An open-population hierarchical distance sampling model

USGS Publications Warehouse

Sollmann, Rachel; Beth Gardner,; Richard B Chandler,; Royle, J. Andrew; T Scott Sillett,

2015-01-01

Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for island scrub-jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying number of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

An open-population hierarchical distance sampling model.

PubMed

Sollmann, Rahel; Gardner, Beth; Chandler, Richard B; Royle, J Andrew; Sillett, T Scott

2015-02-01

Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for Island Scrub-Jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying numbers of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

MUSIDH, multiple use of simulated demographic histories, a novel method to reduce computation time in microsimulation models of infectious diseases.

PubMed

Fischer, E A J; De Vlas, S J; Richardus, J H; Habbema, J D F

2008-09-01

Microsimulation of infectious diseases requires simulation of many life histories of interacting individuals. In particular, relatively rare infections such as leprosy need to be studied in very large populations. Computation time increases disproportionally with the size of the simulated population. We present a novel method, MUSIDH, an acronym for multiple use of simulated demographic histories, to reduce computation time. Demographic history refers to the processes of birth, death and all other demographic events that should be unrelated to the natural course of an infection, thus non-fatal infections. MUSIDH attaches a fixed number of infection histories to each demographic history, and these infection histories interact as if being the infection history of separate individuals. With two examples, mumps and leprosy, we show that the method can give a factor 50 reduction in computation time at the cost of a small loss in precision. The largest reductions are obtained for rare infections with complex demographic histories.

Small area estimation of obesity prevalence and dietary patterns: a model applied to Rio de Janeiro city, Brazil.

PubMed

Cataife, Guido

2014-03-01

We propose the use of previously developed small area estimation techniques to monitor obesity and dietary habits in developing countries and apply the model to Rio de Janeiro city. We estimate obesity prevalence rates at the Census Tract through a combinatorial optimization spatial microsimulation model that matches body mass index and socio-demographic data in Brazil's 2008-9 family expenditure survey with Census 2010 socio-demographic data. Obesity ranges from 8% to 25% in most areas and affects the poor almost as much as the rich. Male and female obesity rates are uncorrelated at the small area level. The model is an effective tool to understand the complexity of the problem and to aid in policy design. © 2013 Published by Elsevier Ltd.

Benchmarking novel approaches for modelling species range dynamics

PubMed Central

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H.; Moore, Kara A.; Zimmermann, Niklaus E.

2016-01-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species’ range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species’ response to climate change but also emphasise several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. PMID:26872305

Benchmarking novel approaches for modelling species range dynamics.

PubMed

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E

2016-08-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. © 2016 John Wiley & Sons Ltd.

Space-Time Smoothing of Complex Survey Data: Small Area Estimation for Child Mortality.

PubMed

Mercer, Laina D; Wakefield, Jon; Pantazis, Athena; Lutambi, Angelina M; Masanja, Honorati; Clark, Samuel

2015-12-01

Many people living in low and middle-income countries are not covered by civil registration and vital statistics systems. Consequently, a wide variety of other types of data including many household sample surveys are used to estimate health and population indicators. In this paper we combine data from sample surveys and demographic surveillance systems to produce small area estimates of child mortality through time. Small area estimates are necessary to understand geographical heterogeneity in health indicators when full-coverage vital statistics are not available. For this endeavor spatio-temporal smoothing is beneficial to alleviate problems of data sparsity. The use of conventional hierarchical models requires careful thought since the survey weights may need to be considered to alleviate bias due to non-random sampling and non-response. The application that motivated this work is estimation of child mortality rates in five-year time intervals in regions of Tanzania. Data come from Demographic and Health Surveys conducted over the period 1991-2010 and two demographic surveillance system sites. We derive a variance estimator of under five years child mortality that accounts for the complex survey weighting. For our application, the hierarchical models we consider include random effects for area, time and survey and we compare models using a variety of measures including the conditional predictive ordinate (CPO). The method we propose is implemented via the fast and accurate integrated nested Laplace approximation (INLA).

Conceptual Framework for Trait-Based Ecological Risk Assessment for Wildlife Populations Exposed to Pesticides

EPA Science Inventory

Between screening level risk assessments and complex ecological models, a need exists for practical identification of risk based on general information about species, chemicals, and exposure scenarios. Several studies have identified demographic, biological, and toxicological fa...

Cattle demographic history modelled from autosomal sequence variation

PubMed Central

Murray, Caitriona; Huerta-Sanchez, Emilia; Casey, Fergal; Bradley, Daniel G.

2010-01-01

The phylogeography of cattle genetic variants has been extensively described and has informed the history of domestication. However, there remains a dearth of demographic models inferred from such data. Here, we describe sequence diversity at 37 000 bp sampled from 17 genes in cattle from Africa, Europe and India. Clearly distinct population histories are suggested between Bos indicus and Bos taurus, with the former displaying higher diversity statistics. We compare the unfolded site frequency spectra in each to those simulated using a diffusion approximation method and build a best-fitting model of past demography. This implies an earlier, possibly glaciation-induced population bottleneck in B. taurus ancestry with a later, possibly domestication-associated demographic constriction in B. indicus. Strikingly, the modelled indicine history also requires a majority secondary admixture from the South Asian aurochs, indicating a complex, more diffuse domestication process. This perhaps involved multiple domestications and/or introgression from wild oxen to domestic herds; the latter is plausible from archaeological evidence of contemporaneous wild and domestic remains across different regions of South Asia. PMID:20643743

Vegetation Demographics in Earth System Models: a review of progress and priorities

DOE PAGES

Fisher, Rosie A.; Koven, Charles D.; Anderegg, William R. L.; ...

2017-09-18

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). Furthermore, these developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. We review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections butmore » also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We also argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.« less

Vegetation Demographics in Earth System Models: a review of progress and priorities

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

Fisher, Rosie A.; Koven, Charles D.; Anderegg, William R. L.

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). Furthermore, these developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. We review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections butmore » also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We also argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.« less

Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation

NASA Astrophysics Data System (ADS)

Fer, I.; Kelly, R.; Andrews, T.; Dietze, M.; Richardson, A. D.

2016-12-01

Our ability to forecast ecosystems is limited by how well we parameterize ecosystem models. Direct measurements for all model parameters are not always possible and inverse estimation of these parameters through Bayesian methods is computationally costly. A solution to computational challenges of Bayesian calibration is to approximate the posterior probability surface using a Gaussian Process that emulates the complex process-based model. Here we report the integration of this method within an ecoinformatics toolbox, Predictive Ecosystem Analyzer (PEcAn), and its application with two ecosystem models: SIPNET and ED2.1. SIPNET is a simple model, allowing application of MCMC methods both to the model itself and to its emulator. We used both approaches to assimilate flux (CO2 and latent heat), soil respiration, and soil carbon data from Bartlett Experimental Forest. This comparison showed that emulator is reliable in terms of convergence to the posterior distribution. A 10000-iteration MCMC analysis with SIPNET itself required more than two orders of magnitude greater computation time than an MCMC run of same length with its emulator. This difference would be greater for a more computationally demanding model. Validation of the emulator-calibrated SIPNET against both the assimilated data and out-of-sample data showed improved fit and reduced uncertainty around model predictions. We next applied the validated emulator method to the ED2, whose complexity precludes standard Bayesian data assimilation. We used the ED2 emulator to assimilate demographic data from a network of inventory plots. For validation of the calibrated ED2, we compared the model to results from Empirical Succession Mapping (ESM), a novel synthesis of successional patterns in Forest Inventory and Analysis data. Our results revealed that while the pre-assimilation ED2 formulation cannot capture the emergent demographic patterns from ESM analysis, constrained model parameters controlling demographic processes increased their agreement considerably.

Simulating free-roaming cat population management options in open demographic environments.

PubMed

Miller, Philip S; Boone, John D; Briggs, Joyce R; Lawler, Dennis F; Levy, Julie K; Nutter, Felicia B; Slater, Margaret; Zawistowski, Stephen

2014-01-01

Large populations of free-roaming cats (FRCs) generate ongoing concerns for welfare of both individual animals and populations, for human public health, for viability of native wildlife populations, and for local ecological damage. Managing FRC populations is a complex task, without universal agreement on best practices. Previous analyses that use simulation modeling tools to evaluate alternative management methods have focused on relative efficacy of removal (or trap-return, TR), typically involving euthanasia, and sterilization (or trap-neuter-return, TNR) in demographically isolated populations. We used a stochastic demographic simulation approach to evaluate removal, permanent sterilization, and two postulated methods of temporary contraception for FRC population management. Our models include demographic connectivity to neighboring untreated cat populations through natural dispersal in a metapopulation context across urban and rural landscapes, and also feature abandonment of owned animals. Within population type, a given implementation rate of the TR strategy results in the most rapid rate of population decline and (when populations are isolated) the highest probability of population elimination, followed in order of decreasing efficacy by equivalent rates of implementation of TNR and temporary contraception. Even low levels of demographic connectivity significantly reduce the effectiveness of any management intervention, and continued abandonment is similarly problematic. This is the first demographic simulation analysis to consider the use of temporary contraception and account for the realities of FRC dispersal and owned cat abandonment.

Space-Time Smoothing of Complex Survey Data: Small Area Estimation for Child Mortality

PubMed Central

Mercer, Laina D; Wakefield, Jon; Pantazis, Athena; Lutambi, Angelina M; Masanja, Honorati; Clark, Samuel

2016-01-01

Many people living in low and middle-income countries are not covered by civil registration and vital statistics systems. Consequently, a wide variety of other types of data including many household sample surveys are used to estimate health and population indicators. In this paper we combine data from sample surveys and demographic surveillance systems to produce small area estimates of child mortality through time. Small area estimates are necessary to understand geographical heterogeneity in health indicators when full-coverage vital statistics are not available. For this endeavor spatio-temporal smoothing is beneficial to alleviate problems of data sparsity. The use of conventional hierarchical models requires careful thought since the survey weights may need to be considered to alleviate bias due to non-random sampling and non-response. The application that motivated this work is estimation of child mortality rates in five-year time intervals in regions of Tanzania. Data come from Demographic and Health Surveys conducted over the period 1991–2010 and two demographic surveillance system sites. We derive a variance estimator of under five years child mortality that accounts for the complex survey weighting. For our application, the hierarchical models we consider include random effects for area, time and survey and we compare models using a variety of measures including the conditional predictive ordinate (CPO). The method we propose is implemented via the fast and accurate integrated nested Laplace approximation (INLA). PMID:27468328

Modeling association among demographic parameters in analysis of open population capture-recapture data.

PubMed

Link, William A; Barker, Richard J

2005-03-01

We present a hierarchical extension of the Cormack-Jolly-Seber (CJS) model for open population capture-recapture data. In addition to recaptures of marked animals, we model first captures of animals and losses on capture. The parameter set includes capture probabilities, survival rates, and birth rates. The survival rates and birth rates are treated as a random sample from a bivariate distribution, thus the model explicitly incorporates correlation in these demographic rates. A key feature of the model is that the likelihood function, which includes a CJS model factor, is expressed entirely in terms of identifiable parameters; losses on capture can be factored out of the model. Since the computational complexity of classical likelihood methods is prohibitive, we use Markov chain Monte Carlo in a Bayesian analysis. We describe an efficient candidate-generation scheme for Metropolis-Hastings sampling of CJS models and extensions. The procedure is illustrated using mark-recapture data for the moth Gonodontis bidentata.

Modeling association among demographic parameters in analysis of open population capture-recapture data

USGS Publications Warehouse

Link, William A.; Barker, Richard J.

2005-01-01

We present a hierarchical extension of the Cormack–Jolly–Seber (CJS) model for open population capture–recapture data. In addition to recaptures of marked animals, we model first captures of animals and losses on capture. The parameter set includes capture probabilities, survival rates, and birth rates. The survival rates and birth rates are treated as a random sample from a bivariate distribution, thus the model explicitly incorporates correlation in these demographic rates. A key feature of the model is that the likelihood function, which includes a CJS model factor, is expressed entirely in terms of identifiable parameters; losses on capture can be factored out of the model. Since the computational complexity of classical likelihood methods is prohibitive, we use Markov chain Monte Carlo in a Bayesian analysis. We describe an efficient candidate-generation scheme for Metropolis–Hastings sampling of CJS models and extensions. The procedure is illustrated using mark-recapture data for the moth Gonodontis bidentata.

ENVIRONMENTAL CONSEQUENCES OF LAND USE CHANGE: ACCOUNTING FOR COMPLEXITY WITH AGENT-BASED MODELS

EPA Science Inventory

The effects of people on ecosystems and the impacts of ecosystem services on human well-being are being viewed increasingly as an integrated system. Demographic and economic pressures change a variety of ecological indicators, which can then result in reduced quality of ecosystem...

Global dynamics of a network-based SIQRS epidemic model with demographics and vaccination

NASA Astrophysics Data System (ADS)

Huang, Shouying; Chen, Fengde; Chen, Lijuan

2017-02-01

This paper investigates a new SIQRS epidemic model with demographics and vaccination on complex heterogeneous networks. We analytically derive the basic reproduction number R0, which determines not only the existence of endemic equilibrium but also the global dynamics of the model. The permanence of the disease and the globally asymptotical stability of disease-free equilibrium are proved in detail. By using a monotone iterative technique, we show that the unique endemic equilibrium is globally attractive under certain conditions. Our results really improve and enrich the results in Li et al (2014) [14]. Interestingly, the basic reproduction number R0 bears no relation to the degree-dependent birth, but our simulations indicate that the degree-dependent birth does affect the epidemic dynamics. Furthermore, we find that quarantine plays a more active role than vaccination in controlling the disease.

Demographic Computer Library.

ERIC Educational Resources Information Center

Shaw, David C.; Johnson, Dorothy M.

The complete comprehension of this paper requires a firm grasp of both mathematical demography and FORTRAN programming. The paper aims at the establishment of a language with which complex demographic manipulations can be briefly expressed in a form intelligible both to demographic analysts and to computers. The Demographic Computer Library (DCL)…

The complex contribution of sociodemographics to decision-making power in gay male couples

PubMed Central

Perry, Nicholas S.; Huebner, David M.; Baucom, Brian R. W.; Hoff, Colleen C.

2016-01-01

Relationship power is an important dyadic construct in close relationships that is associated with relationship health and partner’s individual health. Understanding what predicts power in heterosexual couples has proven difficult, and even less is known about gay couples. Resource models of power posit that demographic characteristics associated with social status (e.g., age, income) confer power within the relationship, which in turn shapes relationship outcomes. We tested this model in a sample of gay male couples (N=566 couples), and extended it by examining race and HIV status. Multilevel modeling was used to test associations between demographic bases of power and decision-making power. We also examined relative associations among demographic bases and decision-making power with relationship satisfaction, given the literature on power imbalances and overall relationship functioning. Results showed that individual income was positively associated with decision-making power, as was participant’s HIV status, with HIV-positive men reporting greater power. Age differences within the relationship interacted with relationship length to predict decision-making power, but not satisfaction. HIV-concordant positive couples were less satisfied than concordant negative couples. Higher power partners were less satisfied than lower power partners. Demographic factors contributing to decision-making power among same-sex male couples appear to share some similarities with heterosexual couples (e.g., income is associated with power), as well as have unique features (e.g., HIV status influences power). However, these same demographics did not reliably predict relationship satisfaction in the manner that existing power theories suggest. Findings indicate important considerations for theories of power among same-sex male couples. PMID:27606937

Evaluating Water Demand Using Agent-Based Modeling

NASA Astrophysics Data System (ADS)

Lowry, T. S.

2004-12-01

The supply and demand of water resources are functions of complex, inter-related systems including hydrology, climate, demographics, economics, and policy. To assess the safety and sustainability of water resources, planners often rely on complex numerical models that relate some or all of these systems using mathematical abstractions. The accuracy of these models relies on how well the abstractions capture the true nature of the systems interactions. Typically, these abstractions are based on analyses of observations and/or experiments that account only for the statistical mean behavior of each system. This limits the approach in two important ways: 1) It cannot capture cross-system disruptive events, such as major drought, significant policy change, or terrorist attack, and 2) it cannot resolve sub-system level responses. To overcome these limitations, we are developing an agent-based water resources model that includes the systems of hydrology, climate, demographics, economics, and policy, to examine water demand during normal and extraordinary conditions. Agent-based modeling (ABM) develops functional relationships between systems by modeling the interaction between individuals (agents), who behave according to a probabilistic set of rules. ABM is a "bottom-up" modeling approach in that it defines macro-system behavior by modeling the micro-behavior of individual agents. While each agent's behavior is often simple and predictable, the aggregate behavior of all agents in each system can be complex, unpredictable, and different than behaviors observed in mean-behavior models. Furthermore, the ABM approach creates a virtual laboratory where the effects of policy changes and/or extraordinary events can be simulated. Our model, which is based on the demographics and hydrology of the Middle Rio Grande Basin in the state of New Mexico, includes agent groups of residential, agricultural, and industrial users. Each agent within each group determines its water usage based on its own condition and the condition of the world around it. For example, residential agents can make decisions to convert to or from xeriscaping and/or low-flow appliances based on policy implementation, economic status, weather, and climatic conditions. Agricultural agents may vary their usage by making decisions on crop distribution and irrigation design. Preliminary results show that water usage can be highly irrational under certain conditions. Results also identify sub-sectors within each group that have the highest influence on ensemble group behavior, providing a means for policy makers to target their efforts. Finally, the model is able to predict the impact of low-probability, high-impact events such as catastrophic denial of service due to natural and/or man-made events.

Role of OpenEHR as an open source solution for the regional modelling of patient data in obstetrics.

PubMed

Pahl, Christina; Zare, Mojtaba; Nilashi, Mehrbakhsh; de Faria Borges, Marco Aurélio; Weingaertner, Daniel; Detschew, Vesselin; Supriyanto, Eko; Ibrahim, Othman

2015-06-01

This work investigates, whether openEHR with its reference model, archetypes and templates is suitable for the digital representation of demographic as well as clinical data. Moreover, it elaborates openEHR as a tool for modelling Hospital Information Systems on a regional level based on a national logical infrastructure. OpenEHR is a dual model approach developed for the modelling of Hospital Information Systems enabling semantic interoperability. A holistic solution to this represents the use of dual model based Electronic Healthcare Record systems. Modelling data in the field of obstetrics is a challenge, since different regions demand locally specific information for the process of treatment. Smaller health units in developing countries like Brazil or Malaysia, which until recently handled automatable processes like the storage of sensitive patient data in paper form, start organizational reconstruction processes. This archetype proof-of-concept investigation has tried out some elements of the openEHR methodology in cooperation with a health unit in Colombo, Brazil. Two legal forms provided by the Brazilian Ministry of Health have been analyzed and classified into demographic and clinical data. LinkEHR-Ed editor was used to read, edit and create archetypes. Results show that 33 clinical and demographic concepts, which are necessary to cover data demanded by the Unified National Health System, were identified. Out of the concepts 61% were reused and 39% modified to cover domain requirements. The detailed process of reuse, modification and creation of archetypes is shown. We conclude that, although a major part of demographic and clinical patient data were already represented by existing archetypes, a significant part required major modifications. In this study openEHR proved to be a highly suitable tool in the modelling of complex health data. In combination with LinkEHR-Ed software it offers user-friendly and highly applicable tools, although the complexity built by the vast specifications requires expert networks to define generally excepted clinical models. Finally, this project has pointed out main benefits enclosing high coverage of obstetrics data on the Clinical Knowledge Manager, simple modelling, and wide network and support using openEHR. Moreover, barriers described are enclosing the allocation of clinical content to respective archetypes, as well as stagnant adaption of changes on the Clinical Knowledge Manager leading to redundant efforts in data contribution that need to be addressed in future works. Copyright © 2015 Elsevier Inc. All rights reserved.

Beyond Traditional School Value-Added Models: A Multilevel Analysis of Complex School Effects in Chile

ERIC Educational Resources Information Center

Troncoso, Patricio; Pampaka, Maria; Olsen, Wendy

2016-01-01

School value-added studies have largely demonstrated the effects of socioeconomic and demographic characteristics of the schools and the pupils on performance in standardised tests. Traditionally, these studies have assessed the variation coming only from the schools and the pupils. However, recent studies have shown that the analysis of academic…

Discovering complex interrelationships between socioeconomic status and health in Europe: A case study applying Bayesian Networks.

PubMed

Alvarez-Galvez, Javier

2016-03-01

Studies assume that socioeconomic status determines individuals' states of health, but how does health determine socioeconomic status? And how does this association vary depending on contextual differences? To answer this question, our study uses an additive Bayesian Networks model to explain the interrelationships between health and socioeconomic determinants using complex and messy data. This model has been used to find the most probable structure in a network to describe the interdependence of these factors in five European welfare state regimes. The advantage of this study is that it offers a specific picture to describe the complex interrelationship between socioeconomic determinants and health, producing a network that is controlled by socio-demographic factors such as gender and age. The present work provides a general framework to describe and understand the complex association between socioeconomic determinants and health. Copyright © 2016 Elsevier Inc. All rights reserved.

Demographic Responses To Climate Manipulations Across a Species Range

NASA Astrophysics Data System (ADS)

Oldfather, M. F.

2016-12-01

Species biogeographic responses to climate change will occur through the local extinction and establishment of populations. The overall performance of populations across a species range is shaped by the idiosyncratic sensitivities of demographic rates to the changing climate conditions. Heterogeneous topography partially decouples temperature and soil moisture presenting an opportunity to disentangle demographic sensitivity to multiple local climate variables and refine range shift predictions in response to complex climate change. Since 2013, I have monitored 16 populations of a long-lived alpine plant, Ivesia lycopodioides var. scandularis (Rosaceae) across the entirety of its altitudinal range in the arid White Mountains, CA (3350 - 4420m). I quantified microclimatic soil moisture and temperature, and the demographic rates of over 4,000 individuals. Demographic rates exhibited sensitivity to accumulated degree-days (ex. reproduction), soil volumetric water content (ex. germination), or the interaction between these climate variables (ex. survival). These observations motivated an experimental test of the relationship between demography and local climate with manipulations of increased summertime temperature and precipitation in nine populations. All demographic rates were sensitive to the climate manipulations and the magnitude of the demographic response depended on the population's location within the range. However, the modeled population growth rate was only minimally affected by the manipulations in most populations. The inverse responses of many of the demographic rates may allow populations to demographically buffer against the climate manipulations. However, in one low elevation edge population the negative effect of heating on survival overwhelmed the positive effect on germination, indicating that the capacity of populations to demographically buffer may have a limit.

Demographic variation across successional stages and their effects on the population dynamics of the neotropical palm Euterpe precatoria.

PubMed

Otárola, Mauricio Fernández; Avalos, Gerardo

2014-06-01

• Premise of the study: Environmental heterogeneity is a strong selective force shaping adaptation and population dynamics across temporal and spatial scales. Natural and anthropogenic gradients influence the variation of environmental and biotic factors, which determine population demography and dynamics. Successional gradients are expected to influence demographic parameters, but the relationship between these gradients and the species life history, habitat requirements, and degree of variation in demographic traits remains elusive.• Methods: We used the palm Euterpe precatoria to test the effect of successional stage on plant demography within a continuous population. We calculated demographic parameters for size stages and performed matrix analyses to investigate the demographic variation within primary and secondary forests of La Selva, Costa Rica.• Key results: We observed differences in mortality and recruitment of small juveniles between primary and secondary forests. Matrix models described satisfactorily the chronosequence of population changes, which were characterized by high population growth rate in disturbed areas, and decreased growth rate in old successional forests until reaching stability.• Conclusions: Different demographic parameters can be expressed in contiguous subpopulations along a gradient of successional stages with important consequences for population dynamics. Demographic variation superimposed on these gradients contributes to generate subpopulations with different demographic composition, density, and ecological properties. Therefore, the effects of spatial variation must be reconsidered in the design of demographic analyses of tropical palms, which are prime examples of subtle local adaptation. These considerations are crucial in the implementation of management plans for palm species within spatially complex and heterogeneous tropical landscapes. © 2014 Botanical Society of America, Inc.

Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes.

PubMed

Naujokaitis-Lewis, Ilona; Curtis, Janelle M R

2016-01-01

Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along with demographic parameters in sensitivity routines. GRIP 2.0 is an important decision-support tool that can be used to prioritize research, identify habitat-based thresholds and management intervention points to improve probability of species persistence, and evaluate trade-offs of alternative management options.

Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes

PubMed Central

Curtis, Janelle M.R.

2016-01-01

Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along with demographic parameters in sensitivity routines. GRIP 2.0 is an important decision-support tool that can be used to prioritize research, identify habitat-based thresholds and management intervention points to improve probability of species persistence, and evaluate trade-offs of alternative management options. PMID:27547529

A Proposed Conceptual Model of Military Medical Readiness

DTIC Science & Technology

2007-05-01

critical role in complex military operations in which Medical Readiness 22 technological and information demands necessitate a multi-operator environment...Analysis 33 Coding 34 Data Collection 35 Medical Readiness 6 Boundaries 36 Researcher’s Role and Approach 37 Literature Review 37 The Military Health...Within the external environment, strategic shifts, technological advancements, and changing demographics affect how the Military Health System delivers

The complex contribution of sociodemographics to decision-making power in gay male couples.

PubMed

Perry, Nicholas S; Huebner, David M; Baucom, Brian R W; Hoff, Colleen C

2016-12-01

Relationship power is an important dyadic construct in close relationships that is associated with relationship health and partner's individual health. Understanding what predicts power in heterosexual couples has proven difficult, and even less is known about gay couples. Resource models of power posit that demographic characteristics associated with social status (e.g., age, income) confer power within the relationship, which in turn shapes relationship outcomes. We tested this model in a sample of gay male couples (N = 566 couples) and extended it by examining race and HIV status. Multilevel modeling was used to test associations between demographic bases of power and decision-making power. We also examined relative associations among demographic bases and decision-making power with relationship satisfaction given the literature on power imbalances and overall relationship functioning. Results showed that individual income was positively associated with decision-making power, as was participant's HIV status, with HIV-positive men reporting greater power. Age differences within the relationship interacted with relationship length to predict decision-making power, but not satisfaction. HIV-concordant positive couples were less satisfied than concordant negative couples. Higher power partners were less satisfied than lower power partners. Demographic factors contributing to decision-making power among same-sex male couples appear to share some similarities with heterosexual couples (e.g., income is associated with power) and have unique features (e.g., HIV status influences power). However, these same demographics did not reliably predict relationship satisfaction in the manner that existing power theories suggest. Findings indicate important considerations for theories of power among same-sex male couples. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

DnaSAM: Software to perform neutrality testing for large datasets with complex null models.

PubMed

Eckert, Andrew J; Liechty, John D; Tearse, Brandon R; Pande, Barnaly; Neale, David B

2010-05-01

Patterns of DNA sequence polymorphisms can be used to understand the processes of demography and adaptation within natural populations. High-throughput generation of DNA sequence data has historically been the bottleneck with respect to data processing and experimental inference. Advances in marker technologies have largely solved this problem. Currently, the limiting step is computational, with most molecular population genetic software allowing a gene-by-gene analysis through a graphical user interface. An easy-to-use analysis program that allows both high-throughput processing of multiple sequence alignments along with the flexibility to simulate data under complex demographic scenarios is currently lacking. We introduce a new program, named DnaSAM, which allows high-throughput estimation of DNA sequence diversity and neutrality statistics from experimental data along with the ability to test those statistics via Monte Carlo coalescent simulations. These simulations are conducted using the ms program, which is able to incorporate several genetic parameters (e.g. recombination) and demographic scenarios (e.g. population bottlenecks). The output is a set of diversity and neutrality statistics with associated probability values under a user-specified null model that are stored in easy to manipulate text file. © 2009 Blackwell Publishing Ltd.

Analytical Modelling of the Spread of Disease in Confined and Crowded Spaces

NASA Astrophysics Data System (ADS)

Goscé, Lara; Barton, David A. W.; Johansson, Anders

2014-05-01

Since 1927 and until recently, most models describing the spread of disease have been of compartmental type, based on the assumption that populations are homogeneous and well-mixed. Recent models have utilised agent-based models and complex networks to explicitly study heterogeneous interaction patterns, but this leads to an increasing computational complexity. Compartmental models are appealing because of their simplicity, but their parameters, especially the transmission rate, are complex and depend on a number of factors, which makes it hard to predict how a change of a single environmental, demographic, or epidemiological factor will affect the population. Therefore, in this contribution we propose a middle ground, utilising crowd-behaviour research to improve compartmental models in crowded situations. We show how both the rate of infection as well as the walking speed depend on the local crowd density around an infected individual. The combined effect is that the rate of infection at a population scale has an analytically tractable non-linear dependency on crowd density. We model the spread of a hypothetical disease in a corridor and compare our new model with a typical compartmental model, which highlights the regime in which current models may not produce credible results.

Population, internal migration, and economic growth: an empirical analysis.

PubMed

Moreland, R S

1982-01-01

The role of population growth in the development process has received increasing attention during the last 15 years, as manifested in the literature in 3 broad categories. In the 1st category, the effects of rapid population growth on the growth of income have been studied with the use of simulation models, which sometimes include endogenous population growth. The 2nd category of the literature is concerned with theoretical and empirical studies of the economic determinants of various demographic rates--most usually fertility. Internal migration and dualism is the 3rd population development category to recieve attention. An attempt is made to synthesize developments in these 3 categories by estimating from a consistent set of data a 2 sector economic demographic model in which the major demographic rates are endogenous. Due to the fact that the interactions between economic and demographic variables are nonlinear and complex, the indirect effects of changes in a particular variable may depend upon the balance of numerical coefficients. For this reason it was felt that the model should be empirically grounded. A brief overview of the model is provided, and the model is compared to some similar existing models. Estimation of the model's 9 behavior equations is discussed, followed by a "base run" simulation of a developing country "stereotype" and a report of a number of policy experiments. The relatively new field of economic determinants of demographic variables was drawn upon in estimating equations to endogenize demographic phenomena that are frequently left exogenous in simulation models. The fertility and labor force participation rate functions are fairly standard, but a step beyong existing literature was taken in the life expectancy and intersectorial migration equations. On the economic side, sectoral savings functions were estimated, and it was found that the marginal propensity to save is lower in agriculture than in nonagriculture. Testing to see the effect of a population's age structure on savings rather than assuming a particular direction as Coale-Hoover and Simon do in their models, it was found that a higher proportion of children compete with savings in agriculture but complement savings in industrial areas. This was consistent with the economic value of children in agricultural and nonagricultural regions of less developed countries. The estimated production functions showed that marginal products of labor were considerably higher in agriculture than in nonagriculture. As with other simulation models, the effect of reducing fertility was to accelerate income growth. Reductions in rural fertility were more equitable and raised the overall level of per capita income more than similar efforts directed to urban areas only.

Animal population dynamics: Identification of critical components

USGS Publications Warehouse

Emlen, J.M.; Pikitch, E.K.

1989-01-01

There is a growing interest in the use of population dynamics models in environmental risk assessment and the promulgation of environmental regulatory policies. Unfortunately, because of species and areal differences in the physical and biotic influences on population dynamics, such models must almost inevitably be both complex and species- or site-specific. Given the emormous variety of species and sites of potential concern, this fact presents a problem; it simply is not possible to construct models for all species and circumstances. Therefore, it is useful, before building predictive population models, to discover what input parameters are of critical importance to the desired output. This information should enable the construction of simpler and more generalizable models. As a first step, it is useful to consider population models as composed to two, partly separable classes, one comprising the purely mechanical descriptors of dynamics from given demographic parameter values, and the other describing the modulation of the demographic parameters by environmental factors (changes in physical environment, species interactions, pathogens, xenobiotic chemicals). This division permits sensitivity analyses to be run on the first of these classes, providing guidance for subsequent model simplification. We here apply such a sensitivity analysis to network models of mammalian and avian population dynamics.

Limiting similarity of competitive species and demographic stochasticity

NASA Astrophysics Data System (ADS)

Zheng, Xiu-Deng; Deng, Ling-Ling; Qiang, Wei-Ya; Cressman, Ross; Tao, Yi

2017-04-01

The limiting similarity of competitive species and its relationship with the competitive exclusion principle is still one of the most important concepts in ecology. In the 1970s, May [R. M. May, Stability and Complexity in Model Ecosystems (Princeton University, Princeton, NJ, 1973)] developed a concise theoretical framework to investigate the limiting similarity of competitive species. His theoretical results show that no limiting similarity threshold of competitive species can be identified in the deterministic model system whereby species more similar than this threshold never coexist. Theoretically, for competitive species coexisting in an unvarying environment, deterministic interspecific interactions and demographic stochasticity can be considered two sides of a coin. To investigate how the "tension" between these two forces affects the coexistence of competing species, a simple two-species competitive system based only on May's model system is transformed into an equivalent replicator equation. The effect of demographic stochasticity on the system stability is measured by the expected drift of the Lyapunov function. Our main results show that the limiting similarity of competitive species should not be considered to be an absolute measure. Specifically, very similar competitive species should be able to coexist in an environment with a high productivity level but big differences between competitive species should be necessary in an ecosystem with a low productivity level.

A Bottom-up Vulnerability Analysis of Water Systems with Decentralized Decision Making and Demographic Shifts- the Case of Jordan.

NASA Astrophysics Data System (ADS)

Lachaut, T.; Yoon, J.; Klassert, C. J. A.; Talozi, S.; Mustafa, D.; Knox, S.; Selby, P. D.; Haddad, Y.; Gorelick, S.; Tilmant, A.

2016-12-01

Probabilistic approaches to uncertainty in water systems management can face challenges of several types: non stationary climate, sudden shocks such as conflict-driven migrations, or the internal complexity and dynamics of large systems. There has been a rising trend in the development of bottom-up methods that place focus on the decision side instead of probability distributions and climate scenarios. These approaches are based on defining acceptability thresholds for the decision makers and considering the entire range of possibilities over which such thresholds are crossed. We aim at improving the knowledge on the applicability and relevance of this approach by enlarging its scope beyond climate uncertainty and single decision makers; thus including demographic shifts, internal system dynamics, and multiple stakeholders at different scales. This vulnerability analysis is part of the Jordan Water Project and makes use of an ambitious multi-agent model developed by its teams with the extensive cooperation of the Ministry of Water and Irrigation of Jordan. The case of Jordan is a relevant example for migration spikes, rapid social changes, resource depletion and climate change impacts. The multi-agent modeling framework used provides a consistent structure to assess the vulnerability of complex water resources systems with distributed acceptability thresholds and stakeholder interaction. A proof of concept and preliminary results are presented for a non-probabilistic vulnerability analysis that involves different types of stakeholders, uncertainties other than climatic and the integration of threshold-based indicators. For each stakeholder (agent) a vulnerability matrix is constructed over a multi-dimensional domain, which includes various hydrologic and/or demographic variables.

Emergence of social complexity among coastal hunter-gatherers in the Atacama Desert of northern Chile

PubMed Central

Marquet, Pablo A.; Santoro, Calogero M.; Latorre, Claudio; Standen, Vivien G.; Abades, Sebastián R.; Rivadeneira, Marcelo M.; Arriaza, Bernardo; Hochberg, Michael E.

2012-01-01

The emergence of complex cultural practices in simple hunter-gatherer groups poses interesting questions on what drives social complexity and what causes the emergence and disappearance of cultural innovations. Here we analyze the conditions that underlie the emergence of artificial mummification in the Chinchorro culture in the coastal Atacama Desert in northern Chile and southern Peru. We provide empirical and theoretical evidence that artificial mummification appeared during a period of increased coastal freshwater availability and marine productivity, which caused an increase in human population size and accelerated the emergence of cultural innovations, as predicted by recent models of cultural and technological evolution. Under a scenario of increasing population size and extreme aridity (with little or no decomposition of corpses) a simple demographic model shows that dead individuals may have become a significant part of the landscape, creating the conditions for the manipulation of the dead that led to the emergence of complex mortuary practices. PMID:22891345

The influence of farmer demographic characteristics on environmental behaviour: a review.

PubMed

Burton, Rob J F

2014-03-15

Many agricultural studies have observed a relationship between farmer demographic characteristics and environmental behaviours. These relationships are frequently employed in the construction of models, the identification of farmer types, or as part of more descriptive analyses aimed at understanding farmers' environmental behaviour. However, they have also often been found to be inconsistent or contradictory. Although a considerable body of literature has built up around the subject area, research has a tendency to focus on factors such as the direction, strength and consistency of the relationship - leaving the issue of causality largely to speculation. This review addresses this gap by reviewing literature on 4 key demographic variables: age, experience, education, and gender for hypothesised causal links. Overall the review indicates that the issue of causality is a complex one. Inconsistent relationships can be attributed to the presence of multiple causal pathways, the role of scheme factors in determining which pathway is important, inadequately specified measurements of demographic characteristics, and the treatment of non-linear causalities as linear. In addition, all demographic characteristics were perceived to be influenced (to varying extents) by cultural-historical patterns leading to cohort effects or socialised differences in the relationship with environmental behaviour. The paper concludes that more work is required on the issue of causality. Copyright © 2013 Elsevier Ltd. All rights reserved.

Integrated analysis for population estimation, management impact evaluation, and decision-making for a declining species

USGS Publications Warehouse

Crawford, Brian A.; Moore, Clinton; Norton, Terry M.; Maerz, John C.

2018-01-01

A challenge for making conservation decisions is predicting how wildlife populations respond to multiple, concurrent threats and potential management strategies, usually under substantial uncertainty. Integrated modeling approaches can improve estimation of demographic rates necessary for making predictions, even for rare or cryptic species with sparse data, but their use in management applications is limited. We developed integrated models for a population of diamondback terrapins (Malaclemys terrapin) impacted by road-associated threats to (i) jointly estimate demographic rates from two mark-recapture datasets, while directly estimating road mortality and the impact of management actions deployed during the study; and (ii) project the population using population viability analysis under simulated management strategies to inform decision-making. Without management, population extirpation was nearly certain due to demographic impacts of road mortality, predators, and vegetation. Installation of novel flashing signage increased survival of terrapins that crossed roads by 30%. Signage, along with small roadside barriers installed during the study, increased population persistence probability, but the population was still predicted to decline. Management strategies that included actions targeting multiple threats and demographic rates resulted in the highest persistence probability, and roadside barriers, which increased adult survival, were predicted to increase persistence more than other actions. Our results support earlier findings showing mitigation of multiple threats is likely required to increase the viability of declining populations. Our approach illustrates how integrated models may be adapted to use limited data efficiently, represent system complexity, evaluate impacts of threats and management actions, and provide decision-relevant information for conservation of at-risk populations.

A Model of Compound Heterozygous, Loss-of-Function Alleles Is Broadly Consistent with Observations from Complex-Disease GWAS Datasets

PubMed Central

Sanjak, Jaleal S.; Long, Anthony D.; Thornton, Kevin R.

2017-01-01

The genetic component of complex disease risk in humans remains largely unexplained. A corollary is that the allelic spectrum of genetic variants contributing to complex disease risk is unknown. Theoretical models that relate population genetic processes to the maintenance of genetic variation for quantitative traits may suggest profitable avenues for future experimental design. Here we use forward simulation to model a genomic region evolving under a balance between recurrent deleterious mutation and Gaussian stabilizing selection. We consider multiple genetic and demographic models, and several different methods for identifying genomic regions harboring variants associated with complex disease risk. We demonstrate that the model of gene action, relating genotype to phenotype, has a qualitative effect on several relevant aspects of the population genetic architecture of a complex trait. In particular, the genetic model impacts genetic variance component partitioning across the allele frequency spectrum and the power of statistical tests. Models with partial recessivity closely match the minor allele frequency distribution of significant hits from empirical genome-wide association studies without requiring homozygous effect sizes to be small. We highlight a particular gene-based model of incomplete recessivity that is appealing from first principles. Under that model, deleterious mutations in a genomic region partially fail to complement one another. This model of gene-based recessivity predicts the empirically observed inconsistency between twin and SNP based estimated of dominance heritability. Furthermore, this model predicts considerable levels of unexplained variance associated with intralocus epistasis. Our results suggest a need for improved statistical tools for region based genetic association and heritability estimation. PMID:28103232

Predictive model of complexity in early palliative care: a cohort of advanced cancer patients (PALCOM study).

PubMed

Tuca, Albert; Gómez-Martínez, Mónica; Prat, Aleix

2018-01-01

Model of early palliative care (PC) integrated in oncology is based on shared care from the diagnosis to the end of life and is mainly focused on patients with greater complexity. However, there is no definition or tools to evaluate PC complexity. The objectives of the study were to identify the factors influencing level determination of complexity, propose predictive models, and build a complexity scale of PC. We performed a prospective, observational, multicenter study in a cohort of advanced cancer patients with an estimated prognosis ≤ 6 months. An ad hoc structured evaluation including socio-demographic and clinical data, symptom burden, functional and cognitive status, psychosocial problems, and existential-ethic dilemmas was recorded systematically. According to this multidimensional evaluation, investigator classified patients as high, medium, or low palliative complexity, associated to need of basic or specialized PC. Logistic regression was used to identify the variables influencing determination of level of PC complexity and explore predictive models. We included 324 patients; 41% were classified as having high PC complexity and 42.9% as medium, both levels being associated with specialized PC. Variables influencing determination of PC complexity were as follows: high symptom burden (OR 3.19 95%CI: 1.72-6.17), difficult pain (OR 2.81 95%CI:1.64-4.9), functional status (OR 0.99 95%CI:0.98-0.9), and social-ethical existential risk factors (OR 3.11 95%CI:1.73-5.77). Logistic analysis of variables allowed construct a complexity model and structured scales (PALCOM 1 and 2) with high predictive value (AUC ROC 76%). This study provides a new model and tools to assess complexity in palliative care, which may be very useful to manage referral to specialized PC services, and agree intensity of their intervention in a model of early-shared care integrated in oncology.

Modelling and simulating decision processes of linked lives: An approach based on concurrent processes and stochastic race.

PubMed

Warnke, Tom; Reinhardt, Oliver; Klabunde, Anna; Willekens, Frans; Uhrmacher, Adelinde M

2017-10-01

Individuals' decision processes play a central role in understanding modern migration phenomena and other demographic processes. Their integration into agent-based computational demography depends largely on suitable support by a modelling language. We are developing the Modelling Language for Linked Lives (ML3) to describe the diverse decision processes of linked lives succinctly in continuous time. The context of individuals is modelled by networks the individual is part of, such as family ties and other social networks. Central concepts, such as behaviour conditional on agent attributes, age-dependent behaviour, and stochastic waiting times, are tightly integrated in the language. Thereby, alternative decisions are modelled by concurrent processes that compete by stochastic race. Using a migration model, we demonstrate how this allows for compact description of complex decisions, here based on the Theory of Planned Behaviour. We describe the challenges for the simulation algorithm posed by stochastic race between multiple concurrent complex decisions.

Predictive Modeling of Risk Factors and Complications of Cataract Surgery

PubMed Central

Gaskin, Gregory L; Pershing, Suzann; Cole, Tyler S; Shah, Nigam H

2016-01-01

Purpose To quantify the relationship between aggregated preoperative risk factors and cataract surgery complications, as well as to build a model predicting outcomes on an individual-level—given a constellation of demographic, baseline, preoperative, and intraoperative patient characteristics. Setting Stanford Hospital and Clinics between 1994 and 2013. Design Retrospective cohort study Methods Patients age 40 or older who received cataract surgery between 1994 and 2013. Risk factors, complications, and demographic information were extracted from the Electronic Health Record (EHR), based on International Classification of Diseases, 9th edition (ICD-9) codes, Current Procedural Terminology (CPT) codes, drug prescription information, and text data mining using natural language processing. We used a bootstrapped least absolute shrinkage and selection operator (LASSO) model to identify highly-predictive variables. We built random forest classifiers for each complication to create predictive models. Results Our data corroborated existing literature on postoperative complications—including the association of intraoperative complications, complex cataract surgery, black race, and/or prior eye surgery with an increased risk of any postoperative complications. We also found a number of other, less well-described risk factors, including systemic diabetes mellitus, young age (<60 years old), and hyperopia as risk factors for complex cataract surgery and intra- and post-operative complications. Our predictive models based on aggregated outperformed existing published models. Conclusions The constellations of risk factors and complications described here can guide new avenues of research and provide specific, personalized risk assessment for a patient considering cataract surgery. The predictive capacity of our models can enable risk stratification of patients, which has utility as a teaching tool as well as informing quality/value-based reimbursements. PMID:26692059

Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation

USGS Publications Warehouse

Dunham, Kylee; Grand, James B.

2016-01-01

We examined the effects of complexity and priors on the accuracy of models used to estimate ecological and observational processes, and to make predictions regarding population size and structure. State-space models are useful for estimating complex, unobservable population processes and making predictions about future populations based on limited data. To better understand the utility of state space models in evaluating population dynamics, we used them in a Bayesian framework and compared the accuracy of models with differing complexity, with and without informative priors using sequential importance sampling/resampling (SISR). Count data were simulated for 25 years using known parameters and observation process for each model. We used kernel smoothing to reduce the effect of particle depletion, which is common when estimating both states and parameters with SISR. Models using informative priors estimated parameter values and population size with greater accuracy than their non-informative counterparts. While the estimates of population size and trend did not suffer greatly in models using non-informative priors, the algorithm was unable to accurately estimate demographic parameters. This model framework provides reasonable estimates of population size when little to no information is available; however, when information on some vital rates is available, SISR can be used to obtain more precise estimates of population size and process. Incorporating model complexity such as that required by structured populations with stage-specific vital rates affects precision and accuracy when estimating latent population variables and predicting population dynamics. These results are important to consider when designing monitoring programs and conservation efforts requiring management of specific population segments.

CDMetaPOP: An individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics

USGS Publications Warehouse

Landguth, Erin L; Bearlin, Andrew; Day, Casey; Dunham, Jason B.

