molecular methods. The Zimbabwean samples were all clade I while the Zambian population comprised 80% clade I and 20% clade II in both years of collection. ELISA tests gave an overall infection rate of 2.3% and 2.1% in 2013, and 3.5% and 9.2% in 2014 for Zimbabwe and Zambia respectively. No significant difference was observed between the clades. All populations were resistant to pyrethroids and carbamates but susceptible to organochlorines and organophosphates. Synergist assays indicated that pyrethroid resistance is mediated by cytochrome P450 mono-oxygenases. Resistance intensity tests showed high survival rates after 8-hrs continuous exposure to pyrethroids but exposure to bendiocarb gave the same results as the susceptible control. This is the first record of An. funestus mtDNA clade II occurring in Zambia. No evidence was found to suggest that the clades are markers of biologically separate populations. The ability of An. funestus to withstand prolonged exposure to pyrethroids has serious implications for the use of these insecticides, either through LLINs or IRS, in southern Africa in general and resistance management

Provisioning of Game Meat to Rural Communities as a Benefit of Sport Hunting in Zambia

PubMed Central

White, Paula A.; Belant, Jerrold L.

2015-01-01

Sport hunting has reportedly multiple benefits to economies and local communities; however, few of these benefits have been quantified. As part of their lease agreements with the Zambia Wildlife Authority, sport hunting operators in Zambia are required to provide annually to local communities free of charge i.e., provision a percentage of the meat obtained through sport hunting. We characterized provisioning of game meat to rural communities by the sport hunting industry in Zambia for three game management areas (GMAs) during 2004–2011. Rural communities located within GMAs where sport hunting occurred received on average > 6,000 kgs per GMA of fresh game meat annually from hunting operators. To assess hunting industry compliance, we also compared the amount of meat expected as per the lease agreements versus observed amounts of meat provisioned from three GMAs during 2007–2009. In seven of eight annual comparisons of these GMAs, provisioning of meat exceeded what was required in the lease agreements. Provisioning occurred throughout the hunting season and peaked during the end of the dry season (September–October) coincident with when rural Zambians are most likely to encounter food shortages. We extrapolated our results across all GMAs and estimated 129,771 kgs of fresh game meat provisioned annually by the sport hunting industry to rural communities in Zambia at an approximate value for the meat alone of >US$600,000 exclusive of distribution costs. During the hunting moratorium (2013–2014), this supply of meat has halted, likely adversely affecting rural communities previously reliant on this food source. Proposed alternatives to sport hunting should consider protein provisioning in addition to other benefits (e.g., employment, community pledges, anti-poaching funds) that rural Zambian communities receive from the sport hunting industry. PMID:25693191

Provisioning of game meat to rural communities as a benefit of sport hunting in Zambia.

PubMed

White, Paula A; Belant, Jerrold L

2015-01-01

Sport hunting has reportedly multiple benefits to economies and local communities; however, few of these benefits have been quantified. As part of their lease agreements with the Zambia Wildlife Authority, sport hunting operators in Zambia are required to provide annually to local communities free of charge i.e., provision a percentage of the meat obtained through sport hunting. We characterized provisioning of game meat to rural communities by the sport hunting industry in Zambia for three game management areas (GMAs) during 2004-2011. Rural communities located within GMAs where sport hunting occurred received on average > 6,000 kgs per GMA of fresh game meat annually from hunting operators. To assess hunting industry compliance, we also compared the amount of meat expected as per the lease agreements versus observed amounts of meat provisioned from three GMAs during 2007-2009. In seven of eight annual comparisons of these GMAs, provisioning of meat exceeded what was required in the lease agreements. Provisioning occurred throughout the hunting season and peaked during the end of the dry season (September-October) coincident with when rural Zambians are most likely to encounter food shortages. We extrapolated our results across all GMAs and estimated 129,771 kgs of fresh game meat provisioned annually by the sport hunting industry to rural communities in Zambia at an approximate value for the meat alone of >US$600,000 exclusive of distribution costs. During the hunting moratorium (2013-2014), this supply of meat has halted, likely adversely affecting rural communities previously reliant on this food source. Proposed alternatives to sport hunting should consider protein provisioning in addition to other benefits (e.g., employment, community pledges, anti-poaching funds) that rural Zambian communities receive from the sport hunting industry.

Principal Component Geostatistical Approach for large-dimensional inverse problems.

PubMed

Kitanidis, P K; Lee, J

2014-07-01

The quasi-linear geostatistical approach is for weakly nonlinear underdetermined inverse problems, such as Hydraulic Tomography and Electrical Resistivity Tomography. It provides best estimates as well as measures for uncertainty quantification. However, for its textbook implementation, the approach involves iterations, to reach an optimum, and requires the determination of the Jacobian matrix, i.e., the derivative of the observation function with respect to the unknown. Although there are elegant methods for the determination of the Jacobian, the cost is high when the number of unknowns, m , and the number of observations, n , is high. It is also wasteful to compute the Jacobian for points away from the optimum. Irrespective of the issue of computing derivatives, the computational cost of implementing the method is generally of the order of m 2 n , though there are methods to reduce the computational cost. In this work, we present an implementation that utilizes a matrix free in terms of the Jacobian matrix Gauss-Newton method and improves the scalability of the geostatistical inverse problem. For each iteration, it is required to perform K runs of the forward problem, where K is not just much smaller than m but can be smaller that n . The computational and storage cost of implementation of the inverse procedure scales roughly linearly with m instead of m 2 as in the textbook approach. For problems of very large m , this implementation constitutes a dramatic reduction in computational cost compared to the textbook approach. Results illustrate the validity of the approach and provide insight in the conditions under which this method perform best.

Geostatistical regularization of inverse models for the retrieval of vegetation biophysical variables

NASA Astrophysics Data System (ADS)

Atzberger, C.; Richter, K.

2009-09-01

The robust and accurate retrieval of vegetation biophysical variables using radiative transfer models (RTM) is seriously hampered by the ill-posedness of the inverse problem. With this research we further develop our previously published (object-based) inversion approach [Atzberger (2004)]. The object-based RTM inversion takes advantage of the geostatistical fact that the biophysical characteristics of nearby pixel are generally more similar than those at a larger distance. A two-step inversion based on PROSPECT+SAIL generated look-up-tables is presented that can be easily implemented and adapted to other radiative transfer models. The approach takes into account the spectral signatures of neighboring pixel and optimizes a common value of the average leaf angle (ALA) for all pixel of a given image object, such as an agricultural field. Using a large set of leaf area index (LAI) measurements (n = 58) acquired over six different crops of the Barrax test site, Spain), we demonstrate that the proposed geostatistical regularization yields in most cases more accurate and spatially consistent results compared to the traditional (pixel-based) inversion. Pros and cons of the approach are discussed and possible future extensions presented.

Selective remediation of contaminated sites using a two-level multiphase strategy and geostatistics.

PubMed

Saito, Hirotaka; Goovaerts, Pierre

2003-05-01

Selective soil remediation aims to reduce costs by cleaning only the fraction of an exposure unit (EU) necessary to lower the average concentration below the regulatory threshold. This approach requires a prior stratification of each EU into smaller remediation units (RU) which are then selected according to various criteria. This paper presents a geostatistical framework to account for uncertainties attached to both RU and EU average concentrations in selective remediation. The selection of RUs is based on their impact on the postremediation probability for the EU average concentration to exceed the regulatory threshold, which is assessed using geostatistical stochastic simulation. Application of the technique to a set of 600 dioxin concentrations collected at Piazza Road EPA Superfund site in Missouri shows a substantial decrease in the number of RU remediated compared with single phase remediation. The lower remediation costs achieved by the new strategy are obtained to the detriment of a higher risk of false negatives, yet for this data set this risk remains below the 5% rate set by EPA region 7.

Lead intoxicated children in Kabwe, Zambia.

PubMed

Bose-O'Reilly, Stephan; Yabe, John; Makumba, Joseph; Schutzmeier, Paul; Ericson, Bret; Caravanos, Jack

2017-10-28

Kabwe is a lead contaminated mining town in Zambia. Kabwe has extensive lead contaminated soil and children in Kabwe ingest and inhale high quantities of this toxic dust. The aim of this paper is to analyze the health impact of this exposure for children. Health data from three existing studies were re-analyzed. Over 95% of children living in the most affected townships had high blood lead levels (BLLs) > 10µg/dL. Approximately 50% of those children had BLLs ≥ 45µg/dL. The existing data clearly establishes the presence of a severe environmental health crisis in Kabwe which warrants immediate attention. Copyright © 2017 Elsevier Inc. All rights reserved.

Improving Allocation And Management Of The Health Workforce In Zambia.

PubMed

Walsh, Fiona J; Musonda, Mutinta; Mwila, Jere; Prust, Margaret Lippitt; Vosburg, Kathryn Bradford; Fink, Günther; Berman, Peter; Rockers, Peter C

2017-05-01

Building a health workforce in low-income countries requires a focused investment of time and resources, and ministries of health need tools to create staffing plans and prioritize spending on staff for overburdened health facilities. In Zambia a demand-based workload model was developed to calculate the number of health workers required to meet demands for essential health services and inform a rational and optimized strategy for deploying new public-sector staff members to the country's health facilities. Between 2009 and 2011 Zambia applied this optimized deployment policy, allocating new health workers to areas with the greatest demand for services. The country increased its health worker staffing in districts with fewer than one health worker per 1,000 people by 25.2 percent, adding 949 health workers to facilities that faced severe staffing shortages. At facilities that had had low staffing levels, adding a skilled provider was associated with an additional 103 outpatient consultations per quarter. Policy makers in resource-limited countries should consider using strategic approaches to identifying and deploying a rational distribution of health workers to provide the greatest coverage of health services to their populations. Project HOPE—The People-to-People Health Foundation, Inc.

Evaluation of service quality in family planning clinics in Lusaka, Zambia.

PubMed

Hancock, Nancy L; Vwalika, Bellington; Sitali, Elizabeth Siyama; Mbwili-Muleya, Clara; Chi, Benjamin H; Stuart, Gretchen S

2015-10-01

To determine the quality of contraceptive services in family planning clinics in Lusaka, Zambia, using a standardized approach. We utilized the Quick Investigation of Quality, a cross-sectional survey tool consisting of a facility assessment, client-provider observation and client exit interview, in public-sector family planning clinics. Data were collected on availability of seven contraceptive methods, information given to clients, interpersonal relations between providers and clients, providers' technical competence and mechanisms for continuity and follow-up. Data were collected from five client-provider observations and client exit interviews in each of six public-sector family planning clinics. All clinics had at least two contraceptive methods continuously available for the preceding 6 months. Most providers asked clients about concerns with their contraceptive method (80%) and told clients when to return to the clinic (87%). Most clients reported that the provider advised what to do if a problem develops (93%), described possible side effects (89%), explained how to use the method effectively (85%) and told them when to come for follow-up (83%). Clients were satisfied with services received (93%). This application of the Quick Investigation of Quality showed that the participating family planning clinics in Lusaka, Zambia, were prepared to offer high-quality services with the available commodities and that clients were satisfied with the received services. Despite the subjective client satisfaction, quality improvement efforts are needed to increase contraceptive availability. Although clients perceived the quality of care received to be high, family planning service quality could be improved to continuously offer the full spectrum of contraceptive options. The Quick Investigation of Quality was easily implemented in Lusaka, Zambia, and this simple approach could be utilized in a variety of settings as a modality for quality improvement. Copyright © 2015

Targeting indoor residual spraying for malaria using epidemiological data: a case study of the Zambia experience.

PubMed

Pinchoff, Jessie; Larsen, David A; Renn, Silvia; Pollard, Derek; Fornadel, Christen; Maire, Mark; Sikaala, Chadwick; Sinyangwe, Chomba; Winters, Benjamin; Bridges, Daniel J; Winters, Anna M

2016-01-06

In Zambia and other sub-Saharan African countries affected by ongoing malaria transmission, indoor residual spraying (IRS) for malaria prevention has typically been implemented over large areas, e.g., district-wide, and targeted to peri-urban areas. However, there is a recent shift in some countries, including Zambia, towards the adoption of a more strategic and targeted IRS approach, in coordination with increased emphasis on universal coverage of long-lasting insecticidal nets (LLINs) and effective insecticide resistance management. A true targeted approach would deliver IRS to sub-district areas identified as high-risk, with the goal of maximizing the prevention of malaria cases and deaths. Together with the Government of the Republic of Zambia, a new methodology was developed applying geographic information systems and satellite imagery to support a targeted IRS campaign during the 2014 spray season using health management information system data. This case study focuses on the developed methodology while also highlighting the significant research gaps which must be filled to guide countries on the most effective strategy for IRS targeting in the context of universal LLIN coverage and evolving insecticide resistance.

Bayesian Mediation Analysis

ERIC Educational Resources Information Center

Yuan, Ying; MacKinnon, David P.

2009-01-01

In this article, we propose Bayesian analysis of mediation effects. Compared with conventional frequentist mediation analysis, the Bayesian approach has several advantages. First, it allows researchers to incorporate prior information into the mediation analysis, thus potentially improving the efficiency of estimates. Second, under the Bayesian…

Lusaka, Zambia during SAFARI-2000: A Collection Point for Ozone Pollution

NASA Technical Reports Server (NTRS)

Thompson, Anne M.; Witte, Jacquelyn C.; Freiman, M. Tal; Phahlane, N. Agnes; Coetzee, G. J. R.; Bhartia, P. K. (Technical Monitor)

2002-01-01

In August and September, throughout south central Africa, seasonal clearing of dry vegetation and other fire-related activities lead to intense smoke haze and ozone formation. The first ozone soundings in the heart of the southern African burning region were taken at Lusaka, Zambia (155 deg S, 28 deg E) in early September 2000. Over 90 ppbv ozone was recorded at the surface (1.3 km elevation) and column tropospheric ozone was greater than 50 DU during a stagnant period. These values are much higher than concurrent measurements over Nairobi (1 deg S, 38 deg E) and Irene (25 deg S, 28 deg E, near Pretoria). The heaviest ozone pollution layer (800-500 hPa) over Lusaka is due to recirculated trans-boundary ozone. Starting out over Zambia, Angola, and Namibia, ozone heads east to the Indian Ocean, before turning back over Mozambique and Zimbabwe, heading toward Lusaka. Thus, Lusaka is a collection point for pollution, consistent with a picture of absolutely stable layers recirculating in a gyre over southern Africa.

Increased Economic Relations Between China and Zambia in the Last Decade: Implications on Zambia’s Existing Bilateral Relations with the United States

DTIC Science & Technology

2013-12-13

Pacific region, but also the world at large. China and the U.S. have agreed to a new model of relations, based on practical cooperation and...as a significant model to determine whether the increase in China and Zambia relations lead to a change in the nature of bilateral relations between...a model in countries with similar features and given the circumstances. The last decade has seen China step up its economic activities on the

Precipitation estimation in mountainous terrain using multivariate geostatistics. Part I: structural analysis

USGS Publications Warehouse

Hevesi, Joseph A.; Istok, Jonathan D.; Flint, Alan L.

1992-01-01

Values of average annual precipitation (AAP) are desired for hydrologic studies within a watershed containing Yucca Mountain, Nevada, a potential site for a high-level nuclear-waste repository. Reliable values of AAP are not yet available for most areas within this watershed because of a sparsity of precipitation measurements and the need to obtain measurements over a sufficient length of time. To estimate AAP over the entire watershed, historical precipitation data and station elevations were obtained from a network of 62 stations in southern Nevada and southeastern California. Multivariate geostatistics (cokriging) was selected as an estimation method because of a significant (p = 0.05) correlation of r = .75 between the natural log of AAP and station elevation. A sample direct variogram for the transformed variable, TAAP = ln [(AAP) 1000], was fitted with an isotropic, spherical model defined by a small nugget value of 5000, a range of 190 000 ft, and a sill value equal to the sample variance of 163 151. Elevations for 1531 additional locations were obtained from topographic maps to improve the accuracy of cokriged estimates. A sample direct variogram for elevation was fitted with an isotropic model consisting of a nugget value of 5500 and three nested transition structures: a Gaussian structure with a range of 61 000 ft, a spherical structure with a range of 70 000 ft, and a quasi-stationary, linear structure. The use of an isotropic, stationary model for elevation was considered valid within a sliding-neighborhood radius of 120 000 ft. The problem of fitting a positive-definite, nonlinear model of coregionalization to an inconsistent sample cross variogram for TAAP and elevation was solved by a modified use of the Cauchy-Schwarz inequality. A selected cross-variogram model consisted of two nested structures: a Gaussian structure with a range of 61 000 ft and a spherical structure with a range of 190 000 ft. Cross validation was used for model selection and for

Geo-statistical analysis of Culicoides spp. distribution and abundance in Sicily, Italy.

PubMed

Blanda, Valeria; Blanda, Marcellocalogero; La Russa, Francesco; Scimeca, Rossella; Scimeca, Salvatore; D'Agostino, Rosalia; Auteri, Michelangelo; Torina, Alessandra

2018-02-01

Biting midges belonging to Culicoides imicola, Culicoides obsoletus complex and Culicoides pulicaris complex (Diptera: Ceratopogonidae) are increasingly implicated as vectors of bluetongue virus in Palaearctic regions. Culicoides obsoletus complex includes C. obsoletus (sensu stricto), C. scoticus, C. dewulfi and C. chiopterus. Culicoides pulicaris and C. lupicaris belong to the Culicoides pulicaris complex. The aim of this study was a geo-statistical analysis of the abundance and spatial distribution of Culicoides spp. involved in bluetongue virus transmission. As part of the national bluetongue surveillance plan 7081 catches were collected in 897 Sicilian farms from 2000 to 2013. Onderstepoort-type blacklight traps were used for sample collection and each catch was analysed for the presence of Culicoides spp. and for the presence and abundance of Culicoides vector species (C. imicola, C. pulicaris / C. obsoletus complexes). A geo-statistical analysis was carried out monthly via the interpolation of measured values based on the Inverse Distance Weighted method, using a GIS tool. Raster maps were reclassified into seven classes according to the presence and abundance of Culicoides, in order to obtain suitable maps for Map Algebra operations. Sicilian provinces showing a very high abundance of Culicoides vector species were Messina (80% of the whole area), Palermo (20%) and Catania (12%). A total of 5654 farms fell within the very high risk area for bluetongue (21% of the 26,676 farms active in Sicily); of these, 3483 farms were in Messina, 1567 in Palermo and 604 in Catania. Culicoides imicola was prevalent in Palermo, C. pulicaris in Messina and C. obsoletus complex was very abundant over the whole island with the highest abundance value in Messina. Our study reports the results of a geo-statistical analysis concerning the abundance and spatial distribution of Culicoides spp. in Sicily throughout the fourteen year study. It provides useful decision support in the

Antimicrobial Resistant Enteropathogenic Escherichia coli and Salmonella spp. in Houseflies Infesting Fish in Food Markets in Zambia.

PubMed

Songe, Mwansa M; Hang'ombe, Bernard M; Knight-Jones, Theodore J D; Grace, Delia

2016-12-28

Diarrhea is one of the most common diseases and is a leading cause of death in developing countries. This is often caused by contaminated food. Poor food hygiene standards are exacerbated by the presence of flies which can transmit a variety of infectious microorganisms, particularly through animal source foods. This fact becomes especially important in developing countries like Zambia, where fish is a highly valued source of protein. Our interest in this study was to identify if the flies that beset food markets in Zambia carry important pathogenic bacteria on their bodies, and subsequently if these bacteria carry resistance genes to commonly used antibiotics, which would indicate problems in eradicating these pathogens. The present study took into account fish vendors' and consumers' perception of flies and interest in interventions to reduce their numbers. We conducted semi-structured interviews with (1) traders (comprised of randomly selected males and females) and (2) consumers (including randomly selected males and females). Thereafter, we collected flies found on fish in markets in Mongu and Lusaka districts of Zambia. For the entire study, a total of 418 fly samples were analyzed in the laboratory and Salmonella spp. and enteropathogenic Escherichia coli were isolated from the flies. Further laboratory screening revealed that overall, 17.2% (72/418) (95% CI; 43.2%-65.5%) of total samples analyzed contained Extended-Spectrum Beta-Lactamase (ESBL)-producing E. coli . These significant findings call for a strengthening of the antibiotic administering policy in Zambia and the development of sustainable interventions to reduce fly numbers in food markets and improve food safety and hygiene.

Responding to non-communicable diseases in Zambia: a policy analysis.

PubMed

Mukanu, Mulenga M; Zulu, Joseph Mumba; Mweemba, Chrispin; Mutale, Wilbroad

2017-04-24

Non-communicable diseases (NCDs) are an emerging global health concern. Reports have shown that, in Zambia, NCDs are also an emerging problem and the government has begun initiating a policy response. The present study explores the policy response to NCDs by the Ministry of Health in Zambia using the policy triangle framework of Walt and Gilson. A qualitative approach was used for the study. Data collected through key informant interviews with stakeholders who were involved in the NCD health policy development process as well as review of key planning and policy documents were analysed using thematic analysis. The government's policy response was as a result of international strategies from WHO, evidence of increasing disease burden from NCDs and pressure from interest groups. The government developed the NCD strategic plan based on the WHO Global Action Plan for NCDs 2013-2030. Development of the NCD strategic plan was driven by the government through the Ministry of Health, who set the agenda and adopted the final document. Stakeholders participated in the fine tuning of the draft document from the Ministry of Health. The policy development process was lengthy and this affected consistency in composition of the stakeholders and policy development momentum. Lack of representative research evidence for some prioritised NCDs and use of generic targets and indicators resulted in the NCD strategic plan being inadequate for the Zambian context. The interventions in the strategic plan also underutilised the potential of preventing NCDs through health education. Recent government pronouncements were also seen to be conflicting the risk factor reduction strategies outlined in the NCD strategic plan. The content of the NCD strategic plan inadequately covered all the major NCDs in Zambia. Although contextual factors like international strategies and commitments are crucial catalysts to policy development, there is need for domestication of international guidelines and

Practical Bayesian tomography

NASA Astrophysics Data System (ADS)

Granade, Christopher; Combes, Joshua; Cory, D. G.

2016-03-01

In recent years, Bayesian methods have been proposed as a solution to a wide range of issues in quantum state and process tomography. State-of-the-art Bayesian tomography solutions suffer from three problems: numerical intractability, a lack of informative prior distributions, and an inability to track time-dependent processes. Here, we address all three problems. First, we use modern statistical methods, as pioneered by Huszár and Houlsby (2012 Phys. Rev. A 85 052120) and by Ferrie (2014 New J. Phys. 16 093035), to make Bayesian tomography numerically tractable. Our approach allows for practical computation of Bayesian point and region estimators for quantum states and channels. Second, we propose the first priors on quantum states and channels that allow for including useful experimental insight. Finally, we develop a method that allows tracking of time-dependent states and estimates the drift and diffusion processes affecting a state. We provide source code and animated visual examples for our methods.

Inquiry-Based Science Education: A Scenario on Zambia's High School Science Curriculum

ERIC Educational Resources Information Center

Chabalengula, Vivien M.; Mumba, Frackson

2012-01-01

This paper is aimed at elucidating the current state of inquiry-based science education (IBSE) in Zambia's high school science curriculum. Therefore, we investigated Zambian teachers' conceptions of inquiry; determined inquiry levels in the national high school science curriculum materials, which include syllabi, textbooks and practical exams; and…

Conditioning geostatistical simulations of a heterogeneous paleo-fluvial bedrock aquifer using lithologs and pumping tests

NASA Astrophysics Data System (ADS)

Niazi, A.; Bentley, L. R.; Hayashi, M.

2016-12-01

Geostatistical simulations are used to construct heterogeneous aquifer models. Optimally, such simulations should be conditioned with both lithologic and hydraulic data. We introduce an approach to condition lithologic geostatistical simulations of a paleo-fluvial bedrock aquifer consisting of relatively high permeable sandstone channels embedded in relatively low permeable mudstone using hydraulic data. The hydraulic data consist of two-hour single well pumping tests extracted from the public water well database for a 250-km2 watershed in Alberta, Canada. First, lithologic models of the entire watershed are simulated and conditioned with hard lithological data using transition probability - Markov chain geostatistics (TPROGS). Then, a segment of the simulation around a pumping well is used to populate a flow model (FEFLOW) with either sand or mudstone. The values of the hydraulic conductivity and specific storage of sand and mudstone are then adjusted to minimize the difference between simulated and actual pumping test data using the parameter estimation program PEST. If the simulated pumping test data do not adequately match the measured data, the lithologic model is updated by locally deforming the lithology distribution using the probability perturbation method and the model parameters are again updated with PEST. This procedure is repeated until the simulated and measured data agree within a pre-determined tolerance. The procedure is repeated for each well that has pumping test data. The method creates a local groundwater model that honors both the lithologic model and pumping test data and provides estimates of hydraulic conductivity and specific storage. Eventually, the simulations will be integrated into a watershed-scale groundwater model.

Information Provision in Emergency Settings: The Experience of Refugee Communities in Zambia

ERIC Educational Resources Information Center

Kanyengo, Brendah Kakulwa; Kanyengo, Christine Wamunyima

2011-01-01

This article identifies information provision services in emergency settings using Zambia as a case study by identifying innovative ways of providing library and information services. The thrust of the article is to analyze information management practices of organizations that work within refugee camps and how they take specific cognizance of the…

Bayesian modeling to assess populated areas impacted by radiation from Fukushima

NASA Astrophysics Data System (ADS)

Hultquist, C.; Cervone, G.

2017-12-01

Citizen-led movements producing spatio-temporal big data are increasingly important sources of information about populations that are impacted by natural disasters. Citizen science can be used to fill gaps in disaster monitoring data, in addition to inferring human exposure and vulnerability to extreme environmental impacts. As a response to the 2011 release of radiation from Fukushima, Japan, the Safecast project began collecting open radiation data which grew to be a global dataset of over 70 million measurements to date. This dataset is spatially distributed primarily where humans are located and demonstrates abnormal patterns of population movements as a result of the disaster. Previous work has demonstrated that Safecast is highly correlated in comparison to government radiation observations. However, there is still a scientific need to understand the geostatistical variability of Safecast data and to assess how reliable the data are over space and time. The Bayesian hierarchical approach can be used to model the spatial distribution of datasets and flexibly integrate new flows of data without losing previous information. This enables an understanding of uncertainty in the spatio-temporal data to inform decision makers on areas of high levels of radiation where populations are located. Citizen science data can be scientifically evaluated and used as a critical source of information about populations that are impacted by a disaster.

Principal Component Geostatistical Approach for large-dimensional inverse problems

PubMed Central

Kitanidis, P K; Lee, J

2014-01-01

The quasi-linear geostatistical approach is for weakly nonlinear underdetermined inverse problems, such as Hydraulic Tomography and Electrical Resistivity Tomography. It provides best estimates as well as measures for uncertainty quantification. However, for its textbook implementation, the approach involves iterations, to reach an optimum, and requires the determination of the Jacobian matrix, i.e., the derivative of the observation function with respect to the unknown. Although there are elegant methods for the determination of the Jacobian, the cost is high when the number of unknowns, m, and the number of observations, n, is high. It is also wasteful to compute the Jacobian for points away from the optimum. Irrespective of the issue of computing derivatives, the computational cost of implementing the method is generally of the order of m2n, though there are methods to reduce the computational cost. In this work, we present an implementation that utilizes a matrix free in terms of the Jacobian matrix Gauss-Newton method and improves the scalability of the geostatistical inverse problem. For each iteration, it is required to perform K runs of the forward problem, where K is not just much smaller than m but can be smaller that n. The computational and storage cost of implementation of the inverse procedure scales roughly linearly with m instead of m2 as in the textbook approach. For problems of very large m, this implementation constitutes a dramatic reduction in computational cost compared to the textbook approach. Results illustrate the validity of the approach and provide insight in the conditions under which this method perform best. PMID:25558113

Medical Geography: a Promising Field of Application for Geostatistics

PubMed Central

Goovaerts, P.

2008-01-01

The analysis of health data and putative covariates, such as environmental, socio-economic, behavioral or demographic factors, is a promising application for geostatistics. It presents, however, several methodological challenges that arise from the fact that data are typically aggregated over irregular spatial supports and consist of a numerator and a denominator (i.e. population size). This paper presents an overview of recent developments in the field of health geostatistics, with an emphasis on three main steps in the analysis of areal health data: estimation of the underlying disease risk, detection of areas with significantly higher risk, and analysis of relationships with putative risk factors. The analysis is illustrated using age-adjusted cervix cancer mortality rates recorded over the 1970–1994 period for 118 counties of four states in the Western USA. Poisson kriging allows the filtering of noisy mortality rates computed from small population sizes, enhancing the correlation with two putative explanatory variables: percentage of habitants living below the federally defined poverty line, and percentage of Hispanic females. Area-to-point kriging formulation creates continuous maps of mortality risk, reducing the visual bias associated with the interpretation of choropleth maps. Stochastic simulation is used to generate realizations of cancer mortality maps, which allows one to quantify numerically how the uncertainty about the spatial distribution of health outcomes translates into uncertainty about the location of clusters of high values or the correlation with covariates. Last, geographically-weighted regression highlights the non-stationarity in the explanatory power of covariates: the higher mortality values along the coast are better explained by the two covariates than the lower risk recorded in Utah. PMID:19412347

Medical Geography: a Promising Field of Application for Geostatistics.

PubMed

Goovaerts, P

2009-01-01

The analysis of health data and putative covariates, such as environmental, socio-economic, behavioral or demographic factors, is a promising application for geostatistics. It presents, however, several methodological challenges that arise from the fact that data are typically aggregated over irregular spatial supports and consist of a numerator and a denominator (i.e. population size). This paper presents an overview of recent developments in the field of health geostatistics, with an emphasis on three main steps in the analysis of areal health data: estimation of the underlying disease risk, detection of areas with significantly higher risk, and analysis of relationships with putative risk factors. The analysis is illustrated using age-adjusted cervix cancer mortality rates recorded over the 1970-1994 period for 118 counties of four states in the Western USA. Poisson kriging allows the filtering of noisy mortality rates computed from small population sizes, enhancing the correlation with two putative explanatory variables: percentage of habitants living below the federally defined poverty line, and percentage of Hispanic females. Area-to-point kriging formulation creates continuous maps of mortality risk, reducing the visual bias associated with the interpretation of choropleth maps. Stochastic simulation is used to generate realizations of cancer mortality maps, which allows one to quantify numerically how the uncertainty about the spatial distribution of health outcomes translates into uncertainty about the location of clusters of high values or the correlation with covariates. Last, geographically-weighted regression highlights the non-stationarity in the explanatory power of covariates: the higher mortality values along the coast are better explained by the two covariates than the lower risk recorded in Utah.

The Bayesian reader: explaining word recognition as an optimal Bayesian decision process.

PubMed

Norris, Dennis

2006-04-01

This article presents a theory of visual word recognition that assumes that, in the tasks of word identification, lexical decision, and semantic categorization, human readers behave as optimal Bayesian decision makers. This leads to the development of a computational model of word recognition, the Bayesian reader. The Bayesian reader successfully simulates some of the most significant data on human reading. The model accounts for the nature of the function relating word frequency to reaction time and identification threshold, the effects of neighborhood density and its interaction with frequency, and the variation in the pattern of neighborhood density effects seen in different experimental tasks. Both the general behavior of the model and the way the model predicts different patterns of results in different tasks follow entirely from the assumption that human readers approximate optimal Bayesian decision makers. ((c) 2006 APA, all rights reserved).

A multiscale Bayesian data integration approach for mapping air dose rates around the Fukushima Daiichi Nuclear Power Plant.

PubMed

Wainwright, Haruko M; Seki, Akiyuki; Chen, Jinsong; Saito, Kimiaki

2017-02-01

This paper presents a multiscale data integration method to estimate the spatial distribution of air dose rates in the regional scale around the Fukushima Daiichi Nuclear Power Plant. We integrate various types of datasets, such as ground-based walk and car surveys, and airborne surveys, all of which have different scales, resolutions, spatial coverage, and accuracy. This method is based on geostatistics to represent spatial heterogeneous structures, and also on Bayesian hierarchical models to integrate multiscale, multi-type datasets in a consistent manner. The Bayesian method allows us to quantify the uncertainty in the estimates, and to provide the confidence intervals that are critical for robust decision-making. Although this approach is primarily data-driven, it has great flexibility to include mechanistic models for representing radiation transport or other complex correlations. We demonstrate our approach using three types of datasets collected at the same time over Fukushima City in Japan: (1) coarse-resolution airborne surveys covering the entire area, (2) car surveys along major roads, and (3) walk surveys in multiple neighborhoods. Results show that the method can successfully integrate three types of datasets and create an integrated map (including the confidence intervals) of air dose rates over the domain in high resolution. Moreover, this study provides us with various insights into the characteristics of each dataset, as well as radiocaesium distribution. In particular, the urban areas show high heterogeneity in the contaminant distribution due to human activities as well as large discrepancy among different surveys due to such heterogeneity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Linguistic Landscapes and the Sociolinguistics of Language Vitality in Multilingual Contexts of Zambia

ERIC Educational Resources Information Center

Banda, Felix; Jimaima, Hambaba

2017-01-01

The article illustrates a sociolinguistics of language vitality that accounts for "minority" and unofficial languages across multiple localities in dispersed communities of multilingual speakers of Zambia where only seven out of seventy-three indigenous languages have been designated official and "zoned" for use in specified…

Promotion of couples' voluntary HIV counseling and testing: a comparison of influence networks in Rwanda and Zambia.