2016-01-01

1. Combining landscape demographic and genetics models offers powerful methods for addressing questions for eco-evolutionary applications.2. Using two illustrative examples, we present Cost–Distance Meta-POPulation, a program to simulate changes in neutral and/or selection-driven genotypes through time as a function of individual-based movement, complex spatial population dynamics, and multiple and changing landscape drivers.3. Cost–Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.

Can Psychological, Social and Demographical Factors Predict Clinical Characteristics Symptomatology of Bipolar Affective Disorder and Schizophrenia?

PubMed

Maciukiewicz, Malgorzata; Pawlak, Joanna; Kapelski, Pawel; Łabędzka, Magdalena; Skibinska, Maria; Zaremba, Dorota; Leszczynska-Rodziewicz, Anna; Dmitrzak-Weglarz, Monika; Hauser, Joanna

2016-09-01

Schizophrenia (SCH) is a complex, psychiatric disorder affecting 1 % of population. Its clinical phenotype is heterogeneous with delusions, hallucinations, depression, disorganized behaviour and negative symptoms. Bipolar affective disorder (BD) refers to periodic changes in mood and activity from depression to mania. It affects 0.5-1.5 % of population. Two types of disorder (type I and type II) are distinguished by severity of mania episodes. In our analysis, we aimed to check if clinical and demographical characteristics of the sample are predictors of symptom dimensions occurrence in BD and SCH cases. We included total sample of 443 bipolar and 439 schizophrenia patients. Diagnosis was based on DSM-IV criteria using Structured Clinical Interview for DSM-IV. We applied regression models to analyse associations between clinical and demographical traits from OPCRIT and symptom dimensions. We used previously computed dimensions of schizophrenia and bipolar affective disorder as quantitative traits for regression models. Male gender seemed protective factor for depression dimension in schizophrenia and bipolar disorder sample. Presence of definite psychosocial stressor prior disease seemed risk factor for depressive and suicidal domain in BD and SCH. OPCRIT items describing premorbid functioning seemed related with depression, positive and disorganised dimensions in schizophrenia and psychotic in BD. We proved clinical and demographical characteristics of the sample are predictors of symptom dimensions of schizophrenia and bipolar disorder. We also saw relation between clinical dimensions and course of disorder and impairment during disorder.

Land Use Change on Household Farms in the Ecuadorian Amazon: Design and Implementation of an Agent-Based Model.

PubMed

Mena, Carlos F; Walsh, Stephen J; Frizzelle, Brian G; Xiaozheng, Yao; Malanson, George P

2011-01-01

This paper describes the design and implementation of an Agent-Based Model (ABM) used to simulate land use change on household farms in the Northern Ecuadorian Amazon (NEA). The ABM simulates decision-making processes at the household level that is examined through a longitudinal, socio-economic and demographic survey that was conducted in 1990 and 1999. Geographic Information Systems (GIS) are used to establish spatial relationships between farms and their environment, while classified Landsat Thematic Mapper (TM) imagery is used to set initial land use/land cover conditions for the spatial simulation, assess from-to land use/land cover change patterns, and describe trajectories of land use change at the farm and landscape levels. Results from prior studies in the NEA provide insights into the key social and ecological variables, describe human behavioral functions, and examine population-environment interactions that are linked to deforestation and agricultural extensification, population migration, and demographic change. Within the architecture of the model, agents are classified as active or passive. The model comprises four modules, i.e., initialization, demography, agriculture, and migration that operate individually, but are linked through key household processes. The main outputs of the model include a spatially-explicit representation of the land use/land cover on survey and non-survey farms and at the landscape level for each annual time-step, as well as simulated socio-economic and demographic characteristics of households and communities. The work describes the design and implementation of the model and how population-environment interactions can be addressed in a frontier setting. The paper contributes to land change science by examining important pattern-process relations, advocating a spatial modeling approach that is capable of synthesizing fundamental relationships at the farm level, and links people and environment in complex ways.

Characteristics associated with Sleep Duration, Chronotype, and Social jet lag in Adolescents

PubMed Central

Malone, Susan Kohl; Zemel, Babette S.; Compher, Charlene; Souders, Margaret; Chittams, Jesse; Thompson, Aleda Leis; Lipman, Terri H.

2015-01-01

Sleep is a complex behavior with numerous health implications. Identifying socio-demographic and behavioral characteristics of sleep are important for determining those at greatest risk for sleep-related health disparities. In this cross-sectional study, general linear models were used to examine socio-demographic and behavioral characteristics associated with sleep duration, chronotype, and social jet lag in adolescents. One hundred fifteen participants completed Phase I (self-reported sleep measures); 69 of these participants completed Phase II (actigraphy-estimated sleep measures). Black adolescents had shorter free night sleep than Hispanics. Youth with later chronotypes ate fewer fruits and vegetables, drank more soda, were less physically active, and took more daytime naps. Based on these findings, recommendations for individual support and school policies are provided. PMID:26376832

Using a generalised identity reference model with archetypes to support interoperability of demographics information in electronic health record systems.

PubMed

Xu Chen; Berry, Damon; Stephens, Gaye

2015-01-01

Computerised identity management is in general encountered as a low-level mechanism that enables users in a particular system or region to securely access resources. In the Electronic Health Record (EHR), the identifying information of both the healthcare professionals who access the EHR and the patients whose EHR is accessed, are subject to change. Demographics services have been developed to manage federated patient and healthcare professional identities and to support challenging healthcare-specific use cases in the presence of diverse and sometimes conflicting demographic identities. Demographics services are not the only use for identities in healthcare. Nevertheless, contemporary EHR specifications limit the types of entities that can be the actor or subject of a record to health professionals and patients, thus limiting the use of two level models in other healthcare information systems. Demographics are ubiquitous in healthcare, so for a general identity model to be usable, it should be capable of managing demographic information. In this paper, we introduce a generalised identity reference model (GIRM) based on key characteristics of five surveyed demographic models. We evaluate the GIRM by using it to express the EN13606 demographics model in an extensible way at the metadata level and show how two-level modelling can support the exchange of instances of demographic identities. This use of the GIRM to express demographics information shows its application for standards-compliant two-level modelling alongside heterogeneous demographics models. We advocate this approach to facilitate the interoperability of identities between two-level model-based EHR systems and show the validity and the extensibility of using GIRM for the expression of other health-related identities.

Exploiting Fast-Variables to Understand Population Dynamics and Evolution

NASA Astrophysics Data System (ADS)

Constable, George W. A.; McKane, Alan J.

2018-07-01

We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are caused by individual events while the dynamics are described in terms of the time-evolution of a probability density function. In general, the application of the diffusion approximation still leaves a description that is quite complex. However, in many biological applications one or more of the processes happen slowly relative to the system's other processes, and the dynamics can be approximated as occurring within a slow low-dimensional subspace. We review these time-scale separation arguments and analyse the more simple stochastic dynamics that result in a number of cases. We stress that it is important to retain the demographic noise derived in this way, and emphasise this point by showing that it can alter the direction of selection compared to the prediction made from an analysis of the corresponding deterministic model.

Exploiting Fast-Variables to Understand Population Dynamics and Evolution

NASA Astrophysics Data System (ADS)

Constable, George W. A.; McKane, Alan J.

2017-11-01

We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are caused by individual events while the dynamics are described in terms of the time-evolution of a probability density function. In general, the application of the diffusion approximation still leaves a description that is quite complex. However, in many biological applications one or more of the processes happen slowly relative to the system's other processes, and the dynamics can be approximated as occurring within a slow low-dimensional subspace. We review these time-scale separation arguments and analyse the more simple stochastic dynamics that result in a number of cases. We stress that it is important to retain the demographic noise derived in this way, and emphasise this point by showing that it can alter the direction of selection compared to the prediction made from an analysis of the corresponding deterministic model.

Disease ecology and the global emergence of zoonotic pathogens.

PubMed

Wilcox, Bruce A; Gubler, Duane J

2005-09-01

The incidence and frequency of epidemic transmission of zoonotic diseases, both known and newly recognized, has increased dramatically in the past 30 years. It is thought that this dramatic disease emergence is primarily the result of the social, demographic, and environmental transformation that has occurred globally since World War II. However, the causal linkages have not been elucidated. Investigating emerging zoonotic pathogens as an ecological phenomenon can provide significant insights as to why some of these pathogens have jumped species and caused major epidemics in humans. A review of concepts and theory from biological ecology and of causal factors in disease emergence previously described suggests a general model of global zoonotic disease emergence. The model links demographic and societal factors to land use and land cover change whose associated ecological factors help explain disease emergence. The scale and magnitude of these changes are more significant than those associated with climate change, the effects of which are largely not yet understood. Unfortunately, the complex character and non-linear behavior of the human-natural systems in which host-pathogen systems are embedded makes specific incidences of disease emergence or epidemics inherently difficult to predict. Employing a complex systems analytical approach, however, may show how a few key ecological variables and system properties, including the adaptive capacity of institutions, explains the emergence of infectious diseases and how an integrated, multi-level approach to zoonotic disease control can reduce risk.

Projecting the future of an alpine ungulate under climate change scenarios.

PubMed

White, Kevin S; Gregovich, David P; Levi, Taal

2018-03-01

Climate change represents a primary threat to species persistence and biodiversity at a global scale. Cold adapted alpine species are especially sensitive to climate change and can offer key "early warning signs" about deleterious effects of predicted change. Among mountain ungulates, survival, a key determinant of demographic performance, may be influenced by future climate in complex, and possibly opposing ways. Demographic data collected from 447 mountain goats in 10 coastal Alaska, USA, populations over a 37-year time span indicated that survival is highest during low snowfall winters and cool summers. However, general circulation models (GCMs) predict future increase in summer temperature and decline in winter snowfall. To disentangle how these opposing climate-driven effects influence mountain goat populations, we developed an age-structured population model to project mountain goat population trajectories for 10 different GCM/emissions scenarios relevant for coastal Alaska. Projected increases in summer temperature had stronger negative effects on population trajectories than the positive demographic effects of reduced winter snowfall. In 5 of the 10 GCM/representative concentration pathway (RCP) scenarios, the net effect of projected climate change was extinction over a 70-year time window (2015-2085); smaller initial populations were more likely to go extinct faster than larger populations. Using a resource selection modeling approach, we determined that distributional shifts to higher elevation (i.e., "thermoneutral") summer range was unlikely to be a viable behavioral adaptation strategy; due to the conical shape of mountains, summer range was expected to decline by 17%-86% for 7 of the 10 GCM/RCP scenarios. Projected declines of mountain goat populations are driven by climate-linked bottom-up mechanisms and may have wide ranging implications for alpine ecosystems. These analyses elucidate how projected climate change can negatively alter population dynamics of a sentinel alpine species and provide insight into how demographic modeling can be used to assess risk to species persistence. © 2017 John Wiley & Sons Ltd.

A general temporal data model and the structured population event history register

PubMed Central

Clark, Samuel J.

2010-01-01

At this time there are 37 demographic surveillance system sites active in sub-Saharan Africa, Asia and Central America, and this number is growing continuously. These sites and other longitudinal population and health research projects generate large quantities of complex temporal data in order to describe, explain and investigate the event histories of individuals and the populations they constitute. This article presents possible solutions to some of the key data management challenges associated with those data. The fundamental components of a temporal system are identified and both they and their relationships to each other are given simple, standardized definitions. Further, a metadata framework is proposed to endow this abstract generalization with specific meaning and to bind the definitions of the data to the data themselves. The result is a temporal data model that is generalized, conceptually tractable, and inherently contains a full description of the primary data it organizes. Individual databases utilizing this temporal data model can be customized to suit the needs of their operators without modifying the underlying design of the database or sacrificing the potential to transparently share compatible subsets of their data with other similar databases. A practical working relational database design based on this general temporal data model is presented and demonstrated. This work has arisen out of experience with demographic surveillance in the developing world, and although the challenges and their solutions are more general, the discussion is organized around applications in demographic surveillance. An appendix contains detailed examples and working prototype databases that implement the examples discussed in the text. PMID:20396614

Cross-validation to select Bayesian hierarchical models in phylogenetics.

PubMed

Duchêne, Sebastián; Duchêne, David A; Di Giallonardo, Francesca; Eden, John-Sebastian; Geoghegan, Jemma L; Holt, Kathryn E; Ho, Simon Y W; Holmes, Edward C

2016-05-26

Recent developments in Bayesian phylogenetic models have increased the range of inferences that can be drawn from molecular sequence data. Accordingly, model selection has become an important component of phylogenetic analysis. Methods of model selection generally consider the likelihood of the data under the model in question. In the context of Bayesian phylogenetics, the most common approach involves estimating the marginal likelihood, which is typically done by integrating the likelihood across model parameters, weighted by the prior. Although this method is accurate, it is sensitive to the presence of improper priors. We explored an alternative approach based on cross-validation that is widely used in evolutionary analysis. This involves comparing models according to their predictive performance. We analysed simulated data and a range of viral and bacterial data sets using a cross-validation approach to compare a variety of molecular clock and demographic models. Our results show that cross-validation can be effective in distinguishing between strict- and relaxed-clock models and in identifying demographic models that allow growth in population size over time. In most of our empirical data analyses, the model selected using cross-validation was able to match that selected using marginal-likelihood estimation. The accuracy of cross-validation appears to improve with longer sequence data, particularly when distinguishing between relaxed-clock models. Cross-validation is a useful method for Bayesian phylogenetic model selection. This method can be readily implemented even when considering complex models where selecting an appropriate prior for all parameters may be difficult.

Maternal factors predicting cognitive and behavioral characteristics of children with fetal alcohol spectrum disorders.

PubMed

May, Philip A; Tabachnick, Barbara G; Gossage, J Phillip; Kalberg, Wendy O; Marais, Anna-Susan; Robinson, Luther K; Manning, Melanie A; Blankenship, Jason; Buckley, David; Hoyme, H Eugene; Adnams, Colleen M

2013-06-01

To provide an analysis of multiple predictors of cognitive and behavioral traits for children with fetal alcohol spectrum disorders (FASDs). Multivariate correlation techniques were used with maternal and child data from epidemiologic studies in a community in South Africa. Data on 561 first-grade children with fetal alcohol syndrome (FAS), partial FAS (PFAS), and not FASD and their mothers were analyzed by grouping 19 maternal variables into categories (physical, demographic, childbearing, and drinking) and used in structural equation models (SEMs) to assess correlates of child intelligence (verbal and nonverbal) and behavior. A first SEM using only 7 maternal alcohol use variables to predict cognitive/behavioral traits was statistically significant (B = 3.10, p < .05) but explained only 17.3% of the variance. The second model incorporated multiple maternal variables and was statistically significant explaining 55.3% of the variance. Significantly correlated with low intelligence and problem behavior were demographic (B = 3.83, p < .05) (low maternal education, low socioeconomic status [SES], and rural residence) and maternal physical characteristics (B = 2.70, p < .05) (short stature, small head circumference, and low weight). Childbearing history and alcohol use composites were not statistically significant in the final complex model and were overpowered by SES and maternal physical traits. Although other analytic techniques have amply demonstrated the negative effects of maternal drinking on intelligence and behavior, this highly controlled analysis of multiple maternal influences reveals that maternal demographics and physical traits make a significant enabling or disabling contribution to child functioning in FASD.

Demographics, social position, dental status and oral health-related quality of life in community-dwelling older adults.

PubMed

Rebelo, Maria Augusta Bessa; Cardoso, Evangeline Maria; Robinson, Peter G; Vettore, Mario Vianna

2016-07-01

To identify demographic, socioeconomic and dental clinical predictors of oral health-related quality of life (OHRQoL) in elderly people. Cross-sectional study involving 613 elderly people aged 65-74 years in Manaus, Brazil. Interviews and oral examinations were carried out to collect demographic characteristics (age and sex) and socioeconomic data (income and education), dental clinical measures (DMFT, need of upper and lower dentures) and OHRQoL (GOHAI questionnaire). Structural equation modelling was used to estimate direct and indirect pathways between the variables. Being older predicted lower schooling but higher income. Higher income was linked to better dental status, which was linked to better OHRQoL. There were also indirect pathways. Age and education were linked to OHRQoL, mediated by clinical dental status. Income was associated with dental clinical status via education, and income predicted OHRQoL via education and clinical measures. Our findings elucidate the complex pathways between individual, environmental factors and clinical factors that may determine OHRQoL and support the application of public health approaches to improve oral health in older people.

Proposed model of integrated care to improve health outcomes for individuals with multimorbidities

PubMed Central

Sampalli, Tara; Fox, Roy A; Dickson, Robert; Fox, Jonathan

2012-01-01

Multimorbidity is defined as the coexistence of multiple chronic conditions. Individuals with multimorbidity typically present with complex needs and show significant changes in their functional health and quality of life. Multimorbidity in the aging population is well recognized, but there has been limited research on ways to manage the problem effectively. More recent studies have demonstrated a high prevalence of multimorbidity in the younger demographics aged under 65 years. There is a definite need to develop models of care that can manage these individuals effectively and mitigate the impact of illness on individuals and the financial burden to the health care system. An integrated model of care has been developed and implemented in a facility in Nova Scotia that routinely treats individuals with multiple chronic conditions. This care model is designed to address the specific needs of this complex patient population, with integrated and coordinated care modules that meet the needs of the person versus the disease. The results of a pilot evaluation of this care model are also discussed. PMID:23118532

Modeling the Pre-Industrial Roots of Modern Super-Exponential Population Growth

PubMed Central

Stutz, Aaron Jonas

2014-01-01

To Malthus, rapid human population growth—so evident in 18th Century Europe—was obviously unsustainable. In his Essay on the Principle of Population, Malthus cogently argued that environmental and socioeconomic constraints on population rise were inevitable. Yet, he penned his essay on the eve of the global census size reaching one billion, as nearly two centuries of super-exponential increase were taking off. Introducing a novel extension of J. E. Cohen's hallmark coupled difference equation model of human population dynamics and carrying capacity, this article examines just how elastic population growth limits may be in response to demographic change. The revised model involves a simple formalization of how consumption costs influence carrying capacity elasticity over time. Recognizing that complex social resource-extraction networks support ongoing consumption-based investment in family formation and intergenerational resource transfers, it is important to consider how consumption has impacted the human environment and demography—especially as global population has become very large. Sensitivity analysis of the consumption-cost model's fit to historical population estimates, modern census data, and 21st Century demographic projections supports a critical conclusion. The recent population explosion was systemically determined by long-term, distinctly pre-industrial cultural evolution. It is suggested that modern globalizing transitions in technology, susceptibility to infectious disease, information flows and accumulation, and economic complexity were endogenous products of much earlier biocultural evolution of family formation's embeddedness in larger, hierarchically self-organizing cultural systems, which could potentially support high population elasticity of carrying capacity. Modern super-exponential population growth cannot be considered separately from long-term change in the multi-scalar political economy that connects family formation and intergenerational resource transfers to wider institutions and social networks. PMID:25141019

The association between self-rated health and social environments, health behaviors and health outcomes: a structural equation analysis.

PubMed

Craig, Bevan Adrian; Morton, Darren Peter; Morey, Peter John; Kent, Lillian Marton; Gane, Alva Barry; Butler, Terry Leslie; Rankin, Paul Meredith; Price, Kevin Ross

2018-04-03

The factors shaping the health of the current generation of adolescents are multi-dimensional and complex. The purpose of this study was to explore the determinants of self-rated health (SRH) of adolescents attending a faith-based school system in Australia. A total of 788 students attending 21 Seventh-day Adventist schools in Australia responded to a health and lifestyle survey that assessed SRH as well as potential determinants of SRH including the health outcomes mental health, vitality, body mass index (BMI), select health behaviors, social factors and personal demographics. Structural equation modeling was used to analyze the data and examine the direct and indirect effects of these factors on SRH. The structural model developed was a good fit with the data. The health outcome mental health had the strongest association with SRH (β = 0.17). Several upstream variables were also associated with higher SRH ratings. The health behavior sleep hours had the strongest association with SRH (β total  = 0.178) followed by fruit/vegetable consumption (β total  = 0.144), physical activity (β total  = 0.135) and a vegetarian diet (β total  = 0.103). Of the demographic and social variables measured, adverse childhood experiences (ACEs) had the strongest association with SRH (β total  = - 0.125), negatively influencing SRH, and gender also associated with an increase in SRH (β total  = 0.092), with the influence of these factors being mediated through other variables in the model. This study presents a conceptual model that illustrates the complex network of factors concomitantly associated with SRH in adolescents. The outcomes of the study provide insights into the determinants of adolescent SRH which may inform priority areas for improving this construct.

Understanding variation in human fertility: what can we learn from evolutionary demography?

PubMed

Sear, Rebecca; Lawson, David W; Kaplan, Hillard; Shenk, Mary K

2016-04-19

Decades of research on human fertility has presented a clear picture of how fertility varies, including its dramatic decline over the last two centuries in most parts of the world. Why fertility varies, both between and within populations, is not nearly so well understood. Fertility is a complex phenomenon, partly physiologically and partly behaviourally determined, thus an interdisciplinary approach is required to understand it. Evolutionary demographers have focused on human fertility since the 1980s. The first wave of evolutionary demographic research made major theoretical and empirical advances, investigating variation in fertility primarily in terms of fitness maximization. Research focused particularly on variation within high-fertility populations and small-scale subsistence societies and also yielded a number of hypotheses for why fitness maximization seems to break down as fertility declines during the demographic transition. A second wave of evolutionary demography research on fertility is now underway, paying much more attention to the cultural and psychological mechanisms underpinning fertility. It is also engaging with the complex, multi-causal nature of fertility variation, and with understanding fertility in complex modern and transitioning societies. Here, we summarize the history of evolutionary demographic work on human fertility, describe the current state of the field, and suggest future directions. © 2016 The Author(s).

Understanding variation in human fertility: what can we learn from evolutionary demography?

PubMed Central

Sear, Rebecca; Lawson, David W.; Kaplan, Hillard

2016-01-01

Decades of research on human fertility has presented a clear picture of how fertility varies, including its dramatic decline over the last two centuries in most parts of the world. Why fertility varies, both between and within populations, is not nearly so well understood. Fertility is a complex phenomenon, partly physiologically and partly behaviourally determined, thus an interdisciplinary approach is required to understand it. Evolutionary demographers have focused on human fertility since the 1980s. The first wave of evolutionary demographic research made major theoretical and empirical advances, investigating variation in fertility primarily in terms of fitness maximization. Research focused particularly on variation within high-fertility populations and small-scale subsistence societies and also yielded a number of hypotheses for why fitness maximization seems to break down as fertility declines during the demographic transition. A second wave of evolutionary demography research on fertility is now underway, paying much more attention to the cultural and psychological mechanisms underpinning fertility. It is also engaging with the complex, multi-causal nature of fertility variation, and with understanding fertility in complex modern and transitioning societies. Here, we summarize the history of evolutionary demographic work on human fertility, describe the current state of the field, and suggest future directions. PMID:27022071

The interplay of demography and selection during maize domestication and expansion

USDA-ARS?s Scientific Manuscript database

The history of maize has been characterized by major demographic events including changes in population size associated with domestication and subsequent range expansion as well as gene flow with wild relatives. This complex demographic history and its interplay with selection have shaped diversity ...

Evolutionary transitions towards eusociality in snapping shrimps.

PubMed

Chak, Solomon Tin Chi; Duffy, J Emmett; Hultgren, Kristin M; Rubenstein, Dustin R

2017-03-20

Animal social organization varies from complex societies where reproduction is dominated by a single individual (eusociality) to those where reproduction is more evenly distributed among group members (communal breeding). Yet, how simple groups transition evolutionarily to more complex societies remains unclear. Competing hypotheses suggest that eusociality and communal breeding are alternative evolutionary endpoints, or that communal breeding is an intermediate stage in the transition towards eusociality. We tested these alternative hypotheses in sponge-dwelling shrimps, Synalpheus spp. Although species varied continuously in reproductive skew, they clustered into pair-forming, communal and eusocial categories based on several demographic traits. Evolutionary transition models suggested that eusocial and communal species are discrete evolutionary endpoints that evolved independently from pair-forming ancestors along alternative paths. This 'family-centred' origin of eusociality parallels observations in insects and vertebrates, reinforcing the role of kin selection in the evolution of eusociality and suggesting a general model of animal social evolution.

Density dependence in group dynamics of a highly social mongoose, Suricata suricatta.

PubMed

Bateman, Andrew W; Ozgul, Arpat; Coulson, Tim; Clutton-Brock, Tim H

2012-05-01

1. For social species, the link between individual behaviour and population dynamics is mediated by group-level demography. 2. Populations of obligate cooperative breeders are structured into social groups, which may be subject to inverse density dependence (Allee effects) that result from a dependence on conspecific helpers, but evidence for population-wide Allee effects is rare. 3. We use field data from a long-term study of cooperative meerkats (Suricata suricatta; Schreber, 1776) - a species for which local Allee effects are not reflected in population-level dynamics - to empirically model interannual group dynamics. 4. Using phenomenological population models, modified to incorporate environmental conditions and potential Allee effects, we first investigate overall patterns of group dynamics and find support only for conventional density dependence that increases after years of low rainfall. 5. To explain the observed patterns, we examine specific demographic rates and assess their contributions to overall group dynamics. Although per-capita meerkat mortality is subject to a component Allee effect, it contributes relatively little to observed variation in group dynamics, and other (conventionally density dependent) demographic rates - especially emigration - govern group dynamics. 6. Our findings highlight the need to consider demographic processes and density dependence in subpopulations before drawing conclusions about how behaviour affects population processes in socially complex systems. © 2011 The Authors. Journal of Animal Ecology © 2011 British Ecological Society.

Socio-Demographic Determinants of Economic Growth: Age-Structure, Preindustrial Heritage and Sociolinguistic Integration

ERIC Educational Resources Information Center

Crenshaw, Edward; Robison, Kristopher

2010-01-01

This study establishes a socio-demographic theory of international development derived from selected classical and contemporary sociological theories. Four hypotheses are tested: (1. population growth's effect on development depends on age-structure; (2. historic population density (used here as an indicator of preindustrial social complexity)…

Demographic modelling reveals a history of divergence with gene flow for a glacially tied stonefly in a changing post-Pleistocene landscape

USGS Publications Warehouse

Hotaling, Scott; Muhlfeld, Clint C.; Giersch, J. Joseph; Ali, Omar; Jordan, Steve; Miller, Michael R.; Luikart, Gordon; Weisrock, David W.

2018-01-01

AimClimate warming is causing extensive loss of glaciers in mountainous regions, yet our understanding of how glacial recession influences evolutionary processes and genetic diversity is limited. Linking genetic structure with the influences shaping it can improve understanding of how species respond to environmental change. Here, we used genome-scale data and demographic modelling to resolve the evolutionary history of Lednia tumana, a rare, aquatic insect endemic to alpine streams. We also employed a range of widely used data filtering approaches to quantify how they influenced population structure results.LocationAlpine streams in the Rocky Mountains of Glacier National Park, Montana, USA.TaxonLednia tumana, a stonefly (Order Plecoptera) in the family Nemouridae.MethodsWe generated single nucleotide polymorphism data through restriction-site associated DNA sequencing to assess contemporary patterns of genetic structure for 11 L. tumana populations. Using identified clusters, we assessed demographic history through model selection and parameter estimation in a coalescent framework. During population structure analyses, we filtered our data to assess the influence of singletons, missing data and total number of markers on results.ResultsContemporary patterns of population structure indicate that L. tumana exhibits a pattern of isolation-by-distance among populations within three genetic clusters that align with geography. Mean pairwise genetic differentiation (FST) among populations was 0.033. Coalescent-based demographic modelling supported divergence with gene flow among genetic clusters since the end of the Pleistocene (~13-17 kya), likely reflecting the south-to-north recession of ice sheets that accumulated during the Wisconsin glaciation.Main conclusionsWe identified a link between glacial retreat, evolutionary history and patterns of genetic diversity for a range-restricted stonefly imperiled by climate change. This finding included a history of divergence with gene flow, an unexpected conclusion for a mountaintop species. Beyond L. tumana, this study demonstrates the complexity of assessing genetic structure for weakly differentiated species, shows the degree to which rare alleles and missing data may influence results, and highlights the usefulness of genome-scale data to extend population genetic inquiry in non-model species.

Are species photosynthetic characteristics good predictors of seedling post-hurricane demographic patterns and species spatiotemporal distribution in a hurricane impacted wet montane forest?

NASA Astrophysics Data System (ADS)

Luke, Denneko; McLaren, Kurt

2018-05-01

In situ measurements of leaf level photosynthetic response to light were collected from seedlings of ten tree species from a tropical montane wet forest, the John Crow Mountains, Jamaica. A model-based recursive partitioning ('mob') algorithm was then used to identify species associations based on their fitted photosynthetic response curves. Leaf area dark respiration (RD) and light saturated maximum photosynthetic (Amax) rates were also used as 'mob' partitioning variables, to identify species associations based on seedling demographic patterns (from June 2007 to May 2010) following a hurricane (Aug. 2007) and the spatiotemporal distribution patterns of stems in 2006 and 2012. RD and Amax rates ranged from 1.14 to 2.02 μmol (CO2) m-2s-1 and 2.97-5.87 μmol (CO2) m-2s-1, respectively, placing the ten species in the range of intermediate shade tolerance. Several parsimonious species 'mob' groups were formed based on 1) interspecific differences among species response curves, 2) variations in post-hurricane seedling demographic trends and 3) RD rates and species spatiotemporal distribution patterns at aspects that are more or less exposed to hurricanes. The composition of parsimonious groupings based on photosynthetic curves was not concordant with the groups based on demographic trends but was partially concordant with the RD - species spatiotemporal distribution groups. Our results indicated that the influence of photosynthetic characteristics on demographic traits and species distributions was not straightforward. Rather, there was a complex pattern of interaction between ecophysiological and demographic traits, which determined species successional status, post-hurricane response and ultimately, species distribution at our study site.

A Life-Cycle Model of Human Social Groups Produces a U-Shaped Distribution in Group Size.

PubMed

Salali, Gul Deniz; Whitehouse, Harvey; Hochberg, Michael E

2015-01-01

One of the central puzzles in the study of sociocultural evolution is how and why transitions from small-scale human groups to large-scale, hierarchically more complex ones occurred. Here we develop a spatially explicit agent-based model as a first step towards understanding the ecological dynamics of small and large-scale human groups. By analogy with the interactions between single-celled and multicellular organisms, we build a theory of group lifecycles as an emergent property of single cell demographic and expansion behaviours. We find that once the transition from small-scale to large-scale groups occurs, a few large-scale groups continue expanding while small-scale groups gradually become scarcer, and large-scale groups become larger in size and fewer in number over time. Demographic and expansion behaviours of groups are largely influenced by the distribution and availability of resources. Our results conform to a pattern of human political change in which religions and nation states come to be represented by a few large units and many smaller ones. Future enhancements of the model should include decision-making rules and probabilities of fragmentation for large-scale societies. We suggest that the synthesis of population ecology and social evolution will generate increasingly plausible models of human group dynamics.

A Life-Cycle Model of Human Social Groups Produces a U-Shaped Distribution in Group Size

PubMed Central

Salali, Gul Deniz; Whitehouse, Harvey; Hochberg, Michael E.

2015-01-01

One of the central puzzles in the study of sociocultural evolution is how and why transitions from small-scale human groups to large-scale, hierarchically more complex ones occurred. Here we develop a spatially explicit agent-based model as a first step towards understanding the ecological dynamics of small and large-scale human groups. By analogy with the interactions between single-celled and multicellular organisms, we build a theory of group lifecycles as an emergent property of single cell demographic and expansion behaviours. We find that once the transition from small-scale to large-scale groups occurs, a few large-scale groups continue expanding while small-scale groups gradually become scarcer, and large-scale groups become larger in size and fewer in number over time. Demographic and expansion behaviours of groups are largely influenced by the distribution and availability of resources. Our results conform to a pattern of human political change in which religions and nation states come to be represented by a few large units and many smaller ones. Future enhancements of the model should include decision-making rules and probabilities of fragmentation for large-scale societies. We suggest that the synthesis of population ecology and social evolution will generate increasingly plausible models of human group dynamics. PMID:26381745

Land Use Change on Household Farms in the Ecuadorian Amazon: Design and Implementation of an Agent-Based Model

PubMed Central

Mena, Carlos F.; Walsh, Stephen J.; Frizzelle, Brian G.; Xiaozheng, Yao; Malanson, George P.

2010-01-01

This paper describes the design and implementation of an Agent-Based Model (ABM) used to simulate land use change on household farms in the Northern Ecuadorian Amazon (NEA). The ABM simulates decision-making processes at the household level that is examined through a longitudinal, socio-economic and demographic survey that was conducted in 1990 and 1999. Geographic Information Systems (GIS) are used to establish spatial relationships between farms and their environment, while classified Landsat Thematic Mapper (TM) imagery is used to set initial land use/land cover conditions for the spatial simulation, assess from-to land use/land cover change patterns, and describe trajectories of land use change at the farm and landscape levels. Results from prior studies in the NEA provide insights into the key social and ecological variables, describe human behavioral functions, and examine population-environment interactions that are linked to deforestation and agricultural extensification, population migration, and demographic change. Within the architecture of the model, agents are classified as active or passive. The model comprises four modules, i.e., initialization, demography, agriculture, and migration that operate individually, but are linked through key household processes. The main outputs of the model include a spatially-explicit representation of the land use/land cover on survey and non-survey farms and at the landscape level for each annual time-step, as well as simulated socio-economic and demographic characteristics of households and communities. The work describes the design and implementation of the model and how population-environment interactions can be addressed in a frontier setting. The paper contributes to land change science by examining important pattern-process relations, advocating a spatial modeling approach that is capable of synthesizing fundamental relationships at the farm level, and links people and environment in complex ways. PMID:24436501

Population modeling and its role in toxicological studies

USGS Publications Warehouse

Sauer, John R.; Pendleton, Grey W.; Hoffman, David J.; Rattner, Barnett A.; Burton, G. Allen; Cairns, John

1995-01-01

A model could be defined as any abstraction from reality that is used to provide some insight into the real system. In this discussion, we will use a more specific definition that a model is a set of rules or assumptions, expressed as mathematical equations, that describe how animals survive and reproduce, including the external factors that affect these characteristics. A model simplifies a system, retaining essential components while eliminating parts that are not of interest. ecology has a rich history of using models to gain insight into populations, often borrowing both model structures and analysis methods from demographers and engineers. Much of the development of the models has been a consequence of mathematicians and physicists seeing simple analogies between their models and patterns in natural systems. Consequently, one major application of ecological modeling has been to emphasize the analysis of dynamics of often complex models to provide insight into theoretical aspects of ecology.1

Demographic, genetic and phenotypic characteristics of centenarians in Italy: Focus on gender differences.

PubMed

Montesanto, Alberto; De Rango, Francesco; Pirazzini, Chiara; Guidarelli, Giulia; Domma, Filippo; Franceschi, Claudio; Passarino, Giuseppe

2017-07-01

An impressive and coherent series of epidemiological data from different populations (New England Americans, Mormons, Ashkenazi Jewish, Icelandic, Okinawan Japanese, Italians) suggests that long-lived subjects able to reach the extreme limits of human life, such as centenarians and supercentenarians, represent an extraordinary and informative model to identify the mechanisms responsible for healthy aging and human longevity. In most studies, genetic, demographic and phenotypic characteristics of longevity are discussed separately. However, longevity is a very complex trait due to the complicated interactions of numerous genetic and environmental factors. It is therefore necessary to analyse centenarians with a multidimensional approach, trying to consider different aspects simultaneously. In this review we will focus on Italian centenarians, who have been extensively studied for many years with different approaches, in order to show their peculiarities and the emerging data from the studies carried out on this exceptional population. Copyright © 2017 Elsevier B.V. All rights reserved.

Maternal Factors Predicting Cognitive and Behavioral Characteristics of Children with Fetal Alcohol Spectrum Disorders

PubMed Central

May, Philip A.; Tabachnick, Barbara G.; Gossage, J. Phillip; Kalberg, Wendy O.; Marais, Anna-Susan; Robinson, Luther K.; Manning, Melanie A.; Blankenship, Jason; Buckley, David; Hoyme, H. Eugene; Adnams, Colleen M.

2013-01-01

Objective To provide an analysis of multiple predictors of cognitive and behavioral traits for children with fetal alcohol spectrum disorders (FASD). Method Multivariate correlation techniques were employed with maternal and child data from epidemiologic studies in a community in South Africa. Data on 561 first grade children with fetal alcohol syndrome (FAS), partial FAS (PFAS), and not FASD and their mothers were analyzed by grouping 19 maternal variables into categories (physical, demographic, childbearing, and drinking) and employed in structural equation models (SEM) to assess correlates of child intelligence (verbal and non-verbal) and behavior. Results A first SEM utilizing only seven maternal alcohol use variables to predict cognitive/behavioral traits was statistically significant (B = 3.10, p < .05), but explained only 17.3% of the variance. The second model incorporated multiple maternal variables and was statistically significant explaining 55.3% of the variance. Significantly correlated with low intelligence and problem behavior were demographic (B = 3.83, p < .05) (low maternal education, low socioeconomic status (SES), and rural residence) and maternal physical characteristics (B = 2.70, p < .05) (short stature, small head circumference, and low weight). Childbearing history and alcohol use composites were not statistically significant in the final complex model, and were overpowered by SES and maternal physical traits. Conclusions While other analytic techniques have amply demonstrated the negative effects of maternal drinking on intelligence and behavior, this highly-controlled analysis of multiple maternal influences reveals that maternal demographics and physical traits make a significant enabling or disabling contribution to child functioning in FASD. PMID:23751886

Modeling of Wildlife-Associated Zoonoses: Applications and Caveats

PubMed Central

Lewis, Bryan L.; Marathe, Madhav; Eubank, Stephen; Blackburn, Jason K.

2012-01-01

Abstract Wildlife species are identified as an important source of emerging zoonotic disease. Accordingly, public health programs have attempted to expand in scope to include a greater focus on wildlife and its role in zoonotic disease outbreaks. Zoonotic disease transmission dynamics involving wildlife are complex and nonlinear, presenting a number of challenges. First, empirical characterization of wildlife host species and pathogen systems are often lacking, and insight into one system may have little application to another involving the same host species and pathogen. Pathogen transmission characterization is difficult due to the changing nature of population size and density associated with wildlife hosts. Infectious disease itself may influence wildlife population demographics through compensatory responses that may evolve, such as decreased age to reproduction. Furthermore, wildlife reservoir dynamics can be complex, involving various host species and populations that may vary in their contribution to pathogen transmission and persistence over space and time. Mathematical models can provide an important tool to engage these complex systems, and there is an urgent need for increased computational focus on the coupled dynamics that underlie pathogen spillover at the human–wildlife interface. Often, however, scientists conducting empirical studies on emerging zoonotic disease do not have the necessary skill base to choose, develop, and apply models to evaluate these complex systems. How do modeling frameworks differ and what considerations are important when applying modeling tools to the study of zoonotic disease? Using zoonotic disease examples, we provide an overview of several common approaches and general considerations important in the modeling of wildlife-associated zoonoses. PMID:23199265

Modeling individual effects in the Cormack-Jolly-Seber Model: A state-space formulation

USGS Publications Warehouse

Royle, J. Andrew

2008-01-01

In population and evolutionary biology, there exists considerable interest in individual heterogeneity in parameters of demographic models for open populations. However, flexible and practical solutions to the development of such models have proven to be elusive. In this article, I provide a state-space formulation of open population capture-recapture models with individual effects. The state-space formulation provides a generic and flexible framework for modeling and inference in models with individual effects, and it yields a practical means of estimation in these complex problems via contemporary methods of Markov chain Monte Carlo. A straightforward implementation can be achieved in the software package WinBUGS. I provide an analysis of a simple model with constant parameter detection and survival probability parameters. A second example is based on data from a 7-year study of European dippers, in which a model with year and individual effects is fitted.

Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations.

PubMed

Dinov, Ivo D; Heavner, Ben; Tang, Ming; Glusman, Gustavo; Chard, Kyle; Darcy, Mike; Madduri, Ravi; Pa, Judy; Spino, Cathie; Kesselman, Carl; Foster, Ian; Deutsch, Eric W; Price, Nathan D; Van Horn, John D; Ames, Joseph; Clark, Kristi; Hood, Leroy; Hampstead, Benjamin M; Dauer, William; Toga, Arthur W

2016-01-01

A unique archive of Big Data on Parkinson's Disease is collected, managed and disseminated by the Parkinson's Progression Markers Initiative (PPMI). The integration of such complex and heterogeneous Big Data from multiple sources offers unparalleled opportunities to study the early stages of prevalent neurodegenerative processes, track their progression and quickly identify the efficacies of alternative treatments. Many previous human and animal studies have examined the relationship of Parkinson's disease (PD) risk to trauma, genetics, environment, co-morbidities, or life style. The defining characteristics of Big Data-large size, incongruency, incompleteness, complexity, multiplicity of scales, and heterogeneity of information-generating sources-all pose challenges to the classical techniques for data management, processing, visualization and interpretation. We propose, implement, test and validate complementary model-based and model-free approaches for PD classification and prediction. To explore PD risk using Big Data methodology, we jointly processed complex PPMI imaging, genetics, clinical and demographic data. Collective representation of the multi-source data facilitates the aggregation and harmonization of complex data elements. This enables joint modeling of the complete data, leading to the development of Big Data analytics, predictive synthesis, and statistical validation. Using heterogeneous PPMI data, we developed a comprehensive protocol for end-to-end data characterization, manipulation, processing, cleaning, analysis and validation. Specifically, we (i) introduce methods for rebalancing imbalanced cohorts, (ii) utilize a wide spectrum of classification methods to generate consistent and powerful phenotypic predictions, and (iii) generate reproducible machine-learning based classification that enables the reporting of model parameters and diagnostic forecasting based on new data. We evaluated several complementary model-based predictive approaches, which failed to generate accurate and reliable diagnostic predictions. However, the results of several machine-learning based classification methods indicated significant power to predict Parkinson's disease in the PPMI subjects (consistent accuracy, sensitivity, and specificity exceeding 96%, confirmed using statistical n-fold cross-validation). Clinical (e.g., Unified Parkinson's Disease Rating Scale (UPDRS) scores), demographic (e.g., age), genetics (e.g., rs34637584, chr12), and derived neuroimaging biomarker (e.g., cerebellum shape index) data all contributed to the predictive analytics and diagnostic forecasting. Model-free Big Data machine learning-based classification methods (e.g., adaptive boosting, support vector machines) can outperform model-based techniques in terms of predictive precision and reliability (e.g., forecasting patient diagnosis). We observed that statistical rebalancing of cohort sizes yields better discrimination of group differences, specifically for predictive analytics based on heterogeneous and incomplete PPMI data. UPDRS scores play a critical role in predicting diagnosis, which is expected based on the clinical definition of Parkinson's disease. Even without longitudinal UPDRS data, however, the accuracy of model-free machine learning based classification is over 80%. The methods, software and protocols developed here are openly shared and can be employed to study other neurodegenerative disorders (e.g., Alzheimer's, Huntington's, amyotrophic lateral sclerosis), as well as for other predictive Big Data analytics applications.

Exploiting temporal variability to understand tree recruitment response to climate change

Treesearch

Ines Ibanez; James S. Clark; Shannon LaDeau; Janneke Hill Ris Lambers

2007-01-01

Predicting vegetation shifts under climate change is a challenging endeavor, given the complex interactions between biotic and abiotic variables that influence demographic rates. To determine how current trends and variation in climate change affect seedling establishment, we analyzed demographic responses to spatiotemporal variation to temperature and soil moisture in...

Space-time correlations in urban sprawl.

PubMed

Hernando, A; Hernando, R; Plastino, A

2014-02-06

Understanding demographic and migrational patterns constitutes a great challenge. Millions of individual decisions, motivated by economic, political, demographic, rational and/or emotional reasons underlie the high complexity of demographic dynamics. Significant advances in quantitatively understanding such complexity have been registered in recent years, as those involving the growth of cities but many fundamental issues still defy comprehension. We present here compelling empirical evidence of a high level of regularity regarding time and spatial correlations in urban sprawl, unravelling patterns about the inertia in the growth of cities and their interaction with each other. By using one of the world's most exhaustive extant demographic data basis--that of the Spanish Government's Institute INE, with records covering 111 years and (in 2011) 45 million people, distributed among more than 8000 population nuclei--we show that the inertia of city growth has a characteristic time of 15 years, and its interaction with the growth of other cities has a characteristic distance of 80 km. Distance is shown to be the main factor that entangles two cities (60% of total correlations). The power of our current social theories is thereby enhanced.

Medical Transport of Children with Complex Chronic Conditions

PubMed Central

Lerner, Carlos F.; Kelly, Robert B.; Hamilton, Leslie J.; Klitzner, Thomas S.

2012-01-01

One of the most notable trends in child health has been the increase in the number of children with special health care needs, including those with complex chronic conditions. Care of these children accounts for a growing fraction of health care resources. We examine recent developments in health care, especially with regard to medical transport and prehospital care, that have emerged to adapt to this remarkable demographic trend. One such development is the focus on care coordination, including the dissemination of the patient-centered medical home concept. In the prehospital setting, the need for greater coordination has catalyzed the development of the emergency information form. Training programs for prehospital providers now incorporate specific modules for children with complex conditions. Another notable trend is the shift to a family-centered model of care. We explore efforts toward regionalization of care, including the development of specialized pediatric transport teams, and conclude with recommendations for a research agenda. PMID:22315689

Associations among multiple markers and complex disease: models, algorithms, and applications.

PubMed

Assimes, Themistocles L; Olshen, Adam B; Narasimhan, Balasubramanian; Olshen, Richard A

2008-01-01

This chapter is a report on collaborations among its authors and others over many years. It devolves from our goal of understanding genes, their main and epistatic effects combined with interactions involving demographic and environmental features also, as together they predict genetically complex diseases. Thus, our goal is "association." Particular phenotypes of interest to us are hypertension, insulin resistance, angina, and myocardial infarction. Prediction of complex disease is notoriously difficult, though it would be made easier were we given strand-specific information on genotype. Unfortunately, with current technology, genotypic information comes to us "unphased." While obviously we have strand-specific information when genotype is homozygous, we do not have such information when genotype is heterozygous. To summarize, the ultimate goals of approaches we provide is to predict phenotype, typically untoward or not, within a specific window of time. Our approach is neither through linkage nor from finding haplotype frequencies per se.

Addressing the conundrum of multimorbidity in heart failure: Do we need a more strategic approach to improve health outcomes?

PubMed

Stewart, Simon; Riegel, Barbara; Thompson, David R

2016-02-01

There is clear evidence across the globe that the clinical complexity of patients presenting to hospital with the syndrome of heart failure is increasing - not only in terms of the presence of concurrent disease states, but with additional socio-demographic risk factors that complicate treatment. Management strategies that treat heart failure as the main determinant of health outcomes ignores the multiple and complex issues that will inevitably erode the efficacy and efficiency of current heart failure management programmes. This complex problem (or conundrum) requires a different way of thinking around the complex interactions that underpin poor outcomes in heart failure. In this context, we present the COordinated NUrse-led inteNsified Disease management for continuity of caRe for mUltiMorbidity in Heart Failure (CONUNDRUM-HF) matrix that may well inform future research and models of care to achieve better health outcomes in this rapidly increasing patient population. © The European Society of Cardiology 2015.

DEMOGRAPHIC UNCERTAINTY IN ECOLOGICAL RISK ASSESSMENTS. (R825347)

EPA Science Inventory

We built a Ricker's model incorporating demographic stochasticity to simulate the effects of demographic uncertainty on responses of gray-tailed vole (Microtus canicaudus) populations to pesticide applications. We constructed models with mark-recapture data collected from populat...

Evaluation of habitat suitability models for forest passerines using demographic data

Treesearch

Chadwick D. Rittenhouse; Frank R., III Thompson; William D. Dijak; Joshua J. Millspaugh; Richard L. Clawson

2010-01-01

Habitat suitability is often used as a surrogate for demographic responses (i.e., abundance, survival, fecundity, or population viability) in the application of habitat suitability index (HSI) models. Whether habitat suitability actually relates to demographics, however, has rarely been evaluated. We validated HSI models of breeding habitat suitability for wood thrush...

A population model for a long-lived, resprouting chaparral shrub: Adenostoma fasciculatum

USGS Publications Warehouse

Stohlgren, Thomas J.; Rundel, Philip W.

1986-01-01

Extensive stands of Adenostoma fasciculatum H.&A. (chamise) in the chaparral of California are periodically rejuvenated by fire. A population model based on size-specific demographic characteristics (thinning and fire-caused mortality) was developed to generate probable age distributions within size classes and survivorship curves for typical stands. The model was modified to assess the long term effects of different mortality rates on age distributions. Under observed mean mortality rates (28.7%), model output suggests some shrubs can survive more than 23 fires. A 10% increase in mortality rate by size class slightly shortened the survivorship curve, while a 10% decrease in mortality rate by size class greatly elongated the curve. This approach may be applicable to other long-lived plant species with complex life histories.

Generative Models of Segregation: Investigating Model-Generated Patterns of Residential Segregation by Ethnicity and Socioeconomic Status

PubMed Central

Fossett, Mark

2011-01-01

This paper considers the potential for using agent models to explore theories of residential segregation in urban areas. Results of generative experiments conducted using an agent-based simulation of segregation dynamics document that varying a small number of model parameters representing constructs from urban-ecological theories of segregation can generate a wide range of qualitatively distinct and substantively interesting segregation patterns. The results suggest how complex, macro-level patterns of residential segregation can arise from a small set of simple micro-level social dynamics operating within particular urban-demographic contexts. The promise and current limitations of agent simulation studies are noted and optimism is expressed regarding the potential for such studies to engage and contribute to the broader research literature on residential segregation. PMID:21379372

Investigating European genetic history through computer simulations.

PubMed

Currat, Mathias; Silva, Nuno M

2013-01-01

The genetic diversity of Europeans has been shaped by various evolutionary forces including their demographic history. Genetic data can thus be used to draw inferences on the population history of Europe using appropriate statistical methods such as computer simulation, which constitutes a powerful tool to study complex models. Here, we focus on spatially explicit simulation, a method which takes population movements over space and time into account. We present its main principles and then describe a series of studies using this approach that we consider as particularly significant in the context of European prehistory. All simulation studies agree that ancient demographic events played a significant role in the establishment of the European gene pool; but while earlier works support a major genetic input from the Near East during the Neolithic transition, the most recent ones revalue positively the contribution of pre-Neolithic hunter-gatherers and suggest a possible impact of very ancient demographic events. This result of a substantial genetic continuity from pre-Neolithic times to the present challenges some recent studies analyzing ancient DNA. We discuss the possible reasons for this discrepancy and identify future lines of investigation in order to get a better understanding of European evolution.

Local extinction and recolonization, species effective population size, and modern human origins.

PubMed

Eller, Elise; Hawks, John; Relethford, John H

2004-10-01

A primary objection from a population genetics perspective to a multiregional model of modern human origins is that the model posits a large census size, whereas genetic data suggest a small effective population size. The relationship between census size and effective size is complex, but arguments based on an island model of migration show that if the effective population size reflects the number of breeding individuals and the effects of population subdivision, then an effective population size of 10,000 is inconsistent with the census size of 500,000 to 1,000,000 that has been suggested by archeological evidence. However, these models have ignored the effects of population extinction and recolonization, which increase the expected variance among demes and reduce the inbreeding effective population size. Using models developed for population extinction and recolonization, we show that a large census size consistent with the multiregional model can be reconciled with an effective population size of 10,000, but genetic variation among demes must be high, reflecting low interdeme migration rates and a colonization process that involves a small number of colonists or kin-structured colonization. Ethnographic and archeological evidence is insufficient to determine whether such demographic conditions existed among Pleistocene human populations, and further work needs to be done. More realistic models that incorporate isolation by distance and heterogeneity in extinction rates and effective deme sizes also need to be developed. However, if true, a process of population extinction and recolonization has interesting implications for human demographic history.

Modeling and predicting community responses to events using cultural demographics

NASA Astrophysics Data System (ADS)

Jaenisch, Holger M.; Handley, James W.; Hicklen, Michael L.

2007-04-01

This paper describes a novel capability for modeling and predicting community responses to events (specifically military operations) related to demographics. Demographics in the form of words and/or numbers are used. As an example, State of Alabama annual demographic data for retail sales, auto registration, wholesale trade, shopping goods, and population were used; from which we determined a ranked estimate of the sensitivity of the demographic parameters on the cultural group response. Our algorithm and results are summarized in this paper.

Spatial variability of the effect of air pollution on term birth weight: evaluating influential factors using Bayesian hierarchical models.

PubMed

Li, Lianfa; Laurent, Olivier; Wu, Jun

2016-02-05

Epidemiological studies suggest that air pollution is adversely associated with pregnancy outcomes. Such associations may be modified by spatially-varying factors including socio-demographic characteristics, land-use patterns and unaccounted exposures. Yet, few studies have systematically investigated the impact of these factors on spatial variability of the air pollution's effects. This study aimed to examine spatial variability of the effects of air pollution on term birth weight across Census tracts and the influence of tract-level factors on such variability. We obtained over 900,000 birth records from 2001 to 2008 in Los Angeles County, California, USA. Air pollution exposure was modeled at individual level for nitrogen dioxide (NO2) and nitrogen oxides (NOx) using spatiotemporal models. Two-stage Bayesian hierarchical non-linear models were developed to (1) quantify the associations between air pollution exposure and term birth weight within each tract; and (2) examine the socio-demographic, land-use, and exposure-related factors contributing to the between-tract variability of the associations between air pollution and term birth weight. Higher air pollution exposure was associated with lower term birth weight (average posterior effects: -14.7 (95 % CI: -19.8, -9.7) g per 10 ppb increment in NO2 and -6.9 (95 % CI: -12.9, -0.9) g per 10 ppb increment in NOx). The variation of the association across Census tracts was significantly influenced by the tract-level socio-demographic, exposure-related and land-use factors. Our models captured the complex non-linear relationship between these factors and the associations between air pollution and term birth weight: we observed the thresholds from which the influence of the tract-level factors was markedly exacerbated or attenuated. Exacerbating factors might reflect additional exposure to environmental insults or lower socio-economic status with higher vulnerability, whereas attenuating factors might indicate reduced exposure or higher socioeconomic status with lower vulnerability. Our Bayesian models effectively combined a priori knowledge with training data to infer the posterior association of air pollution with term birth weight and to evaluate the influence of the tract-level factors on spatial variability of such association. This study contributes new findings about non-linear influences of socio-demographic factors, land-use patterns, and unaccounted exposures on spatial variability of the effects of air pollution.

Florida coastal ecological characterization: a socioeconomic study of the southwestern region. Volume I. Text

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

French, C.O.; Parsons, J.W.

1983-08-01

Data are compiled from existing sources on the social and economic characteristics of the southwestern coastal region of Florida, which is made up of Charlotte, Collier, DeSoto, Hillsborough, Lee, Manatee, Monroe, Pasco, Pinellas, and Sarasota Counties. Described are the components and interrelationships among complex processes that include population and demographics characteristics, mineral production, multiple-use conflicts, recreation and tourism, agricultural production, sport and commercial fishing, transportation, industrial and residential development, and environmental issues and regulations. Energetics models of socioeconomic systems are also presented. 43 figures, 98 tables.

Analysis of in vitro fertilization data with multiple outcomes using discrete time-to-event analysis

PubMed Central

Maity, Arnab; Williams, Paige; Ryan, Louise; Missmer, Stacey; Coull, Brent; Hauser, Russ

2014-01-01

In vitro fertilization (IVF) is an increasingly common method of assisted reproductive technology. Because of the careful observation and followup required as part of the procedure, IVF studies provide an ideal opportunity to identify and assess clinical and demographic factors along with environmental exposures that may impact successful reproduction. A major challenge in analyzing data from IVF studies is handling the complexity and multiplicity of outcome, resulting from both multiple opportunities for pregnancy loss within a single IVF cycle in addition to multiple IVF cycles. To date, most evaluations of IVF studies do not make use of full data due to its complex structure. In this paper, we develop statistical methodology for analysis of IVF data with multiple cycles and possibly multiple failure types observed for each individual. We develop a general analysis framework based on a generalized linear modeling formulation that allows implementation of various types of models including shared frailty models, failure specific frailty models, and transitional models, using standard software. We apply our methodology to data from an IVF study conducted at the Brigham and Women’s Hospital, Massachusetts. We also summarize the performance of our proposed methods based on a simulation study. PMID:24317880

Socio-Demographic and Practice-Oriented Factors Related to Proficiency in Problem Solving: A Lifelong Learning Perspective

ERIC Educational Resources Information Center

Desjardins, Richard; Ederer, Peer

2015-01-01

This article explores the relative importance of different socio-demographic and practice-oriented factors that are related to proficiency in problem solving in technology-rich environments (PSTREs) and by extension may be related to complex problem solving (CPS). The empirical analysis focuses on the proficiency measurements of PSTRE made…

[Integration of demographic variables into development plans in the Sahel].

PubMed

Wane, H R

1992-07-01

A founding principle of the Program of Action of N'Djamena is the interdependence of population and development and the need for development strategies to take demographic factors into account. The concept of integration of population variables into development has evolved since its introduction in the 1974 World Population Plan of Action from a simple description of population size, growth rates, and distribution to a stress on harmonizing population policies and development policies with macroeconomic variables. The essence of the concept is the consideration given by development policies and programs to the interrelations between population, resources, the environment, and development factors. Population variables and goals should ideally be treated as endogenous variables in development planning, but in practice the extreme complexity of such a systematic approach limits its ability to be made operational. Usually the most crucial problems only are included. Integrated planning is composed of explicit or implicit population policies intended to influence demographic variables and of socioeconomic policies intended to adapt to demographic change. In the Sahel, only Senegal, Burkina Faso, and Mali have formal population policies, but around 1980 several countries of the region began to show interest in influencing demographic variables as they did economic variables. Fundamental principles for developing an integration strategy can be applied regardless or whether the plan is based on projections, analysis of interaction of a demographic variable with factors specific to a sector, or a monosectorial or multisectorial demoeconomic planning model. Demographic data is used more frequently in diagnosing problems than in developing projections or formulating objectives. The level of disaggregation of demographic projections and estimates tends to be low, despite the great potential utility of demographic projections in planning. Demographic projections can be useful in analyses of the extent of changes and the implications of alternative scenarios of development planning. The most frequently used demographic variables in development planning have been spatial distribution of the population and mortality. An examination of past development plans in Mali relating to population and nutrition and population and health reveals several inconsistencies between stated goals and strategies intended to achieve them. The incoherence can be explained in part by the absence of a coherent national population policy, the failure to translate the population policy into programs that take into account reciprocal effects of demographic trends and economic perspectives and their social effects, and the absence of disaggregated population projections. An example from Senegal demonstrates the constraints imposed by structural adjustment programs on the entire planning process.

COST VS. QUALITY IN DEMOGRAPHIC MODELLING: WHEN IS A VITAL RATE GOOD ENOUGH?

EPA Science Inventory

This presentation will focus on the assessment of quality for demographic parameters to be used in population-level risk assessment. Current population models can handle genetic, demographic, and environmental stochasticity, density dependence, and multiple stressors. However, cu...

Geosimulation of urban growth and demographic decline in the Ruhr: a case study for 2025 using the artificial intelligence of cells and agents

NASA Astrophysics Data System (ADS)

Rienow, Andreas; Stenger, Dirk

2014-07-01

The Ruhr is an "old acquaintance" in the discourse of urban decline in old industrialized cities. The agglomeration has to struggle with archetypical problems of former monofunctional manufacturing cities. Surprisingly, the image of a shrinking city has to be refuted if you shift the focus from socioeconomic wealth to its morphological extension. Thus, it is the objective of this study to meet the challenge of modeling urban sprawl and demographic decline by combining two artificial intelligent solutions: The popular urban cellular automaton SLEUTH simulates urban growth using four simple but effective growth rules. In order to improve its performance, SLEUTH has been modified among others by combining it with a robust probability map based on support vector machines. Additionally, a complex multi-agent system is developed to simulate residential mobility in a shrinking city agglomeration: residential mobility and the housing market of shrinking city systems focuses on the dynamic of interregional housing markets implying the development of potential dwelling areas. The multi-agent system comprises the simulation of population patterns, housing prices, and housing demand in shrinking city agglomerations. Both models are calibrated and validated regarding their localization and quantification performance. Subsequently, the urban landscape configuration and composition of the Ruhr 2025 are simulated. A simple spatial join is used to combine the results serving as valuable inputs for future regional planning in the context of multifarious demographic change and preceding urban growth.

Genetic Heterogeneity in Algerian Human Populations

PubMed Central

Deba, Tahria; Calafell, Francesc; Benhamamouch, Soraya; Comas, David

2015-01-01

The demographic history of human populations in North Africa has been characterized by complex processes of admixture and isolation that have modeled its current gene pool. Diverse genetic ancestral components with different origins (autochthonous, European, Middle Eastern, and sub-Saharan) and genetic heterogeneity in the region have been described. In this complex genetic landscape, Algeria, the largest country in Africa, has been poorly covered, with most of the studies using a single Algerian sample. In order to evaluate the genetic heterogeneity of Algeria, Y-chromosome, mtDNA and autosomal genome-wide makers have been analyzed in several Berber- and Arab-speaking groups. Our results show that the genetic heterogeneity found in Algeria is not correlated with geography or linguistics, challenging the idea of Berber groups being genetically isolated and Arab groups open to gene flow. In addition, we have found that external sources of gene flow into North Africa have been carried more often by females than males, while the North African autochthonous component is more frequent in paternally transmitted genome regions. Our results highlight the different demographic history revealed by different markers and urge to be cautious when deriving general conclusions from partial genomic information or from single samples as representatives of the total population of a region. PMID:26402429

Statistical and Biophysical Models for Predicting Total and Outdoor Water Use in Los Angeles

NASA Astrophysics Data System (ADS)

Mini, C.; Hogue, T. S.; Pincetl, S.

2012-04-01

Modeling water demand is a complex exercise in the choice of the functional form, techniques and variables to integrate in the model. The goal of the current research is to identify the determinants that control total and outdoor residential water use in semi-arid cities and to utilize that information in the development of statistical and biophysical models that can forecast spatial and temporal urban water use. The City of Los Angeles is unique in its highly diverse socio-demographic, economic and cultural characteristics across neighborhoods, which introduces significant challenges in modeling water use. Increasing climate variability also contributes to uncertainties in water use predictions in urban areas. Monthly individual water use records were acquired from the Los Angeles Department of Water and Power (LADWP) for the 2000 to 2010 period. Study predictors of residential water use include socio-demographic, economic, climate and landscaping variables at the zip code level collected from US Census database. Climate variables are estimated from ground-based observations and calculated at the centroid of each zip code by inverse-distance weighting method. Remotely-sensed products of vegetation biomass and landscape land cover are also utilized. Two linear regression models were developed based on the panel data and variables described: a pooled-OLS regression model and a linear mixed effects model. Both models show income per capita and the percentage of landscape areas in each zip code as being statistically significant predictors. The pooled-OLS model tends to over-estimate higher water use zip codes and both models provide similar RMSE values.Outdoor water use was estimated at the census tract level as the residual between total water use and indoor use. This residual is being compared with the output from a biophysical model including tree and grass cover areas, climate variables and estimates of evapotranspiration at very high spatial resolution. A genetic algorithm based model (Shuffled Complex Evolution-UA; SCE-UA) is also being developed to provide estimates of the predictions and parameters uncertainties and to compare against the linear regression models. Ultimately, models will be selected to undertake predictions for a range of climate change and landscape scenarios. Finally, project results will contribute to a better understanding of water demand to help predict future water use and implement targeted landscaping conservation programs to maintain sustainable water needs for a growing population under uncertain climate variability.

Metamodels for Transdisciplinary Analysis of Wildlife Population Dynamics

PubMed Central

Lacy, Robert C.; Miller, Philip S.; Nyhus, Philip J.; Pollak, J. P.; Raboy, Becky E.; Zeigler, Sara L.

2013-01-01

Wildlife population models have been criticized for their narrow disciplinary perspective when analyzing complexity in coupled biological – physical – human systems. We describe a “metamodel” approach to species risk assessment when diverse threats act at different spatiotemporal scales, interact in non-linear ways, and are addressed by distinct disciplines. A metamodel links discrete, individual models that depict components of a complex system, governing the flow of information among models and the sequence of simulated events. Each model simulates processes specific to its disciplinary realm while being informed of changes in other metamodel components by accessing common descriptors of the system, populations, and individuals. Interactions among models are revealed as emergent properties of the system. We introduce a new metamodel platform, both to further explain key elements of the metamodel approach and as an example that we hope will facilitate the development of other platforms for implementing metamodels in population biology, species risk assessments, and conservation planning. We present two examples – one exploring the interactions of dispersal in metapopulations and the spread of infectious disease, the other examining predator-prey dynamics – to illustrate how metamodels can reveal complex processes and unexpected patterns when population dynamics are linked to additional extrinsic factors. Metamodels provide a flexible, extensible method for expanding population viability analyses beyond models of isolated population demographics into more complete representations of the external and intrinsic threats that must be understood and managed for species conservation. PMID:24349567

Evaluating mechanisms of diversification in a Guineo-Congolian tropical forest frog using demographic model selection.

PubMed

Portik, Daniel M; Leaché, Adam D; Rivera, Danielle; Barej, Michael F; Burger, Marius; Hirschfeld, Mareike; Rödel, Mark-Oliver; Blackburn, David C; Fujita, Matthew K

2017-10-01

The accumulation of biodiversity in tropical forests can occur through multiple allopatric and parapatric models of diversification, including forest refugia, riverine barriers and ecological gradients. Considerable debate surrounds the major diversification process, particularly in the West African Lower Guinea forests, which contain a complex geographic arrangement of topographic features and historical refugia. We used genomic data to investigate alternative mechanisms of diversification in the Gaboon forest frog, Scotobleps gabonicus, by first identifying population structure and then performing demographic model selection and spatially explicit analyses. We found that a majority of population divergences are best explained by allopatric models consistent with the forest refugia hypothesis and involve divergence in isolation with subsequent expansion and gene flow. These population divergences occurred simultaneously and conform to predictions based on climatically stable regions inferred through ecological niche modelling. Although forest refugia played a prominent role in the intraspecific diversification of S. gabonicus, we also find evidence for potential interactions between landscape features and historical refugia, including major rivers and elevational barriers such as the Cameroonian Volcanic Line. We outline the advantages of using genomewide variation in a model-testing framework to distinguish between alternative allopatric hypotheses, and the pitfalls of limited geographic and molecular sampling. Although phylogeographic patterns are often species-specific and related to life-history traits, additional comparative studies incorporating genomic data are necessary for separating shared historical processes from idiosyncratic responses to environmental, climatic and geological influences on diversification. © 2017 John Wiley & Sons Ltd.

Correlates of pain symptoms among Iraq and Afghanistan military personnel following combat-related blast exposure.

PubMed

Stratton, Kelcey J; Hawn, Sage E; Amstadter, Ananda B; Cifu, David X; Walker, William C

2014-01-01

Pain complaints are highly prevalent among military servicemembers and Veterans of the recent combat operations in Iraq and Afghanistan. The high comorbidity of pain with conditions such as posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) underscores the importance of a greater understanding of factors associated with complex polytraumatic injuries among military personnel. The present study aimed to identify correlates of current pain among 201 U.S. military personnel who reported at least one blast experience during combat deployment (age [mean +/– standard deviation]: 27.20 +/– 7.58 yr). Theoretically derived subsets of variables were analyzed in successive hierarchical regression models to determine correlates of self-reported pain symptoms. Preliminary models evaluated demographic features, medical and injury characteristics (e.g., TBI classification), psychosocial history (e.g., trauma exposure), and psychiatric variables. A final model was then derived, in which older age, possible or probable mild TBI, depression symptoms, and PTSD re-experiencing symptoms emerged as significant correlates of pain. The findings further the understanding of polytrauma symptoms among military personnel by identifying specific patient characteristics and comorbidity patterns related to pain complaints. Increased awareness of demographic, psychiatric, or medical factors implicated in pain will enhance comprehensive clinical assessment and intervention efforts.

Patterns of Nucleotide Diversity at Photoperiod Related Genes in Norway Spruce [Picea abies (L.) Karst.

PubMed Central

Källman, Thomas; De Mita, Stéphane; Larsson, Hanna; Gyllenstrand, Niclas; Heuertz, Myriam; Parducci, Laura; Suyama, Yoshihisa; Lagercrantz, Ulf; Lascoux, Martin

2014-01-01

The ability of plants to track seasonal changes is largely dependent on genes assigned to the photoperiod pathway, and variation in those genes is thereby important for adaptation to local day length conditions. Extensive physiological data in several temperate conifer species suggest that populations are adapted to local light conditions, but data on the genes underlying this adaptation are more limited. Here we present nucleotide diversity data from 19 genes putatively involved in photoperiodic response in Norway spruce (Picea abies). Based on similarity to model plants the genes were grouped into three categories according to their presumed position in the photoperiod pathway: photoreceptors, circadian clock genes, and downstream targets. An HKA (Hudson, Kreitman and Aquade) test showed a significant excess of diversity at photoreceptor genes, but no departure from neutrality at circadian genes and downstream targets. Departures from neutrality were also tested with Tajima's D and Fay and Wu's H statistics under three demographic scenarios: the standard neutral model, a population expansion model, and a more complex population split model. Only one gene, the circadian clock gene PaPRR3 with a highly positive Tajima's D value, deviates significantly from all tested demographic scenarios. As the PaPRR3 gene harbours multiple non-synonymous variants it appears as an excellent candidate gene for control of photoperiod response in Norway spruce. PMID:24810273

Patterns of nucleotide diversity at photoperiod related genes in Norway spruce [Picea abies (L.) Karst].

PubMed

Källman, Thomas; De Mita, Stéphane; Larsson, Hanna; Gyllenstrand, Niclas; Heuertz, Myriam; Parducci, Laura; Suyama, Yoshihisa; Lagercrantz, Ulf; Lascoux, Martin

2014-01-01

The ability of plants to track seasonal changes is largely dependent on genes assigned to the photoperiod pathway, and variation in those genes is thereby important for adaptation to local day length conditions. Extensive physiological data in several temperate conifer species suggest that populations are adapted to local light conditions, but data on the genes underlying this adaptation are more limited. Here we present nucleotide diversity data from 19 genes putatively involved in photoperiodic response in Norway spruce (Picea abies). Based on similarity to model plants the genes were grouped into three categories according to their presumed position in the photoperiod pathway: photoreceptors, circadian clock genes, and downstream targets. An HKA (Hudson, Kreitman and Aquade) test showed a significant excess of diversity at photoreceptor genes, but no departure from neutrality at circadian genes and downstream targets. Departures from neutrality were also tested with Tajima's D and Fay and Wu's H statistics under three demographic scenarios: the standard neutral model, a population expansion model, and a more complex population split model. Only one gene, the circadian clock gene PaPRR3 with a highly positive Tajima's D value, deviates significantly from all tested demographic scenarios. As the PaPRR3 gene harbours multiple non-synonymous variants it appears as an excellent candidate gene for control of photoperiod response in Norway spruce.

Unconditional or Conditional Logistic Regression Model for Age-Matched Case-Control Data?

PubMed

Kuo, Chia-Ling; Duan, Yinghui; Grady, James

2018-01-01

Matching on demographic variables is commonly used in case-control studies to adjust for confounding at the design stage. There is a presumption that matched data need to be analyzed by matched methods. Conditional logistic regression has become a standard for matched case-control data to tackle the sparse data problem. The sparse data problem, however, may not be a concern for loose-matching data when the matching between cases and controls is not unique, and one case can be matched to other controls without substantially changing the association. Data matched on a few demographic variables are clearly loose-matching data, and we hypothesize that unconditional logistic regression is a proper method to perform. To address the hypothesis, we compare unconditional and conditional logistic regression models by precision in estimates and hypothesis testing using simulated matched case-control data. Our results support our hypothesis; however, the unconditional model is not as robust as the conditional model to the matching distortion that the matching process not only makes cases and controls similar for matching variables but also for the exposure status. When the study design involves other complex features or the computational burden is high, matching in loose-matching data can be ignored for negligible loss in testing and estimation if the distributions of matching variables are not extremely different between cases and controls.

Unconditional or Conditional Logistic Regression Model for Age-Matched Case–Control Data?

PubMed Central

Kuo, Chia-Ling; Duan, Yinghui; Grady, James

2018-01-01

Matching on demographic variables is commonly used in case–control studies to adjust for confounding at the design stage. There is a presumption that matched data need to be analyzed by matched methods. Conditional logistic regression has become a standard for matched case–control data to tackle the sparse data problem. The sparse data problem, however, may not be a concern for loose-matching data when the matching between cases and controls is not unique, and one case can be matched to other controls without substantially changing the association. Data matched on a few demographic variables are clearly loose-matching data, and we hypothesize that unconditional logistic regression is a proper method to perform. To address the hypothesis, we compare unconditional and conditional logistic regression models by precision in estimates and hypothesis testing using simulated matched case–control data. Our results support our hypothesis; however, the unconditional model is not as robust as the conditional model to the matching distortion that the matching process not only makes cases and controls similar for matching variables but also for the exposure status. When the study design involves other complex features or the computational burden is high, matching in loose-matching data can be ignored for negligible loss in testing and estimation if the distributions of matching variables are not extremely different between cases and controls. PMID:29552553

Statistical inference on genetic data reveals the complex demographic history of human populations in central Asia.

PubMed

Palstra, Friso P; Heyer, Evelyne; Austerlitz, Frédéric

2015-06-01

The demographic history of modern humans constitutes a combination of expansions, colonizations, contractions, and remigrations. The advent of large scale genetic data combined with statistically refined methods facilitates inference of this complex history. Here we study the demographic history of two genetically admixed ethnic groups in Central Asia, an area characterized by high levels of genetic diversity and a history of recurrent immigration. Using Approximate Bayesian Computation, we infer that the timing of admixture markedly differs between the two groups. Admixture in the traditionally agricultural Tajiks could be dated back to the onset of the Neolithic transition in the region, whereas admixture in Kyrgyz is more recent, and may have involved the westward movement of Turkic peoples. These results are confirmed by a coalescent method that fits an isolation-with-migration model to the genetic data, with both Central Asian groups having received gene flow from the extremities of Eurasia. Interestingly, our analyses also uncover signatures of gene flow from Eastern to Western Eurasia during Paleolithic times. In conclusion, the high genetic diversity currently observed in these two Central Asian peoples most likely reflects the effects of recurrent immigration that likely started before historical times. Conversely, conquests during historical times may have had a relatively limited genetic impact. These results emphasize the need for a better understanding of the genetic consequences of transmission of culture and technological innovations, as well as those of invasions and conquests. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Accelerating Wright–Fisher Forward Simulations on the Graphics Processing Unit

PubMed Central

Lawrie, David S.

2017-01-01

Forward Wright–Fisher simulations are powerful in their ability to model complex demography and selection scenarios, but suffer from slow execution on the Central Processor Unit (CPU), thus limiting their usefulness. However, the single-locus Wright–Fisher forward algorithm is exceedingly parallelizable, with many steps that are so-called “embarrassingly parallel,” consisting of a vast number of individual computations that are all independent of each other and thus capable of being performed concurrently. The rise of modern Graphics Processing Units (GPUs) and programming languages designed to leverage the inherent parallel nature of these processors have allowed researchers to dramatically speed up many programs that have such high arithmetic intensity and intrinsic concurrency. The presented GPU Optimized Wright–Fisher simulation, or “GO Fish” for short, can be used to simulate arbitrary selection and demographic scenarios while running over 250-fold faster than its serial counterpart on the CPU. Even modest GPU hardware can achieve an impressive speedup of over two orders of magnitude. With simulations so accelerated, one can not only do quick parametric bootstrapping of previously estimated parameters, but also use simulated results to calculate the likelihoods and summary statistics of demographic and selection models against real polymorphism data, all without restricting the demographic and selection scenarios that can be modeled or requiring approximations to the single-locus forward algorithm for efficiency. Further, as many of the parallel programming techniques used in this simulation can be applied to other computationally intensive algorithms important in population genetics, GO Fish serves as an exciting template for future research into accelerating computation in evolution. GO Fish is part of the Parallel PopGen Package available at: http://dl42.github.io/ParallelPopGen/. PMID:28768689

Demographic Faultlines: A Meta-Analysis of the Literature

ERIC Educational Resources Information Center

Thatcher, Sherry M. B.; Patel, Pankaj C.

2011-01-01

We propose and test a theoretical model focusing on antecedents and consequences of demographic faultlines. We also posit contingencies that affect overall team dynamics in the context of demographic faultlines, such as the study setting and performance measurement. Using meta-analysis structural equation modeling with a final data set consisting…

A Rehabilomics framework for personalized and translational rehabilitation research and care for individuals with disabilities: Perspectives and considerations for spinal cord injury

PubMed Central

Wagner, Amy K.

2014-01-01

Despite many people having similar clinical presentation, demographic factors, and clinical care, outcome can differ for those sustaining significant injury such as spinal cord injury (SCI) and traumatic brain injury (TBI). In addition to traditional demographic, social, and clinical factors, variability also may be attributable to innate (including genetic, transcriptomic proteomic, epigenetic) biological variation that individuals bring to recovery and their unique response to their care and environment. Technologies collectively called “-omics” enable simultaneous measurement of an enormous number of biomolecules that can capture many potential biological contributors to heterogeneity of injury/disease course and outcome. Due to the nature of injury and complex disease, and its associations with impairment, disability, and recovery, rehabilitation does not lend itself to a singular “protocolized” plan of therapy. Yet, by nature and by necessity, rehabilitation medicine operates as a functional model of “Personalized Care”. Thus, the challenge for successful programs of translational rehabilitation care and research is to identify viable approaches to examine broad populations, with varied impairments and functional limitations, and to identify effective treatment responses that incorporate personalized protocols to optimize functional recovery. The Rehabilomics framework is a translational model that provides an “-omics” overlay to the scientific study of rehabilitation processes and multidimensional outcomes. Rehabilomics research provides novel opportunities to evaluate the neurobiology of complex injury or chronic disease and can be used to examine methods and treatments for person-centered care among populations with disabilities. Exemplars for application in SCI and other neurorehabilitation populations are discussed. PMID:25029659

Sinks without borders: Snowshoe hare dynamics in a complex landscape

USGS Publications Warehouse

Griffin, Paul C.; Mills, L. Scott

2009-01-01

A full understanding of population dynamics of wide-ranging animals should account for the effects that movement and habitat use have on individual contributions to population growth or decline. Quantifying the per-capita, habitat-specific contribution to population growth can clarify the value of different patch types, and help to differentiate population sources from population sinks. Snowshoe hares, Lepus americanus, routinely use various habitat types in the landscapes they inhabit in the contiguous US, where managing forests for high snowshoe hare density is a priority for conservation of Canada lynx, Lynx canadensis. We estimated density and demographic rates via mark–recapture live trapping and radio-telemetry within four forest stand structure (FSS) types at three study areas within heterogeneous managed forests in western Montana. We found support for known fate survival models with time-varying individual covariates representing the proportion of locations in each of the FSS types, with survival rates decreasing as use of open young and open mature FSS types increased. The per-capita contribution to overall population growth increased with use of the dense mature or dense young FSS types and decreased with use of the open young or open mature FSS types, and relatively high levels of immigration appear to be necessary to sustain hares in the open FSS types. Our results support a conceptual model for snowshoe hares in the southern range in which sink habitats (open areas) prevent the buildup of high hare densities. More broadly, we use this system to develop a novel approach to quantify demographic sources and sinks for animals making routine movements through complex fragmented landscapes.

Functional status predicts acute care readmission in the traumatic spinal cord injury population.

PubMed

Huang, Donna; Slocum, Chloe; Silver, Julie K; Morgan, James W; Goldstein, Richard; Zafonte, Ross; Schneider, Jeffrey C

2018-03-29

Context/objective Acute care readmission has been identified as an important marker of healthcare quality. Most previous models assessing risk prediction of readmission incorporate variables for medical comorbidity. We hypothesized that functional status is a more robust predictor of readmission in the spinal cord injury population than medical comorbidities. Design Retrospective cross-sectional analysis. Setting Inpatient rehabilitation facilities, Uniform Data System for Medical Rehabilitation data from 2002 to 2012 Participants traumatic spinal cord injury patients. Outcome measures A logistic regression model for predicting acute care readmission based on demographic variables and functional status (Functional Model) was compared with models incorporating demographics, functional status, and medical comorbidities (Functional-Plus) or models including demographics and medical comorbidities (Demographic-Comorbidity). The primary outcomes were 3- and 30-day readmission, and the primary measure of model performance was the c-statistic. Results There were a total of 68,395 patients with 1,469 (2.15%) readmitted at 3 days and 7,081 (10.35%) readmitted at 30 days. The c-statistics for the Functional Model were 0.703 and 0.654 for 3 and 30 days. The Functional Model outperformed Demographic-Comorbidity models at 3 days (c-statistic difference: 0.066-0.096) and outperformed two of the three Demographic-Comorbidity models at 30 days (c-statistic difference: 0.029-0.056). The Functional-Plus models exhibited negligible improvements (0.002-0.010) in model performance compared to the Functional models. Conclusion Readmissions are used as a marker of hospital performance. Function-based readmission models in the spinal cord injury population outperform models incorporating medical comorbidities. Readmission risk models for this population would benefit from the inclusion of functional status.

Emerging migration flows in a changing climate in dryland Africa

NASA Astrophysics Data System (ADS)

Kniveton, Dominic R.; Smith, Christopher D.; Black, Richard

2012-06-01

Fears of the movement of large numbers of people as a result of changes in the environment were first voiced in the 1980s (ref. ). Nearly thirty years later the numbers likely to migrate as a result of the impacts of climate change are still, at best, guesswork. Owing to the high prevalence of rainfed agriculture, many livelihoods in sub-Saharan African drylands are particularly vulnerable to changes in climate. One commonly adopted response strategy used by populations to deal with the resulting livelihood stress is migration. Here, we use an agent-based model developed around the theory of planned behaviour to explore how climate and demographic change, defined by the ENSEMBLES project and the United Nations Statistics Division of the Department of Economic and Social Affairs, combine to influence migration within and from Burkina Faso. The emergent migration patterns modelled support framing the nexus of climate change and migration as a complex adaptive system. Using this conceptual framework, we show that the extent of climate-change-related migration is likely to be highly nonlinear and the extent of this nonlinearity is dependent on population growth; therefore supporting migration policy interventions based on both demographic and climate change adaptation.

A comparison of multiple behavior models in a simulation of the aftermath of an improvised nuclear detonation.

PubMed

Parikh, Nidhi; Hayatnagarkar, Harshal G; Beckman, Richard J; Marathe, Madhav V; Swarup, Samarth

2016-11-01

We describe a large-scale simulation of the aftermath of a hypothetical 10kT improvised nuclear detonation at ground level, near the White House in Washington DC. We take a synthetic information approach, where multiple data sets are combined to construct a synthesized representation of the population of the region with accurate demographics, as well as four infrastructures: transportation, healthcare, communication, and power. In this article, we focus on the model of agents and their behavior, which is represented using the options framework. Six different behavioral options are modeled: household reconstitution, evacuation, healthcare-seeking, worry, shelter-seeking, and aiding & assisting others. Agent decision-making takes into account their health status, information about family members, information about the event, and their local environment. We combine these behavioral options into five different behavior models of increasing complexity and do a number of simulations to compare the models.

A comparison of multiple behavior models in a simulation of the aftermath of an improvised nuclear detonation

PubMed Central

Parikh, Nidhi; Hayatnagarkar, Harshal G.; Beckman, Richard J.; Marathe, Madhav V.; Swarup, Samarth

2016-01-01

We describe a large-scale simulation of the aftermath of a hypothetical 10kT improvised nuclear detonation at ground level, near the White House in Washington DC. We take a synthetic information approach, where multiple data sets are combined to construct a synthesized representation of the population of the region with accurate demographics, as well as four infrastructures: transportation, healthcare, communication, and power. In this article, we focus on the model of agents and their behavior, which is represented using the options framework. Six different behavioral options are modeled: household reconstitution, evacuation, healthcare-seeking, worry, shelter-seeking, and aiding & assisting others. Agent decision-making takes into account their health status, information about family members, information about the event, and their local environment. We combine these behavioral options into five different behavior models of increasing complexity and do a number of simulations to compare the models. PMID:27909393

Critical elements of culturally competent communication in the medical encounter: a review and model.

PubMed

Teal, Cayla R; Street, Richard L

2009-02-01

Increasing the cultural competence of physicians is one means of responding to demographic changes in the USA, as well as reducing health disparities. However, in spite of the development and implementation of cultural competence training programs, little is known about the ways cultural competence manifests itself in medical encounters. This paper will present a model of culturally competent communication that offers a framework of studying cultural competence 'in action.' First, we describe four critical elements of culturally competent communication in the medical encounter--communication repertoire, situational awareness, adaptability, and knowledge about core cultural issues. We present a model of culturally competent physician communication that integrates existing frameworks for cultural competence in patient care with models of effective patient-centered communication. The culturally competent communication model includes five communication skills that are depicted as elements of a set in which acquisition of more skills corresponds to increasing complexity and culturally competent communication. The culturally competent communication model utilizes each of the four critical elements to fully develop each skill and apply increasingly sophisticated, contextually appropriate communication behaviors to engage with culturally different patients in complex interactions. It is designed to foster maximum physician sensitivity to cultural variation in patients as the foundation of physician-communication competence in interacting with patients.

Functional Status Outperforms Comorbidities as a Predictor of 30-Day Acute Care Readmissions in the Inpatient Rehabilitation Population.

PubMed

Shih, Shirley L; Zafonte, Ross; Bates, David W; Gerrard, Paul; Goldstein, Richard; Mix, Jacqueline; Niewczyk, Paulette; Greysen, S Ryan; Kazis, Lewis; Ryan, Colleen M; Schneider, Jeffrey C

2016-10-01

Functional status is associated with patient outcomes, but is rarely included in hospital readmission risk models. The objective of this study was to determine whether functional status is a better predictor of 30-day acute care readmission than traditionally investigated variables including demographics and comorbidities. Retrospective database analysis between 2002 and 2011. 1158 US inpatient rehabilitation facilities. 4,199,002 inpatient rehabilitation facility admissions comprising patients from 16 impairment groups within the Uniform Data System for Medical Rehabilitation database. Logistic regression models predicting 30-day readmission were developed based on age, gender, comorbidities (Elixhauser comorbidity index, Deyo-Charlson comorbidity index, and Medicare comorbidity tier system), and functional status [Functional Independence Measure (FIM)]. We hypothesized that (1) function-based models would outperform demographic- and comorbidity-based models and (2) the addition of demographic and comorbidity data would not significantly enhance function-based models. For each impairment group, Function Only Models were compared against Demographic-Comorbidity Models and Function Plus Models (Function-Demographic-Comorbidity Models). The primary outcome was 30-day readmission, and the primary measure of model performance was the c-statistic. All-cause 30-day readmission rate from inpatient rehabilitation facilities to acute care hospitals was 9.87%. C-statistics for the Function Only Models were 0.64 to 0.70. For all 16 impairment groups, the Function Only Model demonstrated better c-statistics than the Demographic-Comorbidity Models (c-statistic difference: 0.03-0.12). The best-performing Function Plus Models exhibited negligible improvements in model performance compared to Function Only Models, with c-statistic improvements of only 0.01 to 0.05. Readmissions are currently used as a marker of hospital performance, with recent financial penalties to hospitals for excessive readmissions. Function-based readmission models outperform models based only on demographics and comorbidities. Readmission risk models would benefit from the inclusion of functional status as a primary predictor. Copyright © 2016 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Predictive Big Data Analytics: A Study of Parkinson’s Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations

PubMed Central

Dinov, Ivo D.; Heavner, Ben; Tang, Ming; Glusman, Gustavo; Chard, Kyle; Darcy, Mike; Madduri, Ravi; Pa, Judy; Spino, Cathie; Kesselman, Carl; Foster, Ian; Deutsch, Eric W.; Price, Nathan D.; Van Horn, John D.; Ames, Joseph; Clark, Kristi; Hood, Leroy; Hampstead, Benjamin M.; Dauer, William; Toga, Arthur W.

2016-01-01

Background A unique archive of Big Data on Parkinson’s Disease is collected, managed and disseminated by the Parkinson’s Progression Markers Initiative (PPMI). The integration of such complex and heterogeneous Big Data from multiple sources offers unparalleled opportunities to study the early stages of prevalent neurodegenerative processes, track their progression and quickly identify the efficacies of alternative treatments. Many previous human and animal studies have examined the relationship of Parkinson’s disease (PD) risk to trauma, genetics, environment, co-morbidities, or life style. The defining characteristics of Big Data–large size, incongruency, incompleteness, complexity, multiplicity of scales, and heterogeneity of information-generating sources–all pose challenges to the classical techniques for data management, processing, visualization and interpretation. We propose, implement, test and validate complementary model-based and model-free approaches for PD classification and prediction. To explore PD risk using Big Data methodology, we jointly processed complex PPMI imaging, genetics, clinical and demographic data. Methods and Findings Collective representation of the multi-source data facilitates the aggregation and harmonization of complex data elements. This enables joint modeling of the complete data, leading to the development of Big Data analytics, predictive synthesis, and statistical validation. Using heterogeneous PPMI data, we developed a comprehensive protocol for end-to-end data characterization, manipulation, processing, cleaning, analysis and validation. Specifically, we (i) introduce methods for rebalancing imbalanced cohorts, (ii) utilize a wide spectrum of classification methods to generate consistent and powerful phenotypic predictions, and (iii) generate reproducible machine-learning based classification that enables the reporting of model parameters and diagnostic forecasting based on new data. We evaluated several complementary model-based predictive approaches, which failed to generate accurate and reliable diagnostic predictions. However, the results of several machine-learning based classification methods indicated significant power to predict Parkinson’s disease in the PPMI subjects (consistent accuracy, sensitivity, and specificity exceeding 96%, confirmed using statistical n-fold cross-validation). Clinical (e.g., Unified Parkinson's Disease Rating Scale (UPDRS) scores), demographic (e.g., age), genetics (e.g., rs34637584, chr12), and derived neuroimaging biomarker (e.g., cerebellum shape index) data all contributed to the predictive analytics and diagnostic forecasting. Conclusions Model-free Big Data machine learning-based classification methods (e.g., adaptive boosting, support vector machines) can outperform model-based techniques in terms of predictive precision and reliability (e.g., forecasting patient diagnosis). We observed that statistical rebalancing of cohort sizes yields better discrimination of group differences, specifically for predictive analytics based on heterogeneous and incomplete PPMI data. UPDRS scores play a critical role in predicting diagnosis, which is expected based on the clinical definition of Parkinson’s disease. Even without longitudinal UPDRS data, however, the accuracy of model-free machine learning based classification is over 80%. The methods, software and protocols developed here are openly shared and can be employed to study other neurodegenerative disorders (e.g., Alzheimer’s, Huntington’s, amyotrophic lateral sclerosis), as well as for other predictive Big Data analytics applications. PMID:27494614

Integrating data from multiple sources for insights into demographic processes: Simulation studies and proof of concept for hierarchical change-in-ratio models.