PubMed

Kelley, April L; Hagaman, Ashley K; Wall, Kristin M; Karita, Etienne; Kilembe, William; Bayingana, Roger; Tichacek, Amanda; Kautzman, Michele; Allen, Susan A

2016-08-08

Many African adults do not know that partners in steady or cohabiting relationships can have different HIV test results. Despite WHO recommendations for couples' voluntary counseling and testing (CVCT), fewer than 10 % of couples have been jointly tested and counseled. We examine the roles and interactions of influential network leaders (INLs) and influential network agents (INAs) in promoting CVCT in Kigali, Rwanda and Lusaka, Zambia. INLs were identified in the faith-based, non-governmental, private, and health sectors. Each INL recruited and mentored several INAs who promoted CVCT. INLs and INAs were interviewed about demographic characteristics, promotional efforts, and working relationships. We also surveyed CVCT clients about sources of CVCT information. In Zambia, 53 INAs and 31 INLs were surveyed. In Rwanda, 33 INAs and 27 INLs were surveyed. Most (75 %-90 %) INAs believed that INL support was necessary for their promotional work. Zambian INLs reported being more engaged with their INAs than Rwandan INLs, with 58 % of Zambian INLs reporting that they gave a lot of support to their INAs versus 39 % in Rwanda. INAs in both Rwanda and Zambia reported promoting CVCT via group forums (77 %-97 %) and speaking to a community leader about CVCT (79 %-88 %) in the past month. More Rwandan INAs and INLs reported previous joint or individual HIV testing compared with their Zambian counterparts, of which more than half had not been tested. In Zambia and Rwanda, 1271 and 3895 CVCT clients were surveyed, respectively. Hearing about CVCT from INAs during one-on-one promotions was the most frequent source of information reported by clients in Zambia (71 %). In contrast, Rwandan couples who tested were more likely to have heard about CVCT from a previously tested couple (59 %). CVCT has long been endorsed for HIV prevention but few couples have been reached. Influential social networks can successfully promote evidence-based HIV prevention in Africa. Support from

Antimicrobial Resistant Enteropathogenic Escherichia coli and Salmonella spp. in Houseflies Infesting Fish in Food Markets in Zambia

PubMed Central

Songe, Mwansa M.; Hang’ombe, Bernard M.; Knight-Jones, Theodore J. D.; Grace, Delia

2016-01-01

Diarrhea is one of the most common diseases and is a leading cause of death in developing countries. This is often caused by contaminated food. Poor food hygiene standards are exacerbated by the presence of flies which can transmit a variety of infectious microorganisms, particularly through animal source foods. This fact becomes especially important in developing countries like Zambia, where fish is a highly valued source of protein. Our interest in this study was to identify if the flies that beset food markets in Zambia carry important pathogenic bacteria on their bodies, and subsequently if these bacteria carry resistance genes to commonly used antibiotics, which would indicate problems in eradicating these pathogens. The present study took into account fish vendors’ and consumers’ perception of flies and interest in interventions to reduce their numbers. We conducted semi-structured interviews with (1) traders (comprised of randomly selected males and females) and (2) consumers (including randomly selected males and females). Thereafter, we collected flies found on fish in markets in Mongu and Lusaka districts of Zambia. For the entire study, a total of 418 fly samples were analyzed in the laboratory and Salmonella spp. and enteropathogenic Escherichia coli were isolated from the flies. Further laboratory screening revealed that overall, 17.2% (72/418) (95% CI; 43.2%–65.5%) of total samples analyzed contained Extended-Spectrum Beta-Lactamase (ESBL)-producing E. coli. These significant findings call for a strengthening of the antibiotic administering policy in Zambia and the development of sustainable interventions to reduce fly numbers in food markets and improve food safety and hygiene. PMID:28036049

Aspergillus section Flavi community structure in Zambia influences aflatoxin contamination of Maize and Groundnut

USDA-ARS?s Scientific Manuscript database

Aflatoxins are cancer-causing, immuno-suppressive mycotoxins that frequently contaminate important staples in Zambia including maize and groundnut. Several species within Aspergillus section Flavi have been implicated as causal agents of aflatoxin contamination in Africa. However, Aspergillus popula...

Developing a Nutrition and Health Education Program for Primary Schools in Zambia

ERIC Educational Resources Information Center

Sherman, Jane; Muehlhoff, Ellen

2007-01-01

School-based health and nutrition interventions in developing countries aim at improving children's nutrition and learning ability. In addition to the food and health inputs, children need access to education that is relevant to their lives, of good quality, and effective in its approach. Based on evidence from the Zambia Nutrition Education in…

Report from the Field: Education under Structural Adjustment in Nigeria and Zambia.

ERIC Educational Resources Information Center

Babalola, Joel B.; Lungwangwa, Geoffrey; Adeyinka, Augustus A.

1999-01-01

Investigates the effects of the Structural Adjustment Program (SAP) on the educational systems in Nigeria and Zambia. Reports that SAP impacted the public expenditure on education, the purchasing power of the incomes earned by both learning institutions and their staff, and on access, equity, and quality indicators in education at all levels. (CMK)

Evaluation of a TB infection control implementation initiative in out-patient HIV clinics in Zambia and Botswana.

PubMed

Emerson, C; Lipke, V; Kapata, N; Mwananyambe, N; Mwinga, A; Garekwe, M; Lanje, S; Moshe, Y; Pals, S L; Nakashima, A K; Miller, B

2016-07-01

Out-patient human immunodeficiency virus (HIV) care and treatment clinics in Zambia and Botswana, countries with a high burden of HIV and TB infection. To develop a tuberculosis infection control (TB IC) training and implementation package and evaluate the implementation of TB IC activities in facilities implementing the package. Prospective program evaluation of a TB IC training and implementation package using a standardized facility risk assessment tool, qualitative interviews with facility health care workers and measures of pre- and post-test performance. A composite measure of facility performance in TB IC improved from 32% at baseline to 50% at 1 year among eight facilities in Zambia, and from 27% to 80% at 6 months among 10 facilities in Botswana. Although there was marked improvement in indicators of managerial, administrative and environmental controls, key ongoing challenges remained in ensuring access to personal protective equipment and implementing TB screening in health care workers. TB IC activities at out-patient HIV clinics in Zambia and Botswana improved after training using the implementation package. Continued infrastructure support, as well as monitoring and evaluation, are needed to support the scale-up and sustainability of TB IC programs in facilities in low-resource countries.

Bayesian demography 250 years after Bayes

PubMed Central

Bijak, Jakub; Bryant, John

2016-01-01

Bayesian statistics offers an alternative to classical (frequentist) statistics. It is distinguished by its use of probability distributions to describe uncertain quantities, which leads to elegant solutions to many difficult statistical problems. Although Bayesian demography, like Bayesian statistics more generally, is around 250 years old, only recently has it begun to flourish. The aim of this paper is to review the achievements of Bayesian demography, address some misconceptions, and make the case for wider use of Bayesian methods in population studies. We focus on three applications: demographic forecasts, limited data, and highly structured or complex models. The key advantages of Bayesian methods are the ability to integrate information from multiple sources and to describe uncertainty coherently. Bayesian methods also allow for including additional (prior) information next to the data sample. As such, Bayesian approaches are complementary to many traditional methods, which can be productively re-expressed in Bayesian terms. PMID:26902889

Costing commodity and human resource needs for integrated community case management in thie differing community health strategies of Ethiopia, Kenya and Zambia.

PubMed

Nefdt, Rory; Ribaira, Eric; Diallo, Khassoum

2014-10-01

To ensure correct and appropriate funding is available, there is a need to estimate resource needs for improved planning and implementation of integrated Community Case Management (iCCM). To compare and estimate costs for commodity and human resource needs for iCCM, based on treatment coverage rates, bottlenecks and national targets in Ethiopia, Kenya and Zambia from 2014 to 2016. Resource needs were estimated using Ministry of Health (MoH) targets fronm 2014 to 2016 for implementation of case management of pneumonia, diarrhea and malaria through iCCM based on epidemiological, demographic, economic, intervention coverage and other health system parameters. Bottleneck analysis adjusted cost estimates against system barriers. Ethiopia, Kenya and Zambia were chosen to compare differences in iCCM costs in different programmatic implementation landscapes. Coverage treatment rates through iCCM are lowest in Ethiopia, followed by Kenya and Zambia, but Ethiopia had the greatest increases between 2009 and 2012. Deployment of health extension workers (HEWs) in Ethiopia is more advanced compared to Kenya and Zambia, which have fewer equivalent cadres (called commu- nity health workers (CHWs)) covering a smaller proportion of the population. Between 2014 and 2016, the propor- tion of treatments through iCCM compared to health centres are set to increase from 30% to 81% in Ethiopia, 1% to 18% in Kenya and 3% to 22% in Zambia. The total estimated cost of iCCM for these three years are USD 75,531,376 for Ethiopia, USD 19,839,780 for Kenya and USD 33,667,742 for Zambia. Projected per capita expen- diture for 2016 is USD 0.28 for Ethiopia, USD 0.20 in Kenya and USD 0.98 in Zambia. Commodity costs for pneumonia and diarrhea were a small fraction of the total iCCM budget for all three countries (less than 3%), while around 80% of the costs related to human resources. Analysis of coverage, demography and epidemiology data improves estimates of fimding requirements for iCCM. Bottleneck

Intelligent Decisions Need Intelligent Choice of Models and Data - a Bayesian Justifiability Analysis for Models with Vastly Different Complexity

NASA Astrophysics Data System (ADS)

Nowak, W.; Schöniger, A.; Wöhling, T.; Illman, W. A.

2016-12-01

Model-based decision support requires justifiable models with good predictive capabilities. This, in turn, calls for a fine adjustment between predictive accuracy (small systematic model bias that can be achieved with rather complex models), and predictive precision (small predictive uncertainties that can be achieved with simpler models with fewer parameters). The implied complexity/simplicity trade-off depends on the availability of informative data for calibration. If not available, additional data collection can be planned through optimal experimental design. We present a model justifiability analysis that can compare models of vastly different complexity. It rests on Bayesian model averaging (BMA) to investigate the complexity/performance trade-off dependent on data availability. Then, we disentangle the complexity component from the performance component. We achieve this by replacing actually observed data by realizations of synthetic data predicted by the models. This results in a "model confusion matrix". Based on this matrix, the modeler can identify the maximum model complexity that can be justified by the available (or planned) amount and type of data. As a side product, the matrix quantifies model (dis-)similarity. We apply this analysis to aquifer characterization via hydraulic tomography, comparing four models with a vastly different number of parameters (from a homogeneous model to geostatistical random fields). As a testing scenario, we consider hydraulic tomography data. Using subsets of these data, we determine model justifiability as a function of data set size. The test case shows that geostatistical parameterization requires a substantial amount of hydraulic tomography data to be justified, while a zonation-based model can be justified with more limited data set sizes. The actual model performance (as opposed to model justifiability), however, depends strongly on the quality of prior geological information.

The Psychology of Bayesian Reasoning

DTIC Science & Technology

2014-10-21

The psychology of Bayesian reasoning David R. Mandel* Socio-Cognitive Systems Section, Defence Research and Development Canada and Department...belief revision, subjective probability, human judgment, psychological methods. Most psychological research on Bayesian reasoning since the 1970s has...attention to some important problems with the conventional approach to studying Bayesian reasoning in psychology that has been dominant since the

Women's knowledge and attitudes surrounding abortion in Zambia: a cross-sectional survey across three provinces

PubMed Central

Cresswell, Jenny A; Schroeder, Rosalyn; Dennis, Mardieh; Owolabi, Onikepe; Vwalika, Bellington; Musheke, Maurice; Campbell, Oona; Filippi, Veronique

2016-01-01

Objectives In Zambia, despite a relatively liberal legal framework, there remains a substantial burden of unsafe abortion. Many women do not use skilled providers in a well-equipped setting, even where these are available. The aim of this study was to describe women's knowledge of the law relating to abortion and attitudes towards abortion in Zambia. Setting Community-based survey in Central, Copperbelt and Lusaka provinces. Participants 1484 women of reproductive age (15–44 years). Primary and secondary outcome measures Correct knowledge of the legal grounds for abortion, attitudes towards abortion services and the previous abortions of friends, family or other confidants. Descriptive statistics and multivariable logistic regression were used to analyse how knowledge and attitudes varied according to sociodemographic characteristics. Results Overall, just 16% (95% CI 11% to 21%) of women of reproductive age correctly identified the grounds for which abortion is legal. Only 40% (95% CI 32% to 45% of women of reproductive age knew that abortion was legally permitted in the extreme situation where the pregnancy threatens the life of the mother. Even in urban areas of Lusaka province, only 55% (95% CI 41% to 67%) of women knew that an abortion could legally take place to save the mother's life. Attitudes remain conservative. Women with correct knowledge of abortion law in Zambia tended to have more liberal attitudes towards abortion and access to safe abortion services. Neither correct knowledge of the law nor attitudes towards abortion were associated with knowing someone who previously had an induced abortion. Conclusions Poor knowledge and conservative attitudes are important obstacles to accessing safe abortion services. Changing knowledge and attitudes can be challenging for policymakers and public health practitioners alike. Zambia could draw on its previous experience in dealing with its large HIV epidemic to learn cross-cutting lessons in effective mass

Health system productivity change in Zambia: A focus on the child health services.

PubMed

Achoki, Tom; Kinfu, Yohannes; Masiye, Felix; Frederix, Geert W J; Hovels, Anke; Leufkens, Hubert G

2017-02-01

Efficiency and productivity improvement have become central in global health debates. In this study, we explored productivity change, particularly the contribution of technological progress and efficiency gains associated with improvements in child survival in Zambia (population 15 million). Productivity was measured by applying the Malmquist productivity index on district-level panel data. The effect of socioeconomic factors was further analyzed by applying an ordinary least squares regression technique. During 2004-2009, overall productivity in Zambia increased by 5.0 per cent, a change largely attributed to technological progress rather than efficiency gains. Within-country productivity comparisons revealed wide heterogeneity in favor of more urbanized and densely populated districts. Improved cooking methods, improved sanitation, and better educated populations tended to improve productive gains, whereas larger household size had an adverse effect. Addressing such district-level factors and ensuring efficient delivery and optimal application of existing health technologies offer a practical pathway for further improving population health.

Epidemiological analysis of tick-borne diseases in Zambia.

PubMed

Simuunza, Martin; Weir, William; Courcier, Emily; Tait, Andy; Shiels, Brian

2011-02-10

Tick-borne diseases are a constraint to livestock production in many developing countries as they cause high morbidity and mortality, which results in decreased production of meat, milk and other livestock by-products. The most important tick-borne diseases of livestock in sub-Saharan Africa are East Coast fever (caused by Theileria parva), babesiosis (caused by Babesia bigemina and B. bovis), anaplasmosis (caused by Anaplasma marginale) and heartwater (caused by Ehrlichia ruminantium). Despite their economic importance, information on the epidemiology of these diseases in many countries, including Zambia, is often inadequate, making rational disease control strategies difficult to implement. In this study 18S and 16S rRNA gene PCR assays were used for a comprehensive epidemiological analysis of tick-borne disease of cattle in three provinces of Zambia (Lusaka, Central and Eastern). All the disease pathogens under study (T. parva, T. mutans, T. taurotragi, B. bovis, B. bigemina, Anaplasma spp and E. ruminantium) were prevalent in each of the provinces surveyed. However, variation was observed in prevalence between regions and seasons. There was no association between live vaccination against East Coast fever and being PCR positive for T. parva. A number of risk factors were shown to be associated with (a) the occurrence of tick-borne pathogens in cattle and (b) cattle tick burdens in the wet season. A negative association was observed between the number of co-infecting pathogens and the erythrocyte packed cell volume (PCV) of carrier cattle. Crown Copyright © 2010. Published by Elsevier B.V. All rights reserved.

Factors Contributing to the Failure to Use Condoms among Students in Zambia

ERIC Educational Resources Information Center

Mbulo, Lazarous; Newman, Ian M.; Shell, Duane F.

2007-01-01

This study explored factors that may predict condom use among college and high school students in Zambia. Using the Social Cognitive Theory, this study examined the relationship of drinking behaviors, alcohol-sexual expectations, education level, and religion to condom use among 961 students. The results of the study show that condom use was low…

Embers to Bonfires: An Analysis of Early Childhood Teacher Training in Zambia

ERIC Educational Resources Information Center

Evans-Palmer, Teri E.; Shen, Mei-Yi

2017-01-01

This study examined a five-year project initiated by the Women's Global Connection (WGC) to train pre-primary teachers in schools serving HIV/AIDS orphans in Zambia. The researchers evaluated the contextual factors of the training initiative to clarify why some teachers possess high self-efficacy, while others do not. The article analyses the…

Mantle Structure Beneath East Africa and Zambia from Body Wave Tomography

NASA Astrophysics Data System (ADS)

Mulibo, G.; Nyblade, A.; Tugume, F.

2011-12-01

In this study, P and S travel time residuals from teleseismic earthquakes recorded on over 60 temporary AfricaArray seismic stations deployed in Uganda, Kenya, Tanzania and Zambia between 2007 and 2011 are being inverted, together with travel time residuals from previous deployments, for a 3D image of mantle wave speeds variations extending to a depth of 1200 km. Preliminary results show that at depths of 200 km of less, low wave speed anomalies are well developed beneath the Eastern and Western Branches of the East African Rift System. At deep depths, the low wave speed anomalies focus under the center and southern part of the East African Plateau and extend into the transition zone. At transition zone depths and within the top part of the lower mantle, the low wave speed anomaly shifts to the southwest beneath Zambia, indicating that the low wave speed anomaly is continuous across the transition zone and that it extends into the lower mantle. This result suggests that the upper mantle low wave speed anomaly beneath East Africa is connected to the African superplume anomaly in the lower mantle beneath southern Africa.

Spatial distribution of Munida intermedia and M. sarsi (crustacea: Anomura) on the Galician continental shelf (NW Spain): Application of geostatistical analysis

NASA Astrophysics Data System (ADS)

Freire, J.; González-Gurriarán, E.; Olaso, I.

1992-12-01

Geostatistical methodology was used to analyse spatial structure and distribution of the epibenthic crustaceans Munida intermedia and M. sarsi within sets of data which had been collected during three survey cruises carried out on the Galician continental shelf (1983 and 1984). This study investigates the feasibility of using geostatistics for data collected according to traditional methods and of enhancing such methodology. The experimental variograms were calculated (pooled variance minus spatial covariance between samples taken one pair at a time vs. distance) and fitted to a 'spherical' model. The spatial structure model was used to estimate the abundance and distribution of the populations studied using the technique of kriging. The species display spatial structures, which are well marked during high density periods and in some areas (especially northern shelf). Geostatistical analysis allows identification of the density gradients in space as well as the patch grain along the continental shelf of 16-25 km diameter for M. intermedia and 12-20 km for M. sarsi. Patches of both species have a consistent location throughout the different cruises. As in other geographical areas, M. intermedia and M. sarsi usually appear at depths ranging from 200 to 500 m, with the highest densities in the continental shelf area located between Fisterra and Estaca de Bares. Althouh sampling was not originally designed specifically for geostatistics, this assay provides a measurement of spatial covariance, and shows variograms with variable structure depending on population density and geographical area. These ideas are useful in improving the design of future sampling cruises.

Etiologic pattern of genital ulcers in Lusaka, Zambia: has chancroid been eliminated?

PubMed

Makasa, Mpundu; Buve, Anne; Sandøy, Ingvild Fossgard

2012-10-01

Genital ulcers are a public health problem in developing countries. The World Health Organization recommends the use of syndromic guidelines for sexually transmitted infection treatment in resource-constrained countries. Monitoring local etiologies provides information that may aid policy for sexually transmitted infection treatment. We investigated the etiology of genital ulcer disease among outpatients in Lusaka, Zambia. Swabs from genital ulcers of 200 patients were tested using polymerase chain reaction for Treponema pallidum, herpes simplex virus types 1 (HSV-1) and 2 (HSV-2), Haemophilus ducreyi, and Chlamydia trachomatis. The prevalence of the detected pathogens was as follows; HSV-2, 28%; T. pallidum, 11.5%; C. trachomatis, 3%; HSV-1, 0.5%; and H. ducreyi, 0%. Coinfection with HSV-2 and T. pallidum was 1.5%, and coinfection of HSV-2 and C. trachomatis was 1%. In 55% of the patients, no etiologic diagnosis could be established. H. ducreyi was not detected, whereas HSV-2 and T. pallidum were the commonest pathogens. Nondetection of H. ducreyi requires further studies. If the present findings are validated, treatment guidelines would require to be revised in Zambia.

Basics of Bayesian methods.

PubMed

Ghosh, Sujit K

2010-01-01

Bayesian methods are rapidly becoming popular tools for making statistical inference in various fields of science including biology, engineering, finance, and genetics. One of the key aspects of Bayesian inferential method is its logical foundation that provides a coherent framework to utilize not only empirical but also scientific information available to a researcher. Prior knowledge arising from scientific background, expert judgment, or previously collected data is used to build a prior distribution which is then combined with current data via the likelihood function to characterize the current state of knowledge using the so-called posterior distribution. Bayesian methods allow the use of models of complex physical phenomena that were previously too difficult to estimate (e.g., using asymptotic approximations). Bayesian methods offer a means of more fully understanding issues that are central to many practical problems by allowing researchers to build integrated models based on hierarchical conditional distributions that can be estimated even with limited amounts of data. Furthermore, advances in numerical integration methods, particularly those based on Monte Carlo methods, have made it possible to compute the optimal Bayes estimators. However, there is a reasonably wide gap between the background of the empirically trained scientists and the full weight of Bayesian statistical inference. Hence, one of the goals of this chapter is to bridge the gap by offering elementary to advanced concepts that emphasize linkages between standard approaches and full probability modeling via Bayesian methods.

Hydraulic Conductivity Estimation using Bayesian Model Averaging and Generalized Parameterization

NASA Astrophysics Data System (ADS)

Tsai, F. T.; Li, X.

2006-12-01

Non-uniqueness in parameterization scheme is an inherent problem in groundwater inverse modeling due to limited data. To cope with the non-uniqueness problem of parameterization, we introduce a Bayesian Model Averaging (BMA) method to integrate a set of selected parameterization methods. The estimation uncertainty in BMA includes the uncertainty in individual parameterization methods as the within-parameterization variance and the uncertainty from using different parameterization methods as the between-parameterization variance. Moreover, the generalized parameterization (GP) method is considered in the geostatistical framework in this study. The GP method aims at increasing the flexibility of parameterization through the combination of a zonation structure and an interpolation method. The use of BMP with GP avoids over-confidence in a single parameterization method. A normalized least-squares estimation (NLSE) is adopted to calculate the posterior probability for each GP. We employee the adjoint state method for the sensitivity analysis on the weighting coefficients in the GP method. The adjoint state method is also applied to the NLSE problem. The proposed methodology is implemented to the Alamitos Barrier Project (ABP) in California, where the spatially distributed hydraulic conductivity is estimated. The optimal weighting coefficients embedded in GP are identified through the maximum likelihood estimation (MLE) where the misfits between the observed and calculated groundwater heads are minimized. The conditional mean and conditional variance of the estimated hydraulic conductivity distribution using BMA are obtained to assess the estimation uncertainty.

Underutilisation of routinely collected data in the HIV programme in Zambia: a review of quantitatively analysed peer-reviewed articles.

PubMed

Munthali, Tendai; Musonda, Patrick; Mee, Paul; Gumede, Sehlulekile; Schaap, Ab; Mwinga, Alwyn; Phiri, Caroline; Kapata, Nathan; Michelo, Charles; Todd, Jim

2017-06-13

The extent to which routinely collected HIV data from Zambia has been used in peer-reviewed published articles remains unexplored. This paper is an analysis of peer-reviewed articles that utilised routinely collected HIV data from Zambia within six programme areas from 2004 to 2014. Articles on HIV, published in English, listed in the Directory of open access journals, African Journals Online, Google scholar, and PubMed were reviewed. Only articles from peer-reviewed journals, that utilised routinely collected data and included quantitative data analysis methods were included. Multi-country studies involving Zambia and another country, where the specific results for Zambia were not reported, as well as clinical trials and intervention studies that did not take place under routine care conditions were excluded, although community trials which referred patients to the routine clinics were included. Independent extraction was conducted using a predesigned data collection form. Pooled analysis was not possible due to diversity in topics reviewed. A total of 69 articles were extracted for review. Of these, 7 were excluded. From the 62 articles reviewed, 39 focused on HIV treatment and retention in care, 15 addressed prevention of mother-to-child transmission, 4 assessed social behavioural change, and 4 reported on voluntary counselling and testing. In our search, no articles were found on condom programming or voluntary male medical circumcision. The most common outcome measures reported were CD4+ count, clinical failure or mortality. The population analysed was children in 13 articles, women in 16 articles, and both adult men and women in 33 articles. During the 10 year period of review, only 62 articles were published analysing routinely collected HIV data in Zambia. Serious consideration needs to be made to maximise the utility of routinely collected data, and to benefit from the funds and efforts to collect these data. This could be achieved with government support

Distance Learners' Perspective on User-Friendly Instructional Materials at the University of Zambia

ERIC Educational Resources Information Center

Simui, F.; Thompson, L. C.; Mundende, K.; Mwewa, G.; Kakana, F.; Chishiba, A.; Namangala, B.

2017-01-01

This case study focuses on print-based instructional materials available to distance education learners at the University of Zambia. Using the Visual Paradigm Software, we model distance education learners' voices into sociograms to make a contribution to the ongoing discourse on quality distance learning in poorly resourced communities. Emerging…

Premature adult mortality in urban Zambia: a repeated population-based cross-sectional study

PubMed Central

Timæus, Ian M; Banda, Richard; Thankian, Kusanthan; Banda, Andrew; Lemba, Musonda; Stringer, Jeffrey S A; Chi, Benjamin H

2016-01-01

Objectives To measure the sex-specific and community-specific mortality rates for adults in Lusaka, Zambia, and to identify potential individual-level, household-level and community-level correlates of premature mortality. We conducted 12 survey rounds of a population-based cross-sectional study between 2004 and 2011, and collected data via a structured interview with a household head. Setting Households in Lusaka District, Zambia, 2004–2011. Participants 43 064 household heads (88% female) who enumerated 123 807 adult household members aged between 15 and 60 years. Primary outcome Premature adult mortality. Results The overall mortality rate was 16.2/1000 person-years for men and 12.3/1000 person-years for women. The conditional probability of dying between age 15 and 60 (45q15) was 0.626 for men and 0.537 for women. The top three causes of death for men and women were infectious in origin (ie, tuberculosis, HIV and malaria). We observed an over twofold variation of mortality rates between communities. The mortality rate was 1.98 times higher (95% CI 1.57 to 2.51) in households where a family member required nursing care, 1.44 times higher (95% CI 1.22 to 1.71) during the cool dry season, and 1.28 times higher (95% CI 1.06 to 1.54) in communities with low-cost housing. Conclusions To meet Zambia's development goals, further investigation is needed into the factors associated with adult mortality. Mortality can potentially be reduced through focus on high-need households and communities, and improved infectious disease prevention and treatment services. PMID:26940113

Geostatistical uncertainty of assessing air quality using high-spatial-resolution lichen data: A health study in the urban area of Sines, Portugal.

PubMed

Ribeiro, Manuel C; Pinho, P; Branquinho, C; Llop, Esteve; Pereira, Maria J

2016-08-15

In most studies correlating health outcomes with air pollution, personal exposure assignments are based on measurements collected at air-quality monitoring stations not coinciding with health data locations. In such cases, interpolators are needed to predict air quality in unsampled locations and to assign personal exposures. Moreover, a measure of the spatial uncertainty of exposures should be incorporated, especially in urban areas where concentrations vary at short distances due to changes in land use and pollution intensity. These studies are limited by the lack of literature comparing exposure uncertainty derived from distinct spatial interpolators. Here, we addressed these issues with two interpolation methods: regression Kriging (RK) and ordinary Kriging (OK). These methods were used to generate air-quality simulations with a geostatistical algorithm. For each method, the geostatistical uncertainty was drawn from generalized linear model (GLM) analysis. We analyzed the association between air quality and birth weight. Personal health data (n=227) and exposure data were collected in Sines (Portugal) during 2007-2010. Because air-quality monitoring stations in the city do not offer high-spatial-resolution measurements (n=1), we used lichen data as an ecological indicator of air quality (n=83). We found no significant difference in the fit of GLMs with any of the geostatistical methods. With RK, however, the models tended to fit better more often and worse less often. Moreover, the geostatistical uncertainty results showed a marginally higher mean and precision with RK. Combined with lichen data and land-use data of high spatial resolution, RK is a more effective geostatistical method for relating health outcomes with air quality in urban areas. This is particularly important in small cities, which generally do not have expensive air-quality monitoring stations with high spatial resolution. Further, alternative ways of linking human activities with their

An analytical perspective of Global health initiatives in Tanzania and Zambia.

PubMed

Mwisongo, Aziza; Soumare, Alice Ntamwishimiro; Nabyonga-Orem, Juliet

2016-07-18

A number of Global health initiatives (GHIs) have been created to support low and middle income countries. Their support has been of different forms. The African Region has benefitted immensely from GHIs and continues to register an increase in health partnerships and initiatives. However, information on the functioning and operationalisation of GHIs in the countries is limited. This study involved two country case studies, one in Tanzania and the other one in Zambia. Data were collected using a semi-structured questionnaire. The aims were to understand and profile the GHIs supporting health development and to assess their governance and alignment with country priorities, harmonisation and alignment of their interventions and efforts, and contribution towards health systems strengthening. The respondents included senior officers from health stakeholder agencies at the national and sub-national levels. The qualitative data were analysed using thematic content analysis in MAXQDA software. Health systems in both Tanzania and Zambia are decentralised. They have benefitted from GHI support in fighting the common health problems of HIV/AIDS, tuberculosis, malaria and vaccine-preventable diseases. In both countries, no GHI adequately made use of the existing Sector-wide Approach (SWAp) mechanisms but they largely operate through their unique structures and committees. GHI efforts to improve general health governance have not been matched with similar efforts from the countries. Their support to health system strengthening has not been comprehensive but has involved the selection of a few areas some of which were disease-focused. On the positive side, however, in both Tanzania and Zambia improved alignment with the countries' priorities is noted in that most of the proposals submitted to the GHIs refer to the priorities, objectives and strategies in the national health development plans and, GHIs depend on the national health information systems. GHIs are important funders

"These things are dangerous": Understanding induced abortion trajectories in urban Zambia.

PubMed

Coast, Ernestina; Murray, Susan F

2016-03-01

Unsafe abortion is a significant but preventable cause of global maternal mortality and morbidity. Zambia has among the most liberal abortion laws in sub-Saharan Africa, however this alone does not guarantee access to safe abortion, and 30% of maternal mortality is attributable to unsafe procedures. Too little is known about the pathways women take to reach abortion services in such resource-poor settings, or what informs care-seeking behaviours, barriers and delays. In-depth qualitative interviews were conducted in 2013 with 112 women who accessed abortion-related care in a Lusaka tertiary government hospital at some point in their pathway. The sample included women seeking safe abortion and also those receiving hospital care following unsafe abortion. We identified a typology of three care-seeking trajectories that ended in the use of hospital services: clinical abortion induced in hospital; clinical abortion initiated elsewhere, with post-abortion care in hospital; and non-clinical abortion initiated elsewhere, with post-abortion care in hospital. Framework analyses of 70 transcripts showed that trajectories to a termination of an unwanted pregnancy can be complex and iterative. Individuals may navigate private and public formal healthcare systems and consult unqualified providers, often trying multiple strategies. We found four major influences on which trajectory a woman followed, as well as the complexity and timing of her trajectory: i) the advice of trusted others ii) perceptions of risk iii) delays in care-seeking and receipt of services and iv) economic cost. Even though abortion is legal in Zambia, girls and women still take significant risks to terminate unwanted pregnancies. Levels of awareness about the legality of abortion and its provision remain low even in urban Zambia, especially among adolescents. Unofficial payments required by some providers can be a major barrier to safe care. Timely access to safe abortion services depends on chance rather

Surgical Capacity at District Hospitals in Zambia: From 2012 to 2016.

PubMed

Cheelo, Mweene; Brugha, Ruairi; Bijlmakers, Leon; Kachimba, John; McCauley, Tracey; Gajewski, Jakub

2018-05-21

Sub-Saharan Africa has one of the highest burdens of surgically treatable conditions in the world and the highest unmet need, especially in rural areas. Zambia is one of the countries in the region taking steps to improve surgical care for its rural populations. To demonstrate changes in surgical capacity in Zambia's district hospitals over a 3-year period and to provide a baseline from which future interventions in surgical care can be assessed. A cross-sectional assessment of surgical capacity, using a modified WHO questionnaire, was administered in first-level hospitals in nine of Zambia's ten provinces between November 2012 and February 2013 and again between February and April 2016. The two assessments allowed measurement of changes in surgical workforce, infrastructure, equipment, drugs and consumables; and numbers of major surgical procedures performed over two 12-month periods prior to the assessments. There was a significant increase, 2013-2016, in number of theatre staff, from 174 (mean 4.4; SD 1.7) to 235 (mean 6; SD 2.9), P = 0.02. However, the percentage of hospitals with functioning anaesthetic machines dropped from 64 to 41%. There was also a drop in hospitals reporting availability of instruments, drugs and consumables from 38 to 24 (97-62%) and from 28 to 24 (72-62%), respectively. The median number of caesarean sections in 2012 was 99 [interquartile range (IQR) 42-187] and 100 (IQR 42-126) in 2015 (P value =0.53). The median number of major surgical procedures in 2012 was 54 (IQR 10-113) and 66 (IQR 18-168) in 2015 (P = 0.45). An increase in the first-level hospital surgical workforce between 2013 and 2016 was accompanied by reductions in essential equipment and consumables for surgery, and no changes in surgical output. Periodic monitoring of resource availability is needed to address shortages and make safe surgery available to rural populations.

Adherence to Point-of-Use Water Treatment over Short-Term Implementation: Parallel Crossover Trials of Flocculation-Disinfection Sachets in Pakistan and Zambia.

PubMed

Shaheed, A; Rathore, S; Bastable, A; Bruce, J; Cairncross, S; Brown, J

2018-06-05

The health benefits of point-of-use (POU) water treatment can only be realized through high adherence: correct, consistent, and sustained use. We conducted parallel randomized, longitudinal crossover trials measuring short-term adherence to two single-use flocculant-disinfectant sachets in Pakistan and Zambia. In both trials, adherence declined sharply for both products over the eight week surveillance periods, with overall lower adherence to both products in Zambia. There was no significant difference in adherence between the two products. Estimated median daily production of treated water dropped over the crossover period from 2.5 to 1.4 L person -1 day -1 (46% decline) in Pakistan and from 1.4 to 1.1 L person -1 day -1 (21% decline) in Zambia. The percentage of surveillance points with detectable total chlorine in household drinking water declined from 70% to 49% in Pakistan and rose marginally from 28% to 30% in Zambia. The relatively low and decreasing adherence observed in this study suggests that these products would have provided little protection from waterborne disease risk in these settings. Our findings underscore the challenge of achieving high adherence to POU water treatment, even under conditions of short-term adoption with intensive follow-up.

Prevalence and predictors of squamous intraepithelial lesions of the cervix in HIV-infected women in Lusaka, Zambia

PubMed Central

Parham, Groesbeck P.; Sahasrabuddhe, Vikrant V.; Mwanahamuntu, Mulindi H.; Shepherd, Bryan E.; Hicks, Michael L.; Stringer, Elizabeth M.; Vermund, Sten H.

2009-01-01

Objectives HIV-infected women living in resource-constrained nations like Zambia are now accessing antiretroviral therapy and thus may live long enough for HPV-induced cervical cancer to manifest and progress. We evaluated the prevalence and predictors of cervical squamous intraepithelial lesions (SIL) among HIV-infected women in Zambia. Methods We screened 150 consecutive, non-pregnant HIV-infected women accessing HIV/AIDS care services in Lusaka, Zambia. We collected cervical specimens for cytological analysis by liquid-based monolayer cytology (ThinPrep Pap Test®) and HPV typing using the Roche Linear Array® PCR assay. Results The median age of study participants was 36 years (range 23-49 years) and their median CD4+ count was 165/μL (range 7-942). The prevalence of SIL on cytology was 76% (114/150), of which 23.3% (35/150) women had low-grade SIL, 32.6% (49/150) had high-grade SIL, and 20% (30/150) had lesions suspicious for squamous cell carcinoma (SCC). High-risk HPV types were present in 85.3% (128/150) women. On univariate analyses, age of the participant, CD4+ cell count, and presence of any high-risk HPV type were significantly associated with the presence of severely abnormal cytological lesions (i.e., high-grade SIL and lesions suspicious for SCC). Multivariable logistic regression modeling suggested the presence of any high-risk HPV type as an independent predictor of severely abnormal cytology (adjusted OR: 12.4, 95% CI 2.62-58.1, p=0.02). Conclusions The high prevalence of abnormal squamous cytology in our study is one of the highest reported in any population worldwide. Screening of HIV-infected women in resource-constrained settings like Zambia should be implemented to prevent development of HPV-induced SCC. PMID:16875716

"Health regains but livelihoods lag": findings from a study with people on ART in Zambia and Kenya.

PubMed

Samuels, Fiona A; Rutenberg, Naomi

2011-06-01

Although ART is increasingly accessible and eases some stresses, it creates other challenges including the importance of food security to enhance ART-effectiveness. This paper explores the role livelihood strategies play in achieving food security and maintaining nutritional status among ART patients in Kenya and Zambia. Ongoing quantitative studies exploring adherence to ART in Mombasa, Kenya (n=118) and in Lusaka, Zambia (n=375) were used to identify the relationship between BMI and adherence; an additional set of in-depth interviews with people on ART (n=32) and members of their livelihood networks (n=64) were undertaken. Existing frameworks and scales for measuring food security and a positive deviance approach was used to analyse data. Findings show the majority of people on ART in Zambia are food insecure; similarly most respondents in both countries report missing meals. Snacking is important for dietary intake, especially in Kenya. Most food is purchased in both countries. Having assets is key for achieving livelihood security in both Kenya and Zambia. Food supplementation is critical to survival and for developing social capital since most is shared amongst family members and others. Whilst family and friends are key to an individual's livelihood network, often more significant for daily survival is proximity to people and the ability to act immediately, characteristics most often found amongst neighbours and tenants. In both countries findings show that with ART health has rebounded but livelihoods lag. Similarly, in both countries respondents with high adherence and high BMI are more self-reliant, have multiple income sources and assets; those with low adherence and low BMI have more tenuous livelihoods and were less likely to have farms/gardens. Food supplementation is, therefore, not a long-term solution. Building on existing livelihood strategies represents an alternative for programme managers and policy-makers as do other strategies including

Bayesian flood forecasting methods: A review

NASA Astrophysics Data System (ADS)

Han, Shasha; Coulibaly, Paulin

2017-08-01

Over the past few decades, floods have been seen as one of the most common and largely distributed natural disasters in the world. If floods could be accurately forecasted in advance, then their negative impacts could be greatly minimized. It is widely recognized that quantification and reduction of uncertainty associated with the hydrologic forecast is of great importance for flood estimation and rational decision making. Bayesian forecasting system (BFS) offers an ideal theoretic framework for uncertainty quantification that can be developed for probabilistic flood forecasting via any deterministic hydrologic model. It provides suitable theoretical structure, empirically validated models and reasonable analytic-numerical computation method, and can be developed into various Bayesian forecasting approaches. This paper presents a comprehensive review on Bayesian forecasting approaches applied in flood forecasting from 1999 till now. The review starts with an overview of fundamentals of BFS and recent advances in BFS, followed with BFS application in river stage forecasting and real-time flood forecasting, then move to a critical analysis by evaluating advantages and limitations of Bayesian forecasting methods and other predictive uncertainty assessment approaches in flood forecasting, and finally discusses the future research direction in Bayesian flood forecasting. Results show that the Bayesian flood forecasting approach is an effective and advanced way for flood estimation, it considers all sources of uncertainties and produces a predictive distribution of the river stage, river discharge or runoff, thus gives more accurate and reliable flood forecasts. Some emerging Bayesian forecasting methods (e.g. ensemble Bayesian forecasting system, Bayesian multi-model combination) were shown to overcome limitations of single model or fixed model weight and effectively reduce predictive uncertainty. In recent years, various Bayesian flood forecasting approaches have been

Taenia solium from a community perspective: Preliminary costing data in the Katete and Sinda districts in Eastern Zambia.

PubMed

Hobbs, Emma C; Mwape, Kabemba E; Devleesschauwer, Brecht; Gabriël, Sarah; Chembensofu, Mwelwa; Mambwe, Moses; Phiri, Isaac K; Masuku, Maxwell; Zulu, Gideon; Colston, Angela; Willingham, Arve Lee; Berkvens, Dirk; Dorny, Pierre; Bottieau, Emmanuel; Speybroeck, Niko

2018-02-15

The tapeworm Taenia solium is endemic in Zambia, however its socioeconomic cost is unknown. During a large-scale interventional study conducted in Zambia, baseline economic costs of human and porcine T. solium infections were measured. Questionnaire surveys were conducted within three neighbourhoods in Zambia's Eastern province in 2015 and 2016. A human health questionnaire, capturing costs of clinical symptoms commonly attributable to human cysticercosis and taeniasis, was conducted in randomly selected households (n = 267). All pig-keeping households were administered a pig socioeconomic questionnaire (n = 271) that captured pig demographic data, costs of pig-keeping, and economic losses from porcine cysticercosis. Of all respondents 62% had reportedly experienced at least one of the surveyed symptoms. Seizure-like episodes were reported by 12%, severe chronic headaches by 36%, and vision problems by 23% of respondents. These complaints resulted in 147 health care consultations and 17 hospitalizations in the five years preceding the study, and an estimated productivity loss of 608 working days per year. Of all pigs 69% were bought within villages. Nearly all adult pigs were sold to local traders, and tongue palpation for detection of cysticerci was commonly performed. Reportedly, 95% of pig owners could not sell tongue-positive pigs, while infected pigs fetched only 45% of the normal sale value. These preliminary costing data indicate that human and porcine T. solium infections substantially impact endemic areas of Eastern Zambia. A full socioeconomic burden assessment may enable improved T. solium management in sub-Saharan Africa. Copyright © 2018 Ross University School of Veterinary Medicine. Published by Elsevier B.V. All rights reserved.

Early Childhood Care and Education in Zambia: An Integral Part of Educational Provision?

ERIC Educational Resources Information Center

Thomas, Carolyn M.; Thomas, Matthew A. M.

2009-01-01

The field of international development has recently been consumed by a shift in contemporary educational discourse, one that moves Early Childhood Care and Education (ECCE) closer to the forefront of what is considered progressive policy formation. In Zambia, the current educational environment seems to indicate that the creation and continued…

Factors Related to Pre-Service Teachers' Attitudes towards Inclusion: A Case for Zambia

ERIC Educational Resources Information Center

Muwana, Florence Chuzu; Ostrosky, Michaelene M.

2014-01-01

Inclusive education has become a global trend in the provision of services for students with disabilities. In Zambia and other developing nations, international initiatives from UNESCO and other nongovernmental organisations have contributed to the consensus that all children have a right to a free and appropriate education and that all students…

Impact of inaccessible spaces on community participation of people with mobility limitations in Zambia

PubMed Central

Nitz, Jennifer C.; de Jonge, Desleigh

2014-01-01

Background The study investigated the perspective of people with mobility limitations (PWML) in Zambia, firstly of their accessibility to public buildings and spaces, and secondly of how their capacity to participate in a preferred lifestyle has been affected. Objectives Firstly to provide insight into the participation experiences of PWML in the social, cultural, economic, political and civic life areas and the relationship of these with disability in Zambia. Secondly to establish how the Zambian disability context shape the experiences of participation by PWML. Method A qualitative design was used to gather data from 75 PWML in five of the nine provinces of Zambia. Focus group discussions and personal interviews were used to examine the accessibility of the built environment and how this impacted on the whole family’s participation experiences. The nominal group technique was utilised to rank inaccessible buildings and facilities which posed barriers to opportunities in life areas and how this interfered with the whole family’s lifestyle. Results Inaccessibility of education institutions, workplaces and spaces have contributed to reduced participation with negative implications for personal, family, social and economic aspects of the lives of participants. Government buildings, service buildings, and transportation were universally identified as most important but least accessible. Conclusion Zambians with mobility limitations have been disadvantaged in accessing services and facilities provided to the public, depriving them and their dependants of full and equitable life participation because of reduced economic capacity. This study will assist in informing government of the need to improve environmental access to enable equal rights for all citizens. PMID:28729994

Socio-economic gradients in prevalent tuberculosis in Zambia and the Western Cape of South Africa.

PubMed

Yates, Tom A; Ayles, Helen; Leacy, Finbarr P; Schaap, A; Boccia, Delia; Beyers, Nulda; Godfrey-Faussett, Peter; Floyd, Sian

2018-04-01

To describe the associations between socio-economic position and prevalent tuberculosis in the 2010 ZAMSTAR Tuberculosis Prevalence Survey, one of the first large tuberculosis prevalence surveys in Southern Africa in the HIV era. The main analyses used data on 34 446 individuals in Zambia and 30 017 individuals in South Africa with evaluable tuberculosis culture results. Logistic regression was used to estimate adjusted odds ratios for prevalent TB by two measures of socio-economic position: household wealth, derived from data on assets using principal components analysis, and individual educational attainment. Mediation analysis was used to evaluate potential mechanisms for the observed social gradients. The quartile with highest household wealth index in Zambia and South Africa had, respectively, 0.55 (95% CI 0.33-0.92) times and 0.70 (95% CI 0.54-0.93) times the adjusted odds of prevalent TB of the bottom quartile. College or university-educated individuals in Zambia and South Africa had, respectively, 0.25 (95% CI 0.12-0.54) and 0.42 (95% CI 0.25-0.70) times the adjusted odds of prevalent TB of individuals who had received only primary education. We found little evidence that these associations were mediated via several key proximal risk factors for TB, including HIV status. These data suggest that social determinants of TB remain important even in the context of generalised HIV epidemics. © 2018 The Authors. Tropical Medicine & International Health Published by John Wiley & Sons Ltd.

Gender, British Administration and Mission Management of Education in Zambia 1900-1939

ERIC Educational Resources Information Center

Allen, Julia

2010-01-01

This article discusses the impact of including gender in the analytical framework in a study of the management and provision of education in Zambia from 1900 to 1939. It shows that a focus on gender allows females to enter the historical narrative and the leadership of women such as Mabel Shaw, Hannah Frances Davidson and Julia Smith can be given…

Downscaling remotely sensed imagery using area-to-point cokriging and multiple-point geostatistical simulation

NASA Astrophysics Data System (ADS)

Tang, Yunwei; Atkinson, Peter M.; Zhang, Jingxiong

2015-03-01

A cross-scale data integration method was developed and tested based on the theory of geostatistics and multiple-point geostatistics (MPG). The goal was to downscale remotely sensed images while retaining spatial structure by integrating images at different spatial resolutions. During the process of downscaling, a rich spatial correlation model in the form of a training image was incorporated to facilitate reproduction of similar local patterns in the simulated images. Area-to-point cokriging (ATPCK) was used as locally varying mean (LVM) (i.e., soft data) to deal with the change of support problem (COSP) for cross-scale integration, which MPG cannot achieve alone. Several pairs of spectral bands of remotely sensed images were tested for integration within different cross-scale case studies. The experiment shows that MPG can restore the spatial structure of the image at a fine spatial resolution given the training image and conditioning data. The super-resolution image can be predicted using the proposed method, which cannot be realised using most data integration methods. The results show that ATPCK-MPG approach can achieve greater accuracy than methods which do not account for the change of support issue.

Organization of Distance Education at the University of Zambia: An Analysis of the Practice.

ERIC Educational Resources Information Center

Nyirenda, Juma E.

1989-01-01

Discussion of two basic organizational models for distance education systems or institutions focuses on the mixed-mode organization at the University of Zambia. Highlights include the development, production, storage, and distribution of teaching materials; communication channels between students and teachers; and the record-keeping system. (11…

High Performance Geostatistical Modeling of Biospheric Resources

NASA Astrophysics Data System (ADS)

Pedelty, J. A.; Morisette, J. T.; Smith, J. A.; Schnase, J. L.; Crosier, C. S.; Stohlgren, T. J.

2004-12-01

We are using parallel geostatistical codes to study spatial relationships among biospheric resources in several study areas. For example, spatial statistical models based on large- and small-scale variability have been used to predict species richness of both native and exotic plants (hot spots of diversity) and patterns of exotic plant invasion. However, broader use of geostastics in natural resource modeling, especially at regional and national scales, has been limited due to the large computing requirements of these applications. To address this problem, we implemented parallel versions of the kriging spatial interpolation algorithm. The first uses the Message Passing Interface (MPI) in a master/slave paradigm on an open source Linux Beowulf cluster, while the second is implemented with the new proprietary Xgrid distributed processing system on an Xserve G5 cluster from Apple Computer, Inc. These techniques are proving effective and provide the basis for a national decision support capability for invasive species management that is being jointly developed by NASA and the US Geological Survey.

Estimating Loss to Follow-Up in HIV-Infected Patients on Antiretroviral Therapy: The Effect of the Competing Risk of Death in Zambia and Switzerland

PubMed Central

Mwango, Albert; Stringer, Jeffrey; Ledergerber, Bruno; Mulenga, Lloyd; Bucher, Heiner C.; Westfall, Andrew O.; Calmy, Alexandra; Boulle, Andrew; Chintu, Namwinga; Egger, Matthias; Chi, Benjamin H.

2011-01-01

Background Loss to follow-up (LTFU) is common in antiretroviral therapy (ART) programmes. Mortality is a competing risk (CR) for LTFU; however, it is often overlooked in cohort analyses. We examined how the CR of death affected LTFU estimates in Zambia and Switzerland. Methods and Findings HIV-infected patients aged ≥18 years who started ART 2004–2008 in observational cohorts in Zambia and Switzerland were included. We compared standard Kaplan-Meier curves with CR cumulative incidence. We calculated hazard ratios for LTFU across CD4 cell count strata using cause-specific Cox models, or Fine and Gray subdistribution models, adjusting for age, gender, body mass index and clinical stage. 89,339 patients from Zambia and 1,860 patients from Switzerland were included. 12,237 patients (13.7%) in Zambia and 129 patients (6.9%) in Switzerland were LTFU and 8,498 (9.5%) and 29 patients (1.6%), respectively, died. In Zambia, the probability of LTFU was overestimated in Kaplan-Meier curves: estimates at 3.5 years were 29.3% for patients starting ART with CD4 cells <100 cells/µl and 15.4% among patients starting with ≥350 cells/µL. The estimates from CR cumulative incidence were 22.9% and 13.6%, respectively. Little difference was found between naïve and CR analyses in Switzerland since only few patients died. The results from Cox and Fine and Gray models were similar: in Zambia the risk of loss to follow-up and death increased with decreasing CD4 counts at the start of ART, whereas in Switzerland there was a trend in the opposite direction, with patients with higher CD4 cell counts more likely to be lost to follow-up. Conclusions In ART programmes in low-income settings the competing risk of death can substantially bias standard analyses of LTFU. The CD4 cell count and other prognostic factors may be differentially associated with LTFU in low-income and high-income settings. PMID:22205933

Un/Doing Gender? A Case Study of School Policy and Practice in Zambia

ERIC Educational Resources Information Center

Bajaj, Monisha

2009-01-01

This article explores an attempt to disrupt gender inequality in a unique, low-cost private school in Ndola, Zambia. It examines deliberate school policies aimed at "undoing gender" or fostering greater gender equity. These include efforts to maintain gender parity at all levels of the school and the requirement that both young men and…

Callings, Work Role Fit, Psychological Meaningfulness and Work Engagement among Teachers in Zambia

ERIC Educational Resources Information Center

Rothmann, Sebastiaan; Hamukang'andu, Lukondo

2013-01-01

Our aim in this study was to investigate the relationships among a calling orientation, work role fit, psychological meaningfulness and work engagement of teachers in Zambia. A quantitative approach was followed and a cross-sectional survey was used. The sample (n = 150) included 75 basic and 75 secondary school teachers in the Choma district of…

Access, Quality, and Opportunity: A Case Study of Zambia Open Community Schools (ZOCS)

ERIC Educational Resources Information Center

Mwalimu, Michelle

2011-01-01

Community schools and other approaches to Alternative Primary Education or APE have increased access to primary education for underserved populations in Africa, Asia, and Latin America as a major goal of the Education for All (EFA) movement. In Zambia, a country where an estimated 20 percent of the basic education enrollment now attends community…

Hepatitis disease detection using Bayesian theory

NASA Astrophysics Data System (ADS)

Maseleno, Andino; Hidayati, Rohmah Zahroh

2017-02-01

This paper presents hepatitis disease diagnosis using a Bayesian theory for better understanding of the theory. In this research, we used a Bayesian theory for detecting hepatitis disease and displaying the result of diagnosis process. Bayesian algorithm theory is rediscovered and perfected by Laplace, the basic idea is using of the known prior probability and conditional probability density parameter, based on Bayes theorem to calculate the corresponding posterior probability, and then obtained the posterior probability to infer and make decisions. Bayesian methods combine existing knowledge, prior probabilities, with additional knowledge derived from new data, the likelihood function. The initial symptoms of hepatitis which include malaise, fever and headache. The probability of hepatitis given the presence of malaise, fever, and headache. The result revealed that a Bayesian theory has successfully identified the existence of hepatitis disease.

Bayesian Fundamentalism or Enlightenment? On the explanatory status and theoretical contributions of Bayesian models of cognition.

PubMed

Jones, Matt; Love, Bradley C

2011-08-01

The prominence of Bayesian modeling of cognition has increased recently largely because of mathematical advances in specifying and deriving predictions from complex probabilistic models. Much of this research aims to demonstrate that cognitive behavior can be explained from rational principles alone, without recourse to psychological or neurological processes and representations. We note commonalities between this rational approach and other movements in psychology - namely, Behaviorism and evolutionary psychology - that set aside mechanistic explanations or make use of optimality assumptions. Through these comparisons, we identify a number of challenges that limit the rational program's potential contribution to psychological theory. Specifically, rational Bayesian models are significantly unconstrained, both because they are uninformed by a wide range of process-level data and because their assumptions about the environment are generally not grounded in empirical measurement. The psychological implications of most Bayesian models are also unclear. Bayesian inference itself is conceptually trivial, but strong assumptions are often embedded in the hypothesis sets and the approximation algorithms used to derive model predictions, without a clear delineation between psychological commitments and implementational details. Comparing multiple Bayesian models of the same task is rare, as is the realization that many Bayesian models recapitulate existing (mechanistic level) theories. Despite the expressive power of current Bayesian models, we argue they must be developed in conjunction with mechanistic considerations to offer substantive explanations of cognition. We lay out several means for such an integration, which take into account the representations on which Bayesian inference operates, as well as the algorithms and heuristics that carry it out. We argue this unification will better facilitate lasting contributions to psychological theory, avoiding the pitfalls

Estimation of Groundwater Radon in North Carolina Using Land Use Regression and Bayesian Maximum Entropy.

PubMed

Messier, Kyle P; Campbell, Ted; Bradley, Philip J; Serre, Marc L

2015-08-18

Radon ((222)Rn) is a naturally occurring chemically inert, colorless, and odorless radioactive gas produced from the decay of uranium ((238)U), which is ubiquitous in rocks and soils worldwide. Exposure to (222)Rn is likely the second leading cause of lung cancer after cigarette smoking via inhalation; however, exposure through untreated groundwater is also a contributing factor to both inhalation and ingestion routes. A land use regression (LUR) model for groundwater (222)Rn with anisotropic geological and (238)U based explanatory variables is developed, which helps elucidate the factors contributing to elevated (222)Rn across North Carolina. The LUR is also integrated into the Bayesian Maximum Entropy (BME) geostatistical framework to increase accuracy and produce a point-level LUR-BME model of groundwater (222)Rn across North Carolina including prediction uncertainty. The LUR-BME model of groundwater (222)Rn results in a leave-one out cross-validation r(2) of 0.46 (Pearson correlation coefficient = 0.68), effectively predicting within the spatial covariance range. Modeled results of (222)Rn concentrations show variability among intrusive felsic geological formations likely due to average bedrock (238)U defined on the basis of overlying stream-sediment (238)U concentrations that is a widely distributed consistently analyzed point-source data.

Bayesian Maximum Entropy space/time estimation of surface water chloride in Maryland using river distances.

PubMed

Jat, Prahlad; Serre, Marc L

2016-12-01

Widespread contamination of surface water chloride is an emerging environmental concern. Consequently accurate and cost-effective methods are needed to estimate chloride along all river miles of potentially contaminated watersheds. Here we introduce a Bayesian Maximum Entropy (BME) space/time geostatistical estimation framework that uses river distances, and we compare it with Euclidean BME to estimate surface water chloride from 2005 to 2014 in the Gunpowder-Patapsco, Severn, and Patuxent subbasins in Maryland. River BME improves the cross-validation R 2 by 23.67% over Euclidean BME, and river BME maps are significantly different than Euclidean BME maps, indicating that it is important to use river BME maps to assess water quality impairment. The river BME maps of chloride concentration show wide contamination throughout Baltimore and Columbia-Ellicott cities, the disappearance of a clean buffer separating these two large urban areas, and the emergence of multiple localized pockets of contamination in surrounding areas. The number of impaired river miles increased by 0.55% per year in 2005-2009 and by 1.23% per year in 2011-2014, corresponding to a marked acceleration of the rate of impairment. Our results support the need for control measures and increased monitoring of unassessed river miles. Copyright © 2016. Published by Elsevier Ltd.

Health and agricultural productivity: Evidence from Zambia.

PubMed

Fink, Günther; Masiye, Felix

2015-07-01

We evaluate the productivity effects of investment in preventive health technology through a randomized controlled trial in rural Zambia. In the experiment, access to subsidized bed nets was randomly assigned at the community level; 516 farmers were followed over a one-year farming period. We find large positive effects of preventative health investment on productivity: among farmers provided with access to free nets, harvest value increased by US$ 76, corresponding to about 14.7% of the average output value. While only limited information was collected on farming inputs, shifts in the extensive and the intensive margins of labor supply appear to be the most likely mechanism underlying the productivity improvements observed. Copyright © 2015 Elsevier B.V. All rights reserved.

Strengthening Faculty Recruitment for Health Professions Training in Basic Sciences in Zambia

PubMed Central

Simuyemba, Moses; Talib, Zohray; Michelo, Charles; Mutale, Wilbroad; Zulu, Joseph; Andrews, Ben; Katubulushi, Max; Njelesani, Evariste; Bowa, Kasonde; Maimbolwa, Margaret; Mudenda, John; Mulla, Yakub

2014-01-01

Zambia is facing a crisis in its human resources for health (HRH), with deficits in the number and skill mix of health workers. The University of Zambia School of Medicine (UNZA SOM) was the only medical school in the country for decades, but recently it was joined by three new medical schools—two private and one public. In addition to expanding medical education, the government has also approved several allied health programs, including pharmacy, physiotherapy, biomedical sciences, and environmental health. This expansion has been constrained by insufficient numbers of faculty. Through a grant from the Medical Education Partnership Initiative (MEPI), UNZA SOM has been investing in ways to address faculty recruitment, training, and retention. The MEPI-funded strategy involves directly sponsoring a cohort of faculty at UNZA SOM during the five-year grant, as well as establishing more than a dozen new master’s programs, with the goal that all sponsored faculty are locally trained and retained. Because the issue of limited basic science faculty plagues medical schools throughout Sub-Saharan Africa, this strategy of using seed funding to build sustainable local capacity to recruit, train, and retain faculty could be a model for the region. PMID:25072591

School effects on non-verbal intelligence and nutritional status in rural Zambia

PubMed Central

Hein, Sascha; Tan, Mei; Reich, Jodi; Thuma, Philip E.; Grigorenko, Elena L.

2015-01-01

This study uses hierarchical linear modeling (HLM) to examine the school factors (i.e., related to school organization and teacher and student body) associated with non-verbal intelligence (NI) and nutritional status (i.e., body mass index; BMI) of 4204 3rd to 7th graders in rural areas of Southern Province, Zambia. Results showed that 23.5% and 7.7% of the NI and BMI variance, respectively, were conditioned by differences between schools. The set of 14 school factors accounted for 58.8% and 75.9% of the between-school differences in NI and BMI, respectively. Grade-specific HLM yielded higher between-school variation of NI (41%) and BMI (14.6%) for students in grade 3 compared to grades 4 to 7. School factors showed a differential pattern of associations with NI and BMI across grades. The distance to a health post and teacher’s teaching experience were the strongest predictors of NI (particularly in grades 4, 6 and 7); the presence of a preschool was linked to lower BMI in grades 4 to 6. Implications for improving access and quality of education in rural Zambia are discussed. PMID:27175053

Strengthening faculty recruitment for health professions training in basic sciences in Zambia.

PubMed

Simuyemba, Moses; Talib, Zohray; Michelo, Charles; Mutale, Wilbroad; Zulu, Joseph; Andrews, Ben; Nzala, Selestine; Katubulushi, Max; Njelesani, Evariste; Bowa, Kasonde; Maimbolwa, Margaret; Mudenda, John; Mulla, Yakub

2014-08-01

Zambia is facing a crisis in its human resources for health, with deficits in the number and skill mix of health workers. The University of Zambia School of Medicine (UNZA SOM) was the only medical school in the country for decades, but recently it was joined by three new medical schools--two private and one public. In addition to expanding medical education, the government has also approved several allied health programs, including pharmacy, physiotherapy, biomedical sciences, and environmental health. This expansion has been constrained by insufficient numbers of faculty. Through a grant from the Medical Education Partnership Initiative (MEPI), UNZA SOM has been investing in ways to address faculty recruitment, training, and retention. The MEPI-funded strategy involves directly sponsoring a cohort of faculty at UNZA SOM during the five-year grant, as well as establishing more than a dozen new master's programs, with the goal that all sponsored faculty are locally trained and retained. Because the issue of limited basic science faculty plagues medical schools throughout Sub-Saharan Africa, this strategy of using seed funding to build sustainable local capacity to recruit, train, and retain faculty could be a model for the region.

A local approach for focussed Bayesian fusion

NASA Astrophysics Data System (ADS)

Sander, Jennifer; Heizmann, Michael; Goussev, Igor; Beyerer, Jürgen

2009-04-01

Local Bayesian fusion approaches aim to reduce high storage and computational costs of Bayesian fusion which is separated from fixed modeling assumptions. Using the small world formalism, we argue why this proceeding is conform with Bayesian theory. Then, we concentrate on the realization of local Bayesian fusion by focussing the fusion process solely on local regions that are task relevant with a high probability. The resulting local models correspond then to restricted versions of the original one. In a previous publication, we used bounds for the probability of misleading evidence to show the validity of the pre-evaluation of task specific knowledge and prior information which we perform to build local models. In this paper, we prove the validity of this proceeding using information theoretic arguments. For additional efficiency, local Bayesian fusion can be realized in a distributed manner. Here, several local Bayesian fusion tasks are evaluated and unified after the actual fusion process. For the practical realization of distributed local Bayesian fusion, software agents are predestinated. There is a natural analogy between the resulting agent based architecture and criminal investigations in real life. We show how this analogy can be used to improve the efficiency of distributed local Bayesian fusion additionally. Using a landscape model, we present an experimental study of distributed local Bayesian fusion in the field of reconnaissance, which highlights its high potential.

Planning spatial sampling of the soil from an uncertain reconnaissance variogram

NASA Astrophysics Data System (ADS)

Lark, R. Murray; Hamilton, Elliott M.; Kaninga, Belinda; Maseka, Kakoma K.; Mutondo, Moola; Sakala, Godfrey M.; Watts, Michael J.

2017-12-01

An estimated variogram of a soil property can be used to support a rational choice of sampling intensity for geostatistical mapping. However, it is known that estimated variograms are subject to uncertainty. In this paper we address two practical questions. First, how can we make a robust decision on sampling intensity, given the uncertainty in the variogram? Second, what are the costs incurred in terms of oversampling because of uncertainty in the variogram model used to plan sampling? To achieve this we show how samples of the posterior distribution of variogram parameters, from a computational Bayesian analysis, can be used to characterize the effects of variogram parameter uncertainty on sampling decisions. We show how one can select a sample intensity so that a target value of the kriging variance is not exceeded with some specified probability. This will lead to oversampling, relative to the sampling intensity that would be specified if there were no uncertainty in the variogram parameters. One can estimate the magnitude of this oversampling by treating the tolerable grid spacing for the final sample as a random variable, given the target kriging variance and the posterior sample values. We illustrate these concepts with some data on total uranium content in a relatively sparse sample of soil from agricultural land near mine tailings in the Copperbelt Province of Zambia.

Fairness and legitimacy of decisions during delivery of malaria services and ITN interventions in Zambia.