PubMed

Nilsen, Erlend B; Strand, Olav

2018-01-01

We developed a model for estimating demographic rates and population abundance based on multiple data sets revealing information about population age- and sex structure. Such models have previously been described in the literature as change-in-ratio models, but we extend the applicability of the models by i) using time series data allowing the full temporal dynamics to be modelled, by ii) casting the model in an explicit hierarchical modelling framework, and by iii) estimating parameters based on Bayesian inference. Based on sensitivity analyses we conclude that the approach developed here is able to obtain estimates of demographic rate with high precision whenever unbiased data of population structure are available. Our simulations revealed that this was true also when data on population abundance are not available or not included in the modelling framework. Nevertheless, when data on population structure are biased due to different observability of different age- and sex categories this will affect estimates of all demographic rates. Estimates of population size is particularly sensitive to such biases, whereas demographic rates can be relatively precisely estimated even with biased observation data as long as the bias is not severe. We then use the models to estimate demographic rates and population abundance for two Norwegian reindeer (Rangifer tarandus) populations where age-sex data were available for all harvested animals, and where population structure surveys were carried out in early summer (after calving) and late fall (after hunting season), and population size is counted in winter. We found that demographic rates were similar regardless whether we include population count data in the modelling, but that the estimated population size is affected by this decision. This suggest that monitoring programs that focus on population age- and sex structure will benefit from collecting additional data that allow estimation of observability for different age- and sex classes. In addition, our sensitivity analysis suggests that focusing monitoring towards changes in demographic rates might be more feasible than monitoring abundance in many situations where data on population age- and sex structure can be collected.

Shifting Quaternary migration patterns in the Bahamian archipelago: Evidence from the Zamia pumila complex at the northern limits of the Caribbean island biodiversity hotspot.

PubMed

Salas-Leiva, Dayana E; Meerow, Alan W; Calonje, Michael; Francisco-Ortega, Javier; Griffith, M Patrick; Nakamura, Kyoko; Sánchez, Vanessa; Knowles, Lindy; Knowles, David

2017-05-01

The Bahamas archipelago is formed by young, tectonically stable carbonate banks that harbor direct geological evidence of global ice-volume changes. We sought to detect signatures of major changes on gene flow patterns and reconstruct the phylogeographic history of the monophyletic Zamia pumila complex across the Bahamas. Nuclear molecular markers with both high and low mutation rates were used to capture two different time scale signatures and test several gene flow and demographic hypotheses. Single-copy nuclear genes unveiled apparent ancestral admixture on Andros, suggesting a significant role of this island as main hub of diversity of the archipelago. We detected demographic and spatial expansion of the Zamia pumila complex on both paleo-provinces around the Piacenzian (Pliocene)/Gelasian (Pleistocene). Populations evidenced signatures of different migration models that have occurred at two different times. Populations on Long Island ( Z. lucayana ) may either represent a secondary colonization of the Bahamas by Zamia or a rapid and early-divergence event of at least one population on the Bahamas. Despite changes in migration patterns with global climate, expected heterozygosity with both marker systems remains within the range reported for cycads, but with significant levels of increased inbreeding detected by the microsatellites. This finding is likely associated with reduced gene flow between and within paleo-provinces, accompanied by genetic drift, as rising seas enforced isolation. Our study highlights the importance of the maintenance of the predominant direction of genetic exchange and the role of overseas dispersion among the islands during climate oscillations. © 2017 Botanical Society of America.

The Brainomics/Localizer database.

PubMed

Papadopoulos Orfanos, Dimitri; Michel, Vincent; Schwartz, Yannick; Pinel, Philippe; Moreno, Antonio; Le Bihan, Denis; Frouin, Vincent

2017-01-01

The Brainomics/Localizer database exposes part of the data collected by the in-house Localizer project, which planned to acquire four types of data from volunteer research subjects: anatomical MRI scans, functional MRI data, behavioral and demographic data, and DNA sampling. Over the years, this local project has been collecting such data from hundreds of subjects. We had selected 94 of these subjects for their complete datasets, including all four types of data, as the basis for a prior publication; the Brainomics/Localizer database publishes the data associated with these 94 subjects. Since regulatory rules prevent us from making genetic data available for download, the database serves only anatomical MRI scans, functional MRI data, behavioral and demographic data. To publish this set of heterogeneous data, we use dedicated software based on the open-source CubicWeb semantic web framework. Through genericity in the data model and flexibility in the display of data (web pages, CSV, JSON, XML), CubicWeb helps us expose these complex datasets in original and efficient ways. Copyright © 2015 Elsevier Inc. All rights reserved.

Climate Variability and Human Migration in the Netherlands, 1865–1937

PubMed Central

Jennings, Julia A.; Gray, Clark L.

2014-01-01

Human migration is frequently cited as a potential social outcome of climate change and variability, and these effects are often assumed to be stronger in the past when economies were less developed and markets more localized. Yet, few studies have used historical data to test the relationship between climate and migration directly. In addition, the results of recent studies that link demographic and climate data are not consistent with conventional narratives of displacement responses. Using longitudinal individual-level demographic data from the Historical Sample of the Netherlands (HSN) and climate data that cover the same period, we examine the effects of climate variability on migration using event history models. Only internal moves in the later period and for certain social groups are associated with negative climate conditions, and the strength and direction of the observed effects change over time. International moves decrease with extreme rainfall, suggesting that the complex relationships between climate and migration that have been observed for contemporary populations extend into the nineteenth century. PMID:25937689

Demographic consequences of climate change and land cover help explain a history of extirpations and range contraction in a declining snake species.

PubMed

Pomara, Lars Y; LeDee, Olivia E; Martin, Karl J; Zuckerberg, Benjamin

2014-07-01

Developing conservation strategies for threatened species increasingly requires understanding vulnerabilities to climate change, in terms of both demographic sensitivities to climatic and other environmental factors, and exposure to variability in those factors over time and space. We conducted a range-wide, spatially explicit climate change vulnerability assessment for Eastern Massasauga (Sistrurus catenatus), a declining endemic species in a region showing strong environmental change. Using active season and winter adult survival estimates derived from 17 data sets throughout the species' range, we identified demographic sensitivities to winter drought, maximum precipitation during the summer, and the proportion of the surrounding landscape dominated by agricultural and urban land cover. Each of these factors was negatively associated with active season adult survival rates in binomial generalized linear models. We then used these relationships to back-cast adult survival with dynamic climate variables from 1950 to 2008 using spatially explicit demographic models. Demographic models for 189 population locations predicted known extant and extirpated populations well (AUC = 0.75), and models based on climate and land cover variables were superior to models incorporating either of those effects independently. These results suggest that increasing frequencies and severities of extreme events, including drought and flooding, have been important drivers of the long-term spatiotemporal variation in a demographic rate. We provide evidence that this variation reflects nonadaptive sensitivity to climatic stressors, which are contributing to long-term demographic decline and range contraction for a species of high-conservation concern. Range-wide demographic modeling facilitated an understanding of spatial shifts in climatic suitability and exposure, allowing the identification of important climate refugia for a dispersal-limited species. Climate change vulnerability assessment provides a framework for linking demographic and distributional dynamics to environmental change, and can thereby provide unique information for conservation planning and management. © 2013 John Wiley & Sons Ltd.

Sources, Sinks, and Model Accuracy

EPA Science Inventory

Spatial demographic models are a necessary tool for understanding how to manage landscapes sustainably for animal populations. These models, therefore, must offer precise and testable predications about animal population dynamics and how animal demographic parameters respond to ...

Climate, not Aboriginal landscape burning, controlled the historical demography and distribution of fire-sensitive conifer populations across Australia

PubMed Central

Sakaguchi, Shota; Bowman, David M. J. S.; Prior, Lynda D.; Crisp, Michael D.; Linde, Celeste C.; Tsumura, Yoshihiko; Isagi, Yuji

2013-01-01

Climate and fire are the key environmental factors that shape the distribution and demography of plant populations in Australia. Because of limited palaeoecological records in this arid continent, however, it is unclear as to which factor impacted vegetation more strongly, and what were the roles of fire regime changes owing to human activity and megafaunal extinction (since ca 50 kya). To address these questions, we analysed historical genetic, demographic and distributional changes in a widespread conifer species complex that paradoxically grows in fire-prone regions, yet is very sensitive to fire. Genetic demographic analysis showed that the arid populations experienced strong bottlenecks, consistent with range contractions during the Last Glacial Maximum (ca 20 kya) predicted by species distribution models. In southern temperate regions, the population sizes were estimated to have been mostly stable, followed by some expansion coinciding with climate amelioration at the end of the last glacial period. By contrast, in the flammable tropical savannahs, where fire risk is the highest, demographic analysis failed to detect significant population bottlenecks. Collectively, these results suggest that the impact of climate change overwhelmed any modifications to fire regimes by Aboriginal landscape burning and megafaunal extinction, a finding that probably also applies to other fire-prone vegetation across Australia. PMID:24174110

Evaluation of the Use of Zero-Augmented Regression Techniques to Model Incidence of Campylobacter Infections in FoodNet.

PubMed

Tremblay, Marlène; Crim, Stacy M; Cole, Dana J; Hoekstra, Robert M; Henao, Olga L; Döpfer, Dörte

2017-10-01

The Foodborne Diseases Active Surveillance Network (FoodNet) is currently using a negative binomial (NB) regression model to estimate temporal changes in the incidence of Campylobacter infection. FoodNet active surveillance in 483 counties collected data on 40,212 Campylobacter cases between years 2004 and 2011. We explored models that disaggregated these data to allow us to account for demographic, geographic, and seasonal factors when examining changes in incidence of Campylobacter infection. We hypothesized that modeling structural zeros and including demographic variables would increase the fit of FoodNet's Campylobacter incidence regression models. Five different models were compared: NB without demographic covariates, NB with demographic covariates, hurdle NB with covariates in the count component only, hurdle NB with covariates in both zero and count components, and zero-inflated NB with covariates in the count component only. Of the models evaluated, the nonzero-augmented NB model with demographic variables provided the best fit. Results suggest that even though zero inflation was not present at this level, individualizing the level of aggregation and using different model structures and predictors per site might be required to correctly distinguish between structural and observational zeros and account for risk factors that vary geographically.

Rethinking the dispersal of Homo sapiens out of Africa.

PubMed

Groucutt, Huw S; Petraglia, Michael D; Bailey, Geoff; Scerri, Eleanor M L; Parton, Ash; Clark-Balzan, Laine; Jennings, Richard P; Lewis, Laura; Blinkhorn, James; Drake, Nick A; Breeze, Paul S; Inglis, Robyn H; Devès, Maud H; Meredith-Williams, Matthew; Boivin, Nicole; Thomas, Mark G; Scally, Aylwyn

2015-01-01

Current fossil, genetic, and archeological data indicate that Homo sapiens originated in Africa in the late Middle Pleistocene. By the end of the Late Pleistocene, our species was distributed across every continent except Antarctica, setting the foundations for the subsequent demographic and cultural changes of the Holocene. The intervening processes remain intensely debated and a key theme in hominin evolutionary studies. We review archeological, fossil, environmental, and genetic data to evaluate the current state of knowledge on the dispersal of Homo sapiens out of Africa. The emerging picture of the dispersal process suggests dynamic behavioral variability, complex interactions between populations, and an intricate genetic and cultural legacy. This evolutionary and historical complexity challenges simple narratives and suggests that hybrid models and the testing of explicit hypotheses are required to understand the expansion of Homo sapiens into Eurasia. © 2015 Wiley Periodicals, Inc.

A guide to calculating habitat-quality metrics to inform conservation of highly mobile species

USGS Publications Warehouse

Bieri, Joanna A.; Sample, Christine; Thogmartin, Wayne E.; Diffendorfer, James E.; Earl, Julia E.; Erickson, Richard A.; Federico, Paula; Flockhart, D. T. Tyler; Nicol, Sam; Semmens, Darius J.; Skraber, T.; Wiederholt, Ruscena; Mattsson, Brady J.

2018-01-01

Many metrics exist for quantifying the relative value of habitats and pathways used by highly mobile species. Properly selecting and applying such metrics requires substantial background in mathematics and understanding the relevant management arena. To address this multidimensional challenge, we demonstrate and compare three measurements of habitat quality: graph-, occupancy-, and demographic-based metrics. Each metric provides insights into system dynamics, at the expense of increasing amounts and complexity of data and models. Our descriptions and comparisons of diverse habitat-quality metrics provide means for practitioners to overcome the modeling challenges associated with management or conservation of such highly mobile species. Whereas previous guidance for applying habitat-quality metrics has been scattered in diversified tracks of literature, we have brought this information together into an approachable format including accessible descriptions and a modeling case study for a typical example that conservation professionals can adapt for their own decision contexts and focal populations.Considerations for Resource ManagersManagement objectives, proposed actions, data availability and quality, and model assumptions are all relevant considerations when applying and interpreting habitat-quality metrics.Graph-based metrics answer questions related to habitat centrality and connectivity, are suitable for populations with any movement pattern, quantify basic spatial and temporal patterns of occupancy and movement, and require the least data.Occupancy-based metrics answer questions about likelihood of persistence or colonization, are suitable for populations that undergo localized extinctions, quantify spatial and temporal patterns of occupancy and movement, and require a moderate amount of data.Demographic-based metrics answer questions about relative or absolute population size, are suitable for populations with any movement pattern, quantify demographic processes and population dynamics, and require the most data.More real-world examples applying occupancy-based, agent-based, and continuous-based metrics to seasonally migratory species are needed to better understand challenges and opportunities for applying these metrics more broadly.

Fall in homicides in the City of São Paulo: an exploratory analysis of possible determinants

PubMed Central

Peres, Maria Fernanda Tourinho; de Almeida, Juliana Feliciano; Vicentin, Diego; Cerda, Magdalena; Cardia, Nancy; Adorno, Sérgio

2012-01-01

Throughout the first decade of the 2000s the homicide mortality rate (HMR) showed a significant reduction in the state and the city of São Paulo (MSP). The aim of this study is to describe the trend of HMR, socio-demographic indicators, and the investment in social and public security, and to analyze the correlation between HMR and independent variables in the MSP between 1996 and 2008. An exploratory time series ecological study was conducted. The following variables were included: HMR per 100,000 inhabitants, socio-demographic indicators, and investments in social and public security. The moving-averages for all variables were calculated and trends were analyzed through Simple Linear Regression models. Annual percentage changes, the average annual change and periodic percentage changes were calculated for all variables, and the associations between annual percentage changes were tested by Spearman’s correlation analysis. Correlations were found for the proportion of youth in the population (r = 0.69), unemployment rate (r = 0.60), State budget for education and culture (r = 0.87) and health and sanitation (r = 0.56), municipal (r = 0.68) and State (r = 0.53) budget for Public Security, firearms seized (r = 0.69) and the incarceration rate (r = 0.71). The results allow us to support the hypothesis that demographic changes, acceleration of the economy, in particular the fall in unemployment, investment in social policies and changes in public security policies act synergistically to reduce HMR in São Paulo. Complex models of analysis, incorporating the joint action of different potential explanatory variables, should be developed. PMID:22218669

Hierarchical demographic approaches for assessing invasion dynamics of non-indigenous species: An example using northern snakehead (Channa argus)

USGS Publications Warehouse

Jiao, Y.; Lapointe, N.W.R.; Angermeier, P.L.; Murphy, B.R.

2009-01-01

Models of species' demographic features are commonly used to understand population dynamics and inform management tactics. Hierarchical demographic models are ideal for the assessment of non-indigenous species because our knowledge of non-indigenous populations is usually limited, data on demographic traits often come from a species' native range, these traits vary among populations, and traits are likely to vary considerably over time as species adapt to new environments. Hierarchical models readily incorporate this spatiotemporal variation in species' demographic traits by representing demographic parameters as multi-level hierarchies. As is done for traditional non-hierarchical matrix models, sensitivity and elasticity analyses are used to evaluate the contributions of different life stages and parameters to estimates of population growth rate. We applied a hierarchical model to northern snakehead (Channa argus), a fish currently invading the eastern United States. We used a Monte Carlo approach to simulate uncertainties in the sensitivity and elasticity analyses and to project future population persistence under selected management tactics. We gathered key biological information on northern snakehead natural mortality, maturity and recruitment in its native Asian environment. We compared the model performance with and without hierarchy of parameters. Our results suggest that ignoring the hierarchy of parameters in demographic models may result in poor estimates of population size and growth and may lead to erroneous management advice. In our case, the hierarchy used multi-level distributions to simulate the heterogeneity of demographic parameters across different locations or situations. The probability that the northern snakehead population will increase and harm the native fauna is considerable. Our elasticity and prognostic analyses showed that intensive control efforts immediately prior to spawning and/or juvenile-dispersal periods would be more effective (and probably require less effort) than year-round control efforts. Our study demonstrates the importance of considering the hierarchy of parameters in estimating population growth rate and evaluating different management strategies for non-indigenous invasive species. ?? 2009 Elsevier B.V.

Cleft lip with or without cleft palate in Shanghai, China: Evidence for an autosomal major locus

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

Marazita, M.L.; Hu, Dan-Ning; Liu, You-E.

1992-09-01

Orientals are at higher risk for cleft lip with our without cleft palate (CL[+-] P) than Caucasians or blacks. The authors collected demographic and family data to study factors contributing to the etiology of CL[+-]P in Shanghai. The birth incidence of nonsyndromic CL[+-]P (SHanghai 1980-87) was 1.11/1,000, with a male/female ratio of 1.42. Almost 2,000 nonsyndromic CL[+-]P probands were ascertained from individuals operated on during the years 1956-83 at surgical hospitals in Shanghai. Detailed family histories and medical examinations were obtained for the probands and all available family members. Genetic analysis of the probands' families were performed under the mixedmore » model with major locus (ML) and multifactorial (MFT) components. The hypothesis of no familial transmission and of MFT alone could be rejected. Of the ML models, the autosomal recessive was significantly most likely and was assumed for testing three complex hypothesis: (1) ML and sporadics; (2) ML and MFT; (3) ML, MFT, and sporadics. None of the complex models were more likely than the ML alone model. In conclusion, the best-fitting, most parsimonious model for CL[+-]P in Shanghai was that of an autosomal recessive major locus. 37 refs., 1 tab.« less

Level of Satisfaction of Older Persons with Their General Practitioner and Practice: Role of Complexity of Health Problems

PubMed Central

Poot, Antonius J.; den Elzen, Wendy P. J.; Blom, Jeanet W.; Gussekloo, Jacobijn

2014-01-01

Background Satisfaction is widely used to evaluate and direct delivery of medical care; a complicated relationship exists between patient satisfaction, morbidity and age. This study investigates the relationships between complexity of health problems and level of patient satisfaction of older persons with their general practitioner (GP) and practice. Methods and Findings This study is embedded in the ISCOPE (Integrated Systematic Care for Older Persons) study. Enlisted patients aged ≥75 years from 59 practices received a written questionnaire to screen for complex health problems (somatic, functional, psychological and social). For 2664 randomly chosen respondents (median age 82 years; 68% female) information was collected on level of satisfaction (satisfied, neutral, dissatisfied) with their GP and general practice, and demographic and clinical characteristics including complexity of health problems. Of all participants, 4% was dissatisfied with their GP care, 59% neutral and 37% satisfied. Between these three categories no differences were observed in age, gender, country of birth or education level. The percentage of participants dissatisfied with their GP care increased from 0.4% in those with 0 problem domains to 8% in those with 4 domains, i.e. having complex health problems (p<0.001). Per additional health domain with problems, the risk of being dissatisfied increased 1.7 times (95% CI 1.4–2.14; p<0.001). This was independent of age, gender, and demographic and clinical parameters (adjusted OR 1.4, 95% CI 1.1–1.8; p = 0.021). Conclusion In older persons, dissatisfaction with general practice is strongly correlated with rising complexity of health problems, independent of age, demographic and clinical parameters. It remains unclear whether complexity of health problems is a patient characteristic influencing the perception of care, or whether the care is unable to handle the demands of these patients. Prospective studies are needed to investigate the causal associations between care organization, patient characteristics, indicators of quality, and patient perceptions. PMID:24710557

Level of satisfaction of older persons with their general practitioner and practice: role of complexity of health problems.

PubMed

Poot, Antonius J; den Elzen, Wendy P J; Blom, Jeanet W; Gussekloo, Jacobijn

2014-01-01

Satisfaction is widely used to evaluate and direct delivery of medical care; a complicated relationship exists between patient satisfaction, morbidity and age. This study investigates the relationships between complexity of health problems and level of patient satisfaction of older persons with their general practitioner (GP) and practice. This study is embedded in the ISCOPE (Integrated Systematic Care for Older Persons) study. Enlisted patients aged ≥75 years from 59 practices received a written questionnaire to screen for complex health problems (somatic, functional, psychological and social). For 2664 randomly chosen respondents (median age 82 years; 68% female) information was collected on level of satisfaction (satisfied, neutral, dissatisfied) with their GP and general practice, and demographic and clinical characteristics including complexity of health problems. Of all participants, 4% was dissatisfied with their GP care, 59% neutral and 37% satisfied. Between these three categories no differences were observed in age, gender, country of birth or education level. The percentage of participants dissatisfied with their GP care increased from 0.4% in those with 0 problem domains to 8% in those with 4 domains, i.e. having complex health problems (p<0.001). Per additional health domain with problems, the risk of being dissatisfied increased 1.7 times (95% CI 1.4-2.14; p<0.001). This was independent of age, gender, and demographic and clinical parameters (adjusted OR 1.4, 95% CI 1.1-1.8; p = 0.021). In older persons, dissatisfaction with general practice is strongly correlated with rising complexity of health problems, independent of age, demographic and clinical parameters. It remains unclear whether complexity of health problems is a patient characteristic influencing the perception of care, or whether the care is unable to handle the demands of these patients. Prospective studies are needed to investigate the causal associations between care organization, patient characteristics, indicators of quality, and patient perceptions.

Role of demographic stochasticity in a speciation model with sexual reproduction

NASA Astrophysics Data System (ADS)

Lafuerza, Luis F.; McKane, Alan J.

2016-03-01

Recent theoretical studies have shown that demographic stochasticity can greatly increase the tendency of asexually reproducing phenotypically diverse organisms to spontaneously evolve into localized clusters, suggesting a simple mechanism for sympatric speciation. Here we study the role of demographic stochasticity in a model of competing organisms subject to assortative mating. We find that in models with sexual reproduction, noise can also lead to the formation of phenotypic clusters in parameter ranges where deterministic models would lead to a homogeneous distribution. In some cases, noise can have a sizable effect, rendering the deterministic modeling insufficient to understand the phenotypic distribution.

Influence of demographic changes on the impact of vaccination against varicella and herpes zoster in Germany - a mathematical modelling study.

PubMed

Horn, Johannes; Damm, Oliver; Greiner, Wolfgang; Hengel, Hartmut; Kretzschmar, Mirjam E; Siedler, Anette; Ultsch, Bernhard; Weidemann, Felix; Wichmann, Ole; Karch, André; Mikolajczyk, Rafael T

2018-01-09

Epidemiological studies suggest that reduced exposure to varicella might lead to an increased risk for herpes zoster (HZ). Reduction of exposure to varicella is a consequence of varicella vaccination but also of demographic changes. We analyzed how the combination of vaccination programs and demographic dynamics will affect the epidemiology of varicella and HZ in Germany over the next 50 years. We used a deterministic dynamic compartmental model to assess the impact of different varicella and HZ vaccination strategies on varicella and HZ epidemiology in three demographic scenarios, namely the projected population for Germany, the projected population additionally accounting for increased immigration as observed in 2015/2016, and a stationary population. Projected demographic changes alone result in an increase of annual HZ cases by 18.3% and a decrease of varicella cases by 45.7% between 1990 and 2060. Independently of the demographic scenario, varicella vaccination reduces the cumulative number of varicella cases until 2060 by approximately 70%, but also increases HZ cases by 10%. Unlike the currently licensed live attenuated HZ vaccine, the new subunit vaccine candidate might completely counteract this effect. Relative vaccine effects were consistent across all demographic scenarios. Demographic dynamics will be a major determinant of HZ epidemiology in the next 50 years. While stationary population models are appropriate for assessing vaccination impact, models incorporating realistic population structures allow a direct comparison to surveillance data and can thus provide additional input for immunization decision-making and resource planning.

Adaptive or Transactional Leadership in Current Higher Education: A Brief Comparison

ERIC Educational Resources Information Center

Khan, Natalie

2017-01-01

Higher education institutions operate in a complex environment that includes influence from external factors, new technologies for teaching and learning, globalization, and changing student demographics to name a few. Maneuvering such complexity and change requires a leadership strategy that is flexible and supportive. This paper reviews two…

Missed Policy Opportunities to Advance Health Equity by Recording Demographic Data in Electronic Health Records

PubMed Central

Dawes, Daniel E.; Holden, Kisha B.; Mack, Dominic

2015-01-01

The science of eliminating health disparities is complex and dependent on demographic data. The Health Information Technology for Economic and Clinical Health Act (HITECH) encourages the adoption of electronic health records and requires basic demographic data collection; however, current data generated are insufficient to address known health disparities in vulnerable populations, including individuals from diverse racial and ethnic backgrounds, with disabilities, and with diverse sexual identities. We conducted an administrative history of HITECH and identified gaps between the policy objective and required measure. We identified 20 opportunities for change and 5 changes, 2 of which required the collection of less data. Until health care demographic data collection requirements are consistent with public health requirements, the national goal of eliminating health disparities cannot be realized. PMID:25905840

Prototypes of Cognitive Measures for Air Force Officers: Test Development and Item Banking

DTIC Science & Technology

1990-05-01

with the complexity of the relationship. Relationships may be in terms of shape, size, dimensionality, area of embeddedness , rotation, blank/shaded...administration were used. Test directions were read from the booklet. Demographics and test responses were recorded on a machine-scannable answer sheet...as demographic information would be needed to determine whether sample characteristics accounted for the differences in mean scores for NC, FA, and WD

Modeling Relationships Between Flight Crew Demographics and Perceptions of Interval Management

NASA Technical Reports Server (NTRS)

Remy, Benjamin; Wilson, Sara R.

2016-01-01

The Interval Management Alternative Clearances (IMAC) human-in-the-loop simulation experiment was conducted to assess interval management system performance and participants' acceptability and workload while performing three interval management clearance types. Twenty-four subject pilots and eight subject controllers flew ten high-density arrival scenarios into Denver International Airport during two weeks of data collection. This analysis examined the possible relationships between subject pilot demographics on reported perceptions of interval management in IMAC. Multiple linear regression models were created with a new software tool to predict subject pilot questionnaire item responses from demographic information. General patterns were noted across models that may indicate flight crew demographics influence perceptions of interval management.

A dynamic auditory-cognitive system supports speech-in-noise perception in older adults

PubMed Central

Anderson, Samira; White-Schwoch, Travis; Parbery-Clark, Alexandra; Kraus, Nina

2013-01-01

Understanding speech in noise is one of the most complex activities encountered in everyday life, relying on peripheral hearing, central auditory processing, and cognition. These abilities decline with age, and so older adults are often frustrated by a reduced ability to communicate effectively in noisy environments. Many studies have examined these factors independently; in the last decade, however, the idea of the auditory-cognitive system has emerged, recognizing the need to consider the processing of complex sounds in the context of dynamic neural circuits. Here, we use structural equation modeling to evaluate interacting contributions of peripheral hearing, central processing, cognitive ability, and life experiences to understanding speech in noise. We recruited 120 older adults (ages 55 to 79) and evaluated their peripheral hearing status, cognitive skills, and central processing. We also collected demographic measures of life experiences, such as physical activity, intellectual engagement, and musical training. In our model, central processing and cognitive function predicted a significant proportion of variance in the ability to understand speech in noise. To a lesser extent, life experience predicted hearing-in-noise ability through modulation of brainstem function. Peripheral hearing levels did not significantly contribute to the model. Previous musical experience modulated the relative contributions of cognitive ability and lifestyle factors to hearing in noise. Our models demonstrate the complex interactions required to hear in noise and the importance of targeting cognitive function, lifestyle, and central auditory processing in the management of individuals who are having difficulty hearing in noise. PMID:23541911

Reconstructing Demography and Social Behavior During the Neolithic Expansion from Genomic Diversity Across Island Southeast Asia.

PubMed

Vallée, François; Luciani, Aurélien; Cox, Murray P

2016-12-01

Archaeology, linguistics, and increasingly genetics are clarifying how populations moved from mainland Asia, through Island Southeast Asia, and out into the Pacific during the farming revolution. Yet key features of this process remain poorly understood, particularly how social behaviors intersected with demographic drivers to create the patterns of genomic diversity observed across Island Southeast Asia today. Such questions are ripe for computer modeling. Here, we construct an agent-based model to simulate human mobility across Island Southeast Asia from the Neolithic period to the present, with a special focus on interactions between individuals with Asian, Papuan, and mixed Asian-Papuan ancestry. Incorporating key features of the region, including its complex geography (islands and sea), demographic drivers (fecundity and migration), and social behaviors (marriage preferences), the model simultaneously tracks a full suite of genomic markers (autosomes, X chromosome, mitochondrial DNA, and Y chromosome). Using Bayesian inference, model parameters were determined that produce simulations that closely resemble the admixture profiles of 2299 individuals from 84 populations across Island Southeast Asia. The results highlight that greater propensity to migrate and elevated birth rates are related drivers behind the expansion of individuals with Asian ancestry relative to individuals with Papuan ancestry, that offspring preferentially resulted from marriages between Asian women and Papuan men, and that in contrast to current thinking, individuals with Asian ancestry were likely distributed across large parts of western Island Southeast Asia before the Neolithic expansion. Copyright © 2016 Vallée et al.

Reconstructing Demography and Social Behavior During the Neolithic Expansion from Genomic Diversity Across Island Southeast Asia

PubMed Central

Vallée, François; Luciani, Aurélien; Cox, Murray P.

2016-01-01

Archaeology, linguistics, and increasingly genetics are clarifying how populations moved from mainland Asia, through Island Southeast Asia, and out into the Pacific during the farming revolution. Yet key features of this process remain poorly understood, particularly how social behaviors intersected with demographic drivers to create the patterns of genomic diversity observed across Island Southeast Asia today. Such questions are ripe for computer modeling. Here, we construct an agent-based model to simulate human mobility across Island Southeast Asia from the Neolithic period to the present, with a special focus on interactions between individuals with Asian, Papuan, and mixed Asian–Papuan ancestry. Incorporating key features of the region, including its complex geography (islands and sea), demographic drivers (fecundity and migration), and social behaviors (marriage preferences), the model simultaneously tracks a full suite of genomic markers (autosomes, X chromosome, mitochondrial DNA, and Y chromosome). Using Bayesian inference, model parameters were determined that produce simulations that closely resemble the admixture profiles of 2299 individuals from 84 populations across Island Southeast Asia. The results highlight that greater propensity to migrate and elevated birth rates are related drivers behind the expansion of individuals with Asian ancestry relative to individuals with Papuan ancestry, that offspring preferentially resulted from marriages between Asian women and Papuan men, and that in contrast to current thinking, individuals with Asian ancestry were likely distributed across large parts of western Island Southeast Asia before the Neolithic expansion. PMID:27683274

Whole-genome sequence analyses of Western Central African Pygmy hunter-gatherers reveal a complex demographic history and identify candidate genes under positive natural selection

PubMed Central

Hsieh, PingHsun; Veeramah, Krishna R.; Lachance, Joseph; Tishkoff, Sarah A.; Wall, Jeffrey D.; Hammer, Michael F.; Gutenkunst, Ryan N.

2016-01-01

African Pygmies practicing a mobile hunter-gatherer lifestyle are phenotypically and genetically diverged from other anatomically modern humans, and they likely experienced strong selective pressures due to their unique lifestyle in the Central African rainforest. To identify genomic targets of adaptation, we sequenced the genomes of four Biaka Pygmies from the Central African Republic and jointly analyzed these data with the genome sequences of three Baka Pygmies from Cameroon and nine Yoruba famers. To account for the complex demographic history of these populations that includes both isolation and gene flow, we fit models using the joint allele frequency spectrum and validated them using independent approaches. Our two best-fit models both suggest ancient divergence between the ancestors of the farmers and Pygmies, 90,000 or 150,000 yr ago. We also find that bidirectional asymmetric gene flow is statistically better supported than a single pulse of unidirectional gene flow from farmers to Pygmies, as previously suggested. We then applied complementary statistics to scan the genome for evidence of selective sweeps and polygenic selection. We found that conventional statistical outlier approaches were biased toward identifying candidates in regions of high mutation or low recombination rate. To avoid this bias, we assigned P-values for candidates using whole-genome simulations incorporating demography and variation in both recombination and mutation rates. We found that genes and gene sets involved in muscle development, bone synthesis, immunity, reproduction, cell signaling and development, and energy metabolism are likely to be targets of positive natural selection in Western African Pygmies or their recent ancestors. PMID:26888263

A framework for feature extraction from hospital medical data with applications in risk prediction.

PubMed

Tran, Truyen; Luo, Wei; Phung, Dinh; Gupta, Sunil; Rana, Santu; Kennedy, Richard Lee; Larkins, Ann; Venkatesh, Svetha

2014-12-30

Feature engineering is a time consuming component of predictive modeling. We propose a versatile platform to automatically extract features for risk prediction, based on a pre-defined and extensible entity schema. The extraction is independent of disease type or risk prediction task. We contrast auto-extracted features to baselines generated from the Elixhauser comorbidities. Hospital medical records was transformed to event sequences, to which filters were applied to extract feature sets capturing diversity in temporal scales and data types. The features were evaluated on a readmission prediction task, comparing with baseline feature sets generated from the Elixhauser comorbidities. The prediction model was through logistic regression with elastic net regularization. Predictions horizons of 1, 2, 3, 6, 12 months were considered for four diverse diseases: diabetes, COPD, mental disorders and pneumonia, with derivation and validation cohorts defined on non-overlapping data-collection periods. For unplanned readmissions, auto-extracted feature set using socio-demographic information and medical records, outperformed baselines derived from the socio-demographic information and Elixhauser comorbidities, over 20 settings (5 prediction horizons over 4 diseases). In particular over 30-day prediction, the AUCs are: COPD-baseline: 0.60 (95% CI: 0.57, 0.63), auto-extracted: 0.67 (0.64, 0.70); diabetes-baseline: 0.60 (0.58, 0.63), auto-extracted: 0.67 (0.64, 0.69); mental disorders-baseline: 0.57 (0.54, 0.60), auto-extracted: 0.69 (0.64,0.70); pneumonia-baseline: 0.61 (0.59, 0.63), auto-extracted: 0.70 (0.67, 0.72). The advantages of auto-extracted standard features from complex medical records, in a disease and task agnostic manner were demonstrated. Auto-extracted features have good predictive power over multiple time horizons. Such feature sets have potential to form the foundation of complex automated analytic tasks.

Spatial Self-Organization of Vegetation Subject to Climatic Stress-Insights from a System Dynamics-Individual-Based Hybrid Model.

PubMed

Vincenot, Christian E; Carteni, Fabrizio; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco

2016-01-01

In simulation models of populations or communities, individual plants have often been obfuscated in favor of aggregated vegetation. This simplification comes with a loss of biological detail and a smoothing out of the demographic noise engendered by stochastic individual-scale processes and heterogeneities, which is significant among others when studying the viability of small populations facing challenging fluctuating environmental conditions. This consideration has motivated the development of precise plant-centered models. The accuracy gained in the representation of plant biology has then, however, often been balanced by the disappearance in models of important plant-soil interactions (esp. water dynamics) due to the inability of most individual-based frameworks to simulate complex continuous processes. In this study, we used a hybrid modeling approach, namely integrated System Dynamics (SD)-Individual-based (IB), to illustrate the importance of individual plant dynamics to explain spatial self-organization of vegetation in arid environments. We analyzed the behavior of this model under different parameter sets either related to individual plant properties (such as seed dispersal distance and reproductive age) or the environment (such as intensity and yearly distribution of precipitation events). While the results of this work confirmed the prevailing theory on vegetation patterning, they also revealed the importance therein of plant-level processes that cannot be rendered by reaction-diffusion models. Initial spatial distribution of plants, reproductive age, and average seed dispersal distance, by impacting patch size and vegetation aggregation, affected pattern formation and population survival under climatic variations. Besides, changes in precipitation regime altered the demographic structure and spatial organization of vegetation patches by affecting plants differentially depending on their age and biomass. Water availability influenced non-linearly total biomass density. Remarkably, lower precipitation resulted in lower mean plant age yet higher mean individual biomass. Moreover, seasonal variations in rainfall greater than a threshold (here, ±0.45 mm from the 1.3 mm baseline) decreased mean total biomass and generated limit cycles, which, in the case of large variations, were preceded by chaotic demographic and spatial behavior. In some cases, peculiar spatial patterns (e.g., rings) were also engendered. On a technical note, the shortcomings of the present model and the benefit of hybrid modeling for virtual investigations in plant science are discussed.

Spatial Self-Organization of Vegetation Subject to Climatic Stress—Insights from a System Dynamics—Individual-Based Hybrid Model

PubMed Central

Vincenot, Christian E.; Carteni, Fabrizio; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco

2016-01-01

In simulation models of populations or communities, individual plants have often been obfuscated in favor of aggregated vegetation. This simplification comes with a loss of biological detail and a smoothing out of the demographic noise engendered by stochastic individual-scale processes and heterogeneities, which is significant among others when studying the viability of small populations facing challenging fluctuating environmental conditions. This consideration has motivated the development of precise plant-centered models. The accuracy gained in the representation of plant biology has then, however, often been balanced by the disappearance in models of important plant-soil interactions (esp. water dynamics) due to the inability of most individual-based frameworks to simulate complex continuous processes. In this study, we used a hybrid modeling approach, namely integrated System Dynamics (SD)—Individual-based (IB), to illustrate the importance of individual plant dynamics to explain spatial self-organization of vegetation in arid environments. We analyzed the behavior of this model under different parameter sets either related to individual plant properties (such as seed dispersal distance and reproductive age) or the environment (such as intensity and yearly distribution of precipitation events). While the results of this work confirmed the prevailing theory on vegetation patterning, they also revealed the importance therein of plant-level processes that cannot be rendered by reaction-diffusion models. Initial spatial distribution of plants, reproductive age, and average seed dispersal distance, by impacting patch size and vegetation aggregation, affected pattern formation and population survival under climatic variations. Besides, changes in precipitation regime altered the demographic structure and spatial organization of vegetation patches by affecting plants differentially depending on their age and biomass. Water availability influenced non-linearly total biomass density. Remarkably, lower precipitation resulted in lower mean plant age yet higher mean individual biomass. Moreover, seasonal variations in rainfall greater than a threshold (here, ±0.45 mm from the 1.3 mm baseline) decreased mean total biomass and generated limit cycles, which, in the case of large variations, were preceded by chaotic demographic and spatial behavior. In some cases, peculiar spatial patterns (e.g., rings) were also engendered. On a technical note, the shortcomings of the present model and the benefit of hybrid modeling for virtual investigations in plant science are discussed. PMID:27252707

Interregional migration in an extended input-output model.

PubMed

Madden, M; Trigg, A B

1990-01-01

"This article develops a two-region version of an extended input-output model that disaggregates consumption among employed, unemployed, and inmigrant households, and which explicitly models the influx into a region of migrants to take up a proportion of any jobs created in the regional economy. The model is empirically tested using real data for the Scotland (UK) regions of Strathclyde and Rest-of-Scotland. Sets of interregional economic, demographic, demo-economic, and econo-demographic multipliers are developed and discussed, and the effects of a range of economic and demographic impacts are modeled. The circumstances under which Hawkins-Simon conditions for non-negativity are breached are identified, and the limits of the model discussed." excerpt

Moving beyond Stylized Economic Network Models: The Hybrid World of the Indian Firm Ownership Network1

PubMed Central

Mani, Dalhia; Moody, James

2014-01-01

A central theme of economic sociology has been to highlight the complexity and diversity of real world markets, but many network models of economic social structure ignore this feature and rely instead on stylized one-dimensional characterizations. Here, the authors return to the basic insight of structural diversity in economic sociology. Using the Indian interorganizational ownership network as their case, they discover a composite—or “hybrid”—model of economic networks that combines elements of prior stylized models. The network contains a disconnected periphery conforming closely to a “transactional” model; a semiperiphery characterized by small, dense clusters with sporadic links, as predicted in “small-world” models; and finally a nested core composed of clusters connected via multiple independent paths. The authors then show how a firm’s position within the mesolevel structure is associated with demographic features such as age and industry and differences in the extent to which firms engage in multiplex and high-value exchanges. PMID:25418990

Socioeconomic Forecasting : [Technical Summary

DOT National Transportation Integrated Search

2012-01-01

Because the traffic forecasts produced by the Indiana : Statewide Travel Demand Model (ISTDM) are driven by : the demographic and socioeconomic inputs to the model, : particular attention must be given to obtaining the most : accurate demographic and...

Demographic and genetic viability of a medium-sized ground-dwelling mammal in a fire prone, rapidly urbanizing landscape.

PubMed

Ramalho, Cristina E; Ottewell, Kym M; Chambers, Brian K; Yates, Colin J; Wilson, Barbara A; Bencini, Roberta; Barrett, Geoff

2018-01-01

The rapid and large-scale urbanization of peri-urban areas poses major and complex challenges for wildlife conservation. We used population viability analysis (PVA) to evaluate the influence of urban encroachment, fire, and fauna crossing structures, with and without accounting for inbreeding effects, on the metapopulation viability of a medium-sized ground-dwelling mammal, the southern brown bandicoot (Isoodon obesulus), in the rapidly expanding city of Perth, Australia. We surveyed two metapopulations over one and a half years, and parameterized the PVA models using largely field-collected data. The models revealed that spatial isolation imposed by housing and road encroachment has major impacts on I. obesulus. Although the species is known to persist in small metapopulations at moderate levels of habitat fragmentation, the models indicate that these populations become highly vulnerable to demographic decline, genetic deterioration, and local extinction under increasing habitat connectivity loss. Isolated metapopulations were also predicted to be highly sensitive to fire, with large-scale fires having greater negative impacts on population abundance than small-scale ones. To reduce the risk of decline and local extirpation of I. obesulus and other small- to medium-sized ground-dwelling mammals in urbanizing, fire prone landscapes, we recommend that remnant vegetation and vegetated, structurally-complex corridors between habitat patches be retained. Well-designed road underpasses can be effective to connect habitat patches and reduce the probability of inbreeding and genetic differentiation; however, adjustment of fire management practices to limit the size of unplanned fires and ensure the retention of long unburnt vegetation will also be required to ensure persistence. Our study supports the evidence that in rapidly urbanizing landscapes, a pro-active conservation approach is required that manages species at the metapopulation level and that prioritizes metapopulations and habitat with greater long-term probability of persistence and conservation capacity, respectively. This strategy may help us prevent future declines and local extirpations, and currently relatively common species from becoming rare.

Demographic and genetic viability of a medium-sized ground-dwelling mammal in a fire prone, rapidly urbanizing landscape

PubMed Central

Ottewell, Kym M.; Chambers, Brian K.; Yates, Colin J.; Wilson, Barbara A.; Bencini, Roberta; Barrett, Geoff

2018-01-01

The rapid and large-scale urbanization of peri-urban areas poses major and complex challenges for wildlife conservation. We used population viability analysis (PVA) to evaluate the influence of urban encroachment, fire, and fauna crossing structures, with and without accounting for inbreeding effects, on the metapopulation viability of a medium-sized ground-dwelling mammal, the southern brown bandicoot (Isoodon obesulus), in the rapidly expanding city of Perth, Australia. We surveyed two metapopulations over one and a half years, and parameterized the PVA models using largely field-collected data. The models revealed that spatial isolation imposed by housing and road encroachment has major impacts on I. obesulus. Although the species is known to persist in small metapopulations at moderate levels of habitat fragmentation, the models indicate that these populations become highly vulnerable to demographic decline, genetic deterioration, and local extinction under increasing habitat connectivity loss. Isolated metapopulations were also predicted to be highly sensitive to fire, with large-scale fires having greater negative impacts on population abundance than small-scale ones. To reduce the risk of decline and local extirpation of I. obesulus and other small- to medium-sized ground-dwelling mammals in urbanizing, fire prone landscapes, we recommend that remnant vegetation and vegetated, structurally-complex corridors between habitat patches be retained. Well-designed road underpasses can be effective to connect habitat patches and reduce the probability of inbreeding and genetic differentiation; however, adjustment of fire management practices to limit the size of unplanned fires and ensure the retention of long unburnt vegetation will also be required to ensure persistence. Our study supports the evidence that in rapidly urbanizing landscapes, a pro-active conservation approach is required that manages species at the metapopulation level and that prioritizes metapopulations and habitat with greater long-term probability of persistence and conservation capacity, respectively. This strategy may help us prevent future declines and local extirpations, and currently relatively common species from becoming rare. PMID:29444118

Intelligent diagnosis of jaundice with dynamic uncertain causality graph model.

PubMed

Hao, Shao-Rui; Geng, Shi-Chao; Fan, Lin-Xiao; Chen, Jia-Jia; Zhang, Qin; Li, Lan-Juan

2017-05-01

Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is fairly difficult to distinguish the cause of jaundice in clinical practice, especially for general practitioners in less developed regions. With collaboration between physicians and artificial intelligence engineers, a comprehensive knowledge base relevant to jaundice was created based on demographic information, symptoms, physical signs, laboratory tests, imaging diagnosis, medical histories, and risk factors. Then a diagnostic modeling and reasoning system using the dynamic uncertain causality graph was proposed. A modularized modeling scheme was presented to reduce the complexity of model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. A "chaining" inference algorithm and weighted logic operation mechanism were employed to guarantee the exactness and efficiency of diagnostic reasoning under situations of incomplete and uncertain information. Moreover, the causal interactions among diseases and symptoms intuitively demonstrated the reasoning process in a graphical manner. Verification was performed using 203 randomly pooled clinical cases, and the accuracy was 99.01% and 84.73%, respectively, with or without laboratory tests in the model. The solutions were more explicable and convincing than common methods such as Bayesian Networks, further increasing the objectivity of clinical decision-making. The promising results indicated that our model could be potentially used in intelligent diagnosis and help decrease public health expenditure.