PubMed

Tuba, Mary; Sandoy, Ingvild F; Bloch, Paul; Byskov, Jens

2010-11-01

Malaria is the leading cause of morbidity and the second leading cause of mortality in Zambia. Perceptions of fairness and legitimacy of decisions relating to treatment of malaria cases within public health facilities and distribution of ITNs were assessed in a district in Zambia. The study was conducted within the framework of REsponse to ACcountable priority setting for Trust in health systems (REACT), a north-south collaborative action research study, which evaluates the Accountability for Reasonableness (AFR) approach to priority setting in Zambia, Tanzania and Kenya. This paper is based on baseline in-depth interviews (IDIs) conducted with 38 decision-makers, who were involved in prioritization of malaria services and ITN distribution at district, facility and community levels in Zambia, one Focus Group Discussion (FGD) with District Health Management Team managers and eight FGDs with outpatients' attendees. Perceptions and attitudes of providers and users and practices of providers were systematized according to the four AFR conditions relevance, publicity, appeals and leadership. Conflicting criteria for judging fairness were used by decision-makers and patients. Decision-makers argued that there was fairness in delivery of malaria treatment and distribution of ITNs based on alleged excessive supply of free malaria medicines, subsidized ITNs, and presence of a qualified health-provider in every facility. Patients argued that there was unfairness due to differences in waiting time, distances to health facilities, erratic supply of ITNs, no responsive appeal mechanisms, inadequate access to malaria medicines, ITNs and health providers, and uncaring providers. Decision-makers only perceived government bodies and donors/NGOs to be legitimate stakeholders to involve during delivery. Patients found government bodies, patients, indigenous healers, chiefs and politicians to be legitimate stakeholders during both planning and delivery. Poor status of the AFR

Fairness and legitimacy of decisions during delivery of malaria services and ITN interventions in zambia

PubMed Central

2010-01-01

Background Malaria is the leading cause of morbidity and the second leading cause of mortality in Zambia. Perceptions of fairness and legitimacy of decisions relating to treatment of malaria cases within public health facilities and distribution of ITNs were assessed in a district in Zambia. The study was conducted within the framework of REsponse to ACcountable priority setting for Trust in health systems (REACT), a north-south collaborative action research study, which evaluates the Accountability for Reasonableness (AFR) approach to priority setting in Zambia, Tanzania and Kenya. Methods This paper is based on baseline in-depth interviews (IDIs) conducted with 38 decision-makers, who were involved in prioritization of malaria services and ITN distribution at district, facility and community levels in Zambia, one Focus Group Discussion (FGD) with District Health Management Team managers and eight FGDs with outpatients' attendees. Perceptions and attitudes of providers and users and practices of providers were systematized according to the four AFR conditions relevance, publicity, appeals and leadership. Results Conflicting criteria for judging fairness were used by decision-makers and patients. Decision-makers argued that there was fairness in delivery of malaria treatment and distribution of ITNs based on alleged excessive supply of free malaria medicines, subsidized ITNs, and presence of a qualified health-provider in every facility. Patients argued that there was unfairness due to differences in waiting time, distances to health facilities, erratic supply of ITNs, no responsive appeal mechanisms, inadequate access to malaria medicines, ITNs and health providers, and uncaring providers. Decision-makers only perceived government bodies and donors/NGOs to be legitimate stakeholders to involve during delivery. Patients found government bodies, patients, indigenous healers, chiefs and politicians to be legitimate stakeholders during both planning and delivery

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

Education and Zambia's Democratic Development: Reconstituting "Something" from the Predatory Project of Neoliberal Globalization

ERIC Educational Resources Information Center

Abdi, Ali A.; Ellis, Lee

2007-01-01

Zambia, a central African country of about 10 million people, is currently exposed to the nonsubjective forces of globalization, including institutional weaknesses such as high unemployment rated and chronic levels of poverty that ipso facto problematize its governance and social development priorities. The first part of the article focuses on an…

The role of geostatistics in medical geology

NASA Astrophysics Data System (ADS)

Goovaerts, Pierre

2014-05-01

Since its development in the mining industry, geostatistics has emerged as the primary tool for spatial data analysis in various fields, ranging from earth and atmospheric sciences, to agriculture, soil science, remote sensing, and more recently environmental exposure assessment. In the last few years, these tools have been tailored to the field of medical geography or spatial epidemiology, which is concerned with the study of spatial patterns of disease incidence and mortality and the identification of potential 'causes' of disease, such as environmental exposure, diet and unhealthy behaviors, economic or socio-demographic factors. On the other hand, medical geology is an emerging interdisciplinary scientific field studying the relationship between natural geological factors and their effects on human and animal health. This paper provides an introduction to the field of medical geology with an overview of geostatistical methods available for the analysis of geological and health data. Key concepts are illustrated using the mapping of groundwater arsenic concentrations across eleven Michigan counties and the exploration of its relationship to the incidence of prostate cancer at the township level. Arsenic in drinking-water is a major problem and has received much attention because of the large human population exposed and the extremely high concentrations (e.g. 600 to 700 μg/L) recorded in many instances. Few studies have however assessed the risks associated with exposure to low levels of arsenic (say < 50 μg/L) most commonly found in drinking water in the United States. In the Michigan thumb region, arsenopyrite (up to 7% As by weight) has been identified in the bedrock of the Marshall Sandstone aquifer, one of the region's most productive aquifers. Epidemiologic studies have suggested a possible associationbetween exposure to inorganic arsenic and prostate cancer mortality, including a study of populations residing in Utah. The information available for the

Local Geostatistical Models and Big Data in Hydrological and Ecological Applications

NASA Astrophysics Data System (ADS)

Hristopulos, Dionissios

2015-04-01

The advent of the big data era creates new opportunities for environmental and ecological modelling but also presents significant challenges. The availability of remote sensing images and low-cost wireless sensor networks implies that spatiotemporal environmental data to cover larger spatial domains at higher spatial and temporal resolution for longer time windows. Handling such voluminous data presents several technical and scientific challenges. In particular, the geostatistical methods used to process spatiotemporal data need to overcome the dimensionality curse associated with the need to store and invert large covariance matrices. There are various mathematical approaches for addressing the dimensionality problem, including change of basis, dimensionality reduction, hierarchical schemes, and local approximations. We present a Stochastic Local Interaction (SLI) model that can be used to model local correlations in spatial data. SLI is a random field model suitable for data on discrete supports (i.e., regular lattices or irregular sampling grids). The degree of localization is determined by means of kernel functions and appropriate bandwidths. The strength of the correlations is determined by means of coefficients. In the "plain vanilla" version the parameter set involves scale and rigidity coefficients as well as a characteristic length. The latter determines in connection with the rigidity coefficient the correlation length of the random field. The SLI model is based on statistical field theory and extends previous research on Spartan spatial random fields [2,3] from continuum spaces to explicitly discrete supports. The SLI kernel functions employ adaptive bandwidths learned from the sampling spatial distribution [1]. The SLI precision matrix is expressed explicitly in terms of the model parameter and the kernel function. Hence, covariance matrix inversion is not necessary for parameter inference that is based on leave-one-out cross validation. This property

The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective.

PubMed

Kruschke, John K; Liddell, Torrin M

2018-02-01

In the practice of data analysis, there is a conceptual distinction between hypothesis testing, on the one hand, and estimation with quantified uncertainty on the other. Among frequentists in psychology, a shift of emphasis from hypothesis testing to estimation has been dubbed "the New Statistics" (Cumming 2014). A second conceptual distinction is between frequentist methods and Bayesian methods. Our main goal in this article is to explain how Bayesian methods achieve the goals of the New Statistics better than frequentist methods. The article reviews frequentist and Bayesian approaches to hypothesis testing and to estimation with confidence or credible intervals. The article also describes Bayesian approaches to meta-analysis, randomized controlled trials, and power analysis.

Precipitation estimation in mountainous terrain using multivariate geostatistics. Part II: isohyetal maps

USGS Publications Warehouse

Hevesi, Joseph A.; Flint, Alan L.; Istok, Jonathan D.

1992-01-01

Values of average annual precipitation (AAP) may be important for hydrologic characterization of a potential high-level nuclear-waste repository site at Yucca Mountain, Nevada. Reliable measurements of AAP are sparse in the vicinity of Yucca Mountain, and estimates of AAP were needed for an isohyetal mapping over a 2600-square-mile watershed containing Yucca Mountain. Estimates were obtained with a multivariate geostatistical model developed using AAP and elevation data from a network of 42 precipitation stations in southern Nevada and southeastern California. An additional 1531 elevations were obtained to improve estimation accuracy. Isohyets representing estimates obtained using univariate geostatistics (kriging) defined a smooth and continuous surface. Isohyets representing estimates obtained using multivariate geostatistics (cokriging) defined an irregular surface that more accurately represented expected local orographic influences on AAP. Cokriging results included a maximum estimate within the study area of 335 mm at an elevation of 7400 ft, an average estimate of 157 mm for the study area, and an average estimate of 172 mm at eight locations in the vicinity of the potential repository site. Kriging estimates tended to be lower in comparison because the increased AAP expected for remote mountainous topography was not adequately represented by the available sample. Regression results between cokriging estimates and elevation were similar to regression results between measured AAP and elevation. The position of the cokriging 250-mm isohyet relative to the boundaries of pinyon pine and juniper woodlands provided indirect evidence of improved estimation accuracy because the cokriging result agreed well with investigations by others concerning the relationship between elevation, vegetation, and climate in the Great Basin. Calculated estimation variances were also mapped and compared to evaluate improvements in estimation accuracy. Cokriging estimation variances

Introduction to this Special Issue on Geostatistics and Scaling of Remote Sensing

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.

1999-01-01

The germination of this special PE&RS issue began at the Royal Geographical Society (with the Institute of British Geographers)(RCS-IBC) annual meeting in January, 1997 held at the University of Exeter in Exeter, England. The cold and snow of an England winter were greatly tempered by the friendly and cordial discussions that ensued at the meeting on possible ways to foster both dialog and research across "the Big Pond" between geographers in the US and the UK on the use of geostatistics and geospatial techniques for remote sensing of land surface processes. It was decided that one way to stimulate and enhance cooperation on the application of geostatistics and geospatial methods in remote sensing was to hold parallel sessions on these topics at appropriate meeting venues in 1998 in both the US and the UK Selected papers given at these sessions would be published as a special issue of PE&RS on the US side, and as a special issue of Computers and Geosciences (C&G) on the UK side, to highlight the commonality in research on geostatistics and geospatial methods in remote sensing and spatial data analysis on both sides of the Atlantic Ocean. As a consequence, a session on "Ceostatistics and Geospatial Techniques for Remote Sensing of Land Surface Processes" was held at the Association of American Geographers (AAG) annual meeting in Boston, Massachusetts in March, 1998, sponsored by the AAG's Remote Sensing Specialty Group (RSSG). A similar session was held at the RGS-IBG annual meeting in Guildford, Surrey, England in January 1998, organized by the Modeling and Advanced Techniques Special Interest Group (MAT SIG) of the Remote Sensing Society (RSS). The six papers that in part, comprise this issue of PE&RS, are the US complement to such a dual journal publication effort. Both of us are co-editors of each of the journal special issues, with the lead editor of each journal being from their respective side of the Atlantic where the journals are published. The special

A Novel Approach of Understanding and Incorporating Error of Chemical Transport Models into a Geostatistical Framework

NASA Astrophysics Data System (ADS)

Reyes, J.; Vizuete, W.; Serre, M. L.; Xu, Y.

2015-12-01

The EPA employs a vast monitoring network to measure ambient PM2.5 concentrations across the United States with one of its goals being to quantify exposure within the population. However, there are several areas of the country with sparse monitoring spatially and temporally. One means to fill in these monitoring gaps is to use PM2.5 modeled estimates from Chemical Transport Models (CTMs) specifically the Community Multi-scale Air Quality (CMAQ) model. CMAQ is able to provide complete spatial coverage but is subject to systematic and random error due to model uncertainty. Due to the deterministic nature of CMAQ, often these uncertainties are not quantified. Much effort is employed to quantify the efficacy of these models through different metrics of model performance. Currently evaluation is specific to only locations with observed data. Multiyear studies across the United States are challenging because the error and model performance of CMAQ are not uniform over such large space/time domains. Error changes regionally and temporally. Because of the complex mix of species that constitute PM2.5, CMAQ error is also a function of increasing PM2.5 concentration. To address this issue we introduce a model performance evaluation for PM2.5 CMAQ that is regionalized and non-linear. This model performance evaluation leads to error quantification for each CMAQ grid. Areas and time periods of error being better qualified. The regionalized error correction approach is non-linear and is therefore more flexible at characterizing model performance than approaches that rely on linearity assumptions and assume homoscedasticity of CMAQ predictions errors. Corrected CMAQ data are then incorporated into the modern geostatistical framework of Bayesian Maximum Entropy (BME). Through cross validation it is shown that incorporating error-corrected CMAQ data leads to more accurate estimates than just using observed data by themselves.

Efficient geostatistical inversion of transient groundwater flow using preconditioned nonlinear conjugate gradients

NASA Astrophysics Data System (ADS)

Klein, Ole; Cirpka, Olaf A.; Bastian, Peter; Ippisch, Olaf

2017-04-01

In the geostatistical inverse problem of subsurface hydrology, continuous hydraulic parameter fields, in most cases hydraulic conductivity, are estimated from measurements of dependent variables, such as hydraulic heads, under the assumption that the parameter fields are autocorrelated random space functions. Upon discretization, the continuous fields become large parameter vectors with O (104 -107) elements. While cokriging-like inversion methods have been shown to be efficient for highly resolved parameter fields when the number of measurements is small, they require the calculation of the sensitivity of each measurement with respect to all parameters, which may become prohibitive with large sets of measured data such as those arising from transient groundwater flow. We present a Preconditioned Conjugate Gradient method for the geostatistical inverse problem, in which a single adjoint equation needs to be solved to obtain the gradient of the objective function. Using the autocovariance matrix of the parameters as preconditioning matrix, expensive multiplications with its inverse can be avoided, and the number of iterations is significantly reduced. We use a randomized spectral decomposition of the posterior covariance matrix of the parameters to perform a linearized uncertainty quantification of the parameter estimate. The feasibility of the method is tested by virtual examples of head observations in steady-state and transient groundwater flow. These synthetic tests demonstrate that transient data can reduce both parameter uncertainty and time spent conducting experiments, while the presented methods are able to handle the resulting large number of measurements.

UNIFORMLY MOST POWERFUL BAYESIAN TESTS

PubMed Central

Johnson, Valen E.

2014-01-01

Uniformly most powerful tests are statistical hypothesis tests that provide the greatest power against a fixed null hypothesis among all tests of a given size. In this article, the notion of uniformly most powerful tests is extended to the Bayesian setting by defining uniformly most powerful Bayesian tests to be tests that maximize the probability that the Bayes factor, in favor of the alternative hypothesis, exceeds a specified threshold. Like their classical counterpart, uniformly most powerful Bayesian tests are most easily defined in one-parameter exponential family models, although extensions outside of this class are possible. The connection between uniformly most powerful tests and uniformly most powerful Bayesian tests can be used to provide an approximate calibration between p-values and Bayes factors. Finally, issues regarding the strong dependence of resulting Bayes factors and p-values on sample size are discussed. PMID:24659829

Decentralization in Zambia: resource allocation and district performance.

PubMed

Bossert, Thomas; Chitah, Mukosha Bona; Bowser, Diana

2003-12-01

Zambia implemented an ambitious process of health sector decentralization in the mid 1990s. This article presents an assessment of the degree of decentralization, called 'decision space', that was allowed to districts in Zambia, and an analysis of data on districts available at the national level to assess allocation choices made by local authorities and some indicators of the performance of the health systems under decentralization. The Zambian officials in health districts had a moderate range of choice over expenditures, user fees, contracting, targeting and governance. Their choices were quite limited over salaries and allowances and they did not have control over additional major sources of revenue, like local taxes. The study found that the formula for allocation of government funding which was based on population size and hospital beds resulted in relatively equal per capita expenditures among districts. Decentralization allowed the districts to make decisions on internal allocation of resources and on user fee levels and expenditures. General guidelines for the allocation of resources established a maximum and minimum percentage to be allocated to district offices, hospitals, health centres and communities. Districts tended to exceed the maximum for district offices, but the large urban districts and those without public district hospitals were not even reaching the minimum for hospital allocations. Wealthier and urban districts were more successful in raising revenue through user fees, although the proportion of total expenditures that came from user fees was low. An analysis of available indicators of performance, such as the utilization of health services, immunization coverage and family planning activities, found little variation during the period 1995-98 except for a decline in immunization coverage, which may have also been affected by changes in donor funding. These findings suggest that decentralization may not have had either a positive or

Improved Assimilation of Streamflow and Satellite Soil Moisture with the Evolutionary Particle Filter and Geostatistical Modeling

NASA Astrophysics Data System (ADS)

Yan, Hongxiang; Moradkhani, Hamid; Abbaszadeh, Peyman

2017-04-01

Assimilation of satellite soil moisture and streamflow data into hydrologic models using has received increasing attention over the past few years. Currently, these observations are increasingly used to improve the model streamflow and soil moisture predictions. However, the performance of this land data assimilation (DA) system still suffers from two limitations: 1) satellite data scarcity and quality; and 2) particle weight degeneration. In order to overcome these two limitations, we propose two possible solutions in this study. First, the general Gaussian geostatistical approach is proposed to overcome the limitation in the space/time resolution of satellite soil moisture products thus improving their accuracy at uncovered/biased grid cells. Secondly, an evolutionary PF approach based on Genetic Algorithm (GA) and Markov Chain Monte Carlo (MCMC), the so-called EPF-MCMC, is developed to further reduce weight degeneration and improve the robustness of the land DA system. This study provides a detailed analysis of the joint and separate assimilation of streamflow and satellite soil moisture into a distributed Sacramento Soil Moisture Accounting (SAC-SMA) model, with the use of recently developed EPF-MCMC and the general Gaussian geostatistical approach. Performance is assessed over several basins in the USA selected from Model Parameter Estimation Experiment (MOPEX) and located in different climate regions. The results indicate that: 1) the general Gaussian approach can predict the soil moisture at uncovered grid cells within the expected satellite data quality threshold; 2) assimilation of satellite soil moisture inferred from the general Gaussian model can significantly improve the soil moisture predictions; and 3) in terms of both deterministic and probabilistic measures, the EPF-MCMC can achieve better streamflow predictions. These results recommend that the geostatistical model is a helpful tool to aid the remote sensing technique and the EPF-MCMC is a

Will savannas survive outside the parks? A lesson from Zambia

NASA Astrophysics Data System (ADS)

Kutsch, W.; Merbold, L.; Scholes, B.; Mukelabai, M.

2012-04-01

Miombo woodlands cover the transition zone between dry open savannas and moist forests in Southern Africa. They cover about 2.7 million km2 in southern Africa and provide many ecosystem services that support rural life, including medical products, wild foods, construction timber and fuel. In Zambia, as in many of its neighbouring countries, miombo woodlands are currently experiencing accelerating degradation and clearing, mostly with charcoal production as the initial driver. Domestic energy needs in the growing urban areas are largely satisfied by charcoal, which is less energy-efficient fuel on a tree-to-table basis than the firewood that is used in rural areas, but has a higher energy density and is thus cheaper to transport. This study uses data from inventories and from eddy covariance measurements of carbon exchange to characterize the impact of charcoal production on miombo woodlands. We address the following questions: (i) how much carbon is lost at local as well as at national scale and (ii) does forest degradation result in the loss of a carbon sink? On the basis of our data we (iii) estimate the per capita emissions through deforestation and forest degradation in Zambia and relate it to fossil fuel emissions. Furthermore, (iv) a rough estimate of the energy that is provided by charcoal production to private households at a national level is calculated and (v) options for alternative energy supply to private households are discussed.

Bayesian methods in reliability

NASA Astrophysics Data System (ADS)

Sander, P.; Badoux, R.

1991-11-01

The present proceedings from a course on Bayesian methods in reliability encompasses Bayesian statistical methods and their computational implementation, models for analyzing censored data from nonrepairable systems, the traits of repairable systems and growth models, the use of expert judgment, and a review of the problem of forecasting software reliability. Specific issues addressed include the use of Bayesian methods to estimate the leak rate of a gas pipeline, approximate analyses under great prior uncertainty, reliability estimation techniques, and a nonhomogeneous Poisson process. Also addressed are the calibration sets and seed variables of expert judgment systems for risk assessment, experimental illustrations of the use of expert judgment for reliability testing, and analyses of the predictive quality of software-reliability growth models such as the Weibull order statistics.

Integration of geology, geostatistics, well logs and pressure data to model a heterogeneous supergiant field in Iran

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

Samimi, B.; Bagherpour, H.; Nioc, A.

1995-08-01

The geological reservoir study of the supergiant Ahwaz field significantly improved the history matching process in many aspects, particularly the development of a geostatistical model which allowed a sound basis for changes and by delivering much needed accurate estimates of grid block vertical permeabilities. The geostatistical reservoir evaluation was facilitated by using the Heresim package and litho-stratigraphic zonations for the entire field. For each of the geological zones, 3-dimensional electrolithofacies and petrophysical property distributions (realizations) were treated which captured the heterogeneities which significantly affected fluid flow. However, as this level of heterogeneity was at a significantly smaller scale than themore » flow simulation grid blocks, a scaling up effort was needed to derive the effective flow properties of the blocks (porosity, horizontal and vertical permeability, and water saturation). The properties relating to the static reservoir description were accurately derived by using stream tube techniques developed in-house whereas, the relative permeabilities of the grid block were derived by dynamic pseudo relative permeability techniques. The prediction of vertical and lateral communication and water encroachment was facilitated by a close integration of pressure, saturation data, geostatistical modelling and sedimentological studies of the depositional environments and paleocurrents. The nature of reservoir barriers and baffles varied both vertically and laterally in this heterogeneous reservoir. Maps showing differences in pressure between zones after years of production served as a guide to integrating the static geological studies to the dynamic behaviour of each of the 16 reservoir zones. The use of deep wells being drilled to a deeper reservoir provided data to better understand the sweep efficiency and the continuity of barriers and baffles.« less

Characterization and geostatistical mapping of water salinity: A case study of terminal complex in the Oued Righ Valley (southern Algeria)

NASA Astrophysics Data System (ADS)

Belkesier, Mohamed Saleh; Zeddouri, Aziez; Halassa, Younes; Kechiched, Rabah

2018-05-01

The region of Oued Righ contains large quantities of groundwater hosted by the three aquifers: the Terminal Complex (CT), the Continental Intercalary (CI) and the phreatic aquifer. The present study is focused on the water from CT aquifer in order to characterize their salinity using geostatistical tool for maping. Indeed, water in this aquifer show a high mineralization exceeding the OMS standards. The main hydro-chemical facies of this water is Chloride-Sodium and Sulfate-Sodium. The elementary statistics have been performed on the physico-chemical analysis from 97 wells whereas 766 wells were analyzed on salinity and are used for the geostatistical mapping. The obtained results show a spatial evolution of the salinity toward the direction South to the North. The salinity is locally strong in the central part of Oued Righ valley. The non-parametric geostatistic of indicator kriging was performed on the salinity data using a cut-off of 5230 mg/l which represents the average value in the studied area. The indicator Kriging allows the estimation of salinity probabilities I (5230 mg / l) in the water of the CT aquifer using bloc model (500 x 500 m). The automatic mapping is used to visualize the distribution of the kriged probabilities of salinity. These results can help to ensure a rational and a selective exploitation of groundwater according the salinity contents.

Geostatistical Interpolation of Particle-Size Curves in Heterogeneous Aquifers

NASA Astrophysics Data System (ADS)

Guadagnini, A.; Menafoglio, A.; Secchi, P.

2013-12-01

We address the problem of predicting the spatial field of particle-size curves (PSCs) from measurements associated with soil samples collected at a discrete set of locations within an aquifer system. Proper estimates of the full PSC are relevant to applications related to groundwater hydrology, soil science and geochemistry and aimed at modeling physical and chemical processes occurring in heterogeneous earth systems. Hence, we focus on providing kriging estimates of the entire PSC at unsampled locations. To this end, we treat particle-size curves as cumulative distribution functions, model their densities as functional compositional data and analyze them by embedding these into the Hilbert space of compositional functions endowed with the Aitchison geometry. On this basis, we develop a new geostatistical methodology for the analysis of spatially dependent functional compositional data. Our functional compositional kriging (FCK) approach allows providing predictions at unsampled location of the entire particle-size curve, together with a quantification of the associated uncertainty, by fully exploiting both the functional form of the data and their compositional nature. This is a key advantage of our approach with respect to traditional methodologies, which treat only a set of selected features (e.g., quantiles) of PSCs. Embedding the full PSC into a geostatistical analysis enables one to provide a complete characterization of the spatial distribution of lithotypes in a reservoir, eventually leading to improved predictions of soil hydraulic attributes through pedotransfer functions as well as of soil geochemical parameters which are relevant in sorption/desorption and cation exchange processes. We test our new method on PSCs sampled along a borehole located within an alluvial aquifer near the city of Tuebingen, Germany. The quality of FCK predictions is assessed through leave-one-out cross-validation. A comparison between hydraulic conductivity estimates obtained

Conceptualising Education Quality in Zambia: A Comparative Analysis across the Local, National and Global Discourses

ERIC Educational Resources Information Center

Lee, Jeongmin; Zuilkowski, Stephanie Simmons

2017-01-01

Building on the Education for All movement, the 2030 Agenda for Sustainable Development re-emphasises quality education as a discrete goal. Contextualising the discussion surrounding this goal in Zambia, this study examines how education quality is conceptualised by educational stakeholders at local, national, and global levels. Triangulating…

Two new planthopper species (Hemiptera, Fulgoroidea, Caliscelidae) collected in pitfall traps in Zambia.

PubMed

Chmurova, Lucia; Webb, Michael D

2016-08-22

Two new species of planthoppers in the family Caliscelidae (Hemiptera: Fulgoroidea) are described from Zambia, i.e., Afronaso spinosa sp. n. and Calampocus zambiaensis sp. n. All specimens are flightless males and nearly all were collected from baited pitfall traps (except for one specimen collected from a yellow pan trap), suggesting that they live near to or on the ground.

Is probabilistic bias analysis approximately Bayesian?

PubMed Central

MacLehose, Richard F.; Gustafson, Paul

2011-01-01

Case-control studies are particularly susceptible to differential exposure misclassification when exposure status is determined following incident case status. Probabilistic bias analysis methods have been developed as ways to adjust standard effect estimates based on the sensitivity and specificity of exposure misclassification. The iterative sampling method advocated in probabilistic bias analysis bears a distinct resemblance to a Bayesian adjustment; however, it is not identical. Furthermore, without a formal theoretical framework (Bayesian or frequentist), the results of a probabilistic bias analysis remain somewhat difficult to interpret. We describe, both theoretically and empirically, the extent to which probabilistic bias analysis can be viewed as approximately Bayesian. While the differences between probabilistic bias analysis and Bayesian approaches to misclassification can be substantial, these situations often involve unrealistic prior specifications and are relatively easy to detect. Outside of these special cases, probabilistic bias analysis and Bayesian approaches to exposure misclassification in case-control studies appear to perform equally well. PMID:22157311

A multiple-point geostatistical approach to quantifying uncertainty for flow and transport simulation in geologically complex environments

NASA Astrophysics Data System (ADS)

Cronkite-Ratcliff, C.; Phelps, G. A.; Boucher, A.

2011-12-01

In many geologic settings, the pathways of groundwater flow are controlled by geologic heterogeneities which have complex geometries. Models of these geologic heterogeneities, and consequently, their effects on the simulated pathways of groundwater flow, are characterized by uncertainty. Multiple-point geostatistics, which uses a training image to represent complex geometric descriptions of geologic heterogeneity, provides a stochastic approach to the analysis of geologic uncertainty. Incorporating multiple-point geostatistics into numerical models provides a way to extend this analysis to the effects of geologic uncertainty on the results of flow simulations. We present two case studies to demonstrate the application of multiple-point geostatistics to numerical flow simulation in complex geologic settings with both static and dynamic conditioning data. Both cases involve the development of a training image from a complex geometric description of the geologic environment. Geologic heterogeneity is modeled stochastically by generating multiple equally-probable realizations, all consistent with the training image. Numerical flow simulation for each stochastic realization provides the basis for analyzing the effects of geologic uncertainty on simulated hydraulic response. The first case study is a hypothetical geologic scenario developed using data from the alluvial deposits in Yucca Flat, Nevada. The SNESIM algorithm is used to stochastically model geologic heterogeneity conditioned to the mapped surface geology as well as vertical drill-hole data. Numerical simulation of groundwater flow and contaminant transport through geologic models produces a distribution of hydraulic responses and contaminant concentration results. From this distribution of results, the probability of exceeding a given contaminant concentration threshold can be used as an indicator of uncertainty about the location of the contaminant plume boundary. The second case study considers a

Philosophy and the practice of Bayesian statistics

PubMed Central

Gelman, Andrew; Shalizi, Cosma Rohilla

2015-01-01

A substantial school in the philosophy of science identifies Bayesian inference with inductive inference and even rationality as such, and seems to be strengthened by the rise and practical success of Bayesian statistics. We argue that the most successful forms of Bayesian statistics do not actually support that particular philosophy but rather accord much better with sophisticated forms of hypothetico-deductivism. We examine the actual role played by prior distributions in Bayesian models, and the crucial aspects of model checking and model revision, which fall outside the scope of Bayesian confirmation theory. We draw on the literature on the consistency of Bayesian updating and also on our experience of applied work in social science. Clarity about these matters should benefit not just philosophy of science, but also statistical practice. At best, the inductivist view has encouraged researchers to fit and compare models without checking them; at worst, theorists have actively discouraged practitioners from performing model checking because it does not fit into their framework. PMID:22364575

Robust Bayesian clustering.

PubMed

Archambeau, Cédric; Verleysen, Michel

2007-01-01

A new variational Bayesian learning algorithm for Student-t mixture models is introduced. This algorithm leads to (i) robust density estimation, (ii) robust clustering and (iii) robust automatic model selection. Gaussian mixture models are learning machines which are based on a divide-and-conquer approach. They are commonly used for density estimation and clustering tasks, but are sensitive to outliers. The Student-t distribution has heavier tails than the Gaussian distribution and is therefore less sensitive to any departure of the empirical distribution from Gaussianity. As a consequence, the Student-t distribution is suitable for constructing robust mixture models. In this work, we formalize the Bayesian Student-t mixture model as a latent variable model in a different way from Svensén and Bishop [Svensén, M., & Bishop, C. M. (2005). Robust Bayesian mixture modelling. Neurocomputing, 64, 235-252]. The main difference resides in the fact that it is not necessary to assume a factorized approximation of the posterior distribution on the latent indicator variables and the latent scale variables in order to obtain a tractable solution. Not neglecting the correlations between these unobserved random variables leads to a Bayesian model having an increased robustness. Furthermore, it is expected that the lower bound on the log-evidence is tighter. Based on this bound, the model complexity, i.e. the number of components in the mixture, can be inferred with a higher confidence.

Beyond a Learning Society? It Is All to Be Done Again: Zambia and Zimbabwe

ERIC Educational Resources Information Center

Alexander, David

2006-01-01

This article considers the ways in which educators and learning societies in Zambia and Zimbabwe have had to struggle to create independent, democratic and critical curricula in difficult circumstances over the last 50 years in the context of historical shifts in power, a declining British Empire and the re-emergence of reactionary forces at a…

Geostatistical modelling of soil-transmitted helminth infection in Cambodia: do socioeconomic factors improve predictions?

PubMed

Karagiannis-Voules, Dimitrios-Alexios; Odermatt, Peter; Biedermann, Patricia; Khieu, Virak; Schär, Fabian; Muth, Sinuon; Utzinger, Jürg; Vounatsou, Penelope

2015-01-01

Soil-transmitted helminth infections are intimately connected with poverty. Yet, there is a paucity of using socioeconomic proxies in spatially explicit risk profiling. We compiled household-level socioeconomic data pertaining to sanitation, drinking-water, education and nutrition from readily available Demographic and Health Surveys, Multiple Indicator Cluster Surveys and World Health Surveys for Cambodia and aggregated the data at village level. We conducted a systematic review to identify parasitological surveys and made every effort possible to extract, georeference and upload the data in the open source Global Neglected Tropical Diseases database. Bayesian geostatistical models were employed to spatially align the village-aggregated socioeconomic predictors with the soil-transmitted helminth infection data. The risk of soil-transmitted helminth infection was predicted at a grid of 1×1km covering Cambodia. Additionally, two separate individual-level spatial analyses were carried out, for Takeo and Preah Vihear provinces, to assess and quantify the association between soil-transmitted helminth infection and socioeconomic indicators at an individual level. Overall, we obtained socioeconomic proxies from 1624 locations across the country. Surveys focussing on soil-transmitted helminth infections were extracted from 16 sources reporting data from 238 unique locations. We found that the risk of soil-transmitted helminth infection from 2000 onwards was considerably lower than in surveys conducted earlier. Population-adjusted prevalences for school-aged children from 2000 onwards were 28.7% for hookworm, 1.5% for Ascaris lumbricoides and 0.9% for Trichuris trichiura. Surprisingly, at the country-wide analyses, we did not find any significant association between soil-transmitted helminth infection and village-aggregated socioeconomic proxies. Based also on the individual-level analyses we conclude that socioeconomic proxies might not be good predictors at an

Bayesian networks improve causal environmental ...

EPA Pesticide Factsheets

Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on value

Bayesian Latent Class Analysis Tutorial.

PubMed

Li, Yuelin; Lord-Bessen, Jennifer; Shiyko, Mariya; Loeb, Rebecca

2018-01-01

This article is a how-to guide on Bayesian computation using Gibbs sampling, demonstrated in the context of Latent Class Analysis (LCA). It is written for students in quantitative psychology or related fields who have a working knowledge of Bayes Theorem and conditional probability and have experience in writing computer programs in the statistical language R . The overall goals are to provide an accessible and self-contained tutorial, along with a practical computation tool. We begin with how Bayesian computation is typically described in academic articles. Technical difficulties are addressed by a hypothetical, worked-out example. We show how Bayesian computation can be broken down into a series of simpler calculations, which can then be assembled together to complete a computationally more complex model. The details are described much more explicitly than what is typically available in elementary introductions to Bayesian modeling so that readers are not overwhelmed by the mathematics. Moreover, the provided computer program shows how Bayesian LCA can be implemented with relative ease. The computer program is then applied in a large, real-world data set and explained line-by-line. We outline the general steps in how to extend these considerations to other methodological applications. We conclude with suggestions for further readings.

Towards improving hospital performance in Uganda and Zambia: reflections and opportunities for autonomy.