Intelligent diagnosis of jaundice with dynamic uncertain causality graph model*

PubMed Central

Hao, Shao-rui; Geng, Shi-chao; Fan, Lin-xiao; Chen, Jia-jia; Zhang, Qin; Li, Lan-juan

2017-01-01

Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is fairly difficult to distinguish the cause of jaundice in clinical practice, especially for general practitioners in less developed regions. With collaboration between physicians and artificial intelligence engineers, a comprehensive knowledge base relevant to jaundice was created based on demographic information, symptoms, physical signs, laboratory tests, imaging diagnosis, medical histories, and risk factors. Then a diagnostic modeling and reasoning system using the dynamic uncertain causality graph was proposed. A modularized modeling scheme was presented to reduce the complexity of model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. A “chaining” inference algorithm and weighted logic operation mechanism were employed to guarantee the exactness and efficiency of diagnostic reasoning under situations of incomplete and uncertain information. Moreover, the causal interactions among diseases and symptoms intuitively demonstrated the reasoning process in a graphical manner. Verification was performed using 203 randomly pooled clinical cases, and the accuracy was 99.01% and 84.73%, respectively, with or without laboratory tests in the model. The solutions were more explicable and convincing than common methods such as Bayesian Networks, further increasing the objectivity of clinical decision-making. The promising results indicated that our model could be potentially used in intelligent diagnosis and help decrease public health expenditure. PMID:28471111

Gender in Science and Engineering Faculties: Demographic Inertia Revisited.

PubMed

Thomas, Nicole R; Poole, Daniel J; Herbers, Joan M

2015-01-01

The under-representation of women on faculties of science and engineering is ascribed in part to demographic inertia, which is the lag between retirement of current faculty and future hires. The assumption of demographic inertia implies that, given enough time, gender parity will be achieved. We examine that assumption via a semi-Markov model to predict the future faculty, with simulations that predict the convergence demographic state. Our model shows that existing practices that produce gender gaps in recruitment, retention, and career progression preclude eventual gender parity. Further, we examine sensitivity of the convergence state to current gender gaps to show that all sources of disparity across the entire faculty career must be erased to produce parity: we cannot blame demographic inertia.

Linkage disequilibrium analysis in young populations: Pseudo-vitamin D-deficiency rickets and the founder effect in French Canadians

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

Labuda, M.; Glorieux, F.H.; Labuda, D.

1996-09-01

Pseudo-vitamin D-deficiency rickets (PDDR) was mapped close to D12S90 and between proximal D12S312 and distal (D12S305, D12S104) microsatellites that were subsequently found on a single YAC clone. Analysis of a complex haplotype in linkage disequilibrium (LD) with the disease discriminated among distinct founder effects in French Canadian populations in Acadia and in Charlevoix-Saguenay-Lac-Saint-Jean (Ch-SLSJ), as well as an earlier one in precolonial Europe. A simple demographic model suggested the historical age of the founder effect in Ch-SLSJ to be {approximately}12 generations. The corresponding LD data are consistent with this figure when they are analyzed within the framework of Luria-Delbruck model,more » which takes into account the population growth. Population sampling due to a limited number of first settlers and the rapid demographic expansion appear to have played a major role in the founding of PDDR in Ch-SLSJ and, presumably, other genetic disorders endemic to French Canada. Similarly, the founder effect in Ashkenazim, coinciding with their early settlement in medieval Poland and subsequent expansion eastward, could explain the origin of frequent genetic diseases in this population. 48 refs., 5 figs., 2 tabs.« less

Speciation, population structure, and demographic history of the Mojave Fringe-toed Lizard (Uma scoparia), a species of conservation concern

PubMed Central

Gottscho, Andrew D; Marks, Sharyn B; Jennings, W Bryan

2014-01-01

The North American deserts were impacted by both Neogene plate tectonics and Quaternary climatic fluctuations, yet it remains unclear how these events influenced speciation in this region. We tested published hypotheses regarding the timing and mode of speciation, population structure, and demographic history of the Mojave Fringe-toed Lizard (Uma scoparia), a sand dune specialist endemic to the Mojave Desert of California and Arizona. We sampled 109 individual lizards representing 22 insular dune localities, obtained DNA sequences for 14 nuclear loci, and found that U. scoparia has low genetic diversity relative to the U. notata species complex, comparable to that of chimpanzees and southern elephant seals. Analyses of genotypes using Bayesian clustering algorithms did not identify discrete populations within U. scoparia. Using isolation-with-migration (IM) models and a novel coalescent-based hypothesis testing approach, we estimated that U. scoparia diverged from U. notata in the Pleistocene epoch. The likelihood ratio test and the Akaike Information Criterion consistently rejected nested speciation models that included parameters for migration and population growth of U. scoparia. We reject the Neogene vicariance hypothesis for the speciation of U. scoparia and define this species as a single evolutionarily significant unit for conservation purposes. PMID:25360285

Neuropsychological tests for predicting cognitive decline in older adults

PubMed Central

Baerresen, Kimberly M; Miller, Karen J; Hanson, Eric R; Miller, Justin S; Dye, Richelin V; Hartman, Richard E; Vermeersch, David; Small, Gary W

2015-01-01

Summary Aim To determine neuropsychological tests likely to predict cognitive decline. Methods A sample of nonconverters (n = 106) was compared with those who declined in cognitive status (n = 24). Significant univariate logistic regression prediction models were used to create multivariate logistic regression models to predict decline based on initial neuropsychological testing. Results Rey–Osterrieth Complex Figure Test (RCFT) Retention predicted conversion to mild cognitive impairment (MCI) while baseline Buschke Delay predicted conversion to Alzheimer’s disease (AD). Due to group sample size differences, additional analyses were conducted using a subsample of demographically matched nonconverters. Analyses indicated RCFT Retention predicted conversion to MCI and AD, and Buschke Delay predicted conversion to AD. Conclusion Results suggest RCFT Retention and Buschke Delay may be useful in predicting cognitive decline. PMID:26107318

Joint Inference of Population Assignment and Demographic History

PubMed Central

Choi, Sang Chul; Hey, Jody

2011-01-01

A new approach to assigning individuals to populations using genetic data is described. Most existing methods work by maximizing Hardy–Weinberg and linkage equilibrium within populations, neither of which will apply for many demographic histories. By including a demographic model, within a likelihood framework based on coalescent theory, we can jointly study demographic history and population assignment. Genealogies and population assignments are sampled from a posterior distribution using a general isolation-with-migration model for multiple populations. A measure of partition distance between assignments facilitates not only the summary of a posterior sample of assignments, but also the estimation of the posterior density for the demographic history. It is shown that joint estimates of assignment and demographic history are possible, including estimation of population phylogeny for samples from three populations. The new method is compared to results of a widely used assignment method, using simulated and published empirical data sets. PMID:21775468

Individual heterogeneity in life histories and eco-evolutionary dynamics

PubMed Central

Vindenes, Yngvild; Langangen, Øystein

2015-01-01

Individual heterogeneity in life history shapes eco-evolutionary processes, and unobserved heterogeneity can affect demographic outputs characterising life history and population dynamical properties. Demographic frameworks like matrix models or integral projection models represent powerful approaches to disentangle mechanisms linking individual life histories and population-level processes. Recent developments have provided important steps towards their application to study eco-evolutionary dynamics, but so far individual heterogeneity has largely been ignored. Here, we present a general demographic framework that incorporates individual heterogeneity in a flexible way, by separating static and dynamic traits (discrete or continuous). First, we apply the framework to derive the consequences of ignoring heterogeneity for a range of widely used demographic outputs. A general conclusion is that besides the long-term growth rate lambda, all parameters can be affected. Second, we discuss how the framework can help advance current demographic models of eco-evolutionary dynamics, by incorporating individual heterogeneity. For both applications numerical examples are provided, including an empirical example for pike. For instance, we demonstrate that predicted demographic responses to climate warming can be reversed by increased heritability. We discuss how applications of this demographic framework incorporating individual heterogeneity can help answer key biological questions that require a detailed understanding of eco-evolutionary dynamics. PMID:25807980

Selection and Reduced Population Size Cannot Explain Higher Amounts of Neandertal Ancestry in East Asian than in European Human Populations

PubMed Central

Kim, Bernard Y.; Lohmueller, Kirk E.

2015-01-01

It has been hypothesized that the greater proportion of Neandertal ancestry in East Asians than in Europeans is due to the fact that purifying selection is less effective at removing weakly deleterious Neandertal alleles from East Asian populations. Using simulations of a broad range of models of selection and demography, we have shown that this hypothesis cannot account for the higher proportion of Neandertal ancestry in East Asians than in Europeans. Instead, more complex demographic scenarios, most likely involving multiple pulses of Neandertal admixture, are required to explain the data. PMID:25683122

High Genetic Diversity and Distinctiveness of Rear-Edge Climate Relicts Maintained by Ancient Tetraploidisation for Alnus glutinosa

PubMed Central

Lepais, Olivier; Muller, Serge D.; Ben Saad-Limam, Samia; Benslama, Mohamed; Rhazi, Laila; Belouahem-Abed, Djamila; Daoud-Bouattour, Amina; Gammar, Amor Mokhtar; Ghrabi-Gammar, Zeineb; Bacles, Cécile Fanny Emilie

2013-01-01

Populations located at the rear-edge of a species’ distribution may have disproportionate ecological and evolutionary importance for biodiversity conservation in a changing global environment. Yet genetic studies of such populations remain rare. This study investigates the evolutionary history of North-African low latitude marginal populations of Alnus glutinosa Gaertn., a European tree species that plays a significant ecological role as a keystone of riparian ecosystems. We genotyped 551 adults from 19 populations located across North Africa at 12 microsatellite loci and applied a coalescent-based simulation approach to reconstruct the demographic and evolutionary history of these populations. Surprisingly, Moroccan trees were tetraploids demonstrating a strong distinctiveness of these populations within a species otherwise known as diploid. Best-fitting models of demographic reconstruction revealed the relict nature of Moroccan populations that were found to have withstood past climate change events and to be much older than Algerian and Tunisian populations. This study highlights the complex demographic history that can be encountered in rear-edge distribution margins that here consist of both old stable climate relict and more recent populations, distinctively diverse genetically both quantitatively and qualitatively. We emphasize the high evolutionary and conservation value of marginal rear-edge populations of a keystone riparian species in the context of on-going climate change in the Mediterranean region. PMID:24098677

Developing a rich definition of the person/residence to support ...

EPA Pesticide Factsheets

Characterizing interindividual variation in combined chemical exposures from the use of consumer products is a challenge because of the complexity of these exposures. There are many products commercially available and individuals use combinations of products dictated by their specific needs. Product use varies with an individual’s demographics (e.g., age, gender, ethnicity, family structure, and type of residence). Exposures also occur as a result of other individuals using products in the home (e.g., painting a room exposes all individuals in a home and washing a child exposes both child and adult). Finally, characterizing applied and internal doses requires data on the physiology and behaviors of the individual. The U.S. EPA is developing probabilistic methods of modeling variation in exposure-relevant characteristics of individuals, their residences, and their families. The goal of this effort is the generation of synthetic populations whose characteristics can be used to predict chemical doses from the use of consumer products. A database of population demographics is created by linking data from the U.S. Census with data from U.S. housing surveys. Survey data are linked by matching records based on similarities in the characteristics correlated with the parameters of interest. The demographics are also combined with rules controlling product usage to refine the estimates of the products that individuals in a household may use (e.g., only adults with a you

A structural test of the Integrated Motivational-Volitional model of suicidal behaviour.

PubMed

Dhingra, Katie; Boduszek, Daniel; O'Connor, Rory C

2016-05-30

Suicidal behaviours are highly complex, multi-determined phenomena. Despite this, historically research has tended to focus on bivariate associations between atheoretical demographic and/or psychiatric factors and suicidal behaviour. The aim of this study was to empirically test the Integrated Motivational-Volitional model of suicidal behaviour using structural equation modelling. Healthy adults (N=1809) completed anonymous self-report surveys. The fit of the proposed model was good, and explained 79% of variance in defeat, 83% of variance in entrapment, 61% of variance in suicidal ideation, and 27% of variance in suicide attempts. All proposed paths were significant except for those between goal re-engagement and two factors of suicide resilience (Internal Protective and External Protective) and suicidal ideation; and impulsivity and discomfort intolerance and suicide attempts. These findings represent a preliminary step towards greater clarification of the mechanisms driving suicidal behaviour, and support the utility of basing future research on the Integrated Motivational-Volitional model of suicidal behaviour. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models.

PubMed

Keith, David A; Akçakaya, H Resit; Thuiller, Wilfried; Midgley, Guy F; Pearson, Richard G; Phillips, Steven J; Regan, Helen M; Araújo, Miguel B; Rebelo, Tony G

2008-10-23

Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.

Exome Sequencing Provides Evidence of Polygenic Adaptation to a Fat-Rich Animal Diet in Indigenous Siberian Populations.

PubMed

Hsieh, PingHsun; Hallmark, Brian; Watkins, Joseph; Karafet, Tatiana M; Osipova, Ludmila P; Gutenkunst, Ryan N; Hammer, Michael F

2017-11-01

Siberia is one of the coldest environments on Earth and has great seasonal temperature variation. Long-term settlement in northern Siberia undoubtedly required biological adaptation to severe cold stress, dramatic variation in photoperiod, and limited food resources. In addition, recent archeological studies show that humans first occupied Siberia at least 45,000 years ago; yet our understanding of the demographic history of modern indigenous Siberians remains incomplete. In this study, we use whole-exome sequencing data from the Nganasans and Yakuts to infer the evolutionary history of these two indigenous Siberian populations. Recognizing the complexity of the adaptive process, we designed a model-based test to systematically search for signatures of polygenic selection. Our approach accounts for stochasticity in the demographic process and the hitchhiking effect of classic selective sweeps, as well as potential biases resulting from recombination rate and mutation rate heterogeneity. Our demographic inference shows that the Nganasans and Yakuts diverged ∼12,000-13,000 years ago from East-Asian ancestors in a process involving continuous gene flow. Our polygenic selection scan identifies seven candidate gene sets with Siberian-specific signals. Three of these gene sets are related to diet, especially to fat metabolism, consistent with the hypothesis of adaptation to a fat-rich animal diet. Additional testing rejects the effect of hitchhiking and favors a model in which selection yields small allele frequency changes at multiple unlinked genes. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Modeling subjective evaluation of soundscape quality in urban open spaces: An artificial neural network approach.

PubMed

Yu, Lei; Kang, Jian

2009-09-01

This research aims to explore the feasibility of using computer-based models to predict the soundscape quality evaluation of potential users in urban open spaces at the design stage. With the data from large scale field surveys in 19 urban open spaces across Europe and China, the importance of various physical, behavioral, social, demographical, and psychological factors for the soundscape evaluation has been statistically analyzed. Artificial neural network (ANN) models have then been explored at three levels. It has been shown that for both subjective sound level and acoustic comfort evaluation, a general model for all the case study sites is less feasible due to the complex physical and social environments in urban open spaces; models based on individual case study sites perform well but the application range is limited; and specific models for certain types of location/function would be reliable and practical. The performance of acoustic comfort models is considerably better than that of sound level models. Based on the ANN models, soundscape quality maps can be produced and this has been demonstrated with an example.

What causes childhood stunting among children of San Vicente, Guatemala: Employing complimentary, system-analysis approaches.

PubMed

Voth-Gaeddert, Lee E; Stoker, Matthew; Cornell, Devin; Oerther, Daniel B

2018-04-01

Guatemala has the sixth worst stunting rate with 48% of children under five years of age classified as stunted according to World Health Organization standards. This study utilizes two different yet complimentary system-analysis approaches to analyze correlations among environmental and demographic variables, environmental enteric dysfunction (EED), and child height-for-age (stunting metric) in Guatemala. Two descriptive models constructed around applicable environmental and demographic factors on child height-for-age and EED were analyzed using Network Analysis (NA) and Structural Equation Modeling (SEM). Data from two populations of children between the age of three months and five years were used. The first population (n = 2103) was drawn from the Food for Peace Baseline Survey conducted by the US Agency for International Development (USAID) in 2012, and the second population (n = 372) was drawn from an independent survey conducted by the San Vicente Health Center in 2016. The results from the NA of the height-for-age model confirmed pathogen exposure, nutrition, and prenatal health as important, and the results from the NA of the EED model confirmed water source, water treatment, and type of sanitation as important. The results from the SEM of the height-for-age model confirmed a statistically significant correlation among child height-for-age and child-mother interaction (-0.092, p = 0.076) while the SEM of the EED model confirmed the statistically significant correlation among EED and type of water treatment (-0.115, p = 0.013). Our approach supports important efforts to understand the complex set of factors associated with child stunting among communities sharing similarities with San Vicente. Copyright © 2018 Elsevier GmbH. All rights reserved.

What can complexity do for diabetes management? Linking theory to practice.

PubMed

Cooper, Helen C; Geyer, Robert

2009-08-01

Diabetes presents a multifaceted picture with its rapidly rising prevalence associated with changing demographics and increasing levels of obesity in the developed world. Deaths from diabetes are predicted to rise by 25% over the next 10 years. The enormity of this public health challenge has been recognized the world over, but little attention has been paid to the theoretical frameworks underpinning practical management. This paper aims to introduce complexity theory and discuss its practical application to diabetes, focusing on a single 'tool' to provide an example of how theory can be linked to practice. Critics have questioned the all inclusive nature of complexity seeing it as an intangible concept that fails to offer anything new to health care. However, few have appraised its practical application to a chronic disease that is currently managed using an outdated, linear, reduce and resolve model which fails to address the multiple interacting systems inherent within this condition. This article proposes that complexity theory provides an interprofessional perspective for describing and understanding the processes involved, and provides working 'tools' for patients, carers and practitioners that capture the reality of managing this chronic disease in modern life.

Systems Thinking as a Competency for Community College Leaders in an Era of Increasing Complexity

ERIC Educational Resources Information Center

Davis, Anne Powel

2013-01-01

The pluralistic and often competing goals of myriad constituents, the changing demographics of students, the uncertainty of funding, and the growing demands for accountability from stakeholders have increased the complexity of systems which community college leaders must manage. Emerging from the recent literature on community colleges is a call…

Projecting the success of plant restoration with population viability analysis

USGS Publications Warehouse

Bell, T.J.; Bowles, M.L.; McEachern, A.K.; Brigham, C.A.; Schwartz, M.W.

2003-01-01

Conserving viable populations of plant species requires that they have high probabilities of long-term persistence within natural habitats, such as a chance of extinction in 100 years of less than 5% (Menges 1991, 1998; Brown 1994; Pavlik 1994; Chap. 1, this Vol.). For endangered and threatened species that have been severely reduces in range and whose habitats have been fragmented, important species conservation strategies may include augmenting existing populations or restoring new viable populations (Bowles and Whelan 1994; Chap. 2, this Vol.). Restoration objectives may include increasing population numbers to reduce extinction probability, deterministic manipulations to develop a staged cohort structure, or more complex restoration of a desired genetic structure to allow outcrossing or increase effective population size (DeMauro 1993, 1994; Bowles et al. 1993, 1998; Pavlik 1994; Knapp and Dyer 1998; Chap. 2, this Vol.). These efforts may require translocation of propagules from existing (in situ) populations, or from ex situ botanic gardens or seed storage facilities (Falk et al. 1996; Guerrant and Pavlik 1998; Chap. 2, this Vol.). Population viability analysis (PVA) can provide a critical foundation for plant restoration, as it models demographic projections used to evaluate the probability of population persistence and links plant life history with restoration strategies. It is unknown how well artificially created populations will meet demographic modeling requirements (e.g., due to artificial cohort transitions) and few, if any, PVAs have been applied to restorations. To guide application of PVA to restored populations and to illustrate potential difficulties, we examine effects of planting different life stages, model initial population sizes needed to achieve population viability, and compare demographic characteristics between natural and restored populations. We develop and compare plant population restoration viability analysis (PRVA) case studies of two plant species listed in the USA for which federal recovery planning calls for population restoration: Cirsium pitcheri, a short-lived semelparous herb, and Asclepias meadii, a long-lived iteroparous herb.

Discrete-Choice Modeling Of Non-Working Women’s Trip-Chaining Activity Based

NASA Astrophysics Data System (ADS)

Hayati, Amelia; Pradono; Purboyo, Heru; Maryati, Sri

2018-05-01

Start The urban developments of technology and economics are now changing the lifestyles of the urban societies. It is also changing their travel demand to meet their movement needs. Nowadays, urban women, especially in Bandung, West Java, have a high demand for their daily travel and tend to increase. They have the ease of accessibility to personal modes of transportation and freedom to go anywhere to meet their personal and family needs. This also happens to non-working women or as housewives in the city of Bandung. More than 50% of women’s mobility is outside the home, in the term of trip-chaining, from leaving to returning home in one day. It is based on their complex activities in order to meet the needs of family and home care. While less than 60% of male’s mobility is outdoors, it is a simple trip-chaining or only has a single trip. The trip-chaining has significant differences between non-working women and working-men. This illustrates the pattern of Mom and Dad’s mobility in a family with an activity-based approach for the same purpose, i.e. family welfare. This study explains how complex the trip-chaining of non-working urban women and as housewives, with an activity-based approach done outdoors in a week. Socio-economic and household demographic variables serve as the basis for measuring the independent variables affecting family welfare, as well as the variables of type, time and duration of activities performed by unemployed housewives. This study aims to examine the interrelationships between activity variables, especially the time of activity and travel, and socio-economic of household variables that can generate the complexity of women’s daily travel. Discrete Choice Modeling developed by Ben-Akiva, Chandra Bhat, etc., is used in this study to illustrate the relationship between activity and socio-economic demographic variables based on primary survey data in Bandung, West Java for 466 unemployed housewives. The results of the regression, by Seemingly Unrelated Regression approach methods, showed the interrelationship between all variables, including the complexity of trip chaining of housewives based on their daily activities. The type of mandatory and discretionary activities, and the duration of activities performed during the dismissal in the series of trip chains conducted are intended for the fulfillment of the welfare of all family member.

Population demographics, survival, and reporduction: Alaska sea otter research

USGS Publications Warehouse

Monson, Daniel H.; Bodkin, James L.; Doak, D.F.; Estes, James A.; Tinker, M.T.; Siniff, D.B.; Maldini, Daniela; Calkins, Donald; Atkinson, Shannon; Meehan, Rosa

2004-01-01

The fundamental force behind population change is the balance between age-specific survival and reproductive rates. Thus, understanding population demographics is crucial when trying to interpret trends in population change over time. For many species, demographic rates change as the population’s status (i.e., relative to prey resources) varies. Indices of body condition indicative of individual energy reserves can be a useful gauge of population status. Integrated studies designed to measure (1) population trends; (2) current population status; and (3) demographic rates will provide the most complete picture of the factors driving observed population changes. In particular, estimates of age specific survival and reproduction in conjunction with measures of population change can be integrated into population matrix models useful in explaining observed trends. We focus here on the methods used to measure demographic rates in sea otters, and note the importance of comparable methods between studies. Next, we review the current knowledge of the influence of population status on demographic parameters. We end with examples of the power of matrix modeling as a tool to integrate various types of demographic information for detecting otherwise hard to detect changes in demographic parameters.

Parsimonious estimation of the Wechsler Memory Scale, Fourth Edition demographically adjusted index scores: immediate and delayed memory.

PubMed

Miller, Justin B; Axelrod, Bradley N; Schutte, Christian

2012-01-01

The recent release of the Wechsler Memory Scale Fourth Edition contains many improvements from a theoretical and administration perspective, including demographic corrections using the Advanced Clinical Solutions. Although the administration time has been reduced from previous versions, a shortened version may be desirable in certain situations given practical time limitations in clinical practice. The current study evaluated two- and three-subtest estimations of demographically corrected Immediate and Delayed Memory index scores using both simple arithmetic prorating and regression models. All estimated values were significantly associated with observed index scores. Use of Lin's Concordance Correlation Coefficient as a measure of agreement showed a high degree of precision and virtually zero bias in the models, although the regression models showed a stronger association than prorated models. Regression-based models proved to be more accurate than prorated estimates with less dispersion around observed values, particularly when using three subtest regression models. Overall, the present research shows strong support for estimating demographically corrected index scores on the WMS-IV in clinical practice with an adequate performance using arithmetically prorated models and a stronger performance using regression models to predict index scores.

Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) (Final Report, Version 2)

EPA Science Inventory

EPA's announced the availability of the final report, Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) (Version 2). This update furthered land change modeling by providing nationwide housing developmen...

Holocene Demographic Changes and the Emergence of Complex Societies in Prehistoric Australia.

PubMed

Williams, Alan N; Ulm, Sean; Turney, Chris S M; Rohde, David; White, Gentry

2015-01-01

A continental-scale model of Holocene Australian hunter-gatherer demography and mobility is generated using radiocarbon data and geospatial techniques. Results show a delayed expansion and settlement of much of Australia following the termination of the late Pleistocene until after 9,000 years ago (or 9ka). The onset of the Holocene climatic optimum (9-6ka) coincides with rapid expansion, growth and establishment of regional populations across ~75% of Australia, including much of the arid zone. This diffusion from isolated Pleistocene refugia provides a mechanism for the synchronous spread of pan-continental archaeological and linguistic attributes at this time (e.g. Pama-Nyungan language, Panaramitee art style, backed artefacts). We argue longer patch residence times were possible at the end of the optimum, resulting in a shift to more sedentary lifestyles and establishment of low-level food production in some parts of the continent. The onset of El Niño - Southern Oscillation (ENSO; 4.5-2ka) restricted low-level food production, and resulted in population fragmentation, abandonment of marginal areas, and reduction in ranging territory of ~26%. Importantly, climate amelioration brought about by more pervasive La Niña conditions (post-2ka), resulted in an intensification of the mobility strategies and technological innovations that were developed in the early- to mid-Holocene. These changes resulted in population expansion and utilization of the entire continent. We propose that it was under these demographically packed conditions that the complex social and religious societies observed at colonial contact were formed.

Effects of Mitochondrial DNA Rate Variation on Reconstruction of Pleistocene Demographic History in a Social Avian Species, Pomatostomus superciliosus

PubMed Central

Norman, Janette A.; Blackmore, Caroline J.; Rourke, Meaghan; Christidis, Les

2014-01-01

Mitochondrial sequence data is often used to reconstruct the demographic history of Pleistocene populations in an effort to understand how species have responded to past climate change events. However, departures from neutral equilibrium conditions can confound evolutionary inference in species with structured populations or those that have experienced periods of population expansion or decline. Selection can affect patterns of mitochondrial DNA variation and variable mutation rates among mitochondrial genes can compromise inferences drawn from single markers. We investigated the contribution of these factors to patterns of mitochondrial variation and estimates of time to most recent common ancestor (TMRCA) for two clades in a co-operatively breeding avian species, the white-browed babbler Pomatostomus superciliosus. Both the protein-coding ND3 gene and hypervariable domain I control region sequences showed departures from neutral expectations within the superciliosus clade, and a two-fold difference in TMRCA estimates. Bayesian phylogenetic analysis provided evidence of departure from a strict clock model of molecular evolution in domain I, leading to an over-estimation of TMRCA for the superciliosus clade at this marker. Our results suggest mitochondrial studies that attempt to reconstruct Pleistocene demographic histories should rigorously evaluate data for departures from neutral equilibrium expectations, including variation in evolutionary rates across multiple markers. Failure to do so can lead to serious errors in the estimation of evolutionary parameters and subsequent demographic inferences concerning the role of climate as a driver of evolutionary change. These effects may be especially pronounced in species with complex social structures occupying heterogeneous environments. We propose that environmentally driven differences in social structure may explain observed differences in evolutionary rate of domain I sequences, resulting from longer than expected retention times for matriarchal lineages in the superciliosus clade. PMID:25181547

A dynamic auditory-cognitive system supports speech-in-noise perception in older adults.

PubMed

Anderson, Samira; White-Schwoch, Travis; Parbery-Clark, Alexandra; Kraus, Nina

2013-06-01

Understanding speech in noise is one of the most complex activities encountered in everyday life, relying on peripheral hearing, central auditory processing, and cognition. These abilities decline with age, and so older adults are often frustrated by a reduced ability to communicate effectively in noisy environments. Many studies have examined these factors independently; in the last decade, however, the idea of an auditory-cognitive system has emerged, recognizing the need to consider the processing of complex sounds in the context of dynamic neural circuits. Here, we used structural equation modeling to evaluate the interacting contributions of peripheral hearing, central processing, cognitive ability, and life experiences to understanding speech in noise. We recruited 120 older adults (ages 55-79) and evaluated their peripheral hearing status, cognitive skills, and central processing. We also collected demographic measures of life experiences, such as physical activity, intellectual engagement, and musical training. In our model, central processing and cognitive function predicted a significant proportion of variance in the ability to understand speech in noise. To a lesser extent, life experience predicted hearing-in-noise ability through modulation of brainstem function. Peripheral hearing levels did not significantly contribute to the model. Previous musical experience modulated the relative contributions of cognitive ability and lifestyle factors to hearing in noise. Our models demonstrate the complex interactions required to hear in noise and the importance of targeting cognitive function, lifestyle, and central auditory processing in the management of individuals who are having difficulty hearing in noise. Copyright © 2013 Elsevier B.V. All rights reserved.

Using a syndemics theory approach to study HIV risk taking in a population of men who use the internet to find partners for unprotected sex.

PubMed

Klein, Hugh

2011-11-01

This study examines the value of using syndemics theory as a model for understanding HIV risk taking in a population of men who are at great risk for acquiring and/or transmitting HIV. The principal aim is to provide an empirical test of the applicability of the theory to sexual risk behaviors in this particular research population. The study was based on a national random sample of 332 men who have sex with men, or MSM, who use the Internet to seek men with whom they can engage in unprotected sex. Data collection was conducted via telephone interviews between January 2008 and May 2009. As hypothesized in the syndemics theory model, attitudes toward condom use were central to understanding men's involvement in risky sex. As hypothesized, these attitudes depended on various demographic, psychological/psychosocial functioning, and sex-related preference measures. Also as hypothesized, psychological and psychosocial functioning were found to be very important to the overall model, and as expected, these factors were shaped greatly by factors such as demographic characteristics and childhood maltreatment experiences. The structural equation assessing the fit of the overall model indicated solid support for the syndemics theory approach. Overall, syndemics theory seems to apply fairly well to understanding the complexity of the factors that underlie men's risk-taking practices. The complicated interplay among factors such as attitudes toward condom use, childhood maltreatment experiences, psychological and psychosocial functioning, and substance use and abuse-all of which are central to a syndemics theory approach to studying risk-was demonstrated.

Reconstructing population histories from single nucleotide polymorphism data.

PubMed

Sirén, Jukka; Marttinen, Pekka; Corander, Jukka

2011-01-01

Population genetics encompasses a strong theoretical and applied research tradition on the multiple demographic processes that shape genetic variation present within a species. When several distinct populations exist in the current generation, it is often natural to consider the pattern of their divergence from a single ancestral population in terms of a binary tree structure. Inference about such population histories based on molecular data has been an intensive research topic in the recent years. The most common approach uses coalescent theory to model genealogies of individuals sampled from the current populations. Such methods are able to compare several different evolutionary scenarios and to estimate demographic parameters. However, their major limitation is the enormous computational complexity associated with the indirect modeling of the demographies, which limits the application to small data sets. Here, we propose a novel Bayesian method for inferring population histories from unlinked single nucleotide polymorphisms, which is applicable also to data sets harboring large numbers of individuals from distinct populations. We use an approximation to the neutral Wright-Fisher diffusion to model random fluctuations in allele frequencies. The population histories are modeled as binary rooted trees that represent the historical order of divergence of the different populations. A combination of analytical, numerical, and Monte Carlo integration techniques are utilized for the inferences. A particularly important feature of our approach is that it provides intuitive measures of statistical uncertainty related with the estimates computed, which may be entirely lacking for the alternative methods in this context. The potential of our approach is illustrated by analyses of both simulated and real data sets.

A nonlinear dynamic age-structured model of e-commerce in spain: Stability analysis of the equilibrium by delay and stochastic perturbations

NASA Astrophysics Data System (ADS)

Burgos, C.; Cortés, J.-C.; Shaikhet, L.; Villanueva, R.-J.

2018-11-01

First, we propose a deterministic age-structured epidemiological model to study the diffusion of e-commerce in Spain. Afterwards, we determine the parameters (death, birth and growth rates) of the underlying demographic model as well as the parameters (transmission of the use of e-commerce rates) of the proposed epidemiological model that best fit real data retrieved from the Spanish National Statistical Institute. Motivated by the two following facts: first the dynamics of acquiring the use of a new technology as e-commerce is mainly driven by the feedback after interacting with our peers (family, friends, mates, mass media, etc.), hence having a certain delay, and second the inherent uncertainty of sampled real data and the social complexity of the phenomena under analysis, we introduce aftereffect and stochastic perturbations in the initial deterministic model. This leads to a delayed stochastic model for e-commerce. We then investigate sufficient conditions in order to guarantee the stability in probability of the equilibrium point of the dynamic e-commerce delayed stochastic model. Our theoretical findings are numerically illustrated using real data.

Comparing adult users of public and private dental services in the state of Minas Gerais, Brazil.

PubMed

Pinto, Rafaela da Silveira; de Abreu, Mauro Henrique Nogueira Guimarães; Vargas, Andrea Maria Duarte

2014-08-06

Studying the factors associated with the use of dental services can provide the necessary knowledge to understand the reasons why individuals seek out public healthcare services and the formulation of more appropriate public policies for the present-day reality. This work was a cross-sectional epidemiological study consisting of a sample of adults found in a research databank concerning the conditions of the oral health of the population of the state of Minas Gerais, Brazil. This study examined both main oral health disorders and relevant socioeconomic aspects. The dependent variable was defined as the type of service used, categorized under public and private use. The independent variables were selected and grouped to be inserted in the analysis model according to an adaptation of the behavioral model described by Andersen and Davidson. A hierarchical model was used to analyze the data. The description of variables and bivariate analyses were performed in an attempt to verify possible associations. For each group of variables at each hierarchical level, the gross and adjusted odds ratios (OR) and the respective 95% confidence intervals (CI) were estimated by means of logistic regression. The Complex Samples model from the SPSS statistics program, version 19.0, was used to analyze the sample framework. In the final model, the factors associated with the use of public healthcare services by adults were directly related to the socioeconomic and demographic conditions of the individuals, including: being of a dark-skinned black race/color, belonging to families with more than four household residents and with a lower income level, residing in small towns, having more teeth that need treatment. According to the findings from this study, socioeconomic and demographic factors, as well as normative treatment needs, are associated with the use of public dental services.

Demographic Modelling in Weed Biocontrol

USDA-ARS?s Scientific Manuscript database

Demographic matrix modeling of plant populations can be a powerful tool to identify key life stage transitions that contribute the most to population growth of an invasive plant and hence should be targeted for disruption. Therefore, this approach has the potential to guide the pre-release selection...

Ecotoxicology and spatial modeling in population dynamics: an illustration with brown trout.

PubMed

Chaumot, Arnaud; Charles, Sandrine; Flammarion, Patrick; Auger, Pierre

2003-05-01

We developed a multiregion matrix population model to explore how the demography of a hypothetical brown trout population living in a river network varies in response to different spatial scenarios of cadmium contamination. Age structure, spatial distribution, and demographic and migration processes are taken into account in the model. Chronic or acute cadmium concentrations affect the demographic parameters at the scale of the river range. The outputs of the model constitute population-level end points (the asymptotic population growth rate, the stable age structure, and the asymptotic spatial distribution) that allow comparing the different spatial scenarios of contamination regarding the demographic response at the scale of the whole river network. An analysis of the sensitivity of these end points to lower order parameters enables us to link the local effects of cadmium to the global demographic behavior of the brown trout population. Such a link is of broad interest in the point of view of ecotoxicological management.

Explaining reported puma-related behaviors and behavioral intentions among northern Arizona residents

USGS Publications Warehouse

Mattson, David J.; Ruther, Elizabeth J.

2012-01-01

Management of pumas in the American West is typified by conflict among stakeholders plausibly rooted in life experiences and worldviews. We used a mail questionnaire to assess demographics, nature-views, puma-related life experiences and behaviors, and support for puma-related policies among residents of northern Arizona. Data from the questionnaire (n = 693 respondents) were used to model behaviors and support for policies. Compared to models based on nature-views and life experiences, those based on demographics had virtually no support from the data. The Utilitarian/Dominionistic nature-view had the strongest effect of any variable in six of seven models, and was associated with firearms and opposition to policies that would limit killing pumas. The Humanistic/Moralistic nature-view was positively associated with non-lethal behaviors and policies in five models. Gender had the strongest effect of any demographic variable. Compared to demographics alone, our results suggest that worldviews provide a more meaningful explanation of reported human behaviors and behavioral intentions regarding pumas.

Scaling up complexity in host-pathogens interaction models. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Aguiar, Maíra

2015-12-01

Caused by micro-organisms that are pathogenic to the host, infectious diseases have caused debilitation and premature death to large portions of the human population, leading to serious social-economic concerns. The persistence and increase in the occurrence of infectious diseases as well the emergence or resurgence of vector-borne diseases are closely related with demographic factors such as the uncontrolled urbanization and remarkable population growth, political, social and economical changes, deforestation, development of resistance to insecticides and drugs and increased human travel. In recent years, mathematical modeling became an important tool for the understanding of infectious disease epidemiology and dynamics, addressing ideas about the components of host-pathogen interactions. Acting as a possible tool to understand, predict the spread of infectious diseases these models are also used to evaluate the introduction of intervention strategies like vector control and vaccination. Many scientific papers have been published recently on these topics, and most of the models developed try to incorporate factors focusing on several different aspects of the disease (and eventually biological aspects of the vector), which can imply rich dynamic behavior even in the most basic dynamical models. As one example to be cited, there is a minimalistic dengue model that has shown rich dynamic structures, with bifurcations (Hopf, pitchfork, torus and tangent bifurcations) up to chaotic attractors in unexpected parameter regions [1,2], which was able to describe the large fluctuations observed in empirical outbreak data [3,4].

Accuracy and usefulness of BMI measures based on self-reported weight and height: findings from the NHANES & NHIS 2001-2006.

PubMed

Stommel, Manfred; Schoenborn, Charlotte A

2009-11-19

The Body Mass Index (BMI) based on self-reported height and weight ("self-reported BMI") in epidemiologic studies is subject to measurement error. However, because of the ease and efficiency in gathering height and weight information through interviews, it remains important to assess the extent of error present in self-reported BMI measures and to explore possible adjustment factors as well as valid uses of such self-reported measures. Using the combined 2001-2006 data from the continuous National Health and Nutrition Examination Survey, discrepancies between BMI measures based on self-reported and physical height and weight measures are estimated and socio-demographic predictors of such discrepancies are identified. Employing adjustments derived from the socio-demographic predictors, the self-reported measures of height and weight in the 2001-2006 National Health Interview Survey are used for population estimates of overweight & obesity as well as the prediction of health risks associated with large BMI values. The analysis relies on two-way frequency tables as well as linear and logistic regression models. All point and variance estimates take into account the complex survey design of the studies involved. Self-reported BMI values tend to overestimate measured BMI values at the low end of the BMI scale (< 22) and underestimate BMI values at the high end, particularly at values > 28. The discrepancies also vary systematically with age (younger and older respondents underestimate their BMI more than respondents aged 42-55), gender and the ethnic/racial background of the respondents. BMI scores, adjusted for socio-demographic characteristics of the respondents, tend to narrow, but do not eliminate misclassification of obese people as merely overweight, but health risk estimates associated with variations in BMI values are virtually the same, whether based on self-report or measured BMI values. BMI values based on self-reported height and weight, if corrected for biases associated with socio-demographic characteristics of the survey respondents, can be used to estimate health risks associated with variations in BMI, particularly when using parametric prediction models.

Complex psychotropic polypharmacy in bipolar disorder across varying mood polarities: A prospective cohort study of 2712 inpatients.

PubMed

Golden, Julia C; Goethe, John W; Woolley, Stephen B

2017-10-15

It is common for patients with bipolar disorder (BP) to receive multiple psychotropics, but few studies have assessed demographic and clinical features associated with risk for receiving complex psychotropic polypharmacy. This longitudinal cohort study examined 2712 inpatients with a DSM-IV clinical diagnosis of BP to assess associations between complex polypharmacy (defined as ≥4 psychotropics) and demographic and clinical features; associations with risk of rehospitalization were also examined. Logistic regressions were performed with the sample as a whole and with each of four DSM-IV BP subtypes individually. Complex polypharmacy was present in 21.0%. BP-I depressed patients were more likely to receive complex regimens than BP-I manic, BP-I mixed or BP-II patients. In the sample as a whole, variables significantly associated with complex polypharmacy included female, white, psychotic features and a co-diagnosis of borderline personality, post-traumatic stress or another anxiety disorder. The only examined medication not significantly associated with complex polypharmacy was lithium, although only in BP-I depressed and BP-I mixed. Complex polypharmacy was associated with rehospitalization in BP-I mania within 15 and 30days post index hospitalization. All data were from one clinical facility; results may not generalize to other settings and patient populations. BP-I depression may pose a greater treatment challenge than the other BP subtypes. Lithium may confer an overall advantage compared to other medications in BP-I depressed and BP-I mixed. Further research is needed to guide pharmacotherapy decisions in BP patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Updates to the Demographic and Spatial Allocation Models to ...

EPA Pesticide Factsheets

EPA's announced the availability of the final report, Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) (Version 2). This update furthered land change modeling by providing nationwide housing development scenarios up to 2100. This newest version includes updated population and land use data sets and addresses limitations identified in ICLUS v1 in both the migration and spatial allocation models. The companion user guide (Final Report) describes the development of ICLUS v2 and the updates that were made to the original data sets and the demographic and spatial allocation models. The GIS tool enables users to run SERGoM with the population projections developed for the ICLUS project and allows users to modify the spatial allocation housing density across the landscape.

Disease Extinction Versus Persistence in Discrete-Time Epidemic Models.

PubMed

van den Driessche, P; Yakubu, Abdul-Aziz

2018-04-12

We focus on discrete-time infectious disease models in populations that are governed by constant, geometric, Beverton-Holt or Ricker demographic equations, and give a method for computing the basic reproduction number, [Formula: see text]. When [Formula: see text] and the demographic population dynamics are asymptotically constant or under geometric growth (non-oscillatory), we prove global asymptotic stability of the disease-free equilibrium of the disease models. Under the same demographic assumption, when [Formula: see text], we prove uniform persistence of the disease. We apply our theoretical results to specific discrete-time epidemic models that are formulated for SEIR infections, cholera in humans and anthrax in animals. Our simulations show that a unique endemic equilibrium of each of the three specific disease models is asymptotically stable whenever [Formula: see text].

Neutral dynamics with environmental noise: Age-size statistics and species lifetimes

NASA Astrophysics Data System (ADS)

Kessler, David; Suweis, Samir; Formentin, Marco; Shnerb, Nadav M.

2015-08-01

Neutral dynamics, where taxa are assumed to be demographically equivalent and their abundance is governed solely by the stochasticity of the underlying birth-death process, has proved itself as an important minimal model that accounts for many empirical datasets in genetics and ecology. However, the restriction of the model to demographic [O (√{N }) ] noise yields relatively slow dynamics that appears to be in conflict with both short-term and long-term characteristics of the observed systems. Here we analyze two of these problems—age-size relationships and species extinction time—in the framework of a neutral theory with both demographic and environmental stochasticity. It turns out that environmentally induced variations of the demographic rates control the long-term dynamics and modify dramatically the predictions of the neutral theory with demographic noise only, yielding much better agreement with empirical data. We consider two prototypes of "zero mean" environmental noise, one which is balanced with regard to the arithmetic abundance, another balanced in the logarithmic (fitness) space, study their species lifetime statistics, and discuss their relevance to realistic models of community dynamics.

Characterization of demographic expansions from pairwise comparisons of linked microsatellite haplotypes.

PubMed

Navascués, Miguel; Hardy, Olivier J; Burgarella, Concetta

2009-03-01

This work extends the methods of demographic inference based on the distribution of pairwise genetic differences between individuals (mismatch distribution) to the case of linked microsatellite data. Population genetics theory describes the distribution of mutations among a sample of genes under different demographic scenarios. However, the actual number of mutations can rarely be deduced from DNA polymorphisms. The inclusion of mutation models in theoretical predictions can improve the performance of statistical methods. We have developed a maximum-pseudolikelihood estimator for the parameters that characterize a demographic expansion for a series of linked loci evolving under a stepwise mutation model. Those loci would correspond to DNA polymorphisms of linked microsatellites (such as those found on the Y chromosome or the chloroplast genome). The proposed method was evaluated with simulated data sets and with a data set of chloroplast microsatellites that showed signal for demographic expansion in a previous study. The results show that inclusion of a mutational model in the analysis improves the estimates of the age of expansion in the case of older expansions.

A model comparison approach shows stronger support for economic models of fertility decline

PubMed Central

Shenk, Mary K.; Towner, Mary C.; Kress, Howard C.; Alam, Nurul

2013-01-01

The demographic transition is an ongoing global phenomenon in which high fertility and mortality rates are replaced by low fertility and mortality. Despite intense interest in the causes of the transition, especially with respect to decreasing fertility rates, the underlying mechanisms motivating it are still subject to much debate. The literature is crowded with competing theories, including causal models that emphasize (i) mortality and extrinsic risk, (ii) the economic costs and benefits of investing in self and children, and (iii) the cultural transmission of low-fertility social norms. Distinguishing between models, however, requires more comprehensive, better-controlled studies than have been published to date. We use detailed demographic data from recent fieldwork to determine which models produce the most robust explanation of the rapid, recent demographic transition in rural Bangladesh. To rigorously compare models, we use an evidence-based statistical approach using model selection techniques derived from likelihood theory. This approach allows us to quantify the relative evidence the data give to alternative models, even when model predictions are not mutually exclusive. Results indicate that fertility, measured as either total fertility or surviving children, is best explained by models emphasizing economic factors and related motivations for parental investment. Our results also suggest important synergies between models, implicating multiple causal pathways in the rapidity and degree of recent demographic transitions. PMID:23630293

A craniometric perspective on the transition to agriculture in Europe.

PubMed

Pinhasi, Ron; von Cramon-Taubadel, Noreen

2012-02-01

Debates surrounding the nature of the Neolithic demographic transition in Europe have historically centered on two opposing models: a "demic" diffusion model whereby incoming farmers from the Near East and Anatolia effectively replaced or completely assimilated indigenous Mesolithic foraging communities, and an "indigenist" model resting on the assumption that ideas relating to agriculture and animal domestication diffused from the Near East but with little or no gene flow. The extreme versions of these dichotomous models were heavily contested primarily on the basis of archeological and modern genetic data. However, in recent years a growing acceptance has arisen of the likelihood that both processes were ongoing throughout the Neolithic transition and that a more complex, regional approach is required to fully understand the change from a foraging to a primarily agricultural mode of subsistence in Europe. Craniometric data were particularly useful for testing these more complex scenarios, as they can reliably be employed as a proxy for the genetic relationships among Mesolithic and Neolithic populations. In contrast, modern genetic data assume that modern European populations accurately reflect the genetic structure of Europe at the time of the Neolithic transition, while ancient DNA data are still not geographically or temporally detailed enough to test continent-wide processes. Here, with particular emphasis on the role of craniometric analyses, we review the current state of knowledge regarding the cultural and biological nature of the Neolithic transition in Europe.

[Modeling of an influence of indicators of social stress on demographic processes in regions of the Russian Federation].

PubMed

Burkin, M M; Molchanova, E V

To assess an impact of indicators of social stress on demographic processes in regions of the Russian Federation using statistical methods. The data of Rosstat «Regions of Russia» and «Health care in Russia» were used as information base. Indicators of about 80 subjects of the Russian Federation (without autonomous areas) for the ten-year period (2005-2014) have been created in the form of the database consisting of the following blocks: medico-demographic situation, level of economic development of the territory and wellbeing of the population, development of social infrastructure, ecological and climatic conditions, scientific researches and innovations. In total, there were about 70 indicators. Panel data for 80 regions of Russia in 10 years, which combine both indicators of spatial type (cross-section data), and information on temporary ranks (time-series data), were used. Various models of regression according to the panel data have been realized: the integrated model of regression (pooled model), regression model with the fixed effects (fixed effect model), regression model with random effects (random effect model). Main demographic indicators (life expectancy, birth rate, mortality from the external reasons) are to a great extent connected with socio-economic factors. Social tension (social stress) caused by transition to market economy plays an important role. The integral assessment of the impact of the average per capita monetary income, incidence of alcoholism and alcoholic psychoses, criminality, sales volume of alcoholic beverages per capita and marriage relations on demographic indicators is presented. Results of modeling allow to define the priority directions in the field of development of mental health and psychotherapeutic services in the regions of the Russian Federation.

Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) (Version 2) (External Review Draft)

EPA Science Inventory

EPA announced the availability of the draft report, Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) for a 30-day public comment period. The ICLUS version 2 (v2) modeling tool furthered land change mod...

Selection and reduced population size cannot explain higher amounts of Neandertal ancestry in East Asian than in European human populations.

PubMed

Kim, Bernard Y; Lohmueller, Kirk E

2015-03-05

It has been hypothesized that the greater proportion of Neandertal ancestry in East Asians than in Europeans is due to the fact that purifying selection is less effective at removing weakly deleterious Neandertal alleles from East Asian populations. Using simulations of a broad range of models of selection and demography, we have shown that this hypothesis cannot account for the higher proportion of Neandertal ancestry in East Asians than in Europeans. Instead, more complex demographic scenarios, most likely involving multiple pulses of Neandertal admixture, are required to explain the data. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Florida coastal ecological characterization: a socioeconomic study of the southwestern region. Volume II. Data appendix, Part 2

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

French, C.O.; Parsons, J.W.

1983-08-01

Data are compiled from existing sources on the social and economic characteristics of the southwestern coastal region of Florida, which is made up of Charlotte, Collier, DeSoto, Hillsborough, Lee, Manatee, Monroe, Pasco, Pinellas, and Sarasota Counties. Described are the components and interrelationships among complex processes that include population and demographics characteristics, mineral production, multiple-use conflicts, recreation and tourism, agricultural production, sport and commercial fishing, transportation, industrial and residential development, and environmental issues and regulations. Energetics models of socioeconomic systems are also presented. This volume contains appendices presenting data on land use, public utilities, transportation, recreation and tourism. 21 figures, 141more » tables.« less

Demographic management in a federated healthcare environment.

PubMed

Román, I; Roa, L M; Reina-Tosina, J; Madinabeitia, G

2006-09-01

The purpose of this paper is to provide a further step toward the decentralization of identification and demographic information about persons by solving issues related to the integration of demographic agents in a federated healthcare environment. The aim is to identify a particular person in every system of a federation and to obtain a unified view of his/her demographic information stored in different locations. This work is based on semantic models and techniques, and pursues the reconciliation of several current standardization works including ITU-T's Open Distributed Processing, CEN's prEN 12967, OpenEHR's dual and reference models, CEN's General Purpose Information Components and CORBAmed's PID service. We propose a new paradigm for the management of person identification and demographic data, based on the development of an open architecture of specialized distributed components together with the incorporation of techniques for the efficient management of domain ontologies, in order to have a federated demographic service. This new service enhances previous correlation solutions sharing ideas with different standards and domains like semantic techniques and database systems. The federation philosophy enforces us to devise solutions to the semantic, functional and instance incompatibilities in our approach. Although this work is based on several models and standards, we have improved them by combining their contributions and developing a federated architecture that does not require the centralization of demographic information. The solution is thus a good approach to face integration problems and the applied methodology can be easily extended to other tasks involved in the healthcare organization.

Reconstruction of disease transmission rates: Applications to measles, dengue, and influenza.

PubMed

Lange, Alexander

2016-07-07

Transmission rates are key in understanding the spread of infectious diseases. Using the framework of compartmental models, we introduce a simple method to reconstruct time series of transmission rates directly from incidence or disease-related mortality data. The reconstruction employs differential equations, which model the time evolution of infective stages and strains. Being sensitive to initial values, the method produces asymptotically correct solutions. The computations are fast, with time complexity being quadratic. We apply the reconstruction to data of measles (England and Wales, 1948-1967), dengue (Thailand, 1982-1999), and influenza (U.S., 1910-1927). The Measles example offers comparison with earlier work. Here we re-investigate reporting corrections, include and exclude demographic information. The dengue example deals with the failure of vector-control measures in reducing dengue hemorrhagic fever (DHF) in Thailand. Two competing mechanisms have been held responsible: strain interaction and demographic transitions. Our reconstruction reveals that both explanations are possible, showing that the increase in DHF cases is consistent with decreasing transmission rates resulting from reduced vector counts. The flu example focuses on the 1918/1919 pandemic, examining the transmission rate evolution for an invading strain. Our analysis indicates that the pandemic strain could have circulated in the population for many months before the pandemic was initiated by an event of highly increased transmission. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modelling the effects of penetrance and family size on rates of sporadic and familial disease.

PubMed

Al-Chalabi, Ammar; Lewis, Cathryn M

2011-01-01

Many complex diseases show a diversity of inheritance patterns ranging from familial disease, manifesting with autosomal dominant inheritance, through to simplex families in which only one person is affected, manifesting as apparently sporadic disease. The role of ascertainment bias in generating apparent patterns of inheritance is often overlooked. We therefore explored the role of two key parameters that influence ascertainment, penetrance and family size, in rates of observed familiality. We develop a mathematical model of familiality of disease, with parameters for penetrance, mutation frequency and family size, and test this in a complex disease: amyotrophic lateral sclerosis. Monogenic, high-penetrance variants can explain patterns of inheritance in complex diseases and account for a large proportion of those with no apparent family history. With current demographic trends, rates of familiality will drop further. For example, a variant with penetrance 0.5 will cause apparently sporadic disease in 12% of families of size 10, but 80% of families of size 1. A variant with penetrance 0.9 has only an 11% chance of appearing sporadic in families of a size similar to those of Ireland in the past, compared with 57% in one-child families like many in China. These findings have implications for genetic counselling, disease classification and the design of gene-hunting studies. The distinction between familial and apparently sporadic disease should be considered artificial. Copyright © 2011 S. Karger AG, Basel.

The Earth's Population Can Reach 14 Billion in the 23rd Century without Significant Adverse Effects on Survivability.

PubMed

Krapivin, Vladimir F; Varotsos, Costas A; Soldatov, Vladimir Yu

2017-08-07

This paper presents the results obtained from the study of the sustainable state between nature and human society on a global scale, focusing on the most critical interactions between the natural and anthropogenic processes. Apart from the conventional global models, the basic tool employed herein is the newly proposed complex model entitled "nature-society system (NSS) model", through which a reliable modeling of the processes taking place in the global climate-nature-society system (CNSS) is achieved. This universal tool is mainly based on the information technology that allows the adaptive conformance of the parametric and functional space of this model. The structure of this model includes the global biogeochemical cycles, the hydrological cycle, the demographic processes and a simple climate model. In this model, the survivability indicator is used as a criterion for the survival of humanity, which defines a trend in the dynamics of the total biomass of the biosphere, taking into account the trends of the biocomplexity dynamics of the land and hydrosphere ecosystems. It should be stressed that there are no other complex global models comparable to those of the CNSS model developed here. The potential of this global model is demonstrated through specific examples in which the classification of the terrestrial ecosystem is accomplished by separating 30 soil-plant formations for geographic pixels 4° × 5°. In addition, humanity is considered to be represented by three groups of economic development status (high, transition, developing) and the World Ocean is parameterized by three latitude zones (low, middle, high). The modelling results obtained show the dynamics of the CNSS at the beginning of the 23rd century, according to which the world population can reach the level of 14 billion without the occurrence of major negative impacts.

Characteristics of COPD Patients Using United States Emergency Care or Hospitalization

PubMed Central

Kumbhare, Suchit D.; Beiko, Tatsiana; Wilcox, Susan R.; Strange, Charlie

2016-01-01

Rationale: Several chronic obstructive pulmonary disease (COPD) studies have evaluated risk factors for emergency department (ED) visits or hospitalizations, and found insufficient data available about social and demographic factors that drive these behaviors. This U.S. study was designed to describe the characteristics of COPD patients with ED visits or a hospitalization and to investigate how often common COPD comorbidities are present in these individuals. Methods: Data for 7180 COPD patients regarding demographic factors, comorbidities, smoking status, and ED visits or hospitalization was obtained from the 2012 Behavioral Risk Factor Surveillance System (BRFSS) survey. Logistic regression analysis was used to adjust demographic factors and smoking status to model the correlation between patients with ED visits or hospitalizations and morbidities generating odds ratios (OR) and confidence intervals (CI). Results: Among diagnosed COPD patients in the BRFSS, 16.5% had ED visits or hospitalization in the previous year. These individuals were younger, had a lower socio-economic status (lower education, lower income, and more often unemployed) and 23.4% of the individuals could not visit a doctor because of the financial difficulties compared to 16.7% who had no visit (p<0.0001 for all comparisons). The prevalence of comorbidities was higher in those with ED visits or hospitalization compared to those without. Conclusion: In a population representative of COPD patients, lower socio-economic status and higher comorbidities are associated with ED visits or hospitalization. Studies are needed to further elucidate the complex relationship between COPD, comorbidities, and ED visits or hospitalization. PMID:28848878

DEMOGRAPHIC CONSEQUENCES OF COALESCENCE IN SPORELING POPULATIONS OF MAZZAELLA LAMINARIOIDES (GIGARTINALES, RHODOPHYTA)(1).

PubMed

Santelices, B; Alvarado, J L

2008-06-01

Coalescing macroalgae are ecologically important members of intertidal and shallow subtidal communities. However, we still lack quantitative information on the demographic consequences of coalescence. Using demographic models developed for modular invertebrates, we studied the demography of settlement and early recruitment in the coalescing macroalga Mazzaella laminarioides (Bory) Fredericq. Permanently marked microscopic fields on laboratory-incubated and field-incubated plates were monitored regularly (at 15, 30, 45, and 60 d) using image analysis techniques to evaluate the relative importance of settler abundance, mortality, coalescence (fusion), and fission on the changes in size and numbers of recruits. On the plates, spores settled individually or in groups. Over time, spores in close proximity may coalesce, resulting in a mixture of unisporic and multisporic crusts. When new spores arrive, they may or may not coalesce with previously settled crusts. Coalescence and mortality reduce the number of sporelings, but coalescence increases the size of the sporelings, thereby reducing further probability of sporeling mortality. Crust fissions are negligible in frequency, while the frequency of coalescence increases from ∼25% after only 3 d, to ∼75% after 60 d. Thus, as a result of variable settlement, mortality, and coalescence, any area colonized by M. laminarioides would contain a mixture of crusts of different sizes, ages, and genetic constitution. The interactions between the above three processes create a more complex survivorship curve than the ones known for unitary organisms. © 2008 Phycological Society of America.

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

EPA Science Inventory

Spatial demographic models can help guide monitoring and management activities targeting at-risk species, even in cases where baseline data are lacking. Here, we provide an example of how site-specific changes in land-use and other anthropogenic stressors can be incorporated int...

Demographic matrix model for informing swallow-wort (Vincetoxicum spp.) biological control

USDA-ARS?s Scientific Manuscript database

Demographic matrix modeling of plant populations can be a powerful tool to identify key life stage transitions that contribute the most to population growth of an invasive plant and hence should be targeted for disruption (weak links) by biological control and/or other control tactics. Therefore, t...

A projection of lesser prairie chicken (Tympanuchus pallidicinctus) populations range-wide

USGS Publications Warehouse

Cummings, Jonathan W.; Converse, Sarah J.; Moore, Clinton T.; Smith, David R.; Nichols, Clay T.; Allan, Nathan L.; O'Meilia, Chris M.

2017-08-09

We built a population viability analysis (PVA) model to predict future population status of the lesser prairie-chicken (Tympanuchus pallidicinctus, LEPC) in four ecoregions across the species’ range. The model results will be used in the U.S. Fish and Wildlife Service's (FWS) Species Status Assessment (SSA) for the LEPC. Our stochastic projection model combined demographic rate estimates from previously published literature with demographic rate estimates that integrate the influence of climate conditions. This LEPC PVA projects declining populations with estimated population growth rates well below 1 in each ecoregion regardless of habitat or climate change. These results are consistent with estimates of LEPC population growth rates derived from other demographic process models. Although the absolute magnitude of the decline is unlikely to be as low as modeling tools indicate, several different lines of evidence suggest LEPC populations are declining.

Comparing Mammography Abnormality Features and Genetic Variants in the Prediction of Breast Cancer in Women Recommended for Breast Biopsy

PubMed Central

Burnside, Elizabeth S.; Liu, Jie; Wu, Yirong; Onitilo, Adedayo A.; McCarty, Catherine; Page, C. David; Peissig, Peggy; Trentham-Dietz, Amy; Kitchner, Terrie; Fan, Jun; Yuan, Ming

2015-01-01

Rationale and Objectives The discovery of germline genetic variants associated with breast cancer has engendered interest in risk stratification for improved, targeted detection and diagnosis. However, there has yet to be a comparison of the predictive ability of these genetic variants with mammography abnormality descriptors. Materials and Methods Our IRB-approved, HIPAA-compliant study utilized a personalized medicine registry in which participants consented to provide a DNA sample and participate in longitudinal follow-up. In our retrospective, age-matched, case-controlled study of 373 cases and 395 controls who underwent breast biopsy, we collected risk factors selected a priori based on the literature including: demographic variables based on the Gail model, common germline genetic variants, and diagnostic mammography findings according to BI-RADS. We developed predictive models using logistic regression to determine the predictive ability of: 1) demographic variables, 2) 10 selected genetic variants, or 3) mammography BI-RADS features. We evaluated each model in turn by calculating a risk score for each patient using 10-fold cross validation; used this risk estimate to construct ROC curves; and compared the AUC of each using the DeLong method. Results The performance of the regression model using demographic risk factors was not statistically different from the model using genetic variants (p=0.9). The model using mammography features (AUC = 0.689) was superior to both the demographic model (AUC = .598; p<0.001) and the genetic model (AUC = .601; p<0.001). Conclusion BI-RADS features exceeded the ability of demographic and 10 selected germline genetic variants to predict breast cancer in women recommended for biopsy. PMID:26514439

Demographic faultlines: a meta-analysis of the literature.

PubMed

Thatcher, Sherry M B; Patel, Pankaj C

2011-11-01

We propose and test a theoretical model focusing on antecedents and consequences of demographic faultlines. We also posit contingencies that affect overall team dynamics in the context of demographic faultlines, such as the study setting and performance measurement. Using meta-analysis structural equation modeling with a final data set consisting of 311 data points (i.e., k [predictor-criterion relationships]), from 39 studies that were obtained from 36 papers with a total sample size of 24,388 individuals in 4,366 teams, we found that sex and racial diversity increased demographic faultline strength more than did diversity on the attributes of functional background, educational background, age, and tenure. Demographic faultline strength was found to increase task and relationship conflict as well as decrease team cohesion. Furthermore, although demographic faultline strength decreased both team satisfaction and team performance, there was a stronger decrease in team performance than in team satisfaction. The strength of these relationships increased when the study was conducted in the lab rather than in the field. We describe the theoretical and practical implications of these findings for advancing the study of faultlines. (c) 2011 APA, all rights reserved.

Transcultural perspectives in nursing administration.

PubMed

Andrews, M M

1998-11-01

Population demographics are reshaping the healthcare work force with respect to race, ethnicity, gender, national origin, sexual orientation, age, handicap, disability, and related factors as national sensitivity to various forms of diversity grows. Given the demographic trends, it is inevitable that nurse administrators will need skill in transcultural administration as they manage diversity and identify the cultural origins of conflict in the multicultural workplace. Culture influences the manner in which administrators, staff and patients perceive, identify, define and solve problems. In this article, the complex and interrelated factors that influence workplace diversity are examined.

A climate for speciation: rapid spatial diversification within the Sorex cinereus complex of shrews

USGS Publications Warehouse

Hope, Andrew G.; Speer, Kelly A.; Demboski, John R.; Talbot, Sandra L.; Cook, Joseph A.

2012-01-01

The cyclic climate regime of the late Quaternary caused dramatic environmental change at high latitudes. Although these events may have been brief in periodicity from an evolutionary standpoint, multiple episodes of allopatry and divergence have been implicated in rapid radiations of a number of organisms. Shrews of the Sorex cinereus complex have long challenged taxonomists due to similar morphology and parapatric geographic ranges. Here, multi-locus phylogenetic and demographic assessments using a coalescent framework were combined to investigate spatiotemporal evolution of 13 nominal species with a widespread distribution throughout North America and across Beringia into Siberia. For these species, we first test a hypothesis of recent differentiation in response to Pleistocene climate versus more ancient divergence that would coincide with pre-Pleistocene perturbations. We then investigate the processes driving diversification over multiple continents. Our genetic analyses highlight novel diversity within these morphologically conserved mammals and clarify relationships between geographic distribution and evolutionary history. Demography within and among species indicates both regional stability and rapid expansion. Ancestral ecological differentiation coincident with early cladogenesis within the complex enabled alternating and repeated episodes of allopatry and expansion where successive glacial and interglacial phases each promoted divergence. The Sorex cinereus complex constitutes a valuable model for future comparative assessments of evolution in response to cyclic environmental change.

SNP by SNP by environment interaction network of alcoholism.

PubMed

Zollanvari, Amin; Alterovitz, Gil

2017-03-14

Alcoholism has a strong genetic component. Twin studies have demonstrated the heritability of a large proportion of phenotypic variance of alcoholism ranging from 50-80%. The search for genetic variants associated with this complex behavior has epitomized sequence-based studies for nearly a decade. The limited success of genome-wide association studies (GWAS), possibly precipitated by the polygenic nature of complex traits and behaviors, however, has demonstrated the need for novel, multivariate models capable of quantitatively capturing interactions between a host of genetic variants and their association with non-genetic factors. In this regard, capturing the network of SNP by SNP or SNP by environment interactions has recently gained much interest. Here, we assessed 3,776 individuals to construct a network capable of detecting and quantifying the interactions within and between plausible genetic and environmental factors of alcoholism. In this regard, we propose the use of first-order dependence tree of maximum weight as a potential statistical learning technique to delineate the pattern of dependencies underpinning such a complex trait. Using a predictive based analysis, we further rank the genes, demographic factors, biological pathways, and the interactions represented by our SNP [Formula: see text]SNP[Formula: see text]E network. The proposed framework is quite general and can be potentially applied to the study of other complex traits.

Bayesian History Matching of Complex Infectious Disease Models Using Emulation: A Tutorial and a Case Study on HIV in Uganda

PubMed Central

Andrianakis, Ioannis; Vernon, Ian R.; McCreesh, Nicky; McKinley, Trevelyan J.; Oakley, Jeremy E.; Nsubuga, Rebecca N.; Goldstein, Michael; White, Richard G.

2015-01-01

Advances in scientific computing have allowed the development of complex models that are being routinely applied to problems in disease epidemiology, public health and decision making. The utility of these models depends in part on how well they can reproduce empirical data. However, fitting such models to real world data is greatly hindered both by large numbers of input and output parameters, and by long run times, such that many modelling studies lack a formal calibration methodology. We present a novel method that has the potential to improve the calibration of complex infectious disease models (hereafter called simulators). We present this in the form of a tutorial and a case study where we history match a dynamic, event-driven, individual-based stochastic HIV simulator, using extensive demographic, behavioural and epidemiological data available from Uganda. The tutorial describes history matching and emulation. History matching is an iterative procedure that reduces the simulator's input space by identifying and discarding areas that are unlikely to provide a good match to the empirical data. History matching relies on the computational efficiency of a Bayesian representation of the simulator, known as an emulator. Emulators mimic the simulator's behaviour, but are often several orders of magnitude faster to evaluate. In the case study, we use a 22 input simulator, fitting its 18 outputs simultaneously. After 9 iterations of history matching, a non-implausible region of the simulator input space was identified that was times smaller than the original input space. Simulator evaluations made within this region were found to have a 65% probability of fitting all 18 outputs. History matching and emulation are useful additions to the toolbox of infectious disease modellers. Further research is required to explicitly address the stochastic nature of the simulator as well as to account for correlations between outputs. PMID:25569850

[Older workers and employment].

PubMed

Stössel, U

2008-03-01

Demographic change with its impact on the employment system and the length of work challenges most of the highly industrialized countries. From the point of health sciences the article will discuss findings about whether a prolongation of employment time seems to make sense and which limitations must be reflected. Therefore labour force participation of older workers will be demonstrated before employability as a construct of physical, psychological and social capacity is discussed. With these reflections in mind, the role of an integrated occupational health care approach will be stressed to discuss in which way this can contribute to healthier working conditions for older workers. The complex nature of the problem makes complex solutions necessary, which are not restricted to simple workplace health promotion campaigns. They have to be part of a sophisticated occupational health management system. The rising number of projects and initiatives in this field suggest that the challenges have been recognized and accepted; however we are not able to speak about the implementation of these models already throughout the country.

A Parallel Sliding Region Algorithm to Make Agent-Based Modeling Possible for a Large-Scale Simulation: Modeling Hepatitis C Epidemics in Canada.

PubMed

Wong, William W L; Feng, Zeny Z; Thein, Hla-Hla

2016-11-01

Agent-based models (ABMs) are computer simulation models that define interactions among agents and simulate emergent behaviors that arise from the ensemble of local decisions. ABMs have been increasingly used to examine trends in infectious disease epidemiology. However, the main limitation of ABMs is the high computational cost for a large-scale simulation. To improve the computational efficiency for large-scale ABM simulations, we built a parallelizable sliding region algorithm (SRA) for ABM and compared it to a nonparallelizable ABM. We developed a complex agent network and performed two simulations to model hepatitis C epidemics based on the real demographic data from Saskatchewan, Canada. The first simulation used the SRA that processed on each postal code subregion subsequently. The second simulation processed the entire population simultaneously. It was concluded that the parallelizable SRA showed computational time saving with comparable results in a province-wide simulation. Using the same method, SRA can be generalized for performing a country-wide simulation. Thus, this parallel algorithm enables the possibility of using ABM for large-scale simulation with limited computational resources.

Consequences of parameterization and structure of applied demographic models: a comment on Pardini et al. (2009)

USDA-ARS?s Scientific Manuscript database

In a recently published study, Pardini et al. (2009, hereafter "PDCK" after the authors' initials) developed a demographic model of the invasive weed Alliaria petiolata (garlic mustard, Brassicaceae [M. Bieb] Cavara and Grande). This was then used to identify optimal stages in the plant's life histo...

Demographic Accounting and Model-Building. Education and Development Technical Reports.

ERIC Educational Resources Information Center

Stone, Richard

This report describes and develops a model for coordinating a variety of demographic and social statistics within a single framework. The framework proposed, together with its associated methods of analysis, serves both general and specific functions. The general aim of these functions is to give numerical definition to the pattern of society and…

Pre-release biological control agent recommendations for swallow-wort (Vincetoxicum spp.) informed by demographic matrix models

USDA-ARS?s Scientific Manuscript database

Weed biological control workers have advocated for the advance assessment of agent efficacy in order to minimize the release of host-specific but ineffective agents. One method involves demographic matrix modeling of target weed populations in order to identify plant life stage transitions that cont...

Risk-adjusted capitation based on the Diagnostic Cost Group Model: an empirical evaluation with health survey information.

PubMed Central

Lamers, L M

1999-01-01

OBJECTIVE: To evaluate the predictive accuracy of the Diagnostic Cost Group (DCG) model using health survey information. DATA SOURCES/STUDY SETTING: Longitudinal data collected for a sample of members of a Dutch sickness fund. In the Netherlands the sickness funds provide compulsory health insurance coverage for the 60 percent of the population in the lowest income brackets. STUDY DESIGN: A demographic model and DCG capitation models are estimated by means of ordinary least squares, with an individual's annual healthcare expenditures in 1994 as the dependent variable. For subgroups based on health survey information, costs predicted by the models are compared with actual costs. Using stepwise regression procedures a subset of relevant survey variables that could improve the predictive accuracy of the three-year DCG model was identified. Capitation models were extended with these variables. DATA COLLECTION/EXTRACTION METHODS: For the empirical analysis, panel data of sickness fund members were used that contained demographic information, annual healthcare expenditures, and diagnostic information from hospitalizations for each member. In 1993, a mailed health survey was conducted among a random sample of 15,000 persons in the panel data set, with a 70 percent response rate. PRINCIPAL FINDINGS: The predictive accuracy of the demographic model improves when it is extended with diagnostic information from prior hospitalizations (DCGs). A subset of survey variables further improves the predictive accuracy of the DCG capitation models. The predictable profits and losses based on survey information for the DCG models are smaller than for the demographic model. Most persons with predictable losses based on health survey information were not hospitalized in the preceding year. CONCLUSIONS: The use of diagnostic information from prior hospitalizations is a promising option for improving the demographic capitation payment formula. This study suggests that diagnostic information from outpatient utilization is complementary to DCGs in predicting future costs. PMID:10029506

Bayesian inferences suggest that Amazon Yunga Natives diverged from Andeans less than 5000 ybp: implications for South American prehistory.

PubMed

Scliar, Marilia O; Gouveia, Mateus H; Benazzo, Andrea; Ghirotto, Silvia; Fagundes, Nelson J R; Leal, Thiago P; Magalhães, Wagner C S; Pereira, Latife; Rodrigues, Maira R; Soares-Souza, Giordano B; Cabrera, Lilia; Berg, Douglas E; Gilman, Robert H; Bertorelle, Giorgio; Tarazona-Santos, Eduardo

2014-09-30

Archaeology reports millenary cultural contacts between Peruvian Coast-Andes and the Amazon Yunga, a rainforest transitional region between Andes and Lower Amazonia. To clarify the relationships between cultural and biological evolution of these populations, in particular between Amazon Yungas and Andeans, we used DNA-sequence data, a model-based Bayesian approach and several statistical validations to infer a set of demographic parameters. We found that the genetic diversity of the Shimaa (an Amazon Yunga population) is a subset of that of Quechuas from Central-Andes. Using the Isolation-with-Migration population genetics model, we inferred that the Shimaa ancestors were a small subgroup that split less than 5300 years ago (after the development of complex societies) from an ancestral Andean population. After the split, the most plausible scenario compatible with our results is that the ancestors of Shimaas moved toward the Peruvian Amazon Yunga and incorporated the culture and language of some of their neighbors, but not a substantial amount of their genes. We validated our results using Approximate Bayesian Computations, posterior predictive tests and the analysis of pseudo-observed datasets. We presented a case study in which model-based Bayesian approaches, combined with necessary statistical validations, shed light into the prehistoric demographic relationship between Andeans and a population from the Amazon Yunga. Our results offer a testable model for the peopling of this large transitional environmental region between the Andes and the Lower Amazonia. However, studies on larger samples and involving more populations of these regions are necessary to confirm if the predominant Andean biological origin of the Shimaas is the rule, and not the exception.

A Complex System of Glacial Sub-Refugia Drives Endemic Freshwater Biodiversity on the Tibetan Plateau.

PubMed

Clewing, Catharina; Albrecht, Christian; Wilke, Thomas

2016-01-01

Although only relatively few freshwater invertebrate families are reported from the Tibetan Plateau, the degree of endemism may be high. Many endemic lineages occur within permafrost areas, raising questions about the existence of isolated intra-plateau glacial refugia. Moreover, if such refugia existed, it might be instructive to learn whether they were associated with lakes or with more dynamic ecosystems such as ponds, wetlands, or springs. To study these hypotheses, we used pulmonate snails of the plateau-wide distributed genus Radix as model group and the Lake Donggi Cona drainage system, located in the north-eastern part of the plateau, as model site. First, we performed plateau-wide phylogenetic analyses using mtDNA data to assess the overall relationships of Radix populations inhabiting the Lake Donggi Cona system for revealing refugial lineages. We then conducted regional phylogeographical analyses applying a combination of mtDNA and nuclear AFLP markers to infer the local structure and demographic history of the most abundant endemic Radix clade for identifying location and type of (sub-)refugia within the drainage system. Our phylogenetic analysis showed a high diversity of Radix lineages in the Lake Donggi Cona system. Subsequent phylogeographical analyses of the most abundant endemic clade indicated a habitat-related clustering of genotypes and several Late Pleistocene spatial/demographic expansion events. The most parsimonious explanation for these patterns would be a scenario of an intra-plateau glacial refugium in the Lake Donggi Cona drainage system, which might have consisted of isolated sub-refugia. Though the underlying processes remain unknown, an initial separation of lake and watershed populations could have been triggered by lake-level fluctuations before and during the Last Glacial Maximum. This study inferred the first intra-plateau refugium for freshwater animals on the Tibetan Plateau. It thus sheds new light on the evolutionary history of its endemic taxa and provides important insights into the complex refugial history of a high-altitude ecosystem.

Modelling determinants, impact, and space-time risk of age-specific mortality in rural South Africa: integrating methods to enhance policy relevance.

PubMed

Sartorius, Benn

2013-01-24

There is a lack of reliable data in developing countries to inform policy and optimise resource allocation. Health and socio-demographic surveillance sites (HDSS) have the potential to address this gap. Mortality levels and trends have previously been documented in rural South Africa. However, complex space-time clustering of mortality, determinants, and their impact has not been fully examined. To integrate advanced methods enhance the understanding of the dynamics of mortality in space-time, to identify mortality risk factors and population attributable impact, to relate disparities in risk factor distributions to spatial mortality risk, and thus, to improve policy planning and resource allocation. Agincourt HDSS supplied data for the period 1992-2008. Advanced spatial techniques were used to identify significant age-specific mortality 'hotspots' in space-time. Multivariable Bayesian models were used to assess the effects of the most significant covariates on mortality. Disparities in risk factor profiles in identified hotspots were assessed. Increasing HIV-related mortality and a subsequent decrease possibly attributable to antiretroviral therapy introduction are evident in this rural population. Distinct space-time clustering and variation (even in a small geographic area) of mortality were observed. Several known and novel risk factors were identified, and population impact was quantified. Significant differences in the risk factor profiles of the identified 'hotspots' included ethnicity; maternal, partner, and household deaths; household head demographics; migrancy; education; and poverty. A complex interaction of highly attributable multilevel factors continues to demonstrate differential space-time influences on mortality risk (especially for HIV). High-risk households and villages displayed differential risk factor profiles. This integrated approach could prove valuable to decision makers. Tailored interventions for specific child and adult high-risk mortality areas are needed, such as preventing vertical transmission, ensuring maternal survival, and improving water and sanitation infrastructure. This framework can be applied in other settings within the region.

Borders as membranes :metaphors and models for improved policy in border regions.

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

Malczynski, Leonard A.; Passell, Howard David; Forster, Craig B.

Political borders are controversial and contested spaces. In an attempt to better understand movement along and through political borders, this project applied the metaphor of a membrane to look at how people, ideas, and things ''move'' through a border. More specifically, the research team employed this metaphor in a system dynamics framework to construct a computer model to assess legal and illegal migration on the US-Mexico border. Employing a metaphor can be helpful, as it was in this project, to gain different perspectives on a complex system. In addition to the metaphor, the multidisciplinary team utilized an array of methodsmore » to gather data including traditional literature searches, an experts workshop, a focus group, interviews, and culling expertise from the individuals on the research team. Results from the qualitative efforts revealed strong social as well as economic drivers that motivate individuals to cross the border legally. Based on the information gathered, the team concluded that legal migration dynamics were of a scope we did not want to consider hence, available demographic models sufficiently capture migration at the local level. Results from both the quantitative and qualitative data searches were used to modify a 1977 border model to demonstrate the dynamic nature of illegal migration. Model runs reveal that current US-policies based on neo-classic economic theory have proven ineffective in curbing illegal migration, and that proposed enforcement policies are also likely to be ineffective. We suggest, based on model results, that improvement in economic conditions within Mexico may have the biggest impact on illegal migration to the U.S. The modeling also supports the views expressed in the current literature suggesting that demographic and economic changes within Mexico are likely to slow illegal migration by 2060 with no special interventions made by either government.« less

Islands increase genetic subdivision and disrupt patterns of connectivity of intertidal snails in a complex archipelago.

PubMed

Johnson, Michael S; Black, Robert

2006-12-01

The view that marine species with planktonic dispersal have highly connected, demographically open populations is giving way to recognition that populations may often be largely self-recruiting, or demographically closed. This raises the question of what local conditions might favor isolation of populations. To test the importance of islands for local isolation in species with planktonic larvae, we examined allozyme variation among 35 populations of the intertidal snail Austrocochlea constricta in the Houtman Abrolhos Islands, Western Australia, spanning 60 km. Heterogeneity of allozyme frequencies among populations was high, with average F(ST) of 0.237, indicating highly localized populations. Increased subdivision was associated with islands at different scales: between island groups, separated by deep water gaps, and between disconnected sets of islands within groups. At short distances, up to two km, subdivision increased fivefold between islands compared with that between populations on the same island. Along 11 km of continuous, sheltered shore, there was isolation by distance but among a linear series of islands over similar distance, there was greater subdivision at short distances but no association with distance. These patterns had been seen previously in the direct-developing snail Bembicium vittatum, but its finding in A. constricta confirms for a planktonic disperser the importance of this complex archipelago for both retention of locally produced larvae and disruption of patterns of connectivity. Taken together, these results indicate that islands can increase both the "open" and the "closed" components of recruitment and that applicable models of genetic connectivity depend substantially on local conditions.

Holocene Demographic Changes and the Emergence of Complex Societies in Prehistoric Australia

PubMed Central

Williams, Alan N.; Ulm, Sean; Turney, Chris S. M.; Rohde, David; White, Gentry

2015-01-01

A continental-scale model of Holocene Australian hunter-gatherer demography and mobility is generated using radiocarbon data and geospatial techniques. Results show a delayed expansion and settlement of much of Australia following the termination of the late Pleistocene until after 9,000 years ago (or 9ka). The onset of the Holocene climatic optimum (9-6ka) coincides with rapid expansion, growth and establishment of regional populations across ~75% of Australia, including much of the arid zone. This diffusion from isolated Pleistocene refugia provides a mechanism for the synchronous spread of pan-continental archaeological and linguistic attributes at this time (e.g. Pama-Nyungan language, Panaramitee art style, backed artefacts). We argue longer patch residence times were possible at the end of the optimum, resulting in a shift to more sedentary lifestyles and establishment of low-level food production in some parts of the continent. The onset of El Niño - Southern Oscillation (ENSO; 4.5-2ka) restricted low-level food production, and resulted in population fragmentation, abandonment of marginal areas, and reduction in ranging territory of ~26%. Importantly, climate amelioration brought about by more pervasive La Niña conditions (post-2ka), resulted in an intensification of the mobility strategies and technological innovations that were developed in the early- to mid-Holocene. These changes resulted in population expansion and utilization of the entire continent. We propose that it was under these demographically packed conditions that the complex social and religious societies observed at colonial contact were formed. PMID:26083101

Genetic structure and invasion history of the house mouse (Mus musculus domesticus) in Senegal, West Africa: a legacy of colonial and contemporary times.

PubMed

Lippens, C; Estoup, A; Hima, M K; Loiseau, A; Tatard, C; Dalecky, A; Bâ, K; Kane, M; Diallo, M; Sow, A; Niang, Y; Piry, S; Berthier, K; Leblois, R; Duplantier, J-M; Brouat, C

2017-08-01

Knowledge of the genetic make-up and demographic history of invasive populations is critical to understand invasion mechanisms. Commensal rodents are ideal models to study whether complex invasion histories are typical of introductions involving human activities. The house mouse Mus musculus domesticus is a major invasive synanthropic rodent originating from South-West Asia. It has been largely studied in Europe and on several remote islands, but the genetic structure and invasion history of this taxon have been little investigated in several continental areas, including West Africa. In this study, we focussed on invasive populations of M. m. domesticus in Senegal. In this focal area for European settlers, the distribution area and invasion spread of the house mouse is documented by decades of data on commensal rodent communities. Genetic variation at one mitochondrial locus and 16 nuclear microsatellite markers was analysed from individuals sampled in 36 sites distributed across the country. A combination of phylogeographic and population genetics methods showed that there was a single introduction event on the northern coast of Senegal, from an exogenous (probably West European) source, followed by a secondary introduction from northern Senegal into a coastal site further south. The geographic locations of these introduction sites were consistent with the colonial history of Senegal. Overall, the marked microsatellite genetic structure observed in Senegal, even between sites located close together, revealed a complex interplay of different demographic processes occurring during house mouse spatial expansion, including sequential founder effects and stratified dispersal due to human transport along major roads.

Duplication and population dynamics shape historic patterns of selection and genetic variation at the major histocompatibility complex in rodents

PubMed Central

Winternitz, Jamie C; Wares, John P

2013-01-01

Genetic variation at the major histocompatibility complex (MHC) is vitally important for wildlife populations to respond to pathogen threats. As natural populations can fluctuate greatly in size, a key issue concerns how population cycles and bottlenecks that could reduce genetic diversity will influence MHC genes. Using 454 sequencing, we characterized genetic diversity at the DRB Class II locus in montane voles (Microtus montanus), a North American rodent that regularly undergoes high-amplitude fluctuations in population size. We tested for evidence of historic balancing selection, recombination, and gene duplication to identify mechanisms maintaining allelic diversity. Counter to our expectations, we found strong evidence of purifying selection acting on the DRB locus in montane voles. We speculate that the interplay between population fluctuations and gene duplication might be responsible for the weak evidence of historic balancing selection and strong evidence of purifying selection detected. To further explore this idea, we conducted a phylogenetically controlled comparative analysis across 16 rodent species with varying demographic histories and MHC duplication events (based on the maximum number of alleles detected per individual). On the basis of phylogenetic generalized linear model-averaging, we found evidence that the estimated number of duplicated loci was positively related to allelic diversity and, surprisingly, to the strength of purifying selection at the DRB locus. Our analyses also revealed that species that had undergone population bottlenecks had lower allelic richness than stable species. This study highlights the need to consider demographic history and genetic structure alongside patterns of natural selection to understand resulting patterns of genetic variation at the MHC. PMID:23789067

Putting the "ecology" into environmental flows: ecological dynamics and demographic modelling.

PubMed

Shenton, Will; Bond, Nicholas R; Yen, Jian D L; Mac Nally, Ralph

2012-07-01

There have been significant diversions of water from rivers and streams around the world; natural flow regimes have been perturbed by dams, barriers and excessive extractions. Many aspects of the ecological 'health' of riverine systems have declined due to changes in water flows, which has stimulated the development of thinking about the maintenance and restoration of these systems, which we refer to as environmental flow methodologies (EFMs). Most existing EFMs cannot deliver information on the population viability of species because they: (1) use habitat suitability as a proxy for population status; (2) use historical time series (usually of short duration) to forecast future conditions and flow sequences; (3) cannot, or do not, handle extreme flow events associated with climate variability; and (4) assume process stationarity for flow sequences, which means the past sequences are treated as good indicators of the future. These assumptions undermine the capacity of EFMs to properly represent risks associated with different flow management options; assumption (4) is untenable given most climate-change predictions. We discuss these concerns and advocate the use of demographic modelling as a more appropriate tool for linking population dynamics to flow regime change. A 'meta-species' approach to demographic modelling is discussed as a useful step from habitat based models towards modelling strategies grounded in ecological theory when limited data are available on flow-demographic relationships. Data requirements of demographic models will undoubtedly expose gaps in existing knowledge, but, in so doing, will strengthen future efforts to link changes in river flows with their ecological consequences.

Putting the "Ecology" into Environmental Flows: Ecological Dynamics and Demographic Modelling

NASA Astrophysics Data System (ADS)

Shenton, Will; Bond, Nicholas R.; Yen, Jian D. L.; Mac Nally, Ralph

2012-07-01

There have been significant diversions of water from rivers and streams around the world; natural flow regimes have been perturbed by dams, barriers and excessive extractions. Many aspects of the ecological `health' of riverine systems have declined due to changes in water flows, which has stimulated the development of thinking about the maintenance and restoration of these systems, which we refer to as environmental flow methodologies (EFMs). Most existing EFMs cannot deliver information on the population viability of species because they: (1) use habitat suitability as a proxy for population status; (2) use historical time series (usually of short duration) to forecast future conditions and flow sequences; (3) cannot, or do not, handle extreme flow events associated with climate variability; and (4) assume process stationarity for flow sequences, which means the past sequences are treated as good indicators of the future. These assumptions undermine the capacity of EFMs to properly represent risks associated with different flow management options; assumption (4) is untenable given most climate-change predictions. We discuss these concerns and advocate the use of demographic modelling as a more appropriate tool for linking population dynamics to flow regime change. A `meta-species' approach to demographic modelling is discussed as a useful step from habitat based models towards modelling strategies grounded in ecological theory when limited data are available on flow-demographic relationships. Data requirements of demographic models will undoubtedly expose gaps in existing knowledge, but, in so doing, will strengthen future efforts to link changes in river flows with their ecological consequences.

Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset.

PubMed

Luo, Wei; Nguyen, Thin; Nichols, Melanie; Tran, Truyen; Rana, Santu; Gupta, Sunil; Phung, Dinh; Venkatesh, Svetha; Allender, Steve

2015-01-01

For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.

Demographic modelling with whole-genome data reveals parallel origin of similar Pundamilia cichlid species after hybridization.

PubMed

Meier, Joana I; Sousa, Vitor C; Marques, David A; Selz, Oliver M; Wagner, Catherine E; Excoffier, Laurent; Seehausen, Ole

2017-01-01

Modes and mechanisms of speciation are best studied in young species pairs. In older taxa, it is increasingly difficult to distinguish what happened during speciation from what happened after speciation. Lake Victoria cichlids in the genus Pundamilia encompass a complex of young species and polymorphic populations. One Pundamilia species pair, P. pundamilia and P. nyererei, is particularly well suited to study speciation because sympatric population pairs occur with different levels of phenotypic differentiation and reproductive isolation at different rocky islands within the lake. Genetic distances between allopatric island populations of the same nominal species often exceed those between the sympatric species. It thus remained unresolved whether speciation into P. nyererei and P. pundamilia occurred once, followed by geographical range expansion and interspecific gene flow in local sympatry, or if the species pair arose repeatedly by parallel speciation. Here, we use genomic data and demographic modelling to test these alternative evolutionary scenarios. We demonstrate that gene flow plays a strong role in shaping the observed patterns of genetic similarity, including both gene flow between sympatric species and gene flow between allopatric populations, as well as recent and early gene flow. The best supported model for the origin of P. pundamilia and P. nyererei population pairs at two different islands is one where speciation happened twice, whereby the second speciation event follows shortly after introgression from an allopatric P. nyererei population that arose earlier. Our findings support the hypothesis that very similar species may arise repeatedly, potentially facilitated by introgressed genetic variation. © 2016 John Wiley & Sons Ltd.

Unmet/met need for contraception and self-reported abortion in Ghana.

PubMed

Amo-Adjei, Joshua; Darteh, Eugene K M

2017-10-01

Unmet need for contraception in several sub-Saharan African countries, including Ghana, remains high, with implications for unintended pregnancies and unsafe abortion, associated maternal morbidity and mortality. In this paper, we analysed for any associations between unmet/met need for contraception and the prevalence of abortion. The paper utilizes the 2014 Ghana Demographic Health Survey dataset. Applying descriptive statistics initially, and later, a binary logistic regression, we estimate two different models, taking into account, unmet/met need for contraception (Model 1) and a multivariable one comprising socioeconomic, spatial, cultural and demographic behaviour variables (Model 2) to test the associations between unmet/met need for contraception in Ghana. One-fourth (25%) of sampled women in 2014 had ever had an abortion. The bivariate results showed that women who reported "no unmet" considerably tended to report abortion more than the reference category - not married and no sex in the last 30days. The elevated odds among respondents who indicated "no unmet need" persisted even after controlling for all the relevant confounders. Relatedly, unlike women with an unmet need for spacing, women who desired to limit childbearing had a slightly higher tendency to report an abortion. The linkage between unmet need for contraception appears more complex, particularly when the connections are explored post-abortion. Thus, while an abortion episode is most likely due to unintended pregnancy, contraception may still not be used, after an abortion, probably because of failure, side effects or simply, a dislike for any method. Copyright © 2017 Elsevier B.V. All rights reserved.