PubMed

Hanson, Kara; Atuyambe, Lynn; Kamwanga, Jolly; McPake, Barbara; Mungule, Oswald; Ssengooba, Freddie

2002-07-01

Hospitals have been relatively neglected although their high resource consumption implies that gains from improving the services they deliver may be substantial. Nevertheless, the challenges posed by hospital reforms are great. Hospital autonomy usually consists of both decentralisation, and a greater measure of exposure to market forces. In Uganda and Zambia, more traditional 'decentralisation' of authority to district level authorities includes district hospitals; and some measure of 'autonomy' (known as 'self-accounting status' in Uganda) has been applied to some or all second and third level referral hospitals. The hospital policies pursued in both countries present opportunities to tackle their hospital sectors. In Zambia, purchasing of services means that new incentives and policy mechanisms can come into play. Little advantage has been taken of these opportunities to date. In Uganda, there is no financial link between districts and higher levels of the system, but decentralisation of control over personnel is more advanced. These two components--the alignment of incentives (to promote access and quality for those intended to be covered by the public budget) and the effective decentralisation of control over key resources--seem to us the key tools to address the stubborn problems of hospitals.

Expanding contraceptive choice in the developing world: lessons from the Lao People's Democratic Republic and the Republic of Zambia.

PubMed

d'Arcangues, Catherine M; Ba-Thike, Katherine; Say, Lale

2013-12-01

Women need different forms of contraception over their lifetime. In the developed world, they have access to some 20 different methods. In developing countries, only a few options are available. This paper focuses on four under-used methods: intrauterine devices, implants, emergency contraception and female condoms. It examines reasons for their low uptake, strategies used for their adoption, and challenges in sustaining these efforts, in two countries: Laos and Zambia. In-country documentation and reports from international partners were reviewed; questionnaires were sent and interviews carried out with ministry officials, senior providers, and local representatives of international organisations and international non-governmental organisations. In Laos, the family planning programme is relatively young; its challenges include ensuring the sustainability of services and supplies, improving the quality of IEC to dispel misconceptions surrounding contraception, and developing novel distribution systems to reach rural populations. Zambia has a much older programme, which lost ground in the face of competing health priorities. Its challenges include strengthening the supply chain management, coordinating the multiple groups of providers and ensuring the sustainability of services in rural areas. The contrast offered by Laos and Zambia illustrates the importance of regular evaluation to identify priority areas for improving contraceptive delivery.

Characterization of tabanid flies (Diptera: Tabanidae) in South Africa and Zambia and detection of protozoan parasites they are harbouring.

PubMed

Taioe, Moeti O; Motloang, Makhosazana Y; Namangala, Boniface; Chota, Amos; Molefe, Nthatisi I; Musinguzi, Simon P; Suganuma, Keisuke; Hayes, Polly; Tsilo, Toi J; Chainey, John; Inoue, Noboru; Thekisoe, Oriel M M

2017-08-01

Tabanids are haematophagous flies feeding on livestock and wildlife. In the absence of information on the relationship of tabanid flies and protozoan parasites in South Africa and Zambia, the current study was aimed at characterizing tabanid flies collected in these two countries as well as detecting protozoan parasites they are harbouring. A total of 527 tabanid flies were collected whereby 70·2% were from South Africa and 29·8% were from Zambia. Morphological analysis revealed a total of five different genera collected from the sampled areas namely: Ancala, Atylotus, Haematopota, Philoliche and Tabanus. DNA extracted from South African Tabanus par and Tabanus taeniola tested positive for the presence of Trypanosoma congolense (Savannah) and Trypanosoma theileri whilst one member from T. par was positive for Trypanosoma brucei species. DNA extracted from Zambian tabanid flies tested positive for the presence of Besnoitia species at 1·27% (2/157), Babesia bigemina 5·73% (9/157), Theileria parva 30·11% (30/157) and 9·82% (14/157) for Trypanosoma evansi. This study is the first to report on relationship of Babesia and Theileria parasites with tabanid flies. Further investigations are required to determine the role of tabanids in transmission of the detected protozoan parasites in livestock and wildlife in South Africa and Zambia.

Using intersectionality to explore experiences of disability and HIV among women and men in Zambia.

PubMed

Yoshida, Karen; Hanass-Hancock, Jill; Nixon, Stephanie; Bond, Virginia

2014-01-01

Little is known about the experiences of people with disabilities (PWD) who live with HIV. Existing research largely assumes a "double burden" approach, which views HIV as doubling the load for people already burdened by disability. Intersectionality (a dynamic process of converging systems of relationships) offers an alternative approach for understanding differences in experience. This study uses an intersectional approach to explore the experiences of PWD in Zambia who have become HIV-positive. We conducted semi-structured, in depth interviews with 21 PWD who live with HIV in Zambia (12 women, 9 men). Participants had various impairments (visual, hearing, mobility, intellectual). Interviews were conducted to meet participants' accessibility preferences. Our intersectional analysis demonstrates the dynamic and situational emergent meanings and consequences for PWD who are living with HIV related to: (1) meanings of HIV and disability linked with time and trajectory; (2) oppression and negotiation related to accessing health services and (3) social roles and relationships. Three case studies illustrate these circumstances. Intersectionality offers a complementary approach for examining the complex interrelationship among HIV, disability, gender and time among PWD living with HIV. Findings illustrate directions for improved services and policies for this important group. Rehabilitation services need to take a cross-disability (multiple disabilities) approach working with people living with HIV and disability. Rehabilitation, as illustrated by a CBR approach, needs to include services that will facilitate not only health, but education, jobs and housing for people living with HIV and disability. Rehabilitation needs to make more direct connections with Zambia social service sector to help address the fluctuating experience of living with HIV and disability.

A Bayesian Nonparametric Approach to Test Equating

ERIC Educational Resources Information Center

Karabatsos, George; Walker, Stephen G.

2009-01-01

A Bayesian nonparametric model is introduced for score equating. It is applicable to all major equating designs, and has advantages over previous equating models. Unlike the previous models, the Bayesian model accounts for positive dependence between distributions of scores from two tests. The Bayesian model and the previous equating models are…

Bayesian Model Averaging for Propensity Score Analysis

ERIC Educational Resources Information Center

Kaplan, David; Chen, Jianshen

2013-01-01

The purpose of this study is to explore Bayesian model averaging in the propensity score context. Previous research on Bayesian propensity score analysis does not take into account model uncertainty. In this regard, an internally consistent Bayesian framework for model building and estimation must also account for model uncertainty. The…

Bayesian models: A statistical primer for ecologists

USGS Publications Warehouse

Hobbs, N. Thompson; Hooten, Mevin B.

2015-01-01

Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach.Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals.This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticiansCovers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and moreDeemphasizes computer coding in favor of basic principlesExplains how to write out properly factored statistical expressions representing Bayesian models

The current state of Bayesian methods in medical product development: survey results and recommendations from the DIA Bayesian Scientific Working Group.

PubMed

Natanegara, Fanni; Neuenschwander, Beat; Seaman, John W; Kinnersley, Nelson; Heilmann, Cory R; Ohlssen, David; Rochester, George

2014-01-01

Bayesian applications in medical product development have recently gained popularity. Despite many advances in Bayesian methodology and computations, increase in application across the various areas of medical product development has been modest. The DIA Bayesian Scientific Working Group (BSWG), which includes representatives from industry, regulatory agencies, and academia, has adopted the vision to ensure Bayesian methods are well understood, accepted more broadly, and appropriately utilized to improve decision making and enhance patient outcomes. As Bayesian applications in medical product development are wide ranging, several sub-teams were formed to focus on various topics such as patient safety, non-inferiority, prior specification, comparative effectiveness, joint modeling, program-wide decision making, analytical tools, and education. The focus of this paper is on the recent effort of the BSWG Education sub-team to administer a Bayesian survey to statisticians across 17 organizations involved in medical product development. We summarize results of this survey, from which we provide recommendations on how to accelerate progress in Bayesian applications throughout medical product development. The survey results support findings from the literature and provide additional insight on regulatory acceptance of Bayesian methods and information on the need for a Bayesian infrastructure within an organization. The survey findings support the claim that only modest progress in areas of education and implementation has been made recently, despite substantial progress in Bayesian statistical research and software availability. Copyright © 2013 John Wiley & Sons, Ltd.

An introduction to Bayesian statistics in health psychology.

PubMed

Depaoli, Sarah; Rus, Holly M; Clifton, James P; van de Schoot, Rens; Tiemensma, Jitske

2017-09-01

The aim of the current article is to provide a brief introduction to Bayesian statistics within the field of health psychology. Bayesian methods are increasing in prevalence in applied fields, and they have been shown in simulation research to improve the estimation accuracy of structural equation models, latent growth curve (and mixture) models, and hierarchical linear models. Likewise, Bayesian methods can be used with small sample sizes since they do not rely on large sample theory. In this article, we discuss several important components of Bayesian statistics as they relate to health-based inquiries. We discuss the incorporation and impact of prior knowledge into the estimation process and the different components of the analysis that should be reported in an article. We present an example implementing Bayesian estimation in the context of blood pressure changes after participants experienced an acute stressor. We conclude with final thoughts on the implementation of Bayesian statistics in health psychology, including suggestions for reviewing Bayesian manuscripts and grant proposals. We have also included an extensive amount of online supplementary material to complement the content presented here, including Bayesian examples using many different software programmes and an extensive sensitivity analysis examining the impact of priors.

Molecular characterisation of methicillin-resistant Staphylococcus aureus (MRSA) isolated at a large referral hospital in Zambia.

PubMed

Samutela, Mulemba Tillika; Kalonda, Annie; Mwansa, James; Lukwesa-Musyani, Chileshe; Mwaba, John; Mumbula, Enoch Mulowa; Mwenya, Darlington; Simulundu, Edgar; Kwenda, Geoffrey

2017-01-01

Methicillin-resistant Staphylococcus aureus (MRSA) is globally recognized as an important public health problem. Whereas comprehensive molecular typing data of MRSA strains is available, particularly in Europe, North America and Australia, similar information is very limited in sub-Saharan Africa including Zambia. In this study, thirty two clinical isolates of Staphylococcus aureus , collected at a large referral hospital in Lusaka, Zambia between June 2009 and December 2012 were analysed by Staphylococcal cassette chromosome mec (SCCmec), Staphylococcus protein A gene typing (spa) and detection of the Panton-Valentine Leukocidin genes (pvl) . Three SCC mec types were identified namely SCC mec type IV (65.6%), SCCmec type III (21.9%), SCC mec type I (3.1%). Nine point four percent (9.4%) of the isolates were untypable. Five spa types, which included a novel type, were detected and the most prevalent spa type was t064 (40.6%). Other spa types included spa types t2104 (31.3%), t355 (3.1%) and t1257 (21.9%). The pvl genes were detected in 3 out of 32 isolates. These molecular typing data indicated that the MRSA strains collected in Lusaka were diverse. Although the source of these MRSA was not established, these results stress the need for assessing infection prevention and control procedures at this health-care facility in order to curtail possible nosocomial infections. Furthermore, country-wide surveillance of MRSA in both the community and health-care facilities is recommended for infection prevention and control. To our knowledge, this represents the first study to characterise MRSA using molecular tools in Zambia.

The Nature and Role of Religious Studies at the University of Zambia: 1985-2005

ERIC Educational Resources Information Center

Carmody, Brendan

2008-01-01

The place of religion in higher education has been and remains a complex issue internationally. This article aims to outline the nature and development of Religious Studies at the University of Zambia in Lusaka (UNZA) as an instance of how religion entered higher education in an African setting. In doing so, it will also provide perspectives on…

Markets for hospital services in Zambia.

PubMed

Nakamba, Pamela; Hanson, Kara; McPake, Barbara

2002-01-01

Hospital reforms involving the introduction of measures to increase competition in hospital markets are being implemented in a range of low and middle-income countries. However, little is understood about the operation of hospital markets outside the USA and the UK. This paper assesses the degree of competition for hospital services in two hospital markets in Zambia (Copperbelt and Midlands), and the implications for prices, quality and efficiency. We found substantial differences among different hospital types in prices, costs and quality, suggesting that the hospital service market is a segmented market. The two markets differ significantly in their degree of competition, with the high cost inpatient services market in Copperbelt relatively more competitive than that in the Midlands market. The implications of these differences are discussed in terms of the potential for competition to improve hospital performance, the impact of market structure on equity of access, and how the government should address the problem of the mine hospitals.

Biochar effect on maize yield and soil characteristics in five conservation farming sites in Zambia

USGS Publications Warehouse

Cornelissen, Gerard; Martinsen, Vegard; Shitumbanuma, Victor; Alling, Vanja; Breedveld, Gijs D.; Rutherford, David W.; Sparrevik, Magnus; Hale, Sarah E.; Obia, Alfred; Mulder, Jan

2013-01-01

Biochar addition to agricultural soils can improve soil fertility, with the added bonus of climate change mitigation through carbon sequestration. Conservation farming (CF) is precision farming, often combining minimum tillage, crop rotation and residue retention. In the present farmer-led field trials carried out in Zambia, the use of a low dosage biochar combined with CF minimum tillage was tested as a way to increase crop yields. Using CF minimum tillage allows the biochar to be applied to the area where most of the plant roots are present and mirrors the fertilizer application in CF practices. The CF practice used comprised manually hoe-dug planting 10-L sized basins, where 10%–12% of the land was tilled. Pilot trials were performed with maize cob biochar and wood biochar on five soils with variable physical/chemical characteristics. At a dosage as low as 4 tons/ha, both biochars had a strong positive effect on maize yields in the coarse white aeolian sand of Kaoma, West-Zambia, with yields of 444% ± 114% (p = 0.06) and 352% ± 139% (p = 0.1) of the fertilized reference plots for maize and wood biochar, respectively. Thus for sandy acidic soils, CF and biochar amendment can be a promising combination for increasing harvest yield. Moderate but non-significant effects on yields were observed for maize and wood biochar in a red sandy clay loam ultisol east of Lusaka, central Zambia (University of Zambia, UNZA, site) with growth of 142% ± 42% (p > 0.2) and 131% ± 62% (p > 0.2) of fertilized reference plots, respectively. For three other soils (acidic and neutral clay loams and silty clay with variable cation exchange capacity, CEC), no significant effects on maize yields were observed (p > 0.2). In laboratory trials, 5% of the two biochars were added to the soil samples in order to study the effect of the biochar on physical and chemical soil characteristics. The large increase in crop yield in Kaoma soil was tentatively explained by a combination of an

Assessment of coalbed gas resources of the Kalahari Basin Province of Botswana, Zimbabwe, and Zambia, Africa, 2016

USGS Publications Warehouse

Brownfield, Michael E.; Schenk, Christopher J.; Klett, Timothy R.; Tennyson, Marilyn E.; Mercier, Tracey J.; Gaswirth, Stephanie B.; Marra, Kristen R.; Hawkins, Sarah J.; Finn, Thomas M.; Le, Phuong A.; Leathers-Miller, Heidi M.

2017-02-24

Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 4.5 trillion cubic feet of coalbed gas in the Kalahari Basin Province of Botswana, Zambia, and Zimbabwe, Africa.

Philosophy and the practice of Bayesian statistics.

PubMed

Gelman, Andrew; Shalizi, Cosma Rohilla

2013-02-01

A substantial school in the philosophy of science identifies Bayesian inference with inductive inference and even rationality as such, and seems to be strengthened by the rise and practical success of Bayesian statistics. We argue that the most successful forms of Bayesian statistics do not actually support that particular philosophy but rather accord much better with sophisticated forms of hypothetico-deductivism. We examine the actual role played by prior distributions in Bayesian models, and the crucial aspects of model checking and model revision, which fall outside the scope of Bayesian confirmation theory. We draw on the literature on the consistency of Bayesian updating and also on our experience of applied work in social science. Clarity about these matters should benefit not just philosophy of science, but also statistical practice. At best, the inductivist view has encouraged researchers to fit and compare models without checking them; at worst, theorists have actively discouraged practitioners from performing model checking because it does not fit into their framework. © 2012 The British Psychological Society.

Bayesian modeling of flexible cognitive control

PubMed Central

Jiang, Jiefeng; Heller, Katherine; Egner, Tobias

2014-01-01

“Cognitive control” describes endogenous guidance of behavior in situations where routine stimulus-response associations are suboptimal for achieving a desired goal. The computational and neural mechanisms underlying this capacity remain poorly understood. We examine recent advances stemming from the application of a Bayesian learner perspective that provides optimal prediction for control processes. In reviewing the application of Bayesian models to cognitive control, we note that an important limitation in current models is a lack of a plausible mechanism for the flexible adjustment of control over conflict levels changing at varying temporal scales. We then show that flexible cognitive control can be achieved by a Bayesian model with a volatility-driven learning mechanism that modulates dynamically the relative dependence on recent and remote experiences in its prediction of future control demand. We conclude that the emergent Bayesian perspective on computational mechanisms of cognitive control holds considerable promise, especially if future studies can identify neural substrates of the variables encoded by these models, and determine the nature (Bayesian or otherwise) of their neural implementation. PMID:24929218

Assessment of groundwater level estimation uncertainty using sequential Gaussian simulation and Bayesian bootstrapping

NASA Astrophysics Data System (ADS)

Varouchakis, Emmanouil; Hristopulos, Dionissios

2015-04-01

Space-time geostatistical approaches can improve the reliability of dynamic groundwater level models in areas with limited spatial and temporal data. Space-time residual Kriging (STRK) is a reliable method for spatiotemporal interpolation that can incorporate auxiliary information. The method usually leads to an underestimation of the prediction uncertainty. The uncertainty of spatiotemporal models is usually estimated by determining the space-time Kriging variance or by means of cross validation analysis. For de-trended data the former is not usually applied when complex spatiotemporal trend functions are assigned. A Bayesian approach based on the bootstrap idea and sequential Gaussian simulation are employed to determine the uncertainty of the spatiotemporal model (trend and covariance) parameters. These stochastic modelling approaches produce multiple realizations, rank the prediction results on the basis of specified criteria and capture the range of the uncertainty. The correlation of the spatiotemporal residuals is modeled using a non-separable space-time variogram based on the Spartan covariance family (Hristopulos and Elogne 2007, Varouchakis and Hristopulos 2013). We apply these simulation methods to investigate the uncertainty of groundwater level variations. The available dataset consists of bi-annual (dry and wet hydrological period) groundwater level measurements in 15 monitoring locations for the time period 1981 to 2010. The space-time trend function is approximated using a physical law that governs the groundwater flow in the aquifer in the presence of pumping. The main objective of this research is to compare the performance of two simulation methods for prediction uncertainty estimation. In addition, we investigate the performance of the Spartan spatiotemporal covariance function for spatiotemporal geostatistical analysis. Hristopulos, D.T. and Elogne, S.N. 2007. Analytic properties and covariance functions for a new class of generalized Gibbs

Latin hypercube sampling and geostatistical modeling of spatial uncertainty in a spatially explicit forest landscape model simulation

Treesearch

Chonggang Xu; Hong S. He; Yuanman Hu; Yu Chang; Xiuzhen Li; Rencang Bu

2005-01-01

Geostatistical stochastic simulation is always combined with Monte Carlo method to quantify the uncertainty in spatial model simulations. However, due to the relatively long running time of spatially explicit forest models as a result of their complexity, it is always infeasible to generate hundreds or thousands of Monte Carlo simulations. Thus, it is of great...

Field and office instructions in stream gauging for the Hydrological Survey of Zambia

USGS Publications Warehouse

Bidwell, L.E.

1971-01-01

The importance of water to the basic needs of man is self- evident and needs no particular emphasis. The importance of water to a developing economy cannot be overemphasized. A few decades ago, hydrology was a division of hydraulic engineering and was a tool for project survey, plan, and design. Today hydrology still remains an important part of planning and management of water use projects, but it is imperative that surface and ground-water basic data networks be designed and operated from the standpoint of both present and future water needs. Water problems are ever increasing and ever changing and preparation for the future water demands of Zambia requires knowledge of the hydrology of the country instead of the examination of piecemeal samples for each water use project. The hydrologic survey of Zambia needs to be under the guidance of competent and imaginative hydrologists solidly trained in all elements of basic data collection and analysis and not in the hands of water project planners. Hydrology is a science which requires the highest order of teamwork and the hydrologist will need the help and advice of many employees within the organization to operate the network, provide adequate research, and examine the water needs of the country. It must be thoroughly understood that communication is essential between the hydrological survey and water project planners from both the government and private sectors. It is very important to define the aims and duties of the Hydrological Branch of the Water Affairs Department in a clear cut "Statement of Policy". Personal copies of the statement should be made available to all professional employees and technicians. The reasons for the existence of the Branch may be self-apparent to heads of the organization, but to all other employees the reasons may be vague and unknown. Every member of the technical and administrative staff would benefit by an understanding of the purpose of his work. Nebulous ideas of the function of a

Indoor radon variations in central Iran and its geostatistical map

NASA Astrophysics Data System (ADS)

Hadad, Kamal; Mokhtari, Javad

2015-02-01

We present the results of 2 year indoor radon survey in 10 cities of Yazd province in Central Iran (covering an area of 80,000 km2). We used passive diffusive samplers with LATEX polycarbonate films as Solid State Nuclear Track Detector (SSNTD). This study carried out in central Iran where there are major minerals and uranium mines. Our results indicate that despite few extraordinary high concentrations, average annual concentrations of indoor radon are within ICRP guidelines. When geostatistical spatial distribution of radon mapped onto geographical features of the province it was observed that risk of high radon concentration increases near the Saqand, Bafq, Harat and Abarkooh cities, this depended on the elevation and vicinity of the ores and mines.

Supervised restoration of degraded medical images using multiple-point geostatistics.

PubMed

Pham, Tuan D

2012-06-01

Reducing noise in medical images has been an important issue of research and development for medical diagnosis, patient treatment, and validation of biomedical hypotheses. Noise inherently exists in medical and biological images due to the acquisition and transmission in any imaging devices. Being different from image enhancement, the purpose of image restoration is the process of removing noise from a degraded image in order to recover as much as possible its original version. This paper presents a statistically supervised approach for medical image restoration using the concept of multiple-point geostatistics. Experimental results have shown the effectiveness of the proposed technique which has potential as a new methodology for medical and biological image processing. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Unexpected anthropophily in the potential secondary malaria vectors Anopheles coustani s.l. and Anopheles squamosus in Macha, Zambia.

PubMed

Fornadel, Christen M; Norris, Laura C; Franco, Veronica; Norris, Douglas E

2011-08-01

Anopheles coustani s.l. and Anopheles squamosus are sub-Saharan mosquito species that have been implicated in malaria transmission. Although generally believed to be of negligible importance due to their overwhelmingly zoophilic behavior, An. coustani s.l. and An. squamosus made up a large proportion of the anophelines collected by human landing catches during the 2007-2008 and 2008-2009 rainy seasons in Macha, Zambia. Further, polymerase chain reaction-based blood meal identification showed that the majority of blood meals from these mosquito species caught in human-baited Centers for Disease Control light traps were from human hosts. Although no An. coustani s.l. or An. squamosus were found to be positive for Plasmodium, the demonstrated anthropophilic tendencies of these mosquitoes in southern Zambia suggest their potential as secondary malaria vectors.

Bayesian Decision Support

NASA Astrophysics Data System (ADS)

Berliner, M.

2017-12-01

Bayesian statistical decision theory offers a natural framework for decision-policy making in the presence of uncertainty. Key advantages of the approach include efficient incorporation of information and observations. However, in complicated settings it is very difficult, perhaps essentially impossible, to formalize the mathematical inputs needed in the approach. Nevertheless, using the approach as a template is useful for decision support; that is, organizing and communicating our analyses. Bayesian hierarchical modeling is valuable in quantifying and managing uncertainty such cases. I review some aspects of the idea emphasizing statistical model development and use in the context of sea-level rise.

Exploring Understandings of Inclusion in Schools in Zambia and Tanzania Using Reflective Writing and Photography

ERIC Educational Resources Information Center

Miles, Susie

2011-01-01

In this article I explore insights gained from participating in an exploratory, small-scale study led by the Enabling Education Network (EENET) in 17 schools in northern Zambia and five schools in Tanzania. Facilitating South-based research, while based in a Northern university, raises complex ethical issues about voice and control which are…

Evaluation of recruitment and retention strategies for health workers in rural Zambia.

PubMed

Goma, Fastone M; Tomblin Murphy, Gail; MacKenzie, Adrian; Libetwa, Miriam; Nzala, Selestine H; Mbwili-Muleya, Clara; Rigby, Janet; Gough, Amy

2014-01-01

In response to Zambia's critical human resources for health challenges, a number of strategies have been implemented to recruit and retain health workers in rural and remote areas. Prior to this study, the effectiveness of these strategies had not been investigated. The purpose of this study was to determine the impacts of the various health worker retention strategies on health workers in two rural districts of Zambia. Using a modified outcome mapping approach, cross-sectional qualitative and quantitative data were collected from health workers and other stakeholders through focus group discussions and individual interview questionnaires and were supplemented by administrative data. Key themes emerging from qualitative data were identified from transcripts using thematic analysis. Quantitative data were analyzed descriptively as well as by regression modelling. In the latter, the degree to which variation in health workers' self-reported job satisfaction, likelihood of leaving, and frequency of considering leaving, were modelled as functions of participation in each of several retention strategies while controlling for age, gender, profession, and district. Nineteen health worker recruitment and retention strategies were identified and 45 health care workers interviewed in the two districts; participation in each strategy varied from 0% to 80% of study participants. Although a salary top-up for health workers in rural areas was identified as the most effective incentive, almost none of the recruitment and retention strategies were significant predictors of health workers' job satisfaction, likelihood of leaving, or frequency of considering leaving, which were in large part explained by individual characteristics such as age, gender, and profession. These quantitative findings were consistent with the qualitative data, which indicated that existing strategies fail to address major problems identified by health workers in these districts, such as poor living and

Adherence to antiretroviral therapy (ART) during the early months of treatment in rural Zambia: influence of demographic characteristics and social surroundings of patients

PubMed Central

2012-01-01

Background Around 70% of those living with HIV in need of treatment accessed antiretroviral therapy (ART) in Zambia by 2009. However, sustaining high levels of adherence to ART is a challenge. This study aimed to identify the predictive factors associated with ART adherence during the early months of treatment in rural Zambia. Methods This is a field based observational longitudinal study in Mumbwa district, which is located 150 km west of Lusaka, the capital of Zambia. Treatment naive patients aged over 15 years, who initiated treatment during September-November 2010, were enrolled. Patients were interviewed at the initiation and six weeks later. The treatment adherence was measured according to self-reporting by the patients. Multiple logistic regression analysis was performed to identify the predictive factors associated with the adherence. Results Of 157 patients, 59.9% were fully adherent to the treatment six weeks after starting ART. According to the multivariable analysis, full adherence was associated with being female [Adjusted Odds Ratio (AOR), 3.3; 95% Confidence interval (CI), 1.2-8.9], having a spouse who were also on ART (AOR, 4.4; 95% CI, 1.5-13.1), and experience of food insufficiency in the previous 30 days (AOR, 5.0; 95% CI, 1.8-13.8). Some of the most common reasons for missed doses were long distance to health facilities (n = 21, 53.8%), food insufficiency (n = 20, 51.3%), and being busy with other activities such as work (n = 15, 38.5%). Conclusions The treatment adherence continues to be a significant challenge in rural Zambia. Social supports from spouses and people on ART could facilitate their treatment adherence. This is likely to require attention by ART services in the future, focusing on different social influences on male and female in rural Zambia. In addition, poverty reduction strategies may help to reinforce adherence to ART and could mitigate the influence of HIV infection for poor patients and those who fall into poverty after

Developing a national health research system: participatory approaches to legislative, institutional and networking dimensions in Zambia.

PubMed

Chanda-Kapata, Pascalina; Campbell, Sandy; Zarowsky, Christina

2012-06-06

For many sub-Saharan African countries, a National Health Research System (NHRS) exists more in theory than in reality, with the health system itself receiving the majority of investments. However, this lack of attention to NHRS development can, in fact, frustrate health systems in achieving their desired goals. In this case study, we discuss the ongoing development of Zambia's NHRS. We reflect on our experience in the ongoing consultative development of Zambia's NHRS and offer this reflection and process documentation to those engaged in similar initiatives in other settings. We argue that three streams of concurrent activity are critical in developing an NHRS in a resource-constrained setting: developing a legislative framework to determine and define the system's boundaries and the roles all actors will play within it; creating or strengthening an institution capable of providing coordination, management and guidance to the system; and focusing on networking among institutions and individuals to harmonize, unify and strengthen the overall capacities of the research community.

Moving beyond qualitative evaluations of Bayesian models of cognition.

PubMed

Hemmer, Pernille; Tauber, Sean; Steyvers, Mark

2015-06-01

Bayesian models of cognition provide a powerful way to understand the behavior and goals of individuals from a computational point of view. Much of the focus in the Bayesian cognitive modeling approach has been on qualitative model evaluations, where predictions from the models are compared to data that is often averaged over individuals. In many cognitive tasks, however, there are pervasive individual differences. We introduce an approach to directly infer individual differences related to subjective mental representations within the framework of Bayesian models of cognition. In this approach, Bayesian data analysis methods are used to estimate cognitive parameters and motivate the inference process within a Bayesian cognitive model. We illustrate this integrative Bayesian approach on a model of memory. We apply the model to behavioral data from a memory experiment involving the recall of heights of people. A cross-validation analysis shows that the Bayesian memory model with inferred subjective priors predicts withheld data better than a Bayesian model where the priors are based on environmental statistics. In addition, the model with inferred priors at the individual subject level led to the best overall generalization performance, suggesting that individual differences are important to consider in Bayesian models of cognition.

Bayesian learning

NASA Technical Reports Server (NTRS)

Denning, Peter J.

1989-01-01

In 1983 and 1984, the Infrared Astronomical Satellite (IRAS) detected 5,425 stellar objects and measured their infrared spectra. In 1987 a program called AUTOCLASS used Bayesian inference methods to discover the classes present in these data and determine the most probable class of each object, revealing unknown phenomena in astronomy. AUTOCLASS has rekindled the old debate on the suitability of Bayesian methods, which are computationally intensive, interpret probabilities as plausibility measures rather than frequencies, and appear to depend on a subjective assessment of the probability of a hypothesis before the data were collected. Modern statistical methods have, however, recently been shown to also depend on subjective elements. These debates bring into question the whole tradition of scientific objectivity and offer scientists a new way to take responsibility for their findings and conclusions.

Searching Algorithm Using Bayesian Updates

ERIC Educational Resources Information Center

Caudle, Kyle

2010-01-01

In late October 1967, the USS Scorpion was lost at sea, somewhere between the Azores and Norfolk Virginia. Dr. Craven of the U.S. Navy's Special Projects Division is credited with using Bayesian Search Theory to locate the submarine. Bayesian Search Theory is a straightforward and interesting application of Bayes' theorem which involves searching…

A study of malnourished children in children's hospital Lusaka (Zambia).

PubMed

Khan, A A; Gupta, B M

1979-01-01

The parents of 200 malnourished childred referred and admitted over the July-December 1976 period to the nutrition wing of the Children's University Teaching Hospital, Zambia, were interviewed in an effort to understand the home environment of malnourished children in Lusaka, Zambia. The 1974 incidence of malnutrition in Zambia was about 23% with higher prevalences of marasmus and moderate malnutrition. There were 9.4% severly malnourished children admitted in 1976 as compared with less than 1% in 1971. Many of these children were admitted very late in a hypothermic shocked state which is directly responsible for the increasing incidence of mortality over these years. Plasma or blood transfusion is a standard procedure in all shocked cases of kwashiorkor, yet many of the children still die within 24 hours of admission. Malnutrition incidence was found to be closely linked to the rise in price index. The majority of the children were admitted from the rainy months November to March, the time associated with a higher incidence of gastroenteritis, respiratory infections, and measles. 88% of the children were between 1-3 years old. Marasmus (33.5%) and marasmic kwashiorkor (40.5%) were more frequent. 63% of the malnourished childred had attended the child health clinics in their infancy and were immunized but discontinued attendance one vaccination was completed. The problem of malnutrition was in the toddler age group. 86% of the childred came from urban slums and periurban areas; 83% were from unitary families, living in 1 or 2 bedroom houses with no separate provision for a kitchen. Rural families (14%) were living as joint families. 32% of the children were from large families. 52% of the parents were employed as casual laborers and earning under US $35 per month. There were only 10 families with earnings in excess of US $125 per month and only 8 had good sources of income from farms. As many as 68.5% children were experiencing 1 or more adverse factors which

Comparing the performance of geostatistical models with additional information from covariates for sewage plume characterization.

PubMed

Del Monego, Maurici; Ribeiro, Paulo Justiniano; Ramos, Patrícia

2015-04-01

In this work, kriging with covariates is used to model and map the spatial distribution of salinity measurements gathered by an autonomous underwater vehicle in a sea outfall monitoring campaign aiming to distinguish the effluent plume from the receiving waters and characterize its spatial variability in the vicinity of the discharge. Four different geostatistical linear models for salinity were assumed, where the distance to diffuser, the west-east positioning, and the south-north positioning were used as covariates. Sample variograms were fitted by the Matèrn models using weighted least squares and maximum likelihood estimation methods as a way to detect eventual discrepancies. Typically, the maximum likelihood method estimated very low ranges which have limited the kriging process. So, at least for these data sets, weighted least squares showed to be the most appropriate estimation method for variogram fitting. The kriged maps show clearly the spatial variation of salinity, and it is possible to identify the effluent plume in the area studied. The results obtained show some guidelines for sewage monitoring if a geostatistical analysis of the data is in mind. It is important to treat properly the existence of anomalous values and to adopt a sampling strategy that includes transects parallel and perpendicular to the effluent dispersion.

Meeting human resources for health staffing goals by 2018: a quantitative analysis of policy options in Zambia.

PubMed

Tjoa, Aaron; Kapihya, Margaret; Libetwa, Miriam; Schroder, Kate; Scott, Callie; Lee, Joanne; McCarthy, Elizabeth

2010-06-30

The Ministry of Health (MOH) in Zambia is currently operating with fewer than half of the health workers required to deliver basic health services. The MOH has developed a human resources for health (HRH) strategic plan to address the crisis through improved training, hiring, and retention. However, the projected success of each strategy or combination of strategies is unclear. We developed a model to forecast the size of the public sector health workforce in Zambia over the next ten years to identify a combination of interventions that would expand the workforce to meet staffing targets. The key forecasting variables are training enrolment, graduation rates, public sector entry rates for graduates, and attrition of workforce staff. We model, using Excel (Office, Microsoft; 2007), the effects of changes in these variables on the projected number of doctors, clinical officers, nurses and midwives in the public sector workforce in 2018. With no changes to current training, hiring, and attrition conditions, the total number of doctors, clinical officers, nurses, and midwives will increase from 44% to 59% of the minimum necessary staff by 2018. No combination of changes in staff retention, graduation rates, and public sector entry rates of graduates by 2010, without including training expansion, is sufficient to meet staffing targets by 2018 for any cadre except midwives. Training enrolment needs to increase by a factor of between three and thirteen for doctors, three and four for clinical officers, two and three for nurses, and one and two for midwives by 2010 to reach staffing targets by 2018. Necessary enrolment increases can be held to a minimum if the rates of retention, graduation, and public sector entry increase to 100% by 2010, but will need to increase if these rates remain at 2008 levels. Meeting the minimum need for health workers in Zambia this decade will require an increase in health training school enrolment. Supplemental interventions targeting

Meeting human resources for health staffing goals by 2018: a quantitative analysis of policy options in Zambia

PubMed Central

2010-01-01

Background The Ministry of Health (MOH) in Zambia is currently operating with fewer than half of the health workers required to deliver basic health services. The MOH has developed a human resources for health (HRH) strategic plan to address the crisis through improved training, hiring, and retention. However, the projected success of each strategy or combination of strategies is unclear. Methods We developed a model to forecast the size of the public sector health workforce in Zambia over the next ten years to identify a combination of interventions that would expand the workforce to meet staffing targets. The key forecasting variables are training enrolment, graduation rates, public sector entry rates for graduates, and attrition of workforce staff. We model, using Excel (Office, Microsoft; 2007), the effects of changes in these variables on the projected number of doctors, clinical officers, nurses and midwives in the public sector workforce in 2018. Results With no changes to current training, hiring, and attrition conditions, the total number of doctors, clinical officers, nurses, and midwives will increase from 44% to 59% of the minimum necessary staff by 2018. No combination of changes in staff retention, graduation rates, and public sector entry rates of graduates by 2010, without including training expansion, is sufficient to meet staffing targets by 2018 for any cadre except midwives. Training enrolment needs to increase by a factor of between three and thirteen for doctors, three and four for clinical officers, two and three for nurses, and one and two for midwives by 2010 to reach staffing targets by 2018. Necessary enrolment increases can be held to a minimum if the rates of retention, graduation, and public sector entry increase to 100% by 2010, but will need to increase if these rates remain at 2008 levels. Conclusions Meeting the minimum need for health workers in Zambia this decade will require an increase in health training school enrolment

Strengthening and expanding the capacity of health worker education in Zambia.

PubMed

Michelo, Charles; Zulu, Joseph Mumba; Simuyemba, Moses; Andrews, Benjamin; Katubulushi, Max; Chi, Benjamin; Njelesani, Evariste; Vwalika, Bellington; Bowa, Kasonde; Maimbolwa, Margaret; Chipeta, James; Goma, Fastone; Nzala, Selestine; Banda, Sekelani; Mudenda, John; Ahmed, Yusuf; Hachambwa, Lotti; Wilson, Craig; Vermund, Sten; Mulla, Yakub

2017-01-01

Zambia is facing a chronic shortage of health care workers. The paper aimed at understanding how the Medical Education Partnership Initiative (MEPI) program facilitated strengthening and expanding of the national capacity and quality of medical education as well as processes for retaining faculty in Zambia. Data generated through documentary review, key informant interviews and observations were analyzed using a thematic approach. The MEPI program triggered the development of new postgraduate programs thereby increasing student enrollment. This was achieved by leveraging of existing and new partnerships with other universities and differentiating the old Master in Public Health into specialized curriculum. Furthermore, the MEPI program improved the capacity and quality of training by facilitating installation and integration of new technology such as the eGranary digital library, E-learning methods and clinical skills laboratory into the Schools. This technology enabled easy access to relevant data or information, quicker turn around of experiments and enhanced data recording, display and analysis features for experiments. The program also facilitated transforming of the academic environment into a more conducive work place through strengthening the Staff Development program and support towards research activities. These activities stimulated work motivation and interest in research by faculty. Meanwhile, these processes were inhibited by the inability to upload all courses on to Moodle as well as inadequate operating procedures and feedback mechanisms for the Moodle. Expansion and improvement in training processes for health care workers requires targeted investment within medical institutions and strengthening local and international partnerships.

Enhancing multiple-point geostatistical modeling: 1. Graph theory and pattern adjustment

NASA Astrophysics Data System (ADS)

Tahmasebi, Pejman; Sahimi, Muhammad

2016-03-01

In recent years, higher-order geostatistical methods have been used for modeling of a wide variety of large-scale porous media, such as groundwater aquifers and oil reservoirs. Their popularity stems from their ability to account for qualitative data and the great flexibility that they offer for conditioning the models to hard (quantitative) data, which endow them with the capability for generating realistic realizations of porous formations with very complex channels, as well as features that are mainly a barrier to fluid flow. One group of such models consists of pattern-based methods that use a set of data points for generating stochastic realizations by which the large-scale structure and highly-connected features are reproduced accurately. The cross correlation-based simulation (CCSIM) algorithm, proposed previously by the authors, is a member of this group that has been shown to be capable of simulating multimillion cell models in a matter of a few CPU seconds. The method is, however, sensitive to pattern's specifications, such as boundaries and the number of replicates. In this paper the original CCSIM algorithm is reconsidered and two significant improvements are proposed for accurately reproducing large-scale patterns of heterogeneities in porous media. First, an effective boundary-correction method based on the graph theory is presented by which one identifies the optimal cutting path/surface for removing the patchiness and discontinuities in the realization of a porous medium. Next, a new pattern adjustment method is proposed that automatically transfers the features in a pattern to one that seamlessly matches the surrounding patterns. The original CCSIM algorithm is then combined with the two methods and is tested using various complex two- and three-dimensional examples. It should, however, be emphasized that the methods that we propose in this paper are applicable to other pattern-based geostatistical simulation methods.

Tenofovir in second-line ART in Zambia and South Africa: Collaborative analysis of cohort studies

PubMed Central

Wandeler, Gilles; Keiser, Olivia; Mulenga, Lloyd; Hoffmann, Christopher J; Wood, Robin; Chaweza, Thom; Brennan, Alana; Prozesky, Hans; Garone, Daniela; Giddy, Janet; Chimbetete, Cleophas; Boulle, Andrew; Egger, Matthias

2012-01-01

Objectives Tenofovir (TDF) is increasingly used in second-line antiretroviral treatment (ART) in sub-Saharan Africa. We compared outcomes of second-line ART containing and not containing TDF in cohort studies from Zambia and the Republic of South Africa (RSA). Methods Patients aged ≥ 16 years starting protease inhibitor-based second-line ART in Zambia (1 cohort) and RSA (5 cohorts) were included. We compared mortality, immunological failure (all cohorts) and virological failure (RSA only) between patients receiving and not receiving TDF. Competing risk models and Cox models adjusted for age, sex, CD4 count, time on first-line ART and calendar year were used to analyse mortality and treatment failure, respectively. Hazard ratios (HRs) were combined in fixed-effects meta-analysis. Findings 1,687 patients from Zambia and 1,556 patients from RSA, including 1,350 (80.0%) and 206 (13.2%) patients starting TDF, were followed over 4,471 person-years. Patients on TDF were more likely to have started second-line ART in recent years, and had slightly higher baseline CD4 counts than patients not on TDF. Overall 127 patients died, 532 were lost to follow-up and 240 patients developed immunological failure. In RSA 94 patients had virologic failure. Combined HRs comparing tenofovir with other regimens were 0.60 (95% CI 0.41–0.87) for immunologic failure and 0.63 (0.38–1.05) for mortality. The HR for virologic failure in RSA was 0.28 (0.09–0.90). Conclusions In this observational study patients on TDF-containing second-line ART were less likely to develop treatment failure than patients on other regimens. TDF seems to be an effective component of second-line ART in southern Africa. PMID:22743595

Modern Space/Time Geostatistics using River Distances: Data Integration of Turbidity and E.coli Measurements to Assess Fecal Contamination Along the Raritan River in New Jersey

PubMed Central

Money, Eric S.; Carter, Gail P.; Serre, Marc L.

2009-01-01

Escherichia coli (E.coli) is a widely used indicator of fecal contamination in water bodies. External contact and subsequent ingestion of bacteria coming from fecal contamination can lead to harmful health effects. Since E.coli data are sometimes limited, the objective of this study is to use secondary information in the form of turbidity to improve the assessment of E.coli at un-monitored locations. We obtained all E.coli and turbidity monitoring data available from existing monitoring networks for the 2000 – 2006 time period for the Raritan River Basin, New Jersey. Using collocated measurements we developed a predictive model of E.coli from turbidity data. Using this model, soft data are constructed for E.coli given turbidity measurements at 739 space/time locations where only turbidity was measured. Finally, the Bayesian Maximum Entropy (BME) method of modern space/time geostatistics was used for the data integration of monitored and predicted E.coli data to produce maps showing E.coli concentration estimated daily across the river basin. The addition of soft data in conjunction with the use of river distances reduced estimation error by about 30%. Furthermore, based on these maps, up to 35% of river miles in the Raritan Basin had a probability of E.coli impairment greater than 90% on the most polluted day of the study period. PMID:19544881

Modern space/time geostatistics using river distances: data integration of turbidity and E. coli measurements to assess fecal contamination along the Raritan River in New Jersey.

PubMed

Money, Eric S; Carter, Gail P; Serre, Marc L

2009-05-15

Escherichia coli (E. coli) is a widely used indicator of fecal contamination in water bodies. External contact and subsequent ingestion of bacteria coming from fecal contamination can lead to harmful health effects. Since E. coli data are sometimes limited, the objective of this study is to use secondary information in the form of turbidity to improve the assessment of E. coli at unmonitored locations. We obtained all E. coli and turbidity monitoring data available from existing monitoring networks for the 2000-2006 time period for the Raritan River Basin, New Jersey. Using collocated measurements, we developed a predictive model of E. coli from turbidity data. Using this model, soft data are constructed for E. coli given turbidity measurements at 739 space/time locations where only turbidity was measured. Finally, the Bayesian Maximum Entropy (BME) method of modern space/time geostatistics was used for the data integration of monitored and predicted E. coli data to produce maps showing E. coli concentration estimated daily across the river basin. The addition of soft data in conjunction with the use of river distances reduced estimation error by about 30%. Furthermore, based on these maps, up to 35% of river miles in the Raritan Basin had a probability of E coli impairment greater than 90% on the most polluted day of the study period.

Bayesian just-so stories in psychology and neuroscience.

PubMed

Bowers, Jeffrey S; Davis, Colin J

2012-05-01

According to Bayesian theories in psychology and neuroscience, minds and brains are (near) optimal in solving a wide range of tasks. We challenge this view and argue that more traditional, non-Bayesian approaches are more promising. We make 3 main arguments. First, we show that the empirical evidence for Bayesian theories in psychology is weak. This weakness relates to the many arbitrary ways that priors, likelihoods, and utility functions can be altered in order to account for the data that are obtained, making the models unfalsifiable. It further relates to the fact that Bayesian theories are rarely better at predicting data compared with alternative (and simpler) non-Bayesian theories. Second, we show that the empirical evidence for Bayesian theories in neuroscience is weaker still. There are impressive mathematical analyses showing how populations of neurons could compute in a Bayesian manner but little or no evidence that they do. Third, we challenge the general scientific approach that characterizes Bayesian theorizing in cognitive science. A common premise is that theories in psychology should largely be constrained by a rational analysis of what the mind ought to do. We question this claim and argue that many of the important constraints come from biological, evolutionary, and processing (algorithmic) considerations that have no adaptive relevance to the problem per se. In our view, these factors have contributed to the development of many Bayesian "just so" stories in psychology and neuroscience; that is, mathematical analyses of cognition that can be used to explain almost any behavior as optimal. 2012 APA, all rights reserved.

Epilepsy Care in Zambia: A Study of Traditional Healers

PubMed Central

Baskind, Roy; Birbeck, Gretchen

2005-01-01

Summary Purpose Most people with epilepsy (PWE) reside in developing countries with limited access to medical care. In sub-Saharan Africa (SSA), traditional healers (THs) play a prominent role in caring for PWE, yet little is known about epilepsy care by THs. We conducted a multimethod, qualitative study to better understand the epilepsy care delivered by THs in Zambia. Methods We conducted focus-group discussions with THs, in-depth semistructured interviews with a well-recognized TH at his place of work, and multiple informal interviews with health-care providers in rural Zambia. Results THs recognize the same symptoms that a neurologist elicits to characterize seizure onset (e.g., olfactory hallucinations, jacksonian march, automatisms). Although THs acknowledge a familial propensity for some seizures and endorse causes of symptomatic epilepsy, they believe witchcraft plays a central, provocative role in most seizures. Treatment is initiated after the first seizure and usually incorporates certain plant and animal products. Patients who do not experience further seizures are considered cured. Those who do not respond to therapy may be referred to other healers. Signs of concomitant systemic illness are the most common reason for referral to a hospital. As a consequence of this work, our local Epilepsy Care Team has developed a more collaborative relationship with THs in the region. Conclusions THs obtain detailed event histories, are treatment focused, and may refer patients who have refractory seizures to therapy to other healers. Under some circumstances, they recognize a role for modern health care and refer patients to the hospital. Given their predominance as care providers for PWE, further understanding of their approach to care is important. Collaborative relationships between physicians and THs are needed if we hope to bridge the treatment gap in SSA. PMID:16026565

Developmental assessment, cultural context, gender, and schooling in Zambia.

PubMed

Serpell, Robert; Jere-Folotiya, Jacqueline

2008-04-01

Multiple perspectives on the assessment of children's development at the school-community interface in rural areas of Zambia are discussed in the light of several empirical studies conducted between 1974 and 2005. A longitudinal trace study of a cohort of 46 young people born into a rural, Chewa community in Katete District found that girls' scores in early childhood on a battery of ecoculturally grounded cognitive tests correlated less well than they did for boys with two educational outcomes: number of grades of schooling completed, and adult literacy scores. Conversely, ratings of the children on indigenous conceptions of intelligence by adults familiar with the children in the context of their home village lives predicted the same outcomes better for girls than for boys. A separate, linked experiment compared the performance of 76 Katete school children with that of 84 school children in the capital city of Lusaka on the US standardized Draw-a-Person Test (DPT) and the Panga Munthu Test (PMT), an expanded version of one of the tests developed for the Zambian trace study. Analysis of the correlations among scores on these two tests, age, and teacher ratings suggests that aptitudes evident in the home and school domains are less well integrated for rural girls than for urban boys, and that for a low-income, rural population, the PMT taps the domain of home cognition better than school cognition, while the converse is true of the DPT. Implications for educational assessment in Zambia are discussed, and supportive documentation is cited from two ongoing programs of test development. The authors conclude that if educational testing is to support the process of enhancing educational equity across gender, family socioeconomic status, and residential location, its focus should be broadened to include other dimensions of psychological development such as multilingual and personal-social competencies.

A Preliminary Assessment of Rotavirus Vaccine Effectiveness in Zambia.

PubMed

Beres, Laura K; Tate, Jacqueline E; Njobvu, Lungowe; Chibwe, Bertha; Rudd, Cheryl; Guffey, M Brad; Stringer, Jeffrey S A; Parashar, Umesh D; Chilengi, Roma

2016-05-01

Diarrhea is the third leading cause of child death in Zambia. Up to one-third of diarrhea cases resulting in hospitalization and/or death are caused by vaccine-preventable rotavirus. In January 2012, Zambia initiated a pilot introduction of the Rotarix live, oral rotavirus vaccine in all public health facilities in Lusaka Province. Between July 2012 and October 2013, we conducted a case-control study at 6 public sector sites to estimate rotavirus vaccine effectiveness (VE) in age-eligible children presenting with diarrhea. We computed the odds of having received at least 1 dose of Rotarix among children whose stool was positive for rotavirus antigen (cases) and children whose stool was negative (controls). We adjusted the resulting odds ratio (OR) for patient age, calendar month of presentation, and clinical site, and expressed VE as (1 - adjusted OR) × 100. A total of 91 rotavirus-positive cases and 298 rotavirus-negative controls who had under-5 card-confirmed vaccination status and were ≥6 months of age were included in the case-control analysis. Among rotavirus-positive children who were age-eligible to be vaccinated, 20% were hospitalized. Against rotavirus diarrhea of all severity, the adjusted 2-dose VE was 26% (95% confidence interval [CI], -30% to 58%) among children ≥6 months of age. VE against hospitalized children ≥6 months of age was 56% (95% CI, -34% to 86%). We observed a higher point estimate for VE against increased severity of illness compared with milder disease, but were not powered to detect a low level of VE against milder disease. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

Health worker perspectives on user fee removal in Zambia

PubMed Central

2012-01-01

Background User fees for primary care services were removed in rural districts in Zambia in 2006. Experience from other countries has suggested that health workers play a key role in determining the success of a fee removal policy, but also find the implementation of such a policy challenging. The policy was introduced against a backdrop of a major shortage in qualified health staff. Methods As part of a larger study on the experience and effect of user fee removal in Zambia, a number of case studies at the facility level were conducted. As part of these, quantitative and qualitative data were collected to evaluate health workers’ satisfaction and experiences in charging and non-charging facilities. Results Our findings show that health-care workers have mixed feelings about the policy change and its consequences. We found some evidence that personnel motivation was higher in non-charging facilities compared to facilities still charging. Yet it is unclear whether this effect was due to differences in the user fee policy or to the fact that a lot of staff interviewed in non-charging facilities were working in mission facilities, where we found a significantly higher motivation. Health workers expressed satisfaction with an apparent increase in the number of patients visiting the facilities and the removal of a deterring factor for many needy patients, but also complained about an increased workload. Furthermore, working conditions were said to have worsened, which staff felt was linked to the absence of additional resources to deal with the increased demand or replace the loss of revenue generated by fees. Conclusion These findings highlight the need to pay attention to supply-side measures when removing demand-side barriers such as user fees and in particular to be concerned about the burden that increased demand can place on already over-stretched health workers. PMID:23110690

An Evaluation of Trauma Focused Cognitive Behavioral Therapy for Children in Zambia

PubMed Central

Murray, Laura K; Familiar, Itziar; Skavenski, Stephanie; Jere, Elizabeth; Cohen, Judy; Imasiku, Mwiya; Mayeya, John; Bass, Judith K; Bolton, Paul

2013-01-01

Objectives To monitor and evaluate the feasibility of implementing Trauma Focused-Cognitive Behavioral Therapy (TF-CBT) to address trauma and stress-related symptoms in orphans and vulnerable children (OVC) in Zambia as part of ongoing programming within a non-governmental organization (NGO). Methods As part of ongoing programming, voluntary care-workers administered locally validated assessments to identify children who met criteria for moderate to severe trauma symptomatology. Local lay counselors implemented TF-CBT with identified families, while participating in ongoing supervision. Fifty-eight children and adolescents aged 5–18 completed the TF-CBT treatment, with pre- and post-assessments. Results The mean number of traumas reported by the treatment completers (N=58) was 4.11. Post assessments showed significant reductions in severity of trauma symptoms (p<0.0001), and severity of shame symptoms (p<0.0001). Conclusions Our results suggest that TF-CBT is a feasible treatment option in Zambia for OVC. A decrease in symptoms suggests that a controlled trial is warranted. Implementation factors monitored suggest that it is feasible to integrate and evaluate evidence-based mental health assessments and intervention into programmatic services run by an NGO in low/middle resource countries. Results also support the effectiveness of implementation strategies such as task shifting, and the apprenticeship model of training and supervision. PMID:23768939

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

The economic value of an improved malaria treatment programme in Zambia: results from a contingent valuation survey.

PubMed

Masiye, Felix; Rehnberg, Clas

2005-12-15

Zambia is facing a double crisis of increasing malaria burden and dwindling capacity to deal with the endemic malaria burden. The pursuit of sustainable but equity mechanisms for financing malaria programmes is a subject of crucial policy discussion. This requires that comprehensive accounting of the economic impact of the various malaria programmes. Information on the economic value of programmes is essential in soliciting appropriate funding allocations for malaria control. This paper specifically seeks to elicit a measure of the economic benefits of an improved malaria treatment programme in Zambia. The paper also studies the equity implications in malaria treatment given that demand or malaria treatment is determined by household socio-economic status. A contingent valuation survey of about 300 Zambian households was conducted in four districts. Willingness-to-pay (WTP) was elicited for an improved treatment programme for malaria in order to generate a measure of the economic benefits of the programme. The payment card method was used in eliciting WTP bids. The study reports that malaria treatment has significant economic benefits to society. The total economic benefits of an improved treatment programme were estimated at an equivalent of USD 77 million per annum, representing about 1.8% of Zambia's GDP. The study also reports the theoretically anticipated association between WTP and several socio-economic factors. Our income elasticity of demand is positive and similar in magnitude to estimates reported in similar studies. Finally, from an equity standpoint, the constraints imposed by income and socio-economic status are discussed.

The economic value of an improved malaria treatment programme in Zambia: results from a contingent valuation survey

PubMed Central

Masiye, Felix; Rehnberg, Clas

2005-01-01

Background Zambia is facing a double crisis of increasing malaria burden and dwindling capacity to deal with the endemic malaria burden. The pursuit of sustainable but equity mechanisms for financing malaria programmes is a subject of crucial policy discussion. This requires that comprehensive accounting of the economic impact of the various malaria programmes. Information on the economic value of programmes is essential in soliciting appropriate funding allocations for malaria control. Aims and objectives This paper specifically seeks to elicit a measure of the economic benefits of an improved malaria treatment programme in Zambia. The paper also studies the equity implications in malaria treatment given that demand or malaria treatment is determined by household socio-economic status. Methods A contingent valuation survey of about 300 Zambian households was conducted in four districts. Willingness-to-pay (WTP) was elicited for an improved treatment programme for malaria in order to generate a measure of the economic benefits of the programme. The payment card method was used in eliciting WTP bids. Findings The study reports that malaria treatment has significant economic benefits to society. The total economic benefits of an improved treatment programme were estimated at an equivalent of US$ 77 million per annum, representing about 1.8% of Zambia's GDP. The study also reports the theoretically anticipated association between WTP and several socio-economic factors. Our income elasticity of demand is positive and similar in magnitude to estimates reported in similar studies. Finally, from an equity standpoint, the constraints imposed by income and socio-economic status are discussed. PMID:16356176

Bayesian structural equation modeling in sport and exercise psychology.

PubMed

Stenling, Andreas; Ivarsson, Andreas; Johnson, Urban; Lindwall, Magnus

2015-08-01

Bayesian statistics is on the rise in mainstream psychology, but applications in sport and exercise psychology research are scarce. In this article, the foundations of Bayesian analysis are introduced, and we will illustrate how to apply Bayesian structural equation modeling in a sport and exercise psychology setting. More specifically, we contrasted a confirmatory factor analysis on the Sport Motivation Scale II estimated with the most commonly used estimator, maximum likelihood, and a Bayesian approach with weakly informative priors for cross-loadings and correlated residuals. The results indicated that the model with Bayesian estimation and weakly informative priors provided a good fit to the data, whereas the model estimated with a maximum likelihood estimator did not produce a well-fitting model. The reasons for this discrepancy between maximum likelihood and Bayesian estimation are discussed as well as potential advantages and caveats with the Bayesian approach.

Factors influencing modes of transport and travel time for obstetric care: a mixed methods study in Zambia and Uganda.

PubMed

Sacks, Emma; Vail, Daniel; Austin-Evelyn, Katherine; Greeson, Dana; Atuyambe, Lynn M; Macwan'gi, Mubiana; Kruk, Margaret E; Grépin, Karen A

2016-04-01

Transportation is an important barrier to accessing obstetric care for many pregnant and postpartum women in low-resource settings, particularly in rural areas. However, little is known about how pregnant women travel to health facilities in these settings. We conducted 1633 exit surveys with women who had a recent facility delivery and 48 focus group discussions with women who had either a home or a facility birth in the past year in eight districts in Uganda and Zambia. Quantitative data were analysed using univariate statistics, and qualitative data were analysed using thematic content analysis techniques. On average, women spent 62-68 min travelling to a clinic for delivery. Very different patterns in modes of transport were observed in the two countries: 91% of Ugandan women employed motorized forms of transportation, while only 57% of women in Zambia did. Motorcycle taxis were the most commonly used in Uganda, while cars, trucks and taxis were the most commonly used mode of transportation in Zambia. Lower-income women were less likely to use motorized modes of transportation: in Zambia, women in the poorest quintile took 94 min to travel to a health facility, compared with 34 for the wealthiest quintile; this difference between quintiles was ∼50 min in Uganda. Focus group discussions confirmed that transport is a major challenge due to a number of factors we categorized as the 'three A's:' affordability, accessibility and adequacy of transport options. Women reported that all of these factors had influenced their decision not to deliver in a health facility. The two countries had markedly different patterns of transportation for obstetric care, and modes of transport and travel times varied dramatically by wealth quintile, which policymakers need to take into account when designing obstetric transport interventions. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

A default Bayesian hypothesis test for mediation.

PubMed

Nuijten, Michèle B; Wetzels, Ruud; Matzke, Dora; Dolan, Conor V; Wagenmakers, Eric-Jan

2015-03-01

In order to quantify the relationship between multiple variables, researchers often carry out a mediation analysis. In such an analysis, a mediator (e.g., knowledge of a healthy diet) transmits the effect from an independent variable (e.g., classroom instruction on a healthy diet) to a dependent variable (e.g., consumption of fruits and vegetables). Almost all mediation analyses in psychology use frequentist estimation and hypothesis-testing techniques. A recent exception is Yuan and MacKinnon (Psychological Methods, 14, 301-322, 2009), who outlined a Bayesian parameter estimation procedure for mediation analysis. Here we complete the Bayesian alternative to frequentist mediation analysis by specifying a default Bayesian hypothesis test based on the Jeffreys-Zellner-Siow approach. We further extend this default Bayesian test by allowing a comparison to directional or one-sided alternatives, using Markov chain Monte Carlo techniques implemented in JAGS. All Bayesian tests are implemented in the R package BayesMed (Nuijten, Wetzels, Matzke, Dolan, & Wagenmakers, 2014).

Testing geostatistical methods to combine radar and rain gauges for precipitation mapping in a mountainous region

NASA Astrophysics Data System (ADS)

Erdin, R.; Frei, C.; Sideris, I.; Kuensch, H.-R.

2010-09-01

There is an increasing demand for accurate mapping of precipitation at a spatial resolution of kilometers. Radar and rain gauges - the two main precipitation measurement systems - exhibit complementary strengths and weaknesses. Radar offers high spatial and temporal resolution but lacks accuracy of absolute values, whereas rain gauges provide accurate values at their specific point location but suffer from poor spatial representativeness. Methods of geostatistical mapping have been proposed to combine radar and rain gauge data for quantitative precipitation estimation (QPE). The aim is to combine the respective strengths and compensate for the respective weaknesses of the two observation platforms. Several studies have demonstrated the potential of these methods over topography of moderate complexity, but their performance remains unclear for high-mountain regions where rainfall patterns are complex, the representativeness of rain gauge measurements is limited and radar observations are obstructed. In this study we examine the potential and limitations of two frequently used geostatistical mapping methods for the territory of Switzerland, where the mountain chain of the Alps poses particular challenges to QPE. The two geostatistical methods explored are kriging with external drift (KED) using radar as drift variable and ordinary kriging of radar errors (OKRE). The radar data is a composite from three C-band radars using a constant Z-R relationship, advanced correction processings for visibility, ground clutter and beam shielding and a climatological bias adjustment. The rain gauge data originates from an automatic network with a typical inter-station distance of 25 km. Both combination methods are applied to a set of case examples representing typical rainfall situations in the Alps with their inherent challenges at daily and hourly time resolution. The quality of precipitation estimates is assessed by several skill scores calculated from cross validation errors at

Free will in Bayesian and inverse Bayesian inference-driven endo-consciousness.

PubMed

Gunji, Yukio-Pegio; Minoura, Mai; Kojima, Kei; Horry, Yoichi

2017-12-01

How can we link challenging issues related to consciousness and/or qualia with natural science? The introduction of endo-perspective, instead of exo-perspective, as proposed by Matsuno, Rössler, and Gunji, is considered one of the most promising candidate approaches. Here, we distinguish the endo-from the exo-perspective in terms of whether the external is or is not directly operated. In the endo-perspective, the external can be neither perceived nor recognized directly; rather, one can only indirectly summon something outside of the perspective, which can be illustrated by a causation-reversal pair. On one hand, causation logically proceeds from the cause to the effect. On the other hand, a reversal from the effect to the cause is non-logical and is equipped with a metaphorical structure. We argue that the differences in exo- and endo-perspectives result not from the difference between Western and Eastern cultures, but from differences between modernism and animism. Here, a causation-reversal pair described using a pair of upward (from premise to consequence) and downward (from consequence to premise) causation and a pair of Bayesian and inverse Bayesian inference (BIB inference). Accordingly, the notion of endo-consciousness is proposed as an agent equipped with BIB inference. We also argue that BIB inference can yield both highly efficient computations through Bayesian interference and robust computations through inverse Bayesian inference. By adapting a logical model of the free will theorem to the BIB inference, we show that endo-consciousness can explain free will as a regression of the controllability of voluntary action. Copyright © 2017. Published by Elsevier Ltd.

The Impact of an Unconditional Cash Transfer on Early Child Development: The Zambia Child Grant Program

ERIC Educational Resources Information Center

Seidenfeld, David; Prencipe, Leah; Handa, Sudhanshu; Hawkinson, Laura

2015-01-01

Little research has been conducted on unconditional cash transfers (UCTs) despite their growing prevalence in Africa, including South Africa, Zambia, Zimbabwe, Kenya, Malawi, Lesotho, and Uganda. In this study, researchers implemented a randomized control trial with over 2,500 households to investigate the impact of Africa's child grant program on…

HIV Testing among Adolescents in Ndola, Zambia: How Individual, Relational, and Environmental Factors Relate to Demand

ERIC Educational Resources Information Center

Denison, Julie A.; McCauley, Ann P.; Dunnett-Dagg, Wendy A.; Lungu, Nalakwanji; Sweat, Michael D.

2009-01-01

This study examined how individual, relational and environmental factors related to adolescent demand for HIV voluntary counseling and testing (VCT). A cross-sectional survey among randomly selected 16-19-year-olds in Ndola, Zambia, covered individual (e.g., HIV knowledge), environmental (e.g., distance), and relational factors (e.g., discussed…

Application of Bayesian Approach in Cancer Clinical Trial

PubMed Central

Bhattacharjee, Atanu

2014-01-01

The application of Bayesian approach in clinical trials becomes more useful over classical method. It is beneficial from design to analysis phase. The straight forward statement is possible to obtain through Bayesian about the drug treatment effect. Complex computational problems are simple to handle with Bayesian techniques. The technique is only feasible to performing presence of prior information of the data. The inference is possible to establish through posterior estimates. However, some limitations are present in this method. The objective of this work was to explore the several merits and demerits of Bayesian approach in cancer research. The review of the technique will be helpful for the clinical researcher involved in the oncology to explore the limitation and power of Bayesian techniques. PMID:29147387

Bayesian least squares deconvolution

NASA Astrophysics Data System (ADS)

Asensio Ramos, A.; Petit, P.

2015-11-01

Aims: We develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods: We consider LSD under the Bayesian framework and we introduce a flexible Gaussian process (GP) prior for the LSD profile. This prior allows the result to automatically adapt to the presence of signal. We exploit several linear algebra identities to accelerate the calculations. The final algorithm can deal with thousands of spectral lines in a few seconds. Results: We demonstrate the reliability of the method with synthetic experiments and we apply it to real spectropolarimetric observations of magnetic stars. We are able to recover the magnetic signals using a small number of spectral lines, together with the uncertainty at each velocity bin. This allows the user to consider if the detected signal is reliable. The code to compute the Bayesian LSD profile is freely available.

Bayesian multimodel inference for dose-response studies

USGS Publications Warehouse

Link, W.A.; Albers, P.H.

2007-01-01

Statistical inference in dose?response studies is model-based: The analyst posits a mathematical model of the relation between exposure and response, estimates parameters of the model, and reports conclusions conditional on the model. Such analyses rarely include any accounting for the uncertainties associated with model selection. The Bayesian inferential system provides a convenient framework for model selection and multimodel inference. In this paper we briefly describe the Bayesian paradigm and Bayesian multimodel inference. We then present a family of models for multinomial dose?response data and apply Bayesian multimodel inferential methods to the analysis of data on the reproductive success of American kestrels (Falco sparveriuss) exposed to various sublethal dietary concentrations of methylmercury.