Assessing global range expansion in a cryptic species complex: insights from the red seaweed genus Asparagopsis (Florideophyceae).

PubMed

Zanolla, Marianela; Altamirano, María; Carmona, Raquel; De la Rosa, Julio; Souza-Egipsy, Virginia; Sherwood, Alison; Tsiamis, Konstantinos; Barbosa, Ana Márcia; Muñoz, Antonio Román; Andreakis, Nikos

2018-02-01

The mitochondrial genetic diversity, distribution and invasive potential of multiple cryptic operational taxonomic units (OTUs) of the red invasive seaweed Asparagopsis were assessed by studying introduced Mediterranean and Hawaiian populations. Invasive behavior of each Asparagopsis OTU was inferred from phylogeographic reconstructions, past historical demographic dynamics, recent range expansion assessments and future distributional predictions obtained from demographic models. Genealogical networks resolved Asparagopsis gametophytes and tetrasporophytes into four A. taxiformis and one A. armata cryptic OTUs. Falkenbergia isolates of A. taxiformis L3 were recovered for the first time in the western Mediterranean Sea and represent a new introduction for this area. Neutrality statistics supported past range expansion for A. taxiformis L1 and L2 in Hawaii. On the other hand, extreme geographic expansion and an increase in effective population size were found only for A. taxiformis L2 in the western Mediterranean Sea. Distribution models predicted shifts of the climatically suitable areas and population expansion for A. armata L1 and A. taxiformis L1 and L2. Our integrated study confirms a high invasive risk for A. taxiformis L1 and L2 in temperate and tropical areas. Despite the differences in predictions among modelling approaches, a number of regions were identified as zones with high invasion risk for A. taxiformis L2. Since range shifts are likely climate-driven phenomena, future invasive behavior cannot be excluded for the rest of the lineages. © 2017 Phycological Society of America.

Madeiran Arabidopsis thaliana Reveals Ancient Long-Range Colonization and Clarifies Demography in Eurasia

PubMed Central

Fulgione, Andrea; Koornneef, Maarten; Roux, Fabrice; Hermisson, Joachim; Hancock, Angela M

2018-01-01

Abstract The study of model organisms on islands may shed light on rare long-range dispersal events, uncover signatures of local evolutionary processes, and inform demographic inference on the mainland. Here, we sequenced the genomes of Arabidopsis thaliana samples from the oceanic island of Madeira. These samples include the most diverged worldwide, likely a result of long isolation on the island. We infer that colonization of Madeira happened between 70 and 85 ka, consistent with a propagule dispersal model (of size ≥10), or with an ecological window of opportunity. This represents a clear example of a natural long-range dispersal event in A. thaliana. Long-term effective population size on the island, rather than the founder effect, had the greatest impact on levels of diversity, and rates of coalescence. Our results uncover a selective sweep signature on the ancestral haplotype of a known translocation in Eurasia, as well as the possible importance of the low phosphorous availability in volcanic soils, and altitude, in shaping early adaptations to the island conditions. Madeiran genomes, sheltered from the complexities of continental demography, help illuminate ancient demographic events in Eurasia. Our data support a model in which two separate lineages of A. thaliana, one originating in Africa and the other from the Caucasus expanded and met in Iberia, resulting in a secondary contact zone there. Although previous studies inferred that the westward expansion of A. thaliana coincided with the spread of human agriculture, our results suggest that it happened much earlier (20–40 ka). PMID:29216397

School District Personnel Selection Practices: Exploring the Effects of Demographic Factors on Rural Values within a Person-Organization Fit Model.

ERIC Educational Resources Information Center

Little, Paula S.; Miller, Stephen K.

A study examined the extent to which demographic factors predict rural values in Kentucky public school district hiring officials. Among the demographic factors considered were school district metropolitan classification, school district size, community racial composition, decision makers' position in the organizational hierarchy, and decision…

A Grounded Theory of Sexual Minority Women and Transgender Individuals' Social Justice Activism.

PubMed

Hagen, Whitney B; Hoover, Stephanie M; Morrow, Susan L

2018-01-01

Psychosocial benefits of activism include increased empowerment, social connectedness, and resilience. Yet sexual minority women (SMW) and transgender individuals with multiple oppressed statuses and identities are especially prone to oppression-based experiences, even within minority activist communities. This study sought to develop an empirical model to explain the diverse meanings of social justice activism situated in SMW and transgender individuals' social identities, values, and experiences of oppression and privilege. Using a grounded theory design, 20 SMW and transgender individuals participated in initial, follow-up, and feedback interviews. The most frequent demographic identities were queer or bisexual, White, middle-class women with advanced degrees. The results indicated that social justice activism was intensely relational, replete with multiple benefits, yet rife with experiences of oppression from within and outside of activist communities. The empirically derived model shows the complexity of SMW and transgender individuals' experiences, meanings, and benefits of social justice activism.

The four cultures: Public engagement with science only, art only, neither, or both museums.

PubMed

Shein, Paichi Pat; Li, Yuh-Yuh; Huang, Tai-Chu

2015-11-01

This study uses an art-and-science comparative lens to understand the science culture, particularly the public engagement with science museums. A representational Taiwanese sample of 1863 subjects was categorized into "four cultures," who visit science only, art only, neither, or both museums, resulting in six multivariate logistic regression models. Knowledge of science, interests in scientific and social issues, and socio-demographic variables were considered in the models. Adults with children and males prefer science museums, females prefer art museums, and the young and urban intellects show no strong preference, appearing to be open to both science and art museums. The findings show the complex decisions the public make in visiting museums. It is no longer a strictly science or art decision, as framed by Snow's "The Two Cultures" argument; rather, the possibility of visiting both museums has emerged, a phenomenon we describe as cognitive polyphasia. © The Author(s) 2015.

Applications of genetic data to improve management and conservation of river fishes and their habitats

USGS Publications Warehouse

Scribner, Kim T.; Lowe, Winsor H.; Landguth, Erin L.; Luikart, Gordon; Infante, Dana M.; Whelan, Gary; Muhlfeld, Clint C.

2015-01-01

Environmental variation and landscape features affect ecological processes in fluvial systems; however, assessing effects at management-relevant temporal and spatial scales is challenging. Genetic data can be used with landscape models and traditional ecological assessment data to identify biodiversity hotspots, predict ecosystem responses to anthropogenic effects, and detect impairments to underlying processes. We show that by combining taxonomic, demographic, and genetic data of species in complex riverscapes, managers can better understand the spatial and temporal scales over which environmental processes and disturbance influence biodiversity. We describe how population genetic models using empirical or simulated genetic data quantify effects of environmental processes affecting species diversity and distribution. Our summary shows that aquatic assessment initiatives that use standardized data sets to direct management actions can benefit from integration of genetic data to improve the predictability of disturbance–response relationships of river fishes and their habitats over a broad range of spatial and temporal scales.

Climate-driven range shifts of the king penguin in a fragmented ecosystem

NASA Astrophysics Data System (ADS)

Cristofari, Robin; Liu, Xiaoming; Bonadonna, Francesco; Cherel, Yves; Pistorius, Pierre; Le Maho, Yvon; Raybaud, Virginie; Stenseth, Nils Christian; Le Bohec, Céline; Trucchi, Emiliano

2018-03-01

Range shift is the primary short-term species response to rapid climate change, but it is often hampered by natural or anthropogenic habitat fragmentation. Different critical areas of a species' niche may be exposed to heterogeneous environmental changes and modelling species response under such complex spatial and ecological scenarios presents well-known challenges. Here, we use a biophysical ecological niche model validated through population genomics and palaeodemography to reconstruct past range shifts and identify future vulnerable areas and potential refugia of the king penguin in the Southern Ocean. Integrating genomic and demographic data at the whole-species level with specific biophysical constraints, we present a refined framework for predicting the effect of climate change on species relying on spatially and ecologically distinct areas to complete their life cycle (for example, migratory animals, marine pelagic organisms and central-place foragers) and, in general, on species living in fragmented ecosystems.

Retail Tobacco Exposure: Using Geographic Analysis to Identify Areas With Excessively High Retail Density

PubMed Central

2014-01-01

Introduction: There is great disparity in tobacco outlet density (TOD), with density highest in low-income areas and areas with greater proportions of minority residents, and this disparity may affect cancer incidence. We sought to better understand the nature of this disparity by assessing how these socio-demographic factors relate to TOD at the national level. Methods: Using mixture regression analysis and all of the nearly 65,000 census tracts in the contiguous United States, we aimed to determine the number of latent disparity classes by modeling the relations of proportions of Blacks, Hispanics, and families living in poverty with TOD, controlling for urban/rural status. Results: We identified six disparity classes. There was considerable heterogeneity in relation to TOD for Hispanics in rural settings. For Blacks, there was no relation to TOD in an urban moderate disparity class, and for rural census tracts, the relation was highest in a moderate disparity class. Conclusions: We demonstrated the utility of classifying census tracts on heterogeneity of tobacco risk exposure. This approach provides a better understanding of the complexity of socio-demographic influences of tobacco retailing and creates opportunities for policy makers to more efficiently target areas in greatest need. PMID:23999651

Retail tobacco exposure: using geographic analysis to identify areas with excessively high retail density.

PubMed

Rodriguez, Daniel; Carlos, Heather A; Adachi-Mejia, Anna M; Berke, Ethan M; Sargent, James

2014-02-01

There is great disparity in tobacco outlet density (TOD), with density highest in low-income areas and areas with greater proportions of minority residents, and this disparity may affect cancer incidence. We sought to better understand the nature of this disparity by assessing how these socio-demographic factors relate to TOD at the national level. Using mixture regression analysis and all of the nearly 65,000 census tracts in the contiguous United States, we aimed to determine the number of latent disparity classes by modeling the relations of proportions of Blacks, Hispanics, and families living in poverty with TOD, controlling for urban/rural status. We identified six disparity classes. There was considerable heterogeneity in relation to TOD for Hispanics in rural settings. For Blacks, there was no relation to TOD in an urban moderate disparity class, and for rural census tracts, the relation was highest in a moderate disparity class. We demonstrated the utility of classifying census tracts on heterogeneity of tobacco risk exposure. This approach provides a better understanding of the complexity of socio-demographic influences of tobacco retailing and creates opportunities for policy makers to more efficiently target areas in greatest need.

Prescription Drug Misuse and Sexual Behavior Among Young Adults.

PubMed

Wells, Brooke E; Kelly, Brian C; Rendina, H Jonathon; Parsons, Jeffrey T

2015-01-01

Though research indicates a complex link between substance use and sexual risk behavior, there is limited research on the association between sexual risk behavior and prescription drug misuse. In light of alarming increases in prescription drug misuse and the role of demographic characteristics in sexual risk behavior and outcomes, the current study examined demographic differences (gender, sexual identity, age, relationship status, parental class background, and race/ethnicity) in sexual risk behavior, sexual behavior under the influence of prescription drugs, and sexual risk behavior under the influence of prescription drugs in a sample of 402 young adults (ages 18 to 29) who misused prescription drugs. Nearly half of the sexually active young adult prescription drug misusers in this sample reported recent sex under the influence of prescription drugs; more than three-quarters reported recent sex without a condom; and more than one-third reported recent sex without a condom after using prescription drugs. Zero-inflated Poisson regression models indicated that White race, younger age, higher parental class, and being a heterosexual man were all associated with sexual risk behavior, sex under the influence of prescription drugs, and sexual risk under the influence of prescription drugs. Findings have implications for the targeting of prevention and intervention efforts.

Examining the Link Between Public Transit Use and Active Commuting

PubMed Central

Bopp, Melissa; Gayah, Vikash V.; Campbell, Matthew E.

2015-01-01

Background: An established relationship exists between public transportation (PT) use and physical activity. However, there is limited literature that examines the link between PT use and active commuting (AC) behavior. This study examines this link to determine if PT users commute more by active modes. Methods: A volunteer, convenience sample of adults (n = 748) completed an online survey about AC/PT patterns, demographic, psychosocial, community and environmental factors. t-test compared differences between PT riders and non-PT riders. Binary logistic regression analyses examined the effect of multiple factors on AC and a full logistic regression model was conducted to examine AC. Results: Non-PT riders (n = 596) reported less AC than PT riders. There were several significant relationships with AC for demographic, interpersonal, worksite, community and environmental factors when considering PT use. The logistic multivariate analysis for included age, number of children and perceived distance to work as negative predictors and PT use, feelings of bad weather and lack of on-street bike lanes as a barrier to AC, perceived behavioral control and spouse AC were positive predictors. Conclusions: This study revealed the complex relationship between AC and PT use. Further research should investigate how AC and public transit use are related. PMID:25898405

The Smoking Consequences Questionnaire: Factor structure and predictive validity among Spanish-speaking Latino smokers in the United States.

PubMed

Vidrine, Jennifer Irvin; Vidrine, Damon J; Costello, Tracy J; Mazas, Carlos; Cofta-Woerpel, Ludmila; Mejia, Luz Maria; Wetter, David W

2009-11-01

Much of the existing research on smoking outcome expectancies has been guided by the Smoking Consequences Questionnaire (SCQ ). Although the original version of the SCQ has been modified over time for use in different populations, none of the existing versions have been evaluated for use among Spanish-speaking Latino smokers in the United States. The present study evaluated the factor structure and predictive validity of the 3 previously validated versions of the SCQ--the original, the SCQ-Adult, and the SCQ-Spanish, which was developed with Spanish-speaking smokers in Spain--among Spanish-speaking Latino smokers in Texas. The SCQ-Spanish represented the least complex solution. Each of the SCQ-Spanish scales had good internal consistency, and the predictive validity of the SCQ-Spanish was partially supported. Nearly all the SCQ-Spanish scales predicted withdrawal severity even after controlling for demographics and dependence. Boredom Reduction predicted smoking relapse across the 5- and 12-week follow-up assessments in a multivariate model that also controlled for demographics and dependence. Our results support use of the SCQ-Spanish with Spanish-speaking Latino smokers in the United States.

Competitive Abilities in Experimental Microcosms Are Accurately Predicted by a Demographic Index for R*

PubMed Central

Murrell, Ebony G.; Juliano, Steven A.

2012-01-01

Resource competition theory predicts that R*, the equilibrium resource amount yielding zero growth of a consumer population, should predict species' competitive abilities for that resource. This concept has been supported for unicellular organisms, but has not been well-tested for metazoans, probably due to the difficulty of raising experimental populations to equilibrium and measuring population growth rates for species with long or complex life cycles. We developed an index (Rindex) of R* based on demography of one insect cohort, growing from egg to adult in a non-equilibrium setting, and tested whether Rindex yielded accurate predictions of competitive abilities using mosquitoes as a model system. We estimated finite rate of increase (λ′) from demographic data for cohorts of three mosquito species raised with different detritus amounts, and estimated each species' Rindex using nonlinear regressions of λ′ vs. initial detritus amount. All three species' Rindex differed significantly, and accurately predicted competitive hierarchy of the species determined in simultaneous pairwise competition experiments. Our Rindex could provide estimates and rigorous statistical comparisons of competitive ability for organisms for which typical chemostat methods and equilibrium population conditions are impractical. PMID:22970128

Examining the link between public transit use and active commuting.

PubMed

Bopp, Melissa; Gayah, Vikash V; Campbell, Matthew E

2015-04-17

An established relationship exists between public transportation (PT) use and physical activity. However, there is limited literature that examines the link between PT use and active commuting (AC) behavior. This study examines this link to determine if PT users commute more by active modes. A volunteer, convenience sample of adults (n = 748) completed an online survey about AC/PT patterns, demographic, psychosocial, community and environmental factors. t-test compared differences between PT riders and non-PT riders. Binary logistic regression analyses examined the effect of multiple factors on AC and a full logistic regression model was conducted to examine AC. Non-PT riders (n = 596) reported less AC than PT riders. There were several significant relationships with AC for demographic, interpersonal, worksite, community and environmental factors when considering PT use. The logistic multivariate analysis for included age, number of children and perceived distance to work as negative predictors and PT use, feelings of bad weather and lack of on-street bike lanes as a barrier to AC, perceived behavioral control and spouse AC were positive predictors. This study revealed the complex relationship between AC and PT use. Further research should investigate how AC and public transit use are related.

Biophysical controls on cluster dynamics and architectural differentiation of microbial biofilms in contrasting flow environments

PubMed Central

Hödl, Iris; Mari, Lorenzo; Bertuzzo, Enrico; Suweis, Samir; Besemer, Katharina; Rinaldo, Andrea; Battin, Tom J

2014-01-01

Ecology, with a traditional focus on plants and animals, seeks to understand the mechanisms underlying structure and dynamics of communities. In microbial ecology, the focus is changing from planktonic communities to attached biofilms that dominate microbial life in numerous systems. Therefore, interest in the structure and function of biofilms is on the rise. Biofilms can form reproducible physical structures (i.e. architecture) at the millimetre-scale, which are central to their functioning. However, the spatial dynamics of the clusters conferring physical structure to biofilms remains often elusive. By experimenting with complex microbial communities forming biofilms in contrasting hydrodynamic microenvironments in stream mesocosms, we show that morphogenesis results in ‘ripple-like’ and ‘star-like’ architectures – as they have also been reported from monospecies bacterial biofilms, for instance. To explore the potential contribution of demographic processes to these architectures, we propose a size-structured population model to simulate the dynamics of biofilm growth and cluster size distribution. Our findings establish that basic physical and demographic processes are key forces that shape apparently universal biofilm architectures as they occur in diverse microbial but also in single-species bacterial biofilms. PMID:23879839

Do Stress Trajectories Predict Mortality in Older Men? Longitudinal Findings from the VA Normative Aging Study

PubMed Central

Aldwin, Carolyn M.; Molitor, Nuoo-Ting; Avron, Spiro; Levenson, Michael R.; Molitor, John; Igarashi, Heidi

2011-01-01

We examined long-term patterns of stressful life events (SLE) and their impact on mortality contrasting two theoretical models: allostatic load (linear relationship) and hormesis (inverted U relationship) in 1443 NAS men (aged 41–87 in 1985; M = 60.30, SD = 7.3) with at least two reports of SLEs over 18 years (total observations = 7,634). Using a zero-inflated Poisson growth mixture model, we identified four patterns of SLE trajectories, three showing linear decreases over time with low, medium, and high intercepts, respectively, and one an inverted U, peaking at age 70. Repeating the analysis omitting two health-related SLEs yielded only the first three linear patterns. Compared to the low-stress group, both the moderate and the high-stress groups showed excess mortality, controlling for demographics and health behavior habits, HRs = 1.42 and 1.37, ps <.01 and <.05. The relationship between stress trajectories and mortality was complex and not easily explained by either theoretical model. PMID:21961066

Modeling Global Spatial-Temporal Evolution of Society: Hyperbolic Growth and Historical Cycles

NASA Astrophysics Data System (ADS)

Kurkina, E. S.

2011-09-01

The global historical processes are under consideration; and laws of global evolution of the world community are studied. The world community is considered as a united complex self-developing and self-organizing system. It supposed that the main driving force of social-economical evolution was the positive feedback between the population size and the level of technological development, which was a cause of growth in blow-up regime both of population and of global economic indexes. The study is supported by the results of mathematical modeling founded on a nonlinear heat equation with a source. Every social-economical epoch characterizes by own specific spatial distributed structures. So the global dynamics of world community during the whole history is investigated throughout the prism of the developing of spatial-temporal structures. The model parameters have been chosen so that 1) total population follows stable hyperbolic growth, consistently with the demographic data; 2) the evolution of the World-System goes through 11 stages corresponding to the main historical epochs.

Accurate prediction of pregnancy viability by means of a simple scoring system.

PubMed

Bottomley, Cecilia; Van Belle, Vanya; Kirk, Emma; Van Huffel, Sabine; Timmerman, Dirk; Bourne, Tom

2013-01-01

What is the performance of a simple scoring system to predict whether women will have an ongoing viable intrauterine pregnancy beyond the first trimester? A simple scoring system using demographic and initial ultrasound variables accurately predicts pregnancy viability beyond the first trimester with an area under the curve (AUC) in a receiver operating characteristic curve of 0.924 [95% confidence interval (CI) 0.900-0.947] on an independent test set. Individual demographic and ultrasound factors, such as maternal age, vaginal bleeding and gestational sac size, are strong predictors of miscarriage. Previous mathematical models have combined individual risk factors with reasonable performance. A simple scoring system derived from a mathematical model that can be easily implemented in clinical practice has not previously been described for the prediction of ongoing viability. This was a prospective observational study in a single early pregnancy assessment centre during a 9-month period. A cohort of 1881 consecutive women undergoing transvaginal ultrasound scan at a gestational age <84 days were included. Women were excluded if the first trimester outcome was not known. Demographic features, symptoms and ultrasound variables were tested for their influence on ongoing viability. Logistic regression was used to determine the influence on first trimester viability from demographics and symptoms alone, ultrasound findings alone and then from all the variables combined. Each model was developed on a training data set, and a simple scoring system was derived from this. This scoring system was tested on an independent test data set. The final outcome based on a total of 1435 participants was an ongoing viable pregnancy in 885 (61.7%) and early pregnancy loss in 550 (38.3%) women. The scoring system using significant demographic variables alone (maternal age and amount of bleeding) to predict ongoing viability gave an AUC of 0.724 (95% CI = 0.692-0.756) in the training set and 0.729 (95% CI = 0.684-0.774) in the test set. The scoring system using significant ultrasound variables alone (mean gestation sac diameter, mean yolk sac diameter and the presence of fetal heart beat) gave an AUC of 0.873 (95% CI = 0.850-0.897) and 0.900 (95% CI = 0.871-0.928) in the training and the test sets, respectively. The final scoring system using demographic and ultrasound variables together gave an AUC of 0.901 (95% CI = 0.881-0.920) and 0.924 (CI = 0.900-0.947) in the training and the test sets, respectively. After defining the cut-off at which the sensitivity is 0.90 on the training set, this model performed with a sensitivity of 0.92, specificity of 0.73, positive predictive value of 84.7% and negative predictive value of 85.4% in the test set. BMI and smoking variables were a potential omission in the data collection and might further improve the model performance if included. A further limitation is the absence of information on either bleeding or pain in 18% of women. Caution should be exercised before implementation of this scoring system prior to further external validation studies This simple scoring system incorporates readily available data that are routinely collected in clinical practice and does not rely on complex data entry. As such it could, unlike most mathematical models, be easily incorporated into normal early pregnancy care, where women may appreciate an individualized calculation of the likelihood of ongoing pregnancy viability. Research by V.V.B. supported by Research Council KUL: GOA MaNet, PFV/10/002 (OPTEC), several PhD/postdoc & fellow grants; IWT: TBM070706-IOTA3, PhD Grants; IBBT; Belgian Federal Science Policy Office: IUAP P7/(DYSCO, `Dynamical systems, control and optimization', 2012-2017). T.B. is supported by the Imperial Healthcare NHS Trust NIHR Biomedical Research Centre. Not applicable.

Family support and other social factors precipitating suicidal ideation.

PubMed

Hirsch, J; Ellis, J B

1995-01-01

To examine the effects of family support and demographics on suicidal behavior, 385 subjects completed a demographic questionnaire and a Suicidal Ideation Questionnaire (SIQ). Sixteen percent described themselves as "serious" ideators, while 59% were seen as ideators, numbers consistent with past suicide research. Multiple regression analyses revealed that the type of caregiver a person reported having while growing up accounted for a significant amount of the variance on ideator status. Serious ideators were more common among single parent households. Although many demographic variables were assessed, only the primary caregiver a person had as a child impacted their status as a suicidal ideator. This suggests that suicidal behaviors may occur due to a complex interaction between social factors and childhood care. The influence of living in a single-parent home may contribute to whether or not a person considers suicide.

Florida coastal ecological characterization: a socioeconomic study of the southwestern region. Volume II. Data appendix, Part 3

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

French, C.O.; Parsons, J.W.

1983-08-01

Data are compiled from existing sources on the social and economic characteristics of the southwestern coastal region of Florida, which is made up of Charlotte, Collier, DeSoto, Hillsborough, Lee, Manatee, Monroe, Pasco, Pinellas, and Sarasota Counties. Described are the components and interrelationships among complex processes that include population and demographics characteristics, mineral production, multiple-use conflicts, recreation and tourism, agricultural production, sport and commercial fishing, transportation, industrial and residential development, and environmental issues and regulations. Energetics models of socioeconomic systems are also presented. This volume contains appendices presenting data on mineral and oil production, and environmental issues and regulations. 255 references,more » 20 figures, 91 tables.« less

Florida coastal ecological characterization: a socioeconomic study of the southwestern region. Volume II. Data appendix, Part 1

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

French, C.O.; Parsons, J.W.

1983-08-01

Data are compiled from existing sources on the social and economic characteristics of the southwestern coastal region of Florida, which is made up of Charlotte, Collier, DeSoto, Hillsborough, Lee, Manatee, Monroe, Pasco, Pinellas, and Sarasota Counties. Described are the components and interrelationships among complex processes that include population and demographics characteristics, mineral production, multiple-use conflicts, recreation and tourism, agricultural production, sport and commercial fishing, transportation, industrial and residential development, and environmental issues and regulations. Energetics models of socioeconomic systems are also presented. This volume contains appendices presenting data on population, employment, income, health services, agriculture, fish and game, and industrialmore » development. 9 figures, 246 tables.« less

Updates to the Demographic and Spatial Allocation Models to ...

EPA Pesticide Factsheets

EPA announced the availability of the draft report, Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) for a 30-day public comment period. The ICLUS version 2 (v2) modeling tool furthered land change modeling by providing nationwide housing development scenarios up to 2100. ICLUS V2 includes updated population and land use data sets and addressing limitations identified in ICLUS v1 in both the migration and spatial allocation models. The companion user guide describes the development of ICLUS v2 and the updates that were made to the original data sets and the demographic and spatial allocation models. [2017 UPDATE] Get the latest version of ICLUS and stay up-to-date by signing up to the ICLUS mailing list. The GIS tool enables users to run SERGoM with the population projections developed for the ICLUS project and allows users to modify the spatial allocation housing density across the landscape.

Empirical Succession Mapping and Data Assimilation to Constrain Demographic Processes in an Ecosystem Model

NASA Astrophysics Data System (ADS)

Kelly, R.; Andrews, T.; Dietze, M.

2015-12-01

Shifts in ecological communities in response to environmental change have implications for biodiversity, ecosystem function, and feedbacks to global climate change. Community composition is fundamentally the product of demography, but demographic processes are simplified or missing altogether in many ecosystem, Earth system, and species distribution models. This limitation arises in part because demographic data are noisy and difficult to synthesize. As a consequence, demographic processes are challenging to formulate in models in the first place, and to verify and constrain with data thereafter. Here, we used a novel analysis of the USFS Forest Inventory Analysis to improve the representation of demography in an ecosystem model. First, we created an Empirical Succession Mapping (ESM) based on ~1 million individual tree observations from the eastern U.S. to identify broad demographic patterns related to forest succession and disturbance. We used results from this analysis to guide reformulation of the Ecosystem Demography model (ED), an existing forest simulator with explicit tree demography. Results from the ESM reveal a coherent, cyclic pattern of change in temperate forest tree size and density over the eastern U.S. The ESM captures key ecological processes including succession, self-thinning, and gap-filling, and quantifies the typical trajectory of these processes as a function of tree size and stand density. Recruitment is most rapid in early-successional stands with low density and mean diameter, but slows as stand density increases; mean diameter increases until thinning promotes recruitment of small-diameter trees. Strikingly, the upper bound of size-density space that emerges in the ESM conforms closely to the self-thinning power law often observed in ecology. The ED model obeys this same overall size-density boundary, but overestimates plot-level growth, mortality, and fecundity rates, leading to unrealistic emergent demographic patterns. In particular, the current ED formulation cannot capture steady state dynamics evident in the ESM. Ongoing efforts are aimed at reformulating ED to more closely approach overall forest dynamics evident in the ESM, and then assimilating inventory data to constrain model parameters and initial conditions.

Integrating gene expression data with demographic, clinical, and environmental exposure information to reveal endotypes of childhood asthma

EPA Science Inventory

RATIONALE. Childhood asthma is a multifactorial disease whose pathogenesis involves complex interplay between genetic susceptibility and modulating external factors. Therefore, effectively characterizing these multiple etiological pathways, or “endotypes”, requires an integrative...

Demographic trends of sick leave absenteeism among civil service employees at a federal agency from 2004 to 2012.

PubMed

Gajewski, Kim; Burris, Dara; Spears, D Ross; Sullivan, Kevin; Oyinloye, Oluremi; McNeil, Carrie; Meechan, Paul; Warnock, Eli; Trapp, Jonathan; Decker, K C; Chapman, Sandy

2015-03-01

To investigate the associations between demographic variables and sick leave use. We analyzed sick leave use among civil servants at a federal agency (FA) from 2004 to 2012 by demographic and FA-specific variables. We used a mixed methods approach and type III analysis to build a descriptive model of sick leave proportions and demographic variables. Sick absenteeism usage varied significantly (variation of greater than one sick day per year) by sex, Emergency Operations Center response tier, length of service at the FA, age, and general schedule pay grade level. Our final descriptive model contained age, sex, response tier and an interaction term between age and sex. Future studies should examine these associations on smaller time scales, perhaps breaking the data down by month or day of the week.

Never too old for anonymity: a statistical standard for demographic data sharing via the HIPAA Privacy Rule

PubMed Central

Benitez, Kathleen; Masys, Daniel

2010-01-01

Objective Healthcare organizations must de-identify patient records before sharing data. Many organizations rely on the Safe Harbor Standard of the HIPAA Privacy Rule, which enumerates 18 identifiers that must be suppressed (eg, ages over 89). An alternative model in the Privacy Rule, known as the Statistical Standard, can facilitate the sharing of more detailed data, but is rarely applied because of a lack of published methodologies. The authors propose an intuitive approach to de-identifying patient demographics in accordance with the Statistical Standard. Design The authors conduct an analysis of the demographics of patient cohorts in five medical centers developed for the NIH-sponsored Electronic Medical Records and Genomics network, with respect to the US census. They report the re-identification risk of patient demographics disclosed according to the Safe Harbor policy and the relative risk rate for sharing such information via alternative policies. Measurements The re-identification risk of Safe Harbor demographics ranged from 0.01% to 0.19%. The findings show alternative de-identification models can be created with risks no greater than Safe Harbor. The authors illustrate that the disclosure of patient ages over the age of 89 is possible when other features are reduced in granularity. Limitations The de-identification approach described in this paper was evaluated with demographic data only and should be evaluated with other potential identifiers. Conclusion Alternative de-identification policies to the Safe Harbor model can be derived for patient demographics to enable the disclosure of values that were previously suppressed. The method is generalizable to any environment in which population statistics are available. PMID:21169618

Is temperature the main cause of dengue rise in non-endemic countries? The case of Argentina

PubMed Central

2012-01-01

Background Dengue cases have increased during the last decades, particularly in non-endemic areas, and Argentina was no exception in the southern transmission fringe. Although temperature rise has been blamed for this, human population growth, increased travel and inefficient vector control may also be implicated. The relative contribution of geographic, demographic and climatic of variables on the occurrence of dengue cases was evaluated. Methods According to dengue history in the country, the study was divided in two decades, a first decade corresponding to the reemergence of the disease and the second including several epidemics. Annual dengue risk was modeled by a temperature-based mechanistic model as annual days of possible transmission. The spatial distribution of dengue occurrence was modeled as a function of the output of the mechanistic model, climatic, geographic and demographic variables for both decades. Results According to the temperature-based model dengue risk increased between the two decades, and epidemics of the last decade coincided with high annual risk. Dengue spatial occurrence was best modeled by a combination of climatic, demographic and geographic variables and province as a grouping factor. It was positively associated with days of possible transmission, human population number, population fall and distance to water bodies. When considered separately, the classification performance of demographic variables was higher than that of climatic and geographic variables. Conclusions Temperature, though useful to estimate annual transmission risk, does not fully describe the distribution of dengue occurrence at the country scale. Indeed, when taken separately, climatic variables performed worse than geographic or demographic variables. A combination of the three types was best for this task. PMID:22768874

Unification theory of optimal life histories and linear demographic models in internal stochasticity.

PubMed

Oizumi, Ryo

2014-01-01

Life history of organisms is exposed to uncertainty generated by internal and external stochasticities. Internal stochasticity is generated by the randomness in each individual life history, such as randomness in food intake, genetic character and size growth rate, whereas external stochasticity is due to the environment. For instance, it is known that the external stochasticity tends to affect population growth rate negatively. It has been shown in a recent theoretical study using path-integral formulation in structured linear demographic models that internal stochasticity can affect population growth rate positively or negatively. However, internal stochasticity has not been the main subject of researches. Taking account of effect of internal stochasticity on the population growth rate, the fittest organism has the optimal control of life history affected by the stochasticity in the habitat. The study of this control is known as the optimal life schedule problems. In order to analyze the optimal control under internal stochasticity, we need to make use of "Stochastic Control Theory" in the optimal life schedule problem. There is, however, no such kind of theory unifying optimal life history and internal stochasticity. This study focuses on an extension of optimal life schedule problems to unify control theory of internal stochasticity into linear demographic models. First, we show the relationship between the general age-states linear demographic models and the stochastic control theory via several mathematical formulations, such as path-integral, integral equation, and transition matrix. Secondly, we apply our theory to a two-resource utilization model for two different breeding systems: semelparity and iteroparity. Finally, we show that the diversity of resources is important for species in a case. Our study shows that this unification theory can address risk hedges of life history in general age-states linear demographic models.

Unification Theory of Optimal Life Histories and Linear Demographic Models in Internal Stochasticity

PubMed Central

Oizumi, Ryo

2014-01-01

Life history of organisms is exposed to uncertainty generated by internal and external stochasticities. Internal stochasticity is generated by the randomness in each individual life history, such as randomness in food intake, genetic character and size growth rate, whereas external stochasticity is due to the environment. For instance, it is known that the external stochasticity tends to affect population growth rate negatively. It has been shown in a recent theoretical study using path-integral formulation in structured linear demographic models that internal stochasticity can affect population growth rate positively or negatively. However, internal stochasticity has not been the main subject of researches. Taking account of effect of internal stochasticity on the population growth rate, the fittest organism has the optimal control of life history affected by the stochasticity in the habitat. The study of this control is known as the optimal life schedule problems. In order to analyze the optimal control under internal stochasticity, we need to make use of “Stochastic Control Theory” in the optimal life schedule problem. There is, however, no such kind of theory unifying optimal life history and internal stochasticity. This study focuses on an extension of optimal life schedule problems to unify control theory of internal stochasticity into linear demographic models. First, we show the relationship between the general age-states linear demographic models and the stochastic control theory via several mathematical formulations, such as path–integral, integral equation, and transition matrix. Secondly, we apply our theory to a two-resource utilization model for two different breeding systems: semelparity and iteroparity. Finally, we show that the diversity of resources is important for species in a case. Our study shows that this unification theory can address risk hedges of life history in general age-states linear demographic models. PMID:24945258

A place-based model of local activity spaces: individual place exposure and characteristics

NASA Astrophysics Data System (ADS)

Hasanzadeh, Kamyar; Laatikainen, Tiina; Kyttä, Marketta

2018-01-01

Researchers for long have hypothesized relationships between mobility, urban context, and health. Despite the ample amount of discussions, the empirical findings corroborating such associations remain to be marginal in the literature. It is growingly believed that the weakness of the observed associations can be largely explained by the common misspecification of the geographical context. Researchers coming from different fields have developed a wide range of methods for estimating the extents of these geographical contexts. In this article, we argue that no single approach yet has sufficiently been capable of capturing the complexity of human mobility patterns. Subsequently, we discuss that reaching a better understanding of individual activity spaces can be possible through a spatially sensitive estimation of place exposure. Following this discussion, we take an integrative person and place-based approach to create an individualized residential exposure model (IREM) to estimate the local activity spaces (LAS) of the individuals. This model is created using data collected through public participation GIS. Following a brief comparison of IREM with other commonly used LAS models, the article continues by presenting an empirical study of aging citizens in Helsinki area to demonstrate the usability of the proposed framework. In this study, we identify the main dimensions of LASs and seek their associations with socio-demographic characteristics of individuals and their location in the region. The promising results from comparisons and the interesting findings from the empirical part suggest both a methodological and conceptual improvement in capturing the complexity of local activity spaces.

Exploring the social dimension of sandy beaches through predictive modelling.

PubMed

Domínguez-Tejo, Elianny; Metternicht, Graciela; Johnston, Emma L; Hedge, Luke

2018-05-15

Sandy beaches are unique ecosystems increasingly exposed to human-induced pressures. Consistent with emerging frameworks promoting this holistic approach towards beach management, is the need to improve the integration of social data into management practices. This paper aims to increase understanding of links between demographics and community values and preferred beach activities, as key components of the social dimension of the beach environment. A mixed method approach was adopted to elucidate users' opinions on beach preferences and community values through a survey carried out in Manly Local Government Area in Sydney Harbour, Australia. A proposed conceptual model was used to frame demographic models (using age, education, employment, household income and residence status) as predictors of these two community responses. All possible regression-model combinations were compared using Akaike's information criterion. Best models were then used to calculate quantitative likelihoods of the responses, presented as heat maps. Findings concur with international research indicating the relevance of social and restful activities as important social links between the community and the beach environment. Participant's age was a significant variable in the four predictive models. The use of predictive models informed by demographics could potentially increase our understanding of interactions between the social and ecological systems of the beach environment, as a prelude to integrated beach management approaches. The research represents a practical demonstration of how demographic predictive models could support proactive approaches to beach management. Copyright © 2018 Elsevier Ltd. All rights reserved.

Ultra-Scale Computing for Emergency Evacuation

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

Bhaduri, Budhendra L; Nutaro, James J; Liu, Cheng

2010-01-01

Emergency evacuations are carried out in anticipation of a disaster such as hurricane landfall or flooding, and in response to a disaster that strikes without a warning. Existing emergency evacuation modeling and simulation tools are primarily designed for evacuation planning and are of limited value in operational support for real time evacuation management. In order to align with desktop computing, these models reduce the data and computational complexities through simple approximations and representations of real network conditions and traffic behaviors, which rarely represent real-world scenarios. With the emergence of high resolution physiographic, demographic, and socioeconomic data and supercomputing platforms, itmore » is possible to develop micro-simulation based emergency evacuation models that can foster development of novel algorithms for human behavior and traffic assignments, and can simulate evacuation of millions of people over a large geographic area. However, such advances in evacuation modeling and simulations demand computational capacity beyond the desktop scales and can be supported by high performance computing platforms. This paper explores the motivation and feasibility of ultra-scale computing for increasing the speed of high resolution emergency evacuation simulations.« less

Linked population and economic models: some methodological issues in forecasting, analysis, and policy optimization.

PubMed

Madden, M; Batey Pwj

1983-05-01

Some problems associated with demographic-economic forecasting include finding models appropriate for a declining economy with unemployment, using a multiregional approach in an interregional model, finding a way to show differential consumption while endogenizing unemployment, and avoiding unemployment inconsistencies. The solution to these problems involves the construction of an activity-commodity framework, locating it within a group of forecasting models, and indicating possible ratios towards dynamization of the framework. The authors demonstrate the range of impact multipliers that can be derived from the framework and show how these multipliers relate to Leontief input-output multipliers. It is shown that desired population distribution may be obtained by selecting instruments from the economic sphere to produce, through the constraints vector of an activity-commodity framework, targets selected from demographic activities. The next step in this process, empirical exploitation, was carried out by the authors in the United Kingdom, linking an input-output model with a wide selection of demographic and demographic-economic variables. The generally tenuous control which government has over any variables in systems of this type, especially in market economies, makes application in the policy field of the optimization approach a partly conjectural exercise, although the analytic capacity of the approach can provide clear indications of policy directions.

Hierarchial mark-recapture models: a framework for inference about demographic processes

USGS Publications Warehouse

Link, W.A.; Barker, R.J.

2004-01-01

The development of sophisticated mark-recapture models over the last four decades has provided fundamental tools for the study of wildlife populations, allowing reliable inference about population sizes and demographic rates based on clearly formulated models for the sampling processes. Mark-recapture models are now routinely described by large numbers of parameters. These large models provide the next challenge to wildlife modelers: the extraction of signal from noise in large collections of parameters. Pattern among parameters can be described by strong, deterministic relations (as in ultrastructural models) but is more flexibly and credibly modeled using weaker, stochastic relations. Trend in survival rates is not likely to be manifest by a sequence of values falling precisely on a given parametric curve; rather, if we could somehow know the true values, we might anticipate a regression relation between parameters and explanatory variables, in which true value equals signal plus noise. Hierarchical models provide a useful framework for inference about collections of related parameters. Instead of regarding parameters as fixed but unknown quantities, we regard them as realizations of stochastic processes governed by hyperparameters. Inference about demographic processes is based on investigation of these hyperparameters. We advocate the Bayesian paradigm as a natural, mathematically and scientifically sound basis for inference about hierarchical models. We describe analysis of capture-recapture data from an open population based on hierarchical extensions of the Cormack-Jolly-Seber model. In addition to recaptures of marked animals, we model first captures of animals and losses on capture, and are thus able to estimate survival probabilities w (i.e., the complement of death or permanent emigration) and per capita growth rates f (i.e., the sum of recruitment and immigration rates). Covariation in these rates, a feature of demographic interest, is explicitly described in the model.

Spatial and temporal patterns of neutral and adaptive genetic variation in the endangered African wild dog (Lycaon pictus).

PubMed

Marsden, Clare D; Woodroffe, Rosie; Mills, Michael G L; McNutt, J Weldon; Creel, Scott; Groom, Rosemary; Emmanuel, Masenga; Cleaveland, Sarah; Kat, Pieter; Rasmussen, Gregory S A; Ginsberg, Joshua; Lines, Robin; André, Jean-Marc; Begg, Colleen; Wayne, Robert K; Mable, Barbara K

2012-03-01

Deciphering patterns of genetic variation within a species is essential for understanding population structure, local adaptation and differences in diversity between populations. Whilst neutrally evolving genetic markers can be used to elucidate demographic processes and genetic structure, they are not subject to selection and therefore are not informative about patterns of adaptive variation. As such, assessments of pertinent adaptive loci, such as the immunity genes of the major histocompatibility complex (MHC), are increasingly being incorporated into genetic studies. In this study, we combined neutral (microsatellite, mtDNA) and adaptive (MHC class II DLA-DRB1 locus) markers to elucidate the factors influencing patterns of genetic variation in the African wild dog (Lycaon pictus); an endangered canid that has suffered extensive declines in distribution and abundance. Our genetic analyses found all extant wild dog populations to be relatively small (N(e)  < 30). Furthermore, through coalescent modelling, we detected a genetic signature of a recent and substantial demographic decline, which correlates with human expansion, but contrasts with findings in some other African mammals. We found strong structuring of wild dog populations, indicating the negative influence of extensive habitat fragmentation and loss of gene flow between habitat patches. Across populations, we found that the spatial and temporal structure of microsatellite diversity and MHC diversity were correlated and strongly influenced by demographic stability and population size, indicating the effects of genetic drift in these small populations. Despite this correlation, we detected signatures of selection at the MHC, implying that selection has not been completely overwhelmed by genetic drift. © 2012 Blackwell Publishing Ltd.

Demographic patterns of a widespread long-lived tree are associated with rainfall and disturbances along rainfall gradients in SE Australia

PubMed Central

Cohn, Janet S; Lunt, Ian D; Bradstock, Ross A; Hua, Quan; McDonald, Simon

2013-01-01

Predicting species distributions with changing climate has often relied on climatic variables, but increasingly there is recognition that disturbance regimes should also be included in distribution models. We examined how changes in rainfall and disturbances along climatic gradients determined demographic patterns in a widespread and long-lived tree species, Callitris glaucophylla in SE Australia. We examined recruitment since 1950 in relation to annual (200–600 mm) and seasonal (summer, uniform, winter) rainfall gradients, edaphic factors (topography), and disturbance regimes (vertebrate grazing [tenure and species], fire). A switch from recruitment success to failure occurred at 405 mm mean annual rainfall, coincident with a change in grazing regime. Recruitment was lowest on farms with rabbits below 405 mm rainfall (mean = 0–0.89 cohorts) and highest on less-disturbed tenures with no rabbits above 405 mm rainfall (mean = 3.25 cohorts). Moderate levels of recruitment occurred where farms had no rabbits or less disturbed tenures had rabbits above and below 405 mm rainfall (mean = 1.71–1.77 cohorts). These results show that low annual rainfall and high levels of introduced grazing has led to aging, contracting populations, while higher annual rainfall with low levels of grazing has led to younger, expanding populations. This study demonstrates how demographic patterns vary with rainfall and spatial variations in disturbances, which are linked in complex ways to climatic gradients. Predicting changes in tree distribution with climate change requires knowledge of how rainfall and key disturbances (tenure, vertebrate grazing) will shift along climatic gradients. PMID:23919160

Time delays, population, and economic development

NASA Astrophysics Data System (ADS)

Gori, Luca; Guerrini, Luca; Sodini, Mauro

2018-05-01

This research develops an augmented Solow model with population dynamics and time delays. The model produces either a single stationary state or multiple stationary states (able to characterise different development regimes). The existence of time delays may cause persistent fluctuations in both economic and demographic variables. In addition, the work identifies in a simple way the reasons why economics affects demographics and vice versa.

Chapter 37: Population Trends of the Marbled Murrelet Projected From Demographic Analyses

Treesearch

Steven B. Beissinger

1995-01-01

A demographic model of the Marbled Murrelet is developed to explore likely population trends and factors influencing them. The model was structured to use field data on juvenile ratios, collected near the end of the breeding season and corrected for date of census, to estimate fecundity. Survivorship was estimated for the murrelet based on comparative analyses of...