A guide to Bayesian model selection for ecologists

USGS Publications Warehouse

Hooten, Mevin B.; Hobbs, N.T.

2015-01-01

The steady upward trend in the use of model selection and Bayesian methods in ecological research has made it clear that both approaches to inference are important for modern analysis of models and data. However, in teaching Bayesian methods and in working with our research colleagues, we have noticed a general dissatisfaction with the available literature on Bayesian model selection and multimodel inference. Students and researchers new to Bayesian methods quickly find that the published advice on model selection is often preferential in its treatment of options for analysis, frequently advocating one particular method above others. The recent appearance of many articles and textbooks on Bayesian modeling has provided welcome background on relevant approaches to model selection in the Bayesian framework, but most of these are either very narrowly focused in scope or inaccessible to ecologists. Moreover, the methodological details of Bayesian model selection approaches are spread thinly throughout the literature, appearing in journals from many different fields. Our aim with this guide is to condense the large body of literature on Bayesian approaches to model selection and multimodel inference and present it specifically for quantitative ecologists as neutrally as possible. We also bring to light a few important and fundamental concepts relating directly to model selection that seem to have gone unnoticed in the ecological literature. Throughout, we provide only a minimal discussion of philosophy, preferring instead to examine the breadth of approaches as well as their practical advantages and disadvantages. This guide serves as a reference for ecologists using Bayesian methods, so that they can better understand their options and can make an informed choice that is best aligned with their goals for inference.

Geostatistical three-dimensional modeling of oolite shoals, St. Louis Limestone, southwest Kansas

USGS Publications Warehouse

Qi, L.; Carr, T.R.; Goldstein, R.H.

2007-01-01

In the Hugoton embayment of southwestern Kansas, reservoirs composed of relatively thin (<4 m; <13.1 ft) oolitic deposits within the St. Louis Limestone have produced more than 300 million bbl of oil. The geometry and distribution of oolitic deposits control the heterogeneity of the reservoirs, resulting in exploration challenges and relatively low recovery. Geostatistical three-dimensional (3-D) models were constructed to quantify the geometry and spatial distribution of oolitic reservoirs, and the continuity of flow units within Big Bow and Sand Arroyo Creek fields. Lithofacies in uncored wells were predicted from digital logs using a neural network. The tilting effect from the Laramide orogeny was removed to construct restored structural surfaces at the time of deposition. Well data and structural maps were integrated to build 3-D models of oolitic reservoirs using stochastic simulations with geometry data. Three-dimensional models provide insights into the distribution, the external and internal geometry of oolitic deposits, and the sedimentologic processes that generated reservoir intervals. The structural highs and general structural trend had a significant impact on the distribution and orientation of the oolitic complexes. The depositional pattern and connectivity analysis suggest an overall aggradation of shallow-marine deposits during pulses of relative sea level rise followed by deepening near the top of the St. Louis Limestone. Cemented oolitic deposits were modeled as barriers and baffles and tend to concentrate at the edge of oolitic complexes. Spatial distribution of porous oolitic deposits controls the internal geometry of rock properties. Integrated geostatistical modeling methods can be applicable to other complex carbonate or siliciclastic reservoirs in shallow-marine settings. Copyright ?? 2007. The American Association of Petroleum Geologists. All rights reserved.

Universal Darwinism As a Process of Bayesian Inference.

PubMed

Campbell, John O

2016-01-01

Many of the mathematical frameworks describing natural selection are equivalent to Bayes' Theorem, also known as Bayesian updating. By definition, a process of Bayesian Inference is one which involves a Bayesian update, so we may conclude that these frameworks describe natural selection as a process of Bayesian inference. Thus, natural selection serves as a counter example to a widely-held interpretation that restricts Bayesian Inference to human mental processes (including the endeavors of statisticians). As Bayesian inference can always be cast in terms of (variational) free energy minimization, natural selection can be viewed as comprising two components: a generative model of an "experiment" in the external world environment, and the results of that "experiment" or the "surprise" entailed by predicted and actual outcomes of the "experiment." Minimization of free energy implies that the implicit measure of "surprise" experienced serves to update the generative model in a Bayesian manner. This description closely accords with the mechanisms of generalized Darwinian process proposed both by Dawkins, in terms of replicators and vehicles, and Campbell, in terms of inferential systems. Bayesian inference is an algorithm for the accumulation of evidence-based knowledge. This algorithm is now seen to operate over a wide range of evolutionary processes, including natural selection, the evolution of mental models and cultural evolutionary processes, notably including science itself. The variational principle of free energy minimization may thus serve as a unifying mathematical framework for universal Darwinism, the study of evolutionary processes operating throughout nature.

Adapting the emergency first aid responder course for Zambia through curriculum mapping and blueprinting.

PubMed

Pigoga, Jennifer L; Cunningham, Charmaine; Kafwamfwa, Muhumpu; Wallis, Lee A

2017-12-10

Community members are often the first to witness and respond to medical and traumatic emergencies, making them an essential first link to emergency care systems. The Emergency First Aid Responder (EFAR) programme is short course originally developed to help South Africans manage emergencies at the community level, pending arrival of formal care providers. EFAR was implemented in two rural regions of Zambia in 2015, but no changes were originally made to tailor the course to the new setting. We undertook this study to identify potential refinements in the original EFAR curriculum, and to adapt it to the local context in Zambia. The EFAR curriculum was mapped against available chief complaint data. An expert group used information from the map, in tandem with personal knowledge, to rank each course topic for potential impact on patient outcomes and frequency of use in practice. Individual blueprints were compiled to generate a refined EFAR curriculum, the time breakdown of which reflects the relative weight of each topic. This study was conducted based on data collected in Kasama, a rural region of Zambia's Northern Province. An expert group of five physicians practising emergency medicine was selected; all reviewers have expertise in the Zambian context, EFAR programme and/or curriculum development. The range of emergencies that Zambian EFARs encounter indicates that the course must be broad in scope. The refined curriculum covers 54 topics (seven new) and 25 practical skills (five new). Practical and didactic time devoted to general patient care and scene management increased significantly, while time devoted to most other clinical, presentation-based categories (eg, trauma care) decreased. Discrepancies between original and refined curricula highlight a mismatch between the external curriculum and local context. Even with limited data and resources, curriculum mapping and blueprinting are possible means of resolving these contextual issues. © Article author

Daniel Goodman’s empirical approach to Bayesian statistics

USGS Publications Warehouse

Gerrodette, Tim; Ward, Eric; Taylor, Rebecca L.; Schwarz, Lisa K.; Eguchi, Tomoharu; Wade, Paul; Himes Boor, Gina

2016-01-01

Bayesian statistics, in contrast to classical statistics, uses probability to represent uncertainty about the state of knowledge. Bayesian statistics has often been associated with the idea that knowledge is subjective and that a probability distribution represents a personal degree of belief. Dr. Daniel Goodman considered this viewpoint problematic for issues of public policy. He sought to ground his Bayesian approach in data, and advocated the construction of a prior as an empirical histogram of “similar” cases. In this way, the posterior distribution that results from a Bayesian analysis combined comparable previous data with case-specific current data, using Bayes’ formula. Goodman championed such a data-based approach, but he acknowledged that it was difficult in practice. If based on a true representation of our knowledge and uncertainty, Goodman argued that risk assessment and decision-making could be an exact science, despite the uncertainties. In his view, Bayesian statistics is a critical component of this science because a Bayesian analysis produces the probabilities of future outcomes. Indeed, Goodman maintained that the Bayesian machinery, following the rules of conditional probability, offered the best legitimate inference from available data. We give an example of an informative prior in a recent study of Steller sea lion spatial use patterns in Alaska.

A Gentle Introduction to Bayesian Analysis: Applications to Developmental Research

PubMed Central

van de Schoot, Rens; Kaplan, David; Denissen, Jaap; Asendorpf, Jens B; Neyer, Franz J; van Aken, Marcel AG

2014-01-01

Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First, the ingredients underlying Bayesian methods are introduced using a simplified example. Thereafter, the advantages and pitfalls of the specification of prior knowledge are discussed. To illustrate Bayesian methods explained in this study, in a second example a series of studies that examine the theoretical framework of dynamic interactionism are considered. In the Discussion the advantages and disadvantages of using Bayesian statistics are reviewed, and guidelines on how to report on Bayesian statistics are provided. PMID:24116396

Redressing Gender Inequalities in Education. A Review of Constraints and Priorities in Malawi, Zambia, and Zimbabwe.

ERIC Educational Resources Information Center

Swainson, Nicola

The causes and manifestations of gender inequalities in education in Malawi, Zambia, and Zimbabwe and policy options for redressing them were examined through a review of literature on the causes, nature, and extent of gender disparities in education in the study region and information on efforts to eliminate gender inequality. Special attention…

Assessment of Integrated Environmental Management in Public and Private Schools in the Copperbelt Province of Zambia

ERIC Educational Resources Information Center

Makisa, Kaponda

2016-01-01

Copperbelt Province is one of the ten provinces of Zambia. It has public and private schools which have been faced with escalating levels of environmental problems due to growth in human population and economic growth. The environmental problems which are matters of concern in the schools include, unsound waste management, loss of vegetation…

Predictors of Attitudes toward Intimate Partner Violence: A Comparative Study of Men in Zambia and Kenya

ERIC Educational Resources Information Center

Lawoko, Stephen

2008-01-01

Attitudes toward intimate partner violence (IPV) were compared between Zambian and Kenyan men on sociodemographic, attitudinal, and structural predictors of such attitudes. Data were retrieved from the latest Demographic and Health Surveys in each country. The results showed that many men in Zambia (71%) and Kenya (68%) justified IPV to punish a…

Grassroot Soccer Resiliency Pilot Program: Building Resiliency through Sport-Based Education in Zambia and South Africa

ERIC Educational Resources Information Center

Peacock-Villada, Paola; DeCelles, Jeff; Banda, Peter S.

2007-01-01

Grassroot Soccer (GRS), a U.S.-based nonprofit organization, designed a curriculum and sport-based teaching model to build resiliency, targeting boys and girls in Lusaka, Zambia, and Johannesburg, South Africa, where most children are reminded daily of the devastation caused by AIDS and where many face chronic and acute hardship. Collaborating…

Bayesian Inference: with ecological applications

USGS Publications Warehouse

Link, William A.; Barker, Richard J.

2010-01-01

This text provides a mathematically rigorous yet accessible and engaging introduction to Bayesian inference with relevant examples that will be of interest to biologists working in the fields of ecology, wildlife management and environmental studies as well as students in advanced undergraduate statistics.. This text opens the door to Bayesian inference, taking advantage of modern computational efficiencies and easily accessible software to evaluate complex hierarchical models.

Chapter J: Issues and challenges in the application of geostatistics and spatial-data analysis to the characterization of sand-and-gravel resources

USGS Publications Warehouse

Hack, Daniel R.

2005-01-01

Sand-and-gravel (aggregate) resources are a critical component of the Nation's infrastructure, yet aggregate-mining technologies lag far behind those of metalliferous mining and other sectors. Deposit-evaluation and site-characterization methodologies are antiquated, and few serious studies of the potential applications of spatial-data analysis and geostatistics have been published. However, because of commodity usage and the necessary proximity of a mine to end use, aggregate-resource exploration and evaluation differ fundamentally from comparable activities for metalliferous ores. Acceptable practices, therefore, can reflect this cruder scale. The increasing use of computer technologies is colliding with the need for sand-and-gravel mines to modernize and improve their overall efficiency of exploration, mine planning, scheduling, automation, and other operations. The emergence of megaquarries in the 21st century will also be a contributing factor. Preliminary research into the practical applications of exploratory-data analysis (EDA) have been promising. For example, EDA was used to develop a linear-regression equation to forecast freeze-thaw durability from absorption values for Lower Paleozoic carbonate rocks mined for crushed aggregate from quarries in Oklahoma. Applications of EDA within a spatial context, a method of spatial-data analysis, have also been promising, as with the investigation of undeveloped sand-and-gravel resources in the sedimentary deposits of Pleistocene Lake Bonneville, Utah. Formal geostatistical investigations of sand-and-gravel deposits are quite rare, and the primary focus of those studies that have been completed is on the spatial characterization of deposit thickness and its subsequent effect on ore reserves. A thorough investigation of a gravel deposit in an active aggregate-mining area in central Essex, U.K., emphasized the problems inherent in the geostatistical characterization of particle-size-analysis data. Beyond such factors

Bayesian statistics in medicine: a 25 year review.

PubMed

Ashby, Deborah

2006-11-15

This review examines the state of Bayesian thinking as Statistics in Medicine was launched in 1982, reflecting particularly on its applicability and uses in medical research. It then looks at each subsequent five-year epoch, with a focus on papers appearing in Statistics in Medicine, putting these in the context of major developments in Bayesian thinking and computation with reference to important books, landmark meetings and seminal papers. It charts the growth of Bayesian statistics as it is applied to medicine and makes predictions for the future. From sparse beginnings, where Bayesian statistics was barely mentioned, Bayesian statistics has now permeated all the major areas of medical statistics, including clinical trials, epidemiology, meta-analyses and evidence synthesis, spatial modelling, longitudinal modelling, survival modelling, molecular genetics and decision-making in respect of new technologies.

Bayesian Just-So Stories in Psychology and Neuroscience

ERIC Educational Resources Information Center

Bowers, Jeffrey S.; Davis, Colin J.

2012-01-01

According to Bayesian theories in psychology and neuroscience, minds and brains are (near) optimal in solving a wide range of tasks. We challenge this view and argue that more traditional, non-Bayesian approaches are more promising. We make 3 main arguments. First, we show that the empirical evidence for Bayesian theories in psychology is weak.…

Universal Darwinism As a Process of Bayesian Inference

PubMed Central

Campbell, John O.

2016-01-01

Many of the mathematical frameworks describing natural selection are equivalent to Bayes' Theorem, also known as Bayesian updating. By definition, a process of Bayesian Inference is one which involves a Bayesian update, so we may conclude that these frameworks describe natural selection as a process of Bayesian inference. Thus, natural selection serves as a counter example to a widely-held interpretation that restricts Bayesian Inference to human mental processes (including the endeavors of statisticians). As Bayesian inference can always be cast in terms of (variational) free energy minimization, natural selection can be viewed as comprising two components: a generative model of an “experiment” in the external world environment, and the results of that “experiment” or the “surprise” entailed by predicted and actual outcomes of the “experiment.” Minimization of free energy implies that the implicit measure of “surprise” experienced serves to update the generative model in a Bayesian manner. This description closely accords with the mechanisms of generalized Darwinian process proposed both by Dawkins, in terms of replicators and vehicles, and Campbell, in terms of inferential systems. Bayesian inference is an algorithm for the accumulation of evidence-based knowledge. This algorithm is now seen to operate over a wide range of evolutionary processes, including natural selection, the evolution of mental models and cultural evolutionary processes, notably including science itself. The variational principle of free energy minimization may thus serve as a unifying mathematical framework for universal Darwinism, the study of evolutionary processes operating throughout nature. PMID:27375438

The Bayesian Revolution Approaches Psychological Development

ERIC Educational Resources Information Center

Shultz, Thomas R.

2007-01-01

This commentary reviews five articles that apply Bayesian ideas to psychological development, some with psychology experiments, some with computational modeling, and some with both experiments and modeling. The reviewed work extends the current Bayesian revolution into tasks often studied in children, such as causal learning and word learning, and…

Geological, geomechanical and geostatistical assessment of rockfall hazard in San Quirico Village (Abruzzo, Italy)

NASA Astrophysics Data System (ADS)

Chiessi, Vittorio; D'Orefice, Maurizio; Scarascia Mugnozza, Gabriele; Vitale, Valerio; Cannese, Christian

2010-07-01

This paper describes the results of a rockfall hazard assessment for the village of San Quirico (Abruzzo region, Italy) based on an engineering-geological model. After the collection of geological, geomechanical, and geomorphological data, the rockfall hazard assessment was performed based on two separate approaches: i) simulation of detachment of rock blocks and their downhill movement using a GIS; and ii) application of geostatistical techniques to the analysis of georeferenced observations of previously fallen blocks, in order to assess the probability of arrival of blocks due to potential future collapses. The results show that the trajectographic analysis is significantly influenced by the input parameters, with particular reference to the coefficients of restitution values. In order to solve this problem, the model was calibrated based on repeated field observations. The geostatistical approach is useful because it gives the best estimation of point-source phenomena such as rockfalls; however, the sensitivity of results to basic assumptions, e.g. assessment of variograms and choice of a threshold value, may be problematic. Consequently, interpolations derived from different variograms have been used and compared among them; hence, those showing the lowest errors were adopted. The data sets which were statistically analysed are relevant to both kinetic energy and surveyed rock blocks in the accumulation area. The obtained maps highlight areas susceptible to rock block arrivals, and show that the area accommodating the new settlement of S. Quirico Village has the highest level of hazard according to both probabilistic and deterministic methods.

Bridges between multiple-point geostatistics and texture synthesis: Review and guidelines for future research

NASA Astrophysics Data System (ADS)

Mariethoz, Gregoire; Lefebvre, Sylvain

2014-05-01

Multiple-Point Simulations (MPS) is a family of geostatistical tools that has received a lot of attention in recent years for the characterization of spatial phenomena in geosciences. It relies on the definition of training images to represent a given type of spatial variability, or texture. We show that the algorithmic tools used are similar in many ways to techniques developed in computer graphics, where there is a need to generate large amounts of realistic textures for applications such as video games and animated movies. Similarly to MPS, these texture synthesis methods use training images, or exemplars, to generate realistic-looking graphical textures. Both domains of multiple-point geostatistics and example-based texture synthesis present similarities in their historic development and share similar concepts. These disciplines have however remained separated, and as a result significant algorithmic innovations in each discipline have not been universally adopted. Texture synthesis algorithms present drastically increased computational efficiency, patterns reproduction and user control. At the same time, MPS developed ways to condition models to spatial data and to produce 3D stochastic realizations, which have not been thoroughly investigated in the field of texture synthesis. In this paper we review the possible links between these disciplines and show the potential and limitations of using concepts and approaches from texture synthesis in MPS. We also provide guidelines on how recent developments could benefit both fields of research, and what challenges remain open.

Mapping Disparities in Access to Safe, Timely, and Essential Surgical Care in Zambia.

PubMed

Esquivel, Micaela M; Uribe-Leitz, Tarsicio; Makasa, Emmanuel; Lishimpi, Kennedy; Mwaba, Peter; Bowman, Kendra; Weiser, Thomas G

2016-11-01

Surgical care is widely unavailable in developing countries; advocates recommend that countries evaluate and report on access to surgical care to improve availability and aid health planners in decision making. To analyze the infrastructure, capacity, and availability of surgical care in Zambia to inform health policy priorities. In this observational study, all hospitals providing surgical care were identified in cooperation with the Zambian Ministry of Health. On-site data collection was conducted from February 1 through August 30, 2011, with an adapted World Health Organization Global Initiative for Emergency and Essential Surgical Care survey. Data collection at each facility included interviews with hospital personnel and assessment of material resources. Data were geocoded and analyzed in a data visualization platform from March 1 to December 1, 2015. We analyzed time and distance to surgical services, as well as the proportion of the population living within 2 hours from a facility providing surgical care. Surgical capacity, supplies, human resources, and infrastructure at each surgical facility, as well as the population living within 2 hours from a hospital providing surgical care. Data were collected from all 103 surgical facilities identified as providing surgical care. When including all surgical facilities (regardless of human resources and supplies), 14.9% of the population (2 166 460 of 14 500 000 people) lived more than 2 hours from surgical care. However, only 17 hospitals (16.5%) met the World Health Organization minimum standards of surgical safety; when limiting the analysis to these hospitals, 65.9% of the population (9 552 780 people) lived in an area that was more than 2 hours from a surgical facility. Geographic analysis of emergency and essential surgical care, defined as access to trauma care, obstetric care, and care of common abdominal emergencies, found that 80.7% of the population (11 704 700 people) lived in an area

Place of Delivery Associated With Postnatal Care Utilization Among Childbearing Women in Zambia.

PubMed

Chungu, Charles; Makasa, Mpundu; Chola, Mumbi; Jacobs, Choolwe Nkwemu

2018-01-01

Postnatal care (PNC) utilization is critical to the prevention of maternal morbidity and mortality. Despite its importance, the proportion of women utilizing this service is still low in Zambia. We investigated if place of delivery was associated with PNC utilization in the first 48 h among childbearing women in Zambia. Data from the 2013/14 Zambia Demographic and Health Survey for women, aged 15-49 years, who reported giving birth in the 2 years preceding the survey was used. The data comprised of sociodemographic and other obstetric data, which were cleaned, recoded, and analyzed using STATA version 13 (Stata Corporation, College Station, TX, USA). Multivariate logistic regression was used to examine the association of place of delivery and other background variables. Women who delivered in a health facility were more likely to utilize PNC in the first 48 h compared to those who did not deliver in a health facility: government hospital (AOR 7.24, 95% CI 4.92-11.84), government health center/clinic (AOR 7.15 95% CI 4.79-10.66), other public sector (AOR 23.2 95% CI 3.69-145.91), private hospital/clinic (AOR 10.08 95% CI 3.35-30.35), and Mission hospital/clinic (AOR 8.56 95% CI 4.71-15.53). Additionally, women who were attended to by a skilled personnel during delivery of the baby were more likely to utilize PNC (AOR 2.30, 95% CI 1.57-3.37). Women from rural areas were less likely to utilize PNC in the first 48 h (AOR 0.70, 95% CI 0.53-0.90). Place of delivery was found to be linked with PNC utilization in this population although access to health care is still driven by inequity-related dynamics and imbalances. Given that inequity stresses are heaviest in the rural and poor groups, interventions should aim to reach this group. The study results will help program managers to increase access to health facility delivery and direct interventional efforts toward the affected subpopulations, such as the young and rural women. Furthermore, results will help

Strengthening and expanding the capacity of health worker education in Zambia

PubMed Central

Michelo, Charles; Zulu, Joseph Mumba; Simuyemba, Moses; Andrews, Benjamin; Katubulushi, Max; Chi, Benjamin; Njelesani, Evariste; Vwalika, Bellington; Bowa, Kasonde; Maimbolwa, Margaret; Chipeta, James; Goma, Fastone; Nzala, Selestine; Banda, Sekelani; Mudenda, John; Ahmed, Yusuf; Hachambwa, Lotti; Wilson, Craig; Vermund, Sten; Mulla, Yakub

2017-01-01

Introduction Zambia is facing a chronic shortage of health care workers. The paper aimed at understanding how the Medical Education Partnership Initiative (MEPI) program facilitated strengthening and expanding of the national capacity and quality of medical education as well as processes for retaining faculty in Zambia. Methods Data generated through documentary review, key informant interviews and observations were analyzed using a thematic approach. Results The MEPI program triggered the development of new postgraduate programs thereby increasing student enrollment. This was achieved by leveraging of existing and new partnerships with other universities and differentiating the old Master in Public Health into specialized curriculum. Furthermore, the MEPI program improved the capacity and quality of training by facilitating installation and integration of new technology such as the eGranary digital library, E-learning methods and clinical skills laboratory into the Schools. This technology enabled easy access to relevant data or information, quicker turn around of experiments and enhanced data recording, display and analysis features for experiments. The program also facilitated transforming of the academic environment into a more conducive work place through strengthening the Staff Development program and support towards research activities. These activities stimulated work motivation and interest in research by faculty. Meanwhile, these processes were inhibited by the inability to upload all courses on to Moodle as well as inadequate operating procedures and feedback mechanisms for the Moodle. Conclusion Expansion and improvement in training processes for health care workers requires targeted investment within medical institutions and strengthening local and international partnerships. PMID:28819513

Development of a screening tool to predict malnutrition among children under two years old in Zambia

PubMed Central

Hasegawa, Junko; Ito, Yoichi M; Yamauchi, Taro

2017-01-01

ABSTRACT Background: Maternal and child undernutrition is an important issue, particularly in low- and middle-income countries. Children at high risk of malnutrition should be prioritized to receive necessary interventions to minimize such risk. Several risk factors have been proposed; however, until now, there has been no appropriate evaluation method to identify these children. In sub-Saharan Africa, children commonly receive regular check-ups from community health workers. A simple and easy nutrition assessment method is therefore needed for use by semi-professional health workers. Objectives: The aim of this study was to develop and test a practical screening tool for community use in predicting growth stunting in children under two years in rural Zambia. Methods: Field research was conducted from July to August 2014 in Southern Province, Zambia. Two hundred and sixty-four mother-child pairs participated in the study. Anthropometric measurements were performed on all children and mothers, and all mothers were interviewed. Risk factors for the screening test were estimated by using least absolute shrinkage and selection operator analysis. After re-evaluating all participants using the new screening tool, a receiver operating characteristic curve was drawn to set the cut-off value. Sensitivity and specificity were also calculated. Results: The screening tool included age, weight-for-age Z-score status, birth weight, feeding status, history of sibling death, multiple birth, and maternal education level. The total score ranged from 0 to 22, and the cut-off value was eight. Sensitivity and specificity were 0.963 and 0.697 respectively. Conclusions: A screening tool was developed to predict children at high risk of malnutrition living in Zambia. Further longitudinal studies are needed to confirm the test’s validity in detecting future stunting and to investigate the effectiveness of malnutrition treatment. PMID:28730929

Distance Education Examination Management in a Lowly Resourced North-Eastern Region of Zambia: a Phenomenological Approach

ERIC Educational Resources Information Center

Simui, Francis; Chibale, Henry; Namangala, Boniface

2017-01-01

This paper focuses on the management of distance education examination in a lowly resourced North-Eastern region of Zambia. The study applies Hermeneutic Phenomenology approach to generate and make sense of the data. It is the lived experiences of 2 invigilators and 66 students purposively selected that the study draws its insights from. Meaning…

A Gentle Introduction to Bayesian Analysis: Applications to Developmental Research

ERIC Educational Resources Information Center

van de Schoot, Rens; Kaplan, David; Denissen, Jaap; Asendorpf, Jens B.; Neyer, Franz J.; van Aken, Marcel A. G.

2014-01-01

Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First, the ingredients underlying Bayesian methods are…

Bayesian ensemble refinement by replica simulations and reweighting.

PubMed

Hummer, Gerhard; Köfinger, Jürgen

2015-12-28

We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.

Bayesian ensemble refinement by replica simulations and reweighting

NASA Astrophysics Data System (ADS)

Hummer, Gerhard; Köfinger, Jürgen

2015-12-01

We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.

Exploring SWAp's contribution to the efficient allocation and use of resources in the health sector in Zambia.

PubMed

Chansa, Collins; Sundewall, Jesper; McIntyre, Di; Tomson, Göran; Forsberg, Birger C

2008-07-01

Zambia introduced a sector-wide approach (SWAp) in the health sector in 1993. The goal was to improve efficiency in the use of domestic funds and externally sourced development assistance by integrating these into a joint sectoral framework. Over a decade into its existence, however, the SWAp remains largely unevaluated. This study explores whether the envisaged improvements have been achieved by studying developments in administrative, technical and allocative efficiency in the Zambian health sector from 1990-2006. A case study was conducted using interviews and analysis of secondary data. Respondents represented a cross-section of stakeholders in the Zambian health sector. Secondary data from 1990-2006 were collected for six indicators related to administrative, technical and allocative efficiency. The results showed small improvements in administrative efficiency. Transaction costs still appeared to be high despite the introduction of the SWAp. Indicators for technical efficiency showed a drop in hospital bed utilization rates and government share of funding for drugs. As for allocative efficiency, budget execution did not improve with the SWAp, although there were large variations between both donors and year. Funding levels had apparently improved at district level but declined for hospitals. Finally, the SWAp had not succeeded in bringing all external assistance together under a common framework. Despite strong commitment to implement the SWAp in Zambia, the envisaged efficiency improvements do not seem to have been attained. Possible explanations could be that the SWAp has not been fully developed or that not all parties have completely embraced it. SWAp is not ruled out as a coordination model, but the current setup in Zambia has not proved to be fully effective.

Challenges for health care providers, parents and patients who face a child hood cancer diagnosis in Zambia.

PubMed

Walubita, Mulima; Sikateyo, Bornwell; Zulu, Joseph M

2018-05-02

Zambia is experiencing high prevalence of childhood cancer. However, very few children access and complete treatment for cancer. This study aimed to document the challenges for health care providers, parents and patients who face a child hood cancer diagnosis in Zambia, and their coping strategies. This was an exploratory health facility-based qualitative study that was conducted at a Paediatric oncology ward at referral hospital in Zambia. In-depth individual interviews conducted with fifteen (15) caregivers and seven (7) key informants were analysed using thematic analysis. Several challenges related to managing the childhood cancer diagnosis were recorded. Individual and family challenges were inadequate knowledge on childhood cancer, lack of finances to meet treatment and transport costs as well as long period of hospitalisation that affected women's ability to perform multiple responsibilities. Whereas challenges at community level were inadequate support to address emotional and physical distress and social stigmatisation experienced by caregivers. Health systems issues included inadequate specialised health workers, poor communication among health workers, limited space and beds as well as insufficient supplies such as blood. Cultural related factors were the belief that cancer is a product of witchcraft as well as religious beliefs regarding the role of faith healing in childhood cancer treatment. Coping strategies used by parents/ caregivers included praying to God, material support from organisations and church as well as delaying having another child. Addressing the challenges for health care providers, parents and patients who face a childhood cancer diagnosis may require adopting a systems or an ecological approach that allows developing strategies that simultaneously address challenges related to the individual, family, community, health system and cultural aspects.

Bayesian Decision Theoretical Framework for Clustering

ERIC Educational Resources Information Center

Chen, Mo

2011-01-01

In this thesis, we establish a novel probabilistic framework for the data clustering problem from the perspective of Bayesian decision theory. The Bayesian decision theory view justifies the important questions: what is a cluster and what a clustering algorithm should optimize. We prove that the spectral clustering (to be specific, the…

Modeling Diagnostic Assessments with Bayesian Networks

ERIC Educational Resources Information Center

Almond, Russell G.; DiBello, Louis V.; Moulder, Brad; Zapata-Rivera, Juan-Diego

2007-01-01

This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models…

Identifying barriers to the availability and use of Magnesium Sulphate Injection in resource poor countries: a case study in Zambia.

PubMed

Ridge, Anna L; Bero, Lisa A; Hill, Suzanne R

2010-12-16

Pre-eclampsia and eclampsia are serious complications of pregnancy and major causes of maternal mortality and morbidity worldwide. According to systematic reviews and WHO guidelines magnesium sulphate injection (MgSO4) should be the first -line treatment for severe pre-eclampsia and eclampsia. Studies have shown that this safe and effective medicine is unavailable and underutilized in many resource poor countries. The objective of this study was to identify barriers to the availability and use of MgSO4 in the Zambian Public Health System. A 'fishbone' (Ishikawa) diagram listing probable facilitators to the availability and use of MgSO4 identified from the literature was used to develop an assessment tool. Barriers to availability and use of MgSO4 were assessed at the regulatory/government, supply, procurement, distribution, health facility and health professional levels. The assessment was completed during August 2008 using archival data, and observations at a pragmatic sample of health facilities providing obstetric services in Lusaka District, Zambia. The major barrier to the availability of MgSO4 within the public health system in Zambia was lack of procurement by the Ministry of Health. Other barriers identified included a lack of demand by health professionals at the health centre level and a lack of in-service training in the use of MgSO4. Where there was demand by obstetricians, magnesium sulphate injection was being procured from the private sector by the hospital pharmacy despite not being registered and licensed for use for the treatment of severe pre-eclampsia and eclampsia by the national Pharmaceutical Regulatory Authority. The case study in Zambia highlights the complexities that underlie making essential medicines available and used appropriately. The fishbone diagram is a useful theoretical framework for illustrating the complexity of translating research findings into clinical practice. A better understanding of the supply system and of the pattern

A PCR-based survey of animal African trypanosomosis and selected piroplasm parasites of cattle and goats in Zambia.

PubMed

Musinguzi, Simon Peter; Suganuma, Keisuke; Asada, Masahito; Laohasinnarong, Dusit; Sivakumar, Thillaiampalam; Yokoyama, Naoaki; Namangala, Boniface; Sugimoto, Chihiro; Suzuki, Yasuhiko; Xuan, Xuenan; Inoue, Noboru

2017-01-10

We screened cattle and goats from the districts of Chama, Monze and Mumbwa in Zambia for animal African trypanosomes, Babesia bigemina and Theileria parva using PCRs; 38.1% of the samples tested positive for at least one of the parasite species. The most common parasite was Trypanosoma vivax (19.8%). Its incidence was significantly higher in goats than in cattle, (P<0.05). B. bigemina was found in samples from all the three areas, making it the most widespread of the parasites in Zambia. Among the tested samples, 12.0% of the positive samples were mixed infections. There were significant differences in the infection rates of T. vivax (Mumbwa had a significantly higher infection rate [39.6%, P<0.0001]), Th. parva (Monze had the only cases [P<0.0004]) and B. bigemina (Monze had a significantly higher infection rate [40.5%, P<0.0001]). According to the hematocrit values, the packed cell volume (%) among the cattle with mixed infections was significantly lower than that of the other cattle. The presence of multiple parasite species and mixed infections among the Zambian cattle and goat populations is of both clinical and economic importance to livestock farming. The absence of trypanosomosis among the samples from Monze can be attributed to tsetse eradication efforts that took place around Lake Kariba. This shows that the prevention and control of these parasitic diseases can have a significant impact on the disease status, which can translate directly into the improvement of the livestock sector in Zambia.

A PCR-based survey of animal African trypanosomosis and selected piroplasm parasites of cattle and goats in Zambia

PubMed Central

MUSINGUZI, Simon Peter; SUGANUMA, Keisuke; ASADA, Masahito; LAOHASINNARONG, Dusit; SIVAKUMAR, Thillaiampalam; YOKOYAMA, Naoaki; NAMANGALA, Boniface; SUGIMOTO, Chihiro; SUZUKI, Yasuhiko; XUAN, Xuenan; INOUE, Noboru

2016-01-01

We screened cattle and goats from the districts of Chama, Monze and Mumbwa in Zambia for animal African trypanosomes, Babesia bigemina and Theileria parva using PCRs; 38.1% of the samples tested positive for at least one of the parasite species. The most common parasite was Trypanosoma vivax (19.8%). Its incidence was significantly higher in goats than in cattle, (P<0.05). B. bigemina was found in samples from all the three areas, making it the most widespread of the parasites in Zambia. Among the tested samples, 12.0% of the positive samples were mixed infections. There were significant differences in the infection rates of T. vivax (Mumbwa had a significantly higher infection rate [39.6%, P<0.0001]), Th. parva (Monze had the only cases [P<0.0004]) and B. bigemina (Monze had a significantly higher infection rate [40.5%, P<0.0001]). According to the hematocrit values, the packed cell volume (%) among the cattle with mixed infections was significantly lower than that of the other cattle. The presence of multiple parasite species and mixed infections among the Zambian cattle and goat populations is of both clinical and economic importance to livestock farming. The absence of trypanosomosis among the samples from Monze can be attributed to tsetse eradication efforts that took place around Lake Kariba. This shows that the prevention and control of these parasitic diseases can have a significant impact on the disease status, which can translate directly into the improvement of the livestock sector in Zambia. PMID:27616437

Seasonality, Blood Feeding Behavior, and Transmission of Plasmodium Falciparum by Anopheles Arabiensis after an Extended Drought In Southern Zambia

PubMed Central

Thuma, Philip E.; Mharakurwa, Sungano; Norris, Douglas E.

2014-01-01

Transmission of Plasmodium falciparum is hyperendemic in southern Zambia. However, no data on the entomologic aspects of malaria transmission have been published from Zambia in more than 25 years. We evaluated seasonal malaria transmission by Anopheles arabiensis and An. funestus s.s. and characterized the blood feeding behavior of An. arabiensis in two village areas. Transmission during the 2004–2005 rainy season was nearly zero because of widespread drought. During 2005–2006, the estimated entomologic inoculation rate values were 1.6 and 18.3 infective bites per person per transmission season in each of the two village areas, respectively. Finally, with a human blood index of 0.923, An. arabiensis was substantially more anthropophilic in our study area than comparable samples of indoor-resting An. arabiensis throughout Africa and was the primary vector responsible for transmission of P. falciparum. PMID:17297034

Quantum-Like Representation of Non-Bayesian Inference

NASA Astrophysics Data System (ADS)

Asano, M.; Basieva, I.; Khrennikov, A.; Ohya, M.; Tanaka, Y.

2013-01-01

This research is related to the problem of "irrational decision making or inference" that have been discussed in cognitive psychology. There are some experimental studies, and these statistical data cannot be described by classical probability theory. The process of decision making generating these data cannot be reduced to the classical Bayesian inference. For this problem, a number of quantum-like coginitive models of decision making was proposed. Our previous work represented in a natural way the classical Bayesian inference in the frame work of quantum mechanics. By using this representation, in this paper, we try to discuss the non-Bayesian (irrational) inference that is biased by effects like the quantum interference. Further, we describe "psychological factor" disturbing "rationality" as an "environment" correlating with the "main system" of usual Bayesian inference.

Geostatistical Model-Based Estimates of Schistosomiasis Prevalence among Individuals Aged ≤20 Years in West Africa

PubMed Central

Schur, Nadine; Hürlimann, Eveline; Garba, Amadou; Traoré, Mamadou S.; Ndir, Omar; Ratard, Raoult C.; Tchuem Tchuenté, Louis-Albert; Kristensen, Thomas K.; Utzinger, Jürg; Vounatsou, Penelope

2011-01-01

Background Schistosomiasis is a water-based disease that is believed to affect over 200 million people with an estimated 97% of the infections concentrated in Africa. However, these statistics are largely based on population re-adjusted data originally published by Utroska and colleagues more than 20 years ago. Hence, these estimates are outdated due to large-scale preventive chemotherapy programs, improved sanitation, water resources development and management, among other reasons. For planning, coordination, and evaluation of control activities, it is essential to possess reliable schistosomiasis prevalence maps. Methodology We analyzed survey data compiled on a newly established open-access global neglected tropical diseases database (i) to create smooth empirical prevalence maps for Schistosoma mansoni and S. haematobium for individuals aged ≤20 years in West Africa, including Cameroon, and (ii) to derive country-specific prevalence estimates. We used Bayesian geostatistical models based on environmental predictors to take into account potential clustering due to common spatially structured exposures. Prediction at unobserved locations was facilitated by joint kriging. Principal Findings Our models revealed that 50.8 million individuals aged ≤20 years in West Africa are infected with either S. mansoni, or S. haematobium, or both species concurrently. The country prevalence estimates ranged between 0.5% (The Gambia) and 37.1% (Liberia) for S. mansoni, and between 17.6% (The Gambia) and 51.6% (Sierra Leone) for S. haematobium. We observed that the combined prevalence for both schistosome species is two-fold lower in Gambia than previously reported, while we found an almost two-fold higher estimate for Liberia (58.3%) than reported before (30.0%). Our predictions are likely to overestimate overall country prevalence, since modeling was based on children and adolescents up to the age of 20 years who are at highest risk of infection. Conclusion/Significance We

Bayesian analysis of rare events

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

Straub, Daniel, E-mail: straub@tum.de; Papaioannou, Iason; Betz, Wolfgang

2016-06-01

In many areas of engineering and science there is an interest in predicting the probability of rare events, in particular in applications related to safety and security. Increasingly, such predictions are made through computer models of physical systems in an uncertainty quantification framework. Additionally, with advances in IT, monitoring and sensor technology, an increasing amount of data on the performance of the systems is collected. This data can be used to reduce uncertainty, improve the probability estimates and consequently enhance the management of rare events and associated risks. Bayesian analysis is the ideal method to include the data into themore » probabilistic model. It ensures a consistent probabilistic treatment of uncertainty, which is central in the prediction of rare events, where extrapolation from the domain of observation is common. We present a framework for performing Bayesian updating of rare event probabilities, termed BUS. It is based on a reinterpretation of the classical rejection-sampling approach to Bayesian analysis, which enables the use of established methods for estimating probabilities of rare events. By drawing upon these methods, the framework makes use of their computational efficiency. These methods include the First-Order Reliability Method (FORM), tailored importance sampling (IS) methods and Subset Simulation (SuS). In this contribution, we briefly review these methods in the context of the BUS framework and investigate their applicability to Bayesian analysis of rare events in different settings. We find that, for some applications, FORM can be highly efficient and is surprisingly accurate, enabling Bayesian analysis of rare events with just a few model evaluations. In a general setting, BUS implemented through IS and SuS is more robust and flexible.« less

Bayesian analysis of rare events

NASA Astrophysics Data System (ADS)

Straub, Daniel; Papaioannou, Iason; Betz, Wolfgang

2016-06-01

In many areas of engineering and science there is an interest in predicting the probability of rare events, in particular in applications related to safety and security. Increasingly, such predictions are made through computer models of physical systems in an uncertainty quantification framework. Additionally, with advances in IT, monitoring and sensor technology, an increasing amount of data on the performance of the systems is collected. This data can be used to reduce uncertainty, improve the probability estimates and consequently enhance the management of rare events and associated risks. Bayesian analysis is the ideal method to include the data into the probabilistic model. It ensures a consistent probabilistic treatment of uncertainty, which is central in the prediction of rare events, where extrapolation from the domain of observation is common. We present a framework for performing Bayesian updating of rare event probabilities, termed BUS. It is based on a reinterpretation of the classical rejection-sampling approach to Bayesian analysis, which enables the use of established methods for estimating probabilities of rare events. By drawing upon these methods, the framework makes use of their computational efficiency. These methods include the First-Order Reliability Method (FORM), tailored importance sampling (IS) methods and Subset Simulation (SuS). In this contribution, we briefly review these methods in the context of the BUS framework and investigate their applicability to Bayesian analysis of rare events in different settings. We find that, for some applications, FORM can be highly efficient and is surprisingly accurate, enabling Bayesian analysis of rare events with just a few model evaluations. In a general setting, BUS implemented through IS and SuS is more robust and flexible.

Coupling geostatistics to detailed reservoir description allows better visualization and more accurate characterization/simulation of turbidite reservoirs: Elk Hills oil field, California

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

Allan, M.E.; Wilson, M.L.; Wightman, J.

1996-12-31

The Elk Hills giant oilfield, located in the southern San Joaquin Valley of California, has produced 1.1 billion barrels of oil from Miocene and shallow Pliocene reservoirs. 65% of the current 64,000 BOPD production is from the pressure-supported, deeper Miocene turbidite sands. In the turbidite sands of the 31 S structure, large porosity & permeability variations in the Main Body B and Western 31 S sands cause problems with the efficiency of the waterflooding. These variations have now been quantified and visualized using geostatistics. The end result is a more detailed reservoir characterization for simulation. Traditional reservoir descriptions based onmore » marker correlations, cross-sections and mapping do not provide enough detail to capture the short-scale stratigraphic heterogeneity needed for adequate reservoir simulation. These deterministic descriptions are inadequate to tie with production data as the thinly bedded sand/shale sequences blur into a falsely homogenous picture. By studying the variability of the geologic & petrophysical data vertically within each wellbore and spatially from well to well, a geostatistical reservoir description has been developed. It captures the natural variability of the sands and shales that was lacking from earlier work. These geostatistical studies allow the geologic and petrophysical characteristics to be considered in a probabilistic model. The end-product is a reservoir description that captures the variability of the reservoir sequences and can be used as a more realistic starting point for history matching and reservoir simulation.« less

Coupling geostatistics to detailed reservoir description allows better visualization and more accurate characterization/simulation of turbidite reservoirs: Elk Hills oil field, California

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

Allan, M.E.; Wilson, M.L.; Wightman, J.

1996-01-01

The Elk Hills giant oilfield, located in the southern San Joaquin Valley of California, has produced 1.1 billion barrels of oil from Miocene and shallow Pliocene reservoirs. 65% of the current 64,000 BOPD production is from the pressure-supported, deeper Miocene turbidite sands. In the turbidite sands of the 31 S structure, large porosity permeability variations in the Main Body B and Western 31 S sands cause problems with the efficiency of the waterflooding. These variations have now been quantified and visualized using geostatistics. The end result is a more detailed reservoir characterization for simulation. Traditional reservoir descriptions based on markermore » correlations, cross-sections and mapping do not provide enough detail to capture the short-scale stratigraphic heterogeneity needed for adequate reservoir simulation. These deterministic descriptions are inadequate to tie with production data as the thinly bedded sand/shale sequences blur into a falsely homogenous picture. By studying the variability of the geologic petrophysical data vertically within each wellbore and spatially from well to well, a geostatistical reservoir description has been developed. It captures the natural variability of the sands and shales that was lacking from earlier work. These geostatistical studies allow the geologic and petrophysical characteristics to be considered in a probabilistic model. The end-product is a reservoir description that captures the variability of the reservoir sequences and can be used as a more realistic starting point for history matching and reservoir simulation.« less

Semisupervised learning using Bayesian interpretation: application to LS-SVM.

PubMed

Adankon, Mathias M; Cheriet, Mohamed; Biem, Alain

2011-04-01

Bayesian reasoning provides an ideal basis for representing and manipulating uncertain knowledge, with the result that many interesting algorithms in machine learning are based on Bayesian inference. In this paper, we use the Bayesian approach with one and two levels of inference to model the semisupervised learning problem and give its application to the successful kernel classifier support vector machine (SVM) and its variant least-squares SVM (LS-SVM). Taking advantage of Bayesian interpretation of LS-SVM, we develop a semisupervised learning algorithm for Bayesian LS-SVM using our approach based on two levels of inference. Experimental results on both artificial and real pattern recognition problems show the utility of our method.

Mapping aboveground woody biomass using forest inventory, remote sensing and geostatistical techniques.

PubMed

Yadav, Bechu K V; Nandy, S

2015-05-01

Mapping forest biomass is fundamental for estimating CO₂ emissions, and planning and monitoring of forests and ecosystem productivity. The present study attempted to map aboveground woody biomass (AGWB) integrating forest inventory, remote sensing and geostatistical techniques, viz., direct radiometric relationships (DRR), k-nearest neighbours (k-NN) and cokriging (CoK) and to evaluate their accuracy. A part of the Timli Forest Range of Kalsi Soil and Water Conservation Division, Uttarakhand, India was selected for the present study. Stratified random sampling was used to collect biophysical data from 36 sample plots of 0.1 ha (31.62 m × 31.62 m) size. Species-specific volumetric equations were used for calculating volume and multiplied by specific gravity to get biomass. Three forest-type density classes, viz. 10-40, 40-70 and >70% of Shorea robusta forest and four non-forest classes were delineated using on-screen visual interpretation of IRS P6 LISS-III data of December 2012. The volume in different strata of forest-type density ranged from 189.84 to 484.36 m(3) ha(-1). The total growing stock of the forest was found to be 2,024,652.88 m(3). The AGWB ranged from 143 to 421 Mgha(-1). Spectral bands and vegetation indices were used as independent variables and biomass as dependent variable for DRR, k-NN and CoK. After validation and comparison, k-NN method of Mahalanobis distance (root mean square error (RMSE) = 42.25 Mgha(-1)) was found to be the best method followed by fuzzy distance and Euclidean distance with RMSE of 44.23 and 45.13 Mgha(-1) respectively. DRR was found to be the least accurate method with RMSE of 67.17 Mgha(-1). The study highlighted the potential of integrating of forest inventory, remote sensing and geostatistical techniques for forest biomass mapping.

Non-Bayesian Optical Inference Machines

NASA Astrophysics Data System (ADS)

Kadar, Ivan; Eichmann, George

1987-01-01

In a recent paper, Eichmann and Caulfield) presented a preliminary exposition of optical learning machines suited for use in expert systems. In this paper, we extend the previous ideas by introducing learning as a means of reinforcement by information gathering and reasoning with uncertainty in a non-Bayesian framework2. More specifically, the non-Bayesian approach allows the representation of total ignorance (not knowing) as opposed to assuming equally likely prior distributions.

Overburden, Stigma, and Perceived Agency: Teachers as HIV Prevention Educators in Urban Zambia

PubMed Central

Henning, Margaret; Khanna, Sunil K.

2016-01-01

Sub-Saharan Africa is home to more than 70% of the global HIV-positive population. In Zambia, as well as in other parts of Africa, deaths from AIDS and associated infections have created a generation of households headed by children, a situation that negatively affects the chances for economic and health improvements in the region. In contemplating possible public health interventions around HIV prevention, we found that a growing body of research advocates for school-based HIV programs as an effective strategy to stop the spread of the disease. This work is critical because it explores schoolteachers' perspectives on their potential roles as HIV prevention educators. Semi-structured interviews (n = 12) were conducted among schoolteachers in the Lusaka province of Zambia to collect qualitative data. Analysis of qualitative data revealed three broad and interconnected themes related to the roles and concerns of the participating teachers: 1) the role of overburden; 2) fear of stigma; and 3) perceived lack of agency. These themes are further discussed in the context of the results that focused on the teachers and the adoption of HIV education. Little is known about teachers' perceptions of themselves as HIV educators. Our study suggests that understanding teachers' perceptions and the contextual factors is crucial to the adoption of school-based HIV programs. PMID:29546161

Is green economy achievable through championing green growth? A local government experience from Zambia

PubMed Central

2016-01-01

The need to enhance environmental sustainability, sustainable development and growth that takes into account the well-being of the people and nature because of the increased production and consumption of goods and services is the major driver to the introduction of green economy in Zambia and countries in southern Africa. This article examines the extent to which local government in Zambia has embraced green growth and green economy and critically analyses the concept of green economy and green growth. This study is based on a review of planning and policy documents, a household questionnaire survey and interviews with various institutions, planners and rural development organisations. A number of policies implemented at the local government level were analysed and reflected upon irrespective of whether they contain the components of green growth and green economy and the extent to which they contribute to attaining green economy. The article argues that the need for economic diversification is important as far as green economy is concerned. The article recommends the need to invest in research and development in order to find more carbon-free economic activities. The conclusion is that local government is key to achieving green growth and green economy, because it is involved at all levels, from policy formulation to implementation.

How we implemented an analytical support clinic to strengthen student research capacity in Zambia.

PubMed

Andrews, Ben; Musonda, Patrick; Simuyemba, Moses; Wilson, Craig M; Nzala, Selestine; Vermund, Sten H; Michelo, Charles

2014-12-11

Abstract Background: Research outputs in sub-Saharan Africa may be limited by a scarcity of clinical research expertise. In Zambia, clinical and biomedical postgraduate students are often delayed in graduation due to challenges in completing their research dissertations. We sought to strengthen institutional research capacity by supporting student and faculty researchers through weekly epidemiology and biostatistics clinics. Methods: We instituted a weekly Analytical Support Clinic at the University of Zambia, School of Medicine. A combination of biostatisticians, clinical researchers and epidemiologists meet weekly with clients to address questions of proposal development, data management and analysis. Clinic sign-in sheets were reviewed. Results: 109 students and faculty members accounted for 197 visits to the Clinic. Nearly all clients (107/109, 98.2%) were undergraduate or postgraduate students. Reasons for attending the Clinic were primarily for proposal development (46.7%) and data management/analysis (42.1%). The most common specific reasons for seeking help were data analysis and interpretation (36.5%), development of study design and research questions (26.9%) and sample size calculation (21.8%). Conclusions: The Analytical Support Clinic is an important vehicle for strengthening postgraduate research through one-on-one and small group demand-driven interactions. The clinic approach supplements mentorship from departmental supervisors, providing specific expertise and contextual teaching.

Community attitudes towards childbearing and abortion among HIV-positive women in Nigeria and Zambia.

PubMed

Kavanaugh, Megan L; Moore, Ann M; Akinyemi, Odunayo; Adewole, Isaac; Dzekedzeke, Kumbutso; Awolude, Olutosin; Arulogun, Oyedunni

2013-01-01

Although stigma towards HIV-positive women for both continuing and terminating a pregnancy has been documented, to date few studies have examined relative stigma towards one outcome versus the other. This study seeks to describe community attitudes towards each of two possible elective outcomes of an HIV-positive woman's pregnancy - induced abortion or birth - to determine which garners more stigma and document characteristics of community members associated with stigmatising attitudes towards each outcome. Data come from community-based interviews with reproductive-aged men and women, 2401 in Zambia and 2452 in Nigeria. Bivariate and multivariate analyses revealed that respondents from both countries overwhelmingly favoured continued childbearing for HIV-positive pregnant women, but support for induced abortion was slightly higher in scenarios in which anti-retroviral therapy (ART) was unavailable. Zambian respondents held more stigmatising attitudes towards abortion for HIV-positive women than did Nigerian respondents. Women held more stigmatising attitudes towards abortion for HIV-positive women than men, particularly in Zambia. From a sexual and reproductive health and rights perspective, efforts to assist HIV-positive women in preventing unintended pregnancy and to support them in their pregnancy decisions when they do become pregnant should be encouraged in order to combat the social stigma documented in this paper.

Implementing antiretroviral therapy programs in resource-constrained settings: lessons from Monze, Zambia.

PubMed

Adedimeji, Adebola; Malokota, Oliver; Manafa, Ogenna

2011-05-01

We describe the impact of an antiretroviral therapy program on human resource utilization and service delivery in a rural hospital in Monze, Zambia, using qualitative data. We assess project impact on staff capacity utilization, service delivery, and community perception of care. Increased workload resulted in fatigue, low staff morale, and exacerbated critical manpower shortages, but also an increase in users of antiretroviral therapy, improvement in hospital infrastructure and funding, and an overall community satisfaction with service delivery. Integrating HAART programs within existing hospital units and services may be a good alternative to increase overall efficiency.

BAYESIAN ESTIMATION OF THERMONUCLEAR REACTION RATES

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

Iliadis, C.; Anderson, K. S.; Coc, A.

The problem of estimating non-resonant astrophysical S -factors and thermonuclear reaction rates, based on measured nuclear cross sections, is of major interest for nuclear energy generation, neutrino physics, and element synthesis. Many different methods have been applied to this problem in the past, almost all of them based on traditional statistics. Bayesian methods, on the other hand, are now in widespread use in the physical sciences. In astronomy, for example, Bayesian statistics is applied to the observation of extrasolar planets, gravitational waves, and Type Ia supernovae. However, nuclear physics, in particular, has been slow to adopt Bayesian methods. We presentmore » astrophysical S -factors and reaction rates based on Bayesian statistics. We develop a framework that incorporates robust parameter estimation, systematic effects, and non-Gaussian uncertainties in a consistent manner. The method is applied to the reactions d(p, γ ){sup 3}He, {sup 3}He({sup 3}He,2p){sup 4}He, and {sup 3}He( α , γ ){sup 7}Be, important for deuterium burning, solar neutrinos, and Big Bang nucleosynthesis.« less

Bayesian Exploratory Factor Analysis

PubMed Central

Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi

2014-01-01

This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates from a high dimensional set of psychological measurements. PMID:25431517

Studies of trypanosomiasis in the Luangwa valley, north-eastern Zambia.

PubMed

Laohasinnarong, Dusit; Goto, Yasuyuki; Goto, Yasuhuki; Asada, Masahito; Nakao, Ryo; Hayashida, Kyoko; Kajino, Kiichi; Kawazu, Shin-ichiro; Sugimoto, Chihiro; Inoue, Noboru; Namangala, Boniface

2015-09-30

The present study, conducted in Zambia's Luangwa valley where both animal African trypanosomiasis (AAT) and human African trypanosomiasis (HAT) are endemic, combined the use of microscopy and molecular techniques to determine the presence of trypanosome species in cattle, goats and tsetse flies. This study was conducted between 2008 and 2010 in Petauke, Chama and Isoka districts, north-eastern Zambia. A total of 243 cattle, 36 goats and 546 tsetse flies, were examined for presence of trypanosome species using microscopy, PCR and loop-mediated isothermal amplification (LAMP). There was poor agreement among the test methods used for detection of trypanosomes species in animal blood and tsetse flies. Trypanosomes were observed in 6.1 % (95 % CI: 3.3-8.9 %) of the animals sampled by microscopy, 7.5 % (95 % CI: 4.4-10.6 %) by PCR and 18.6 % (95 % CI: 13.6-23.6 %) by PFR-LAMP. PFR-LAMP was more sensitive for detecting Trypanozoon than KIN-PCR. The highest occurrence of AAT was recorded in cattle from Petauke (58.7 %, 95 % CI: 44.7-72.7 %) while the lowest was from Isoka (5.4 %, 95 % CI: 0.8-10.0 %). Infection of both cattle and goats with Trypanosoma congolense and T. vivax was associated with clinical AAT. When selecting molecular techniques for AAT surveillance in endemic regions, the KIN-PCR and species-specific PCR may be recommended for screening animal or tsetse fly samples for T. congolense and T. vivax, respectively. On the other hand, species-specific PCR and/or LAMP might be of greater value in the screening of animal and human body fluids as well as tsetse fly samples for Trypanozoon.

Prior approval: the growth of Bayesian methods in psychology.

PubMed

Andrews, Mark; Baguley, Thom

2013-02-01

Within the last few years, Bayesian methods of data analysis in psychology have proliferated. In this paper, we briefly review the history or the Bayesian approach to statistics, and consider the implications that Bayesian methods have for the theory and practice of data analysis in psychology.

A geostatistical extreme-value framework for fast simulation of natural hazard events

PubMed Central

Stephenson, David B.

2016-01-01

We develop a statistical framework for simulating natural hazard events that combines extreme value theory and geostatistics. Robust generalized additive model forms represent generalized Pareto marginal distribution parameters while a Student’s t-process captures spatial dependence and gives a continuous-space framework for natural hazard event simulations. Efficiency of the simulation method allows many years of data (typically over 10 000) to be obtained at relatively little computational cost. This makes the model viable for forming the hazard module of a catastrophe model. We illustrate the framework by simulating maximum wind gusts for European windstorms, which are found to have realistic marginal and spatial properties, and validate well against wind gust measurements. PMID:27279768

The moving-window Bayesian Maximum Entropy framework: Estimation of PM2.5 yearly average concentration across the contiguous United States

PubMed Central

Akita, Yasuyuki; Chen, Jiu-Chiuan; Serre, Marc L.

2013-01-01

Geostatistical methods are widely used in estimating long-term exposures for air pollution epidemiological studies, despite their limited capabilities to handle spatial non-stationarity over large geographic domains and uncertainty associated with missing monitoring data. We developed a moving-window (MW) Bayesian Maximum Entropy (BME) method and applied this framework to estimate fine particulate matter (PM2.5) yearly average concentrations over the contiguous U.S. The MW approach accounts for the spatial non-stationarity, while the BME method rigorously processes the uncertainty associated with data missingnees in the air monitoring system. In the cross-validation analyses conducted on a set of randomly selected complete PM2.5 data in 2003 and on simulated data with different degrees of missing data, we demonstrate that the MW approach alone leads to at least 17.8% reduction in mean square error (MSE) in estimating the yearly PM2.5. Moreover, the MWBME method further reduces the MSE by 8.4% to 43.7% with the proportion of incomplete data increased from 18.3% to 82.0%. The MWBME approach leads to significant reductions in estimation error and thus is recommended for epidemiological studies investigating the effect of long-term exposure to PM2.5 across large geographical domains with expected spatial non-stationarity. PMID:22739679

The moving-window Bayesian maximum entropy framework: estimation of PM(2.5) yearly average concentration across the contiguous United States.

PubMed

Akita, Yasuyuki; Chen, Jiu-Chiuan; Serre, Marc L

2012-09-01

Geostatistical methods are widely used in estimating long-term exposures for epidemiological studies on air pollution, despite their limited capabilities to handle spatial non-stationarity over large geographic domains and the uncertainty associated with missing monitoring data. We developed a moving-window (MW) Bayesian maximum entropy (BME) method and applied this framework to estimate fine particulate matter (PM(2.5)) yearly average concentrations over the contiguous US. The MW approach accounts for the spatial non-stationarity, while the BME method rigorously processes the uncertainty associated with data missingness in the air-monitoring system. In the cross-validation analyses conducted on a set of randomly selected complete PM(2.5) data in 2003 and on simulated data with different degrees of missing data, we demonstrate that the MW approach alone leads to at least 17.8% reduction in mean square error (MSE) in estimating the yearly PM(2.5). Moreover, the MWBME method further reduces the MSE by 8.4-43.7%, with the proportion of incomplete data increased from 18.3% to 82.0%. The MWBME approach leads to significant reductions in estimation error and thus is recommended for epidemiological studies investigating the effect of long-term exposure to PM(2.5) across large geographical domains with expected spatial non-stationarity.

A Library Response to the Massification of Higher Education: The Case of the University of Zambia Library

ERIC Educational Resources Information Center

Kanyengo, Christine Wamunyima

2009-01-01

This paper looks at the challenges that libraries in Africa face in responding to massification of higher education by discussing the University of Zambia library's response in library and information resources provision. As a result of massification of higher education, libraries have been forced not only to employ new and different strategies to…

A Primer on Bayesian Analysis for Experimental Psychopathologists

PubMed Central

Krypotos, Angelos-Miltiadis; Blanken, Tessa F.; Arnaudova, Inna; Matzke, Dora; Beckers, Tom

2016-01-01

The principal goals of experimental psychopathology (EPP) research are to offer insights into the pathogenic mechanisms of mental disorders and to provide a stable ground for the development of clinical interventions. The main message of the present article is that those goals are better served by the adoption of Bayesian statistics than by the continued use of null-hypothesis significance testing (NHST). In the first part of the article we list the main disadvantages of NHST and explain why those disadvantages limit the conclusions that can be drawn from EPP research. Next, we highlight the advantages of Bayesian statistics. To illustrate, we then pit NHST and Bayesian analysis against each other using an experimental data set from our lab. Finally, we discuss some challenges when adopting Bayesian statistics. We hope that the present article will encourage experimental psychopathologists to embrace Bayesian statistics, which could strengthen the conclusions drawn from EPP research. PMID:28748068

Bayesian analysis of CCDM models

NASA Astrophysics Data System (ADS)

Jesus, J. F.; Valentim, R.; Andrade-Oliveira, F.

2017-09-01

Creation of Cold Dark Matter (CCDM), in the context of Einstein Field Equations, produces a negative pressure term which can be used to explain the accelerated expansion of the Universe. In this work we tested six different spatially flat models for matter creation using statistical criteria, in light of SNe Ia data: Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Bayesian Evidence (BE). These criteria allow to compare models considering goodness of fit and number of free parameters, penalizing excess of complexity. We find that JO model is slightly favoured over LJO/ΛCDM model, however, neither of these, nor Γ = 3αH0 model can be discarded from the current analysis. Three other scenarios are discarded either because poor fitting or because of the excess of free parameters. A method of increasing Bayesian evidence through reparameterization in order to reducing parameter degeneracy is also developed.

Enhancements to the Bayesian Infrasound Source Location Method

DTIC Science & Technology

2012-09-01

ENHANCEMENTS TO THE BAYESIAN INFRASOUND SOURCE LOCATION METHOD Omar E. Marcillo, Stephen J. Arrowsmith, Rod W. Whitaker, and Dale N. Anderson Los...ABSTRACT We report on R&D that is enabling enhancements to the Bayesian Infrasound Source Location (BISL) method for infrasound event location...the Bayesian Infrasound Source Location Method 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER

Bayesian Inference for Functional Dynamics Exploring in fMRI Data.

PubMed

Guo, Xuan; Liu, Bing; Chen, Le; Chen, Guantao; Pan, Yi; Zhang, Jing

2016-01-01

This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI) data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM), Bayesian Connectivity Change Point Model (BCCPM), and Dynamic Bayesian Variable Partition Model (DBVPM), and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come.

Fundamentals and Recent Developments in Approximate Bayesian Computation

PubMed Central

Lintusaari, Jarno; Gutmann, Michael U.; Dutta, Ritabrata; Kaski, Samuel; Corander, Jukka

2017-01-01

Abstract Bayesian inference plays an important role in phylogenetics, evolutionary biology, and in many other branches of science. It provides a principled framework for dealing with uncertainty and quantifying how it changes in the light of new evidence. For many complex models and inference problems, however, only approximate quantitative answers are obtainable. Approximate Bayesian computation (ABC) refers to a family of algorithms for approximate inference that makes a minimal set of assumptions by only requiring that sampling from a model is possible. We explain here the fundamentals of ABC, review the classical algorithms, and highlight recent developments. [ABC; approximate Bayesian computation; Bayesian inference; likelihood-free inference; phylogenetics; simulator-based models; stochastic simulation models; tree-based models.] PMID:28175922

Improved diagnostic testing and malaria treatment practices in Zambia.

PubMed

Hamer, Davidson H; Ndhlovu, Micky; Zurovac, Dejan; Fox, Matthew; Yeboah-Antwi, Kojo; Chanda, Pascalina; Sipilinyambe, Naawa; Simon, Jonathon L; Snow, Robert W

2007-05-23

Improving the accuracy of malaria diagnosis with rapid antigen-detection diagnostic tests (RDTs) has been proposed as an approach for reducing overtreatment of malaria in the current era of widespread implementation of artemisinin-based combination therapy in sub-Saharan Africa. To assess the association between use of microscopy and RDT and the prescription of antimalarials. Cross-sectional, cluster sample survey, carried out between March and May 2006, of all outpatients treated during 1 working day at government and mission health facilities in 4 sentinel districts in Zambia. Proportions of patients undergoing malaria diagnostic procedures and receiving antimalarial treatment. Seventeen percent of the 104 health facilities surveyed had functional microscopy, 63% had RDTs available, and 73% had 1 or more diagnostics available. Of patients with fever (suspected malaria), 27.8% (95% confidence interval [CI], 13.1%-42.5%) treated in health facilities with malaria diagnostics were tested and 44.6% had positive test results. Of patients with negative blood smear results, 58.4% (95% CI, 36.7%-80.2%) were prescribed an antimalaria drug, as were 35.5% (95% CI, 16.0%-55.0%) of those with a negative RDT result. Of patients with fever who did not have diagnostic tests done, 65.9% were also prescribed antimalarials. In facilities with artemether-lumefantrine in stock, this antimalarial was prescribed to a large proportion of febrile patients with a positive diagnostic test result (blood smear, 75.0% [95% CI, 51.7%-98.3%]; RDT, 70.4% [95% CI, 39.3%-100.0%]), but also to some of those with a negative diagnostic test result (blood smear, 30.4% [95% CI, 8.0%-52. 9%]; RDT, 26.7% [95% CI, 5.7%-47.7%]). Despite efforts to expand the provision of malaria diagnostics in Zambia, they continue to be underused and patients with negative test results frequently receive antimalarials. Provision of new tools to reduce inappropriate use of new expensive antimalarial treatments must be