Predictive Models of Acute Mountain Sickness after Rapid Ascent to Various Altitudes

DTIC Science & Technology

2013-01-01

unclassified relational mountain medicine database containing individ- ual ascent profiles, demographic and physiologic subject descriptors, and...course of AMS, and define the baseline demographics and physiologic descriptors that increase the risk of AMS. In addition, these models provide...substantiated this finding in un- acclimatized women (24). Other physiologic differences between men and women (i.e., differences in endothelial

Relationship between women's characteristics and continuum of care for maternal health in Kenya: Complex survey analysis using structural equation modeling.

PubMed

Owili, Patrick Opiyo; Muga, Miriam Adoyo; Chou, Yiing-Jenq; Hsu, Yi-Hsin Elsa; Huang, Nicole; Chien, Li-Yin

2017-09-01

The objective of this study was to understand and estimate the complex relationships in the continuum of care for maternal health to provide information to improve maternal and newborn health outcomes. Women (n = 4,082) aged 15-49 years in the 2008/2009 Kenya Demographic and Health Survey data were used to explore the complex relationships in the continuum of care for maternal health (i.e., before, during, and after delivery) using structural equation modeling. Results showed that the use of antenatal care was significantly positively related to the use of delivery care (β = 0.06; adjusted odds ratio [AOR] = 1.06; 95% confidence interval [CI]: 1.02-1.10) but not postnatal care, while delivery care was associated with postnatal care (β = 0.68; AOR = 1.97; 95% CI: 1.75-2.22). Socioeconomic status was significantly related to all elements in the continuum of care for maternal health; barriers to delivery of care and personal characteristics were only associated with the use of delivery care (β = 0.34; AOR = 1.40; 95% CI: 1.30-1.52) and postnatal care (β = 0.03; AOR = 1.03; 95% CI: 1.01-1.05), respectively. The three periods of maternal health care were related to each other. Developing a referral system of continuity of care is critical in the Sustainable Development Goals era.

An operational epidemiological model for calibrating agent-based simulations of pandemic influenza outbreaks.

PubMed

Prieto, D; Das, T K

2016-03-01

Uncertainty of pandemic influenza viruses continue to cause major preparedness challenges for public health policymakers. Decisions to mitigate influenza outbreaks often involve tradeoff between the social costs of interventions (e.g., school closure) and the cost of uncontrolled spread of the virus. To achieve a balance, policymakers must assess the impact of mitigation strategies once an outbreak begins and the virus characteristics are known. Agent-based (AB) simulation is a useful tool for building highly granular disease spread models incorporating the epidemiological features of the virus as well as the demographic and social behavioral attributes of tens of millions of affected people. Such disease spread models provide excellent basis on which various mitigation strategies can be tested, before they are adopted and implemented by the policymakers. However, to serve as a testbed for the mitigation strategies, the AB simulation models must be operational. A critical requirement for operational AB models is that they are amenable for quick and simple calibration. The calibration process works as follows: the AB model accepts information available from the field and uses those to update its parameters such that some of its outputs in turn replicate the field data. In this paper, we present our epidemiological model based calibration methodology that has a low computational complexity and is easy to interpret. Our model accepts a field estimate of the basic reproduction number, and then uses it to update (calibrate) the infection probabilities in a way that its effect combined with the effects of the given virus epidemiology, demographics, and social behavior results in an infection pattern yielding a similar value of the basic reproduction number. We evaluate the accuracy of the calibration methodology by applying it for an AB simulation model mimicking a regional outbreak in the US. The calibrated model is shown to yield infection patterns closely replicating the input estimates of the basic reproduction number. The calibration method is also tested to replicate an initial infection incidence trend for a H1N1 outbreak like that of 2009.

Fall risk factors analysis based on sample entropy of plantar kinematic signal during stance phase.

PubMed

Shengyun Liang; Huiyu Jia; Zilong Li; Huiqi Li; Xing Gao; Zuchang Ma; Yingnan Ma; Guoru Zhao

2016-08-01

Falls are a multi-causal phenomenon with a complex interaction. The aim of our research is to study the effect of multiple variables for potential risk of falls and construct an elderly fall risk assessment model based on demographics data and gait characteristics. A total of 101 subjects, whom belong to Malianwa Street, aged above 50 years old and participated in questionnaire survey. Participants were classified into three groups (high, medium and low risk group) according to the score of elderly fall risk assessment scale. In addition, the data of ground reaction force (GRF) and ground reaction moment (GRM) was record when they performed walking at comfortable state. The demographic variables, sample entropy of GRF and GRM, and impulse difference of bilateral foot were considered as potential explanatory variables of risk assessment model. Firstly, we investigated whether different groups could present difference in every variable. Statistical differences were found for the following variables: age (p=2.28e-05); impulse difference (p=0.02036); sample entropy of GRF in vertical direction (p=0.0144); sample entropy of GRM in anterior-posterior direction (p=0.0387). Finally, the multiple regression analysis results indicated that age, impulse difference and sample entropy of resultant GRM could identify individuals who had different levels of fall risk. Therefore, those results could potentially be useful in the fall risk assessment and monitor the state of physical function in elderly population.

Understanding Suicide Risk: Identification of High Risk Groups during High Risk Times

PubMed Central

Overholser, James C.; Braden, Abby; Dieter, Lesa

2012-01-01

Background The assessment of suicide risk is a complex task for mental health professionals. Certain demographic groups are associated with completed suicide including males, divorced adults, and Caucasians. However, demographic variables alone provide a crude assessment of suicide risk. Psychiatric diagnosis and recent life events may improve the identification of high risk individuals. Method The current study evaluated 148 individuals who died by suicide compared to 257 adults who died suddenly from accidents or medical problems. Psychological autopsy was used to assess Axis I psychiatric diagnosis and recent stressful life events. Results Suicide completers were significantly more likely than comparison subjects to have a depressive disorder, a substance abuse disorder, and to have experienced interpersonal conflict in the months leading up to their death. A discriminant function analysis revealed that the combination of demographic variables, recent stressful life events, and psychiatric diagnoses best discriminated between suicide completers and comparison subjects. Conclusions Proper assessment of suicide risk should include a comprehensive evaluation of demographic characteristics, recent life stressors, and psychiatric diagnosis. PMID:22140004

The accuracy of matrix population model projections for coniferous trees in the Sierra Nevada, California

USGS Publications Warehouse

van Mantgem, P.J.; Stephenson, N.L.

2005-01-01

1 We assess the use of simple, size-based matrix population models for projecting population trends for six coniferous tree species in the Sierra Nevada, California. We used demographic data from 16 673 trees in 15 permanent plots to create 17 separate time-invariant, density-independent population projection models, and determined differences between trends projected from initial surveys with a 5-year interval and observed data during two subsequent 5-year time steps. 2 We detected departures from the assumptions of the matrix modelling approach in terms of strong growth autocorrelations. We also found evidence of observation errors for measurements of tree growth and, to a more limited degree, recruitment. Loglinear analysis provided evidence of significant temporal variation in demographic rates for only two of the 17 populations. 3 Total population sizes were strongly predicted by model projections, although population dynamics were dominated by carryover from the previous 5-year time step (i.e. there were few cases of recruitment or death). Fractional changes to overall population sizes were less well predicted. Compared with a null model and a simple demographic model lacking size structure, matrix model projections were better able to predict total population sizes, although the differences were not statistically significant. Matrix model projections were also able to predict short-term rates of survival, growth and recruitment. Mortality frequencies were not well predicted. 4 Our results suggest that simple size-structured models can accurately project future short-term changes for some tree populations. However, not all populations were well predicted and these simple models would probably become more inaccurate over longer projection intervals. The predictive ability of these models would also be limited by disturbance or other events that destabilize demographic rates. ?? 2005 British Ecological Society.

A Superintendent's Role in Creating Community

ERIC Educational Resources Information Center

Ahillen, Marybeth

2010-01-01

The context of leadership in the public school has become increasingly complex with the pressures of high stakes testing and accountability, changing student demographics, and financial challenges. Stakeholders must work together to develop effective strategies to increase student academic performance. Successful superintendents must optimize…

Charles Bonnet Syndrome: A Review of the Literature

ERIC Educational Resources Information Center

O'Farrell, Lauren; Lewis, Sandra; McKenzie, Amy; Jones, Lynda

2010-01-01

Charles Bonnet syndrome (CBS) commonly occurs in older adults with visual impairments, particularly those with age-related macular degeneration. It is characterized by complex visual hallucinations in individuals without mental disorders. The authors explore diagnostic criteria, demographic characteristics, clinical features, theories of…

Scaling in sensitivity analysis

USGS Publications Warehouse

Link, W.A.; Doherty, P.F.

2002-01-01

Population matrix models allow sets of demographic parameters to be summarized by a single value 8, the finite rate of population increase. The consequences of change in individual demographic parameters are naturally measured by the corresponding changes in 8; sensitivity analyses compare demographic parameters on the basis of these changes. These comparisons are complicated by issues of scale. Elasticity analysis attempts to deal with issues of scale by comparing the effects of proportional changes in demographic parameters, but leads to inconsistencies in evaluating demographic rates. We discuss this and other problems of scaling in sensitivity analysis, and suggest a simple criterion for choosing appropriate scales. We apply our suggestions to data for the killer whale, Orcinus orca.

The Impact of Cognitive Stressors in the Emergency Department on Physician Implicit Racial Bias.

PubMed

Johnson, Tiffani J; Hickey, Robert W; Switzer, Galen E; Miller, Elizabeth; Winger, Daniel G; Nguyen, Margaret; Saladino, Richard A; Hausmann, Leslie R M

2016-03-01

The emergency department (ED) is characterized by stressors (e.g., fatigue, stress, time pressure, and complex decision-making) that can pose challenges to delivering high-quality, equitable care. Although it has been suggested that characteristics of the ED may exacerbate reliance on cognitive heuristics, no research has directly investigated whether stressors in the ED impact physician racial bias, a common heuristic. We seek to determine if physicians have different levels of implicit racial bias post-ED shift versus preshift and to examine associations between demographics and cognitive stressors with bias. This repeated-measures study of resident physicians in a pediatric ED used electronic pre- and postshift assessments of implicit racial bias, demographics, and cognitive stressors. Implicit bias was measured using the Race Implicit Association Test (IAT). Linear regression models compared differences in IAT scores pre- to postshift and determined associations between participant demographics and cognitive stressors with postshift IAT and pre- to postshift difference scores. Participants (n = 91) displayed moderate prowhite/antiblack bias on preshift (mean ± SD = 0.50 ± 0.34, d = 1.48) and postshift (mean ± SD = 0.55 ± 0.39, d = 1.40) IAT scores. Overall, IAT scores did not differ preshift to postshift (mean increase = 0.05, 95% CI = -0.02 to 0.14, d = 0.13). Subanalyses revealed increased pre- to postshift bias among participants working when the ED was more overcrowded (mean increase = 0.09, 95% CI = 0.01 to 0.17, d = 0.24) and among those caring for >10 patients (mean increase = 0.17, 95% CI = 0.05 to 0.27, d = 0.47). Residents' demographics (including specialty), fatigue, busyness, stressfulness, and number of shifts were not associated with postshift IAT or difference scores. In multivariable models, ED overcrowding was associated with greater postshift bias (coefficient = 0.11 per 1 unit of NEDOCS score, SE = 0.05, 95% CI = 0.00 to 0.21). While resident implicit bias remained stable overall preshift to postshift, cognitive stressors (overcrowding and patient load) were associated with increased implicit bias. Physicians in the ED should be aware of how cognitive stressors may exacerbate implicit racial bias. © 2016 by the Society for Academic Emergency Medicine.

The Impact of Cognitive Stressors in the Emergency Department on Physician Implicit Racial Bias

PubMed Central

Johnson, Tiffani J.; Hickey, Robert W.; Switzer, Galen E.; Miller, Elizabeth; Winger, Daniel G.; Nguyen, Margaret; Saladino, Richard A.; Hausmann, Leslie R. M.

2016-01-01

Objectives The emergency department (ED) is characterized by stressors (e.g. fatigue, stress, time-pressure, and complex decision-making) that can pose challenges to delivering high quality, equitable care. Although it has been suggested that characteristics of the ED may exacerbate reliance on cognitive heuristics, no research has directly investigated whether stressors in the ED impact physician racial bias, a common heuristic. We seek to determine if physicians have different levels of implicit racial bias post-ED shift versus pre-shift, and to examine associations between demographics and cognitive stressors with bias. Methods This repeated measures study of resident physicians in a pediatric ED used electronic pre- and post-shift assessments of implicit racial bias, demographics, and cognitive stressors. Implicit bias was measured using the Race Implicit Association Test (IAT). Linear regression models compared differences in IAT scores pre- to post-shift, and determined associations between participant demographics and cognitive stressors with post-shift IAT and pre- to post-shift difference scores. Results Participants (n=91) displayed moderate pro-white/anti-black bias on pre-shift (M=0.50, SD=0.34, d=1.48) and post-shift (M=0.55, SD=0.39, d=1.40) IAT scores. Overall, IAT scores did not differ pre-shift to post-shift (mean increase=0.05, 95% CI −0.02,0.14, d=0.13). Sub-analyses revealed increased pre- to post-shift bias among participants working when the ED was more overcrowded (mean increase=0.09, 95% CI 0.01,0.17, d=0.24) and among those caring for >10 patients (mean increase=0.17, 95% CI 0.05,0.27, d=0.47). Residents’ demographics (including specialty), fatigue, busyness, stressfulness, and number of shifts were not associated with post-shift IAT or difference scores. In multivariable models, ED overcrowding was associated with greater post-shift bias (coefficient=0.11 per 1 unit of NEDOCS score, SE=0.05, 95% CI 0.00,0.21). Conclusions While resident implicit bias remained stable overall pre-shift to post-shift, cognitive stressors (overcrowding and patient load) were associated with increased implicit bias. Physicians in the ED should be aware of how cognitive stressors may exacerbate implicit racial bias. PMID:26763939

Development of river flood model in lower reach of urbanized river basin

NASA Astrophysics Data System (ADS)

Yoshimura, Kouhei; Tajima, Yoshimitsu; Sanuki, Hiroshi; Shibuo, Yoshihiro; Sato, Shinji; Lee, SungAe; Furumai, Hiroaki; Koike, Toshio

2014-05-01

Japan, with its natural mountainous landscape, has demographic feature that population is concentrated in lower reach of elevation close to the coast, and therefore flood damage with large socio-economic value tends to occur in low-lying region. Modeling of river flood in such low-lying urbanized river basin is complex due to the following reasons. In upstream it has been experienced urbanization, which changed land covers from natural forest or agricultural fields to residential or industrial area. Hence rate of infiltration and runoff are quite different from natural hydrological settings. In downstream, paved covers and construct of sewerage system in urbanized areas affect direct discharges and it enhances higher and faster flood peak arrival. Also tidal effect from river mouth strongly affects water levels in rivers, which must be taken into account. We develop an integrated river flood model in lower reach of urbanized areas to be able to address above described complex feature, by integrating model components: LSM coupled distributed hydrological model that models anthropogenic influence on river discharges to downstream; urban hydrological model that simulates run off response in urbanized areas; Saint Venant's equation approximated river model that integrates upstream and urban hydrological models with considering tidal effect from downstream. These features are integrated in a common modeling framework so that model interaction can be directly performed. The model is applied to the Tsurumi river basin, urbanized low-lying river basin in Yokohama and model results show that it can simulate water levels in rivers with acceptable model errors. Furthermore the model is able to install miscellaneous water planning constructs, such as runoff reduction pond in urbanized area, flood control field along the river channel, levee, etc. This can be a useful tool to investigate cost performance of hypothetical water management plan against impact of climate change in the region.

Phylogeographic structure of Canthon cyanellus (Coleoptera: Scarabaeidae), a Neotropical dung beetle in the Mexican Transition Zone: Insights on its origin and the impacts of Pleistocene climatic fluctuations on population dynamics.

PubMed

Nolasco-Soto, Janet; González-Astorga, Jorge; Espinosa de Los Monteros, Alejandro; Galante-Patiño, Eduardo; Favila, Mario E

2017-04-01

Canthon cyanellus is a roller dung beetle with a wide distribution range in the tropical forests of the New World. In Mexico, it inhabits the Pacific and the Gulf coasts, the Yucatan Peninsula and the south mainly in the State of Chiapas. This species shows a wide geographical variation in cuticle color, which has been used as defining trait for subspecies. In this study we analyzed the phylogeographic and demographic history of the Mexican populations of C. cyanellus using DNA sequences of the nuclear ITS2, and the mitochondrial COI and 16S genes. We found that not all the current valid subspecies are supported by the molecular analysis. The populations are genetically and geographically structured in five lineages. The diversification events that gave origin to the main lineages within this species complex occurred during the Pleistocine in a time range of 1.63-0.91Myr. The demographic history of these lineages suggests post-glacial expansions toward the middle and the end of the Pleistocene. The combined data of mitochondrial and nuclear DNA suggest that the phylogeographic structure and demographic history of the C. cyanellus populations are the result of: the geological and volcanic activity that occurred from the end of the Pliocene to the Pleistocene; and the contraction and expansion of tropical forests due to the glacial and inter-glacial cycles during the Pleistocene. Landscape changes derived from historical events have affected the demographic history of the populations of this species. The results presented here point to the need to review the taxonomic status and delimitation of the lineages encompassed in the Canthon cyanellus complex. Copyright © 2017 Elsevier Inc. All rights reserved.

Demographic, Maltreatment, and Neurobiological Correlates of PTSD Symptoms in Children and Adolescents

PubMed Central

Hooper, Stephen R.; Woolley, Donald P.; Shenk, Chad E.

2010-01-01

Objective To examine the relationships of demographic, maltreatment, neurostructural and neuropsychological measures with total posttraumatic stress disorder (PTSD) symptoms. Methods Participants included 216 children with maltreatment histories (N = 49), maltreatment and PTSD (N = 49), or no maltreatment (N = 118). Participants received diagnostic interviews, brain imaging, and neuropsychological evaluations. Results We examined a hierarchical regression model comprised of independent variables including demographics, trauma and maltreatment-related variables, and hippocampal volumes and neuropsychological measures to model PTSD symptoms. Important independent contributors to this model were SES, and General Maltreatment and Sexual Abuse Factors. Although hippocampal volumes were not significant, Visual Memory was a significant contributor to this model. Conclusions Similar to adult PTSD, pediatric PTSD symptoms are associated with lower Visual Memory performance. It is an important correlate of PTSD beyond established predictors of PTSD symptoms. These results support models of developmental traumatology and suggest that treatments which enhance visual memory may decrease symptoms of PTSD. PMID:20008084

Psychosocial service needs of pediatric transport accident survivors: Using clinical data-mining to establish demographic and service usage characteristics.

PubMed

Manguy, Alys-Marie; Joubert, Lynette; Bansemer, Leah

2016-09-01

The objectives in this article are the exploration of demographic and service usage data gained through clinical data mining audit and suggesting recommendations for social work service delivery model and future research. The method is clinical data-mining audit of 100 sequentially sampled cases gathering quantitative demographic and service usage data. Descriptive analysis of file audit data raised interesting trends with potential to inform service delivery and usage; the key areas of the results included patient demographics, family involvement and impact, and child safety and risk issues. Transport accidents involving children often include other family members. Care planning must take into account psychosocial issues including patient and family emotional responses, availability of primary carers, and other practical needs that may impact on recovery and discharge planning. This study provides evidence to plan for further research and development of more integrated models of care.

A holistic conceptual framework model to describe medication adherence in and guide interventions in diabetes mellitus.

PubMed

Jaam, Myriam; Awaisu, Ahmed; Mohamed Ibrahim, Mohamed Izham; Kheir, Nadir

2018-04-01

Nonadherence to medications in patients with diabetes, which results in poor treatment outcomes and increased healthcare costs, is commonly reported globally. Factors associated with medication adherence have also been widely studied. However, a clear and comprehensive, disease-specific conceptual framework model that captures all possible factors has not been established. This study aimed to develop a conceptual framework that addresses the complex network of barriers to medication adherence in patients with diabetes. Fourteen databases and grey literature sources were systematically searched for systematic reviews reporting barriers to medication adherence in patients with diabetes. A thematic approach was used to categorize all identified barriers from the reviews and to create a matrix representing the complex network and relations of the different barriers. Eighteen systematic reviews were identified and used for the development of the conceptual framework. Overall, six major themes emerged: patient-, medication-, disease-, provider-, system-, and societal-related factors. Each of these themes was further classified into different sub-categories. It was noted that most interactions were identified to be within the patient-related factors, which not only interact with other themes but also within the same theme. Patient's demographics as well as cultural beliefs were the most notable factors in terms of interactions with other categories and themes. The intricate network and interaction of factors identified between different themes and within individual themes indicate the complexity of the problem of adherence. This framework will potentially enhance the understanding of the complex relation between different barriers for medication adherence in diabetes and will facilitate design of more effective interventions. Future interventions for enhancing medication adherence should look at the overall factors and target multiple themes of barriers to improve patient outcomes. Copyright © 2017 Elsevier Inc. All rights reserved.

Classifying Patients with Chronic Pelvic Pain into Levels of Biopsychosocial Dysfunction Using Latent Class Modeling of Patient Reported Outcome Measures

PubMed Central

Fenton, Bradford W.; Grey, Scott F.; Tossone, Krystel; McCarroll, Michele; Von Gruenigen, Vivian E.

2015-01-01

Chronic pelvic pain affects multiple aspects of a patient's physical, social, and emotional functioning. Latent class analysis (LCA) of Patient Reported Outcome Measures Information System (PROMIS) domains has the potential to improve clinical insight into these patients' pain. Based on the 11 PROMIS domains applied to n=613 patients referred for evaluation in a chronic pelvic pain specialty center, exploratory factor analysis (EFA) was used to identify unidimensional superdomains. Latent profile analysis (LPA) was performed to identify the number of homogeneous classes present and to further define the pain classification system. The EFA combined the 11 PROMIS domains into four unidimensional superdomains of biopsychosocial dysfunction: Pain, Negative Affect, Fatigue, and Social Function. Based on multiple fit criteria, a latent class model revealed four distinct classes of CPP: No dysfunction (3.2%); Low Dysfunction (17.8%); Moderate Dysfunction (53.2%); and High Dysfunction (25.8%). This study is the first description of a novel approach to the complex disease process such as chronic pelvic pain and was validated by demographic, medical, and psychosocial variables. In addition to an essentially normal class, three classes of increasing biopsychosocial dysfunction were identified. The LCA approach has the potential for application to other complex multifactorial disease processes. PMID:26355825

The Role of Permanent Income and Demographics in Black/White Differences in Wealth

ERIC Educational Resources Information Center

Altonji, Joseph G.; Doraszelski, Ulrich

2005-01-01

A large part of the racial disparity with wealth holdings with income and demographic variables can be explained by examining the wealth model of a sample of whites, but only a small fraction when we use a black wealth model. Research finds a higher self-employment rate and a stronger link between self-employment and wealth for whites than for…

The changing demographic, legal, and technological contexts of political representation.

PubMed

Forest, Benjamin

2005-10-25

Three developments have created challenges for political representation in the U.S. and particularly for the use of territorially based representation (election by district). First, the demographic complexity of the U.S. population has grown both in absolute terms and in terms of residential patterns. Second, legal developments since the 1960s have recognized an increasing number of groups as eligible for voting rights protection. Third, the growing technical capacities of computer technology, particularly Geographic Information Systems, have allowed political parties and other organizations to create election districts with increasingly precise political and demographic characteristics. Scholars have made considerable progress in measuring and evaluating the racial and partisan biases of districting plans, and some states have tried to use Geographic Information Systems technology to produce more representative districts. However, case studies of Texas and Arizona illustrate that such analytic and technical advances have not overcome the basic contradictions that underlie the American system of territorial political representation.

Understanding Policy Diffusion in the U.S.: An Information-Theoretical Approach to Unveil Connectivity Structures in Slowly Evolving Complex Systems.

PubMed

Anderson, Ross P; Jimenez, Geronimo; Bae, Jin Yung; Silver, Diana; Macinko, James; Porfiri, Maurizio

2016-01-01

Detecting and explaining the relationships among interacting components has long been a focal point of dynamical systems research. In this paper, we extend these types of data-driven analyses to the realm of public policy, whereby individual legislative entities interact to produce changes in their legal and political environments. We focus on the U.S. public health policy landscape, whose complexity determines our capacity as a society to effectively tackle pressing health issues. It has long been thought that some U.S. states innovate and enact new policies, while others mimic successful or competing states. However, the extent to which states learn from others, and the state characteristics that lead two states to influence one another, are not fully understood. Here, we propose a model-free, information-theoretical method to measure the existence and direction of influence of one state's policy or legal activity on others. Specifically, we tailor a popular notion of causality to handle the slow time-scale of policy adoption dynamics and unravel relationships among states from their recent law enactment histories. The method is validated using surrogate data generated from a new stochastic model of policy activity. Through the analysis of real data in alcohol, driving safety, and impaired driving policy, we provide evidence for the role of geography, political ideology, risk factors, and demographic and economic indicators on a state's tendency to learn from others when shaping its approach to public health regulation. Our method offers a new model-free approach to uncover interactions and establish cause-and-effect in slowly-evolving complex dynamical systems.

Understanding Policy Diffusion in the U.S.: An Information-Theoretical Approach to Unveil Connectivity Structures in Slowly Evolving Complex Systems

PubMed Central

Anderson, Ross P.; Jimenez, Geronimo; Bae, Jin Yung; Silver, Diana; Macinko, James; Porfiri, Maurizio

2017-01-01

Detecting and explaining the relationships among interacting components has long been a focal point of dynamical systems research. In this paper, we extend these types of data-driven analyses to the realm of public policy, whereby individual legislative entities interact to produce changes in their legal and political environments. We focus on the U.S. public health policy landscape, whose complexity determines our capacity as a society to effectively tackle pressing health issues. It has long been thought that some U.S. states innovate and enact new policies, while others mimic successful or competing states. However, the extent to which states learn from others, and the state characteristics that lead two states to influence one another, are not fully understood. Here, we propose a model-free, information-theoretical method to measure the existence and direction of influence of one state’s policy or legal activity on others. Specifically, we tailor a popular notion of causality to handle the slow time-scale of policy adoption dynamics and unravel relationships among states from their recent law enactment histories. The method is validated using surrogate data generated from a new stochastic model of policy activity. Through the analysis of real data in alcohol, driving safety, and impaired driving policy, we provide evidence for the role of geography, political ideology, risk factors, and demographic and economic indicators on a state’s tendency to learn from others when shaping its approach to public health regulation. Our method offers a new model-free approach to uncover interactions and establish cause-and-effect in slowly-evolving complex dynamical systems. PMID:29075163

On valuing patches: Estimating contributions to metapopulation growth with reverse-time capture-recapture modelling

USGS Publications Warehouse

Sanderlin, J.S.; Waser, P.M.; Hines, J.E.; Nichols, J.D.

2012-01-01

Metapopulation ecology has historically been rich in theory, yet analytical approaches for inferring demographic relationships among local populations have been few. We show how reverse-time multi-state capture-recapture models can be used to estimate the importance of local recruitment and interpopulation dispersal to metapopulation growth. We use 'contribution metrics' to infer demographic connectedness among eight local populations of banner-tailed kangaroo rats, to assess their demographic closure, and to investigate sources of variation in these contributions. Using a 7 year dataset, we show that: (i) local populations are relatively independent demographically, and contributions to local population growth via dispersal within the system decline with distance; (ii) growth contributions via local survival and recruitment are greater for adults than juveniles, while contributions involving dispersal are greater for juveniles; (iii) central populations rely more on local recruitment and survival than peripheral populations; (iv) contributions involving dispersal are not clearly related to overall metapopulation density; and (v) estimated contributions from outside the system are unexpectedly large. Our analytical framework can classify metapopulations on a continuum between demographic independence and panmixia, detect hidden population growth contributions, and make inference about other population linkage forms, including rescue effects and source-sink structures. Finally, we discuss differences between demographic and genetic population linkage patterns for our system. ?? 2011 The Royal Society.

Determinants of the spatiotemporal dynamics of the 2009 H1N1 pandemic in Europe: implications for real-time modelling.

PubMed

Merler, Stefano; Ajelli, Marco; Pugliese, Andrea; Ferguson, Neil M

2011-09-01

Influenza pandemics in the last century were characterized by successive waves and differences in impact and timing between different regions, for reasons not clearly understood. The 2009 H1N1 pandemic showed rapid global spread, but with substantial heterogeneity in timing within each hemisphere. Even within Europe substantial variation was observed, with the UK being unique in experiencing a major first wave of transmission in early summer and all other countries having a single major epidemic in the autumn/winter, with a West to East pattern of spread. Here we show that a microsimulation model, parameterised using data about H1N1pdm collected by the beginning of June 2009, explains the occurrence of two waves in UK and a single wave in the rest of Europe as a consequence of timing of H1N1pdm spread, fluxes of travels from US and Mexico, and timing of school vacations. The model provides a description of pandemic spread through Europe, depending on intra-European mobility patterns and socio-demographic structure of the European populations, which is in broad agreement with observed timing of the pandemic in different countries. Attack rates are predicted to depend on the socio-demographic structure, with age dependent attack rates broadly agreeing with available serological data. Results suggest that the observed heterogeneity can be partly explained by the between country differences in Europe: marked differences in school calendars, mobility patterns and sociodemographic structures. Moreover, higher susceptibility of children to infection played a key role in determining the epidemiology of the 2009 pandemic. Our work shows that it would have been possible to obtain a broad-brush prediction of timing of the European pandemic well before the autumn of 2009, much more difficult to achieve with simpler models or pre-pandemic parameterisation. This supports the use of models accounting for the structure of complex modern societies for giving insight to policy makers.

Unravelling the Impacts of Climate and People on Vegetation Dynamics in the Sahel 1982- 2002

NASA Astrophysics Data System (ADS)

Seaquist, J. W.; Hickler, T.; Eklundh, L.; Ardö, J.; Heumann, B. W.

2009-05-01

Satellite sensors have recently shown that much of the Sahel belt of north Africa has experienced significant increases in photosynthetic activity since the early 1980s. This has reignited old debates about the role that people play in shaping land surface status at broad geographical extents. If the human 'footprint' on Sahel vegetation dynamics is measurable, then such impacts may be significant enough alter broad-scale both carbon budgets and climate via land surface atmosphere feedbacks. We test the hypothesis that people have had a measurable impact on vegetation dynamics in the Sahel for the period 1982-2002. We accomplish this by mapping the agreement between potential natural vegetation dynamics predicted by a process-based ecosystem model (Lund Potsdam Jena-Dynamic Global Vegetation Model) and satellite-derived greenness observations (Global Inventory Modelling and Mapping Studies data set) across a geographic grid at a spatial resolution of 0.5 degrees. We then relate this agreement metric to state-of-the-art data sets on demographics, pasture, and cropping. Demographic and agricultural pressures in the Sahel are unable to account for differences between simulated and observed vegetation dynamics, even for the most densely populated areas. But we do identify a weak, positive correlation between data-model agreement and pasture intensity at the Sahel-wide level. This indicates that herding or grazing does not appreciably affect vegetation dynamics in the region. Either people have not had a significant impact on vegetation dynamics in the Sahel or the identification of a human 'footprint' is precluded by inconsistent or subtle vegetation response to complex socio-environmental interactions, and/or limitations in the data used for this study. This research showcases untapped potential for combining ecosystem process models with remote sensing at broad spatial extents for examining the underlying causes of ecosystem change.

Madeiran Arabidopsis thaliana reveals ancient long-range colonization and clarifies demography in Eurasia.

PubMed

Fulgione, Andrea; Koornneef, Maarten; Roux, Fabrice; Hermisson, Joachim; Hancock, Angela M

2017-12-05

The study of model organisms on islands may shed light on rare long-range dispersal events, uncover signatures of local evolutionary processes, and inform demographic inference on the mainland. Here, we sequenced the genomes of Arabidopsis thaliana samples from the oceanic island of Madeira. These samples include the most diverged worldwide, likely a result of long isolation on the island. We infer that colonisation of Madeira happened between 70 and 85 kya, consistent with a propagule dispersal model (of size > =10), or with an ecological window of opportunity. This represents a clear example of a natural long-range dispersal event in A. thaliana. Long-term effective population size on the island, rather than the founder effect, had the greatest impact on levels of diversity, and rates of coalescence. Our results uncover a selective sweep signature on the ancestral haplotype of a known translocation in Eurasia, as well as the possible importance of the low phosphorous availability in volcanic soils, and altitude, in shaping early adaptations to the island conditions. Madeiran genomes, sheltered from the complexities of continental demography, help illuminate ancient demographic events in Eurasia. Our data support a model in which two separate lineages of A. thaliana, one originating in Africa and the other from the Caucasus expanded and met in Iberia, resulting in a secondary contact zone there. While previous studies inferred that the westward expansion of A. thaliana coincided with the spread of human agriculture, our results suggest it happened much earlier (20-40 kya). © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Disentangling the effects of climate and people on Sahel vegetation dynamics

NASA Astrophysics Data System (ADS)

Seaquist, J. W.; Hickler, T.; Eklundh, L.; Ardö, J.; Heumann, B. W.

2008-08-01

The Sahel belt of Africa has been the focus of intensive scientific research since the 1960s, spurred on by the chronic vulnerability of its population to recurring drought and the threat of long-term land degradation. But satellite sensors have recently shown that much of the region has experienced significant increases in photosynthetic activity since the early 1980s, thus re-energizing long-standing debates about the role that people play in shaping land surface status, and thus climate at regional scales. In this paper, we test the hypothesis that people have had a measurable impact on vegetation dynamics in the Sahel for the period 1982 2002. We compare potential natural vegetation dynamics predicted by a process-based ecosystem model with satellite-derived greenness observations, and map the agreement between the two across a geographic grid at a spatial resolution of 0.5°. As aggregated data-model agreement is very good, any local differences between the two could be due to human impact. We then relate this agreement metric to state-of-the-art data sets on demographics, pasture, and cropping. Our findings suggest that demographic and agricultural pressures in the Sahel are unable to account for differences between simulated and observed vegetation dynamics, even for the most densely populated areas. But we do identify a weak, positive correlation between data-model agreement and pasture intensity at the Sahel-wide level. This indicates that herding or grazing does not appreciably affect vegetation dynamics in the region. Either people have not had a significant impact on vegetation dynamics in the Sahel or the identification of a human "footprint" is precluded by inconsistent or subtle vegetation response to complex socio-environmental interactions, and/or limitations in the data used for this study.

Neighbouring populations, opposite dynamics: influence of body size and environmental variation on the demography of stream-resident brown trout (Salmo trutta).

PubMed

Fernández-Chacón, Albert; Genovart, Meritxell; Álvarez, David; Cano, José M; Ojanguren, Alfredo F; Rodriguez-Muñoz, Rolando; Nicieza, Alfredo G

2015-06-01

In organisms such as fish, where body size is considered an important state variable for the study of their population dynamics, size-specific growth and survival rates can be influenced by local variation in both biotic and abiotic factors, but few studies have evaluated the complex relationships between environmental variability and size-dependent processes. We analysed a 6-year capture-recapture dataset of brown trout (Salmo trutta) collected at 3 neighbouring but heterogeneous mountain streams in northern Spain with the aim of investigating the factors shaping the dynamics of local populations. The influence of body size and water temperature on survival and individual growth was assessed under a multi-state modelling framework, an extension of classical capture-recapture models that considers the state (i.e. body size) of the individual in each capture occasion and allows us to obtain state-specific demographic rates and link them to continuous environmental variables. Individual survival and growth patterns varied over space and time, and evidence of size-dependent survival was found in all but the smallest stream. At this stream, the probability of reaching larger sizes was lower compared to the other wider and deeper streams. Water temperature variables performed better in the modelling of the highest-altitude population, explaining over a 99 % of the variability in maturation transitions and survival of large fish. The relationships between body size, temperature and fitness components found in this study highlight the utility of multi-state approaches to investigate small-scale demographic processes in heterogeneous environments, and to provide reliable ecological knowledge for management purposes.

Influence of environmental heterogeneity on the distribution and persistence of a subterranean rodent in a highly unstable landscape.

PubMed

Gómez Fernández, María Jimena; Boston, Emma S M; Gaggiotti, Oscar E; Kittlein, Marcelo J; Mirol, Patricia M

2016-12-01

In this study we combine information from landscape characteristics, demographic inference and species distribution modelling to identify environmental factors that shape the genetic distribution of the fossorial rodent Ctenomys. We sequenced the mtDNA control region and amplified 12 microsatellites from 27 populations distributed across the Iberá wetland ecosystem. Hierarchical Bayesian modelling was used to construct phylogenies and estimate divergence times. We developed species distribution models to determine what climatic variables and soil parameters predicted species presence by comparing the current to the historic and predicted future distribution of the species. Finally, we explore the impact of environmental variables on the genetic structure of Ctenomys based on current and past species distributions. The variables that consistently correlated with the predicted distribution of the species and explained the observed genetic differentiation among populations included the distribution of well-drained sandy soils and temperature seasonality. A core region of stable suitable habitat was identified from the Last Interglacial, which is projected to remain stable into the future. This region is also the most genetically diverse and is currently under strong anthropogenic pressure. Results reveal complex demographic dynamics, which have been in constant change in both time and space, and are likely linked to the evolution of the Paraná River. We suggest that any alteration of soil properties (climatic or anthropic) may significantly impact the availability of suitable habitat and consequently the ability of individuals to disperse. The protection of this core stable habitat is of prime importance given the increasing levels of human disturbance across this wetland system and the threat of climate change.

The Spatial Effect of Socio-Economic Demographics on Transit Ridership: a Case Study in New York

DOT National Transportation Integrated Search

2018-03-01

Demand for vehicle and public transportation systems continues to increase in and around major urban centers. This increase is especially pronounced during the morning and evening commutes and is further complicated by the complex spatial interaction...

Population Genomic Analysis Reveals a Rich Speciation and Demographic History of Orang-utans (Pongo pygmaeus and Pongo abelii)

PubMed Central

Ma, Xin; Kelley, Joanna L.; Eilertson, Kirsten; Musharoff, Shaila; Degenhardt, Jeremiah D.; Martins, André L.; Vinar, Tomas; Kosiol, Carolin; Siepel, Adam; Gutenkunst, Ryan N.; Bustamante, Carlos D.

2013-01-01

To gain insights into evolutionary forces that have shaped the history of Bornean and Sumatran populations of orang-utans, we compare patterns of variation across more than 11 million single nucleotide polymorphisms found by previous mitochondrial and autosomal genome sequencing of 10 wild-caught orang-utans. Our analysis of the mitochondrial data yields a far more ancient split time between the two populations (∼3.4 million years ago) than estimates based on autosomal data (0.4 million years ago), suggesting a complex speciation process with moderate levels of primarily male migration. We find that the distribution of selection coefficients consistent with the observed frequency spectrum of autosomal non-synonymous polymorphisms in orang-utans is similar to the distribution in humans. Our analysis indicates that 35% of genes have evolved under detectable negative selection. Overall, our findings suggest that purifying natural selection, genetic drift, and a complex demographic history are the dominant drivers of genome evolution for the two orang-utan populations. PMID:24194868

Population genomic analysis reveals a rich speciation and demographic history of orang-utans (Pongo pygmaeus and Pongo abelii).

PubMed

Ma, Xin; Kelley, Joanna L; Eilertson, Kirsten; Musharoff, Shaila; Degenhardt, Jeremiah D; Martins, André L; Vinar, Tomas; Kosiol, Carolin; Siepel, Adam; Gutenkunst, Ryan N; Bustamante, Carlos D

2013-01-01

To gain insights into evolutionary forces that have shaped the history of Bornean and Sumatran populations of orang-utans, we compare patterns of variation across more than 11 million single nucleotide polymorphisms found by previous mitochondrial and autosomal genome sequencing of 10 wild-caught orang-utans. Our analysis of the mitochondrial data yields a far more ancient split time between the two populations (~3.4 million years ago) than estimates based on autosomal data (0.4 million years ago), suggesting a complex speciation process with moderate levels of primarily male migration. We find that the distribution of selection coefficients consistent with the observed frequency spectrum of autosomal non-synonymous polymorphisms in orang-utans is similar to the distribution in humans. Our analysis indicates that 35% of genes have evolved under detectable negative selection. Overall, our findings suggest that purifying natural selection, genetic drift, and a complex demographic history are the dominant drivers of genome evolution for the two orang-utan populations.

[Human resources planning: the use of demographic-economic models].

PubMed

Daubon, R E

1980-01-01

This article provides an overview of the evolution of employment at different stages of economic development and describes the employment situation in developing countries, suggesting future trends and means of improvement. The lack of authentic development is reflected in the problem of employment of both natural and human resources in Third World countries. Their occupational structures may be examined in 2 periods, 1 in which a certain pretransitional equilibrium was still observed, and the other following the beginning of industrialization. With increased population growth and the application of development strategies favoring urban areas and manufacturing, a series of imbalances were introduced which had as 1 consequence an ever widening income gap between rural areas, cities, and developed countries. Rural stagnation and population pressure ultimately led to massive urban migration in many areas, swelling the cities and creating an "informal sector" of underemployed persons in marginal activities of low productivity. By 2050, the world labor force will have increased from its present 1.7 billion workers to 3.8 billion, of which only 660 million will be in presently developed countries. Each country must plan the best use of its human resources, and must include employment planning in overall development planning. The development of economic-demographic models, adapted to the context of each country, can be a valuable tool in planning. Various types of economic-demographic models and their uses are described and differentiated. Economic-demographic models of employment have 3 main parts, demography, economy, and training. Their use in the analysis of the impact of specific variables on employment, of policies, and of general strategies is described. Finally, the characteristics and uses of MODEMP, an economic-demographic model created for analysis of labor force and employment problems in Peru, are described.

Lost in the crowd? Using eye-tracking to investigate the effect of complexity on attribute non-attendance in discrete choice experiments.

PubMed

Spinks, Jean; Mortimer, Duncan

2016-02-03

The provision of additional information is often assumed to improve consumption decisions, allowing consumers to more accurately weigh the costs and benefits of alternatives. However, increasing the complexity of decision problems may prompt changes in information processing. This is particularly relevant for experimental methods such as discrete choice experiments (DCEs) where the researcher can manipulate the complexity of the decision problem. The primary aims of this study are (i) to test whether consumers actually process additional information in an already complex decision problem, and (ii) consider the implications of any such 'complexity-driven' changes in information processing for design and analysis of DCEs. A discrete choice experiment (DCE) is used to simulate a complex decision problem; here, the choice between complementary and conventional medicine for different health conditions. Eye-tracking technology is used to capture the number of times and the duration that a participant looks at any part of a computer screen during completion of DCE choice sets. From this we can analyse what has become known in the DCE literature as 'attribute non-attendance' (ANA). Using data from 32 participants, we model the likelihood of ANA as a function of choice set complexity and respondent characteristics using fixed and random effects models to account for repeated choice set completion. We also model whether participants are consistent with regard to which characteristics (attributes) they consider across choice sets. We find that complexity is the strongest predictor of ANA when other possible influences, such as time pressure, ordering effects, survey specific effects and socio-demographic variables (including proxies for prior experience with the decision problem) are considered. We also find that most participants do not apply a consistent information processing strategy across choice sets. Eye-tracking technology shows promise as a way of obtaining additional information from consumer research, improving DCE design, and informing the design of policy measures. With regards to DCE design, results from the present study suggest that eye-tracking data can identify the point at which adding complexity (and realism) to DCE choice scenarios becomes self-defeating due to unacceptable increases in ANA. Eye-tracking data therefore has clear application in the construction of guidelines for DCE design and during piloting of DCE choice scenarios. With regards to design of policy measures such as labelling requirements for CAM and conventional medicines, the provision of additional information has the potential to make difficult decisions even harder and may not have the desired effect on decision-making.

A demographic-economic explanation of political stability: Mauritius as a microcosm.

PubMed

Lempert, D

1987-06-01

"This paper examines current models of economic and political development--social modernization theory, political and economic characteristics of stable regimes, and cross country analysis of political stability--and tests them on the Indian Ocean Island of Mauritius. The analysis continues with a causal explanation for political stability in Mauritius' recent history, derived from an examination of economic policies and demographic patterns. Political change in Mauritius over the past sixty years seems to be explained best by a model for political stability which integrates specific economic and demographic factors. The model, applicable to development in other third world nations, revises Malthus' conclusion that population and economic conditions move in an oscillatory relationship and replaces it with a more comprehensive theory, suggesting that political stability is a function of both economic development and a repeating cyclical relationship between economics and population." excerpt

Developing an Extended Model of the Relation between Work Motivation and Health as Affected by the Work Ability as Part of a Corporate Age Management Approach

PubMed Central

Feißel, Annemarie; Peter, Richard; Swart, Enno

2018-01-01

Due to demographic changes, the employee structure in companies is changing dramatically. It will be necessary to offer employees suitable, age-adequate jobs. As one of its foremost goals, optimized business management strategies must create conditions for guaranteeing a person’s health, work ability, and work motivation. In the context of corporate age management concepts, the literature recommends to retain and integrate older employees in the organization. This paper aims at developing an extended model of the relation between work motivation and health as affected by work ability and at deriving a host of measures that enterprises can apply as part of a corporate age management policy to counteract the impact of demographic changes. The model also takes into consideration factors influencing the relation between work motivation and health as affected by work ability (socio-demographic parameters, occupation, work-related stress). Additionally, the extended model translates the literature-based results into a corporate setting by way of a corporate age management program. The model comprises a process focusing on retaining and promoting work ability in order to maintain or boost work motivation and health. The host of measures presented serves as a basis to preventively counter demographic change on an individual, interpersonal, and structural level. PMID:29673218

Developing an Extended Model of the Relation between Work Motivation and Health as Affected by the Work Ability as Part of a Corporate Age Management Approach.

PubMed

Feißel, Annemarie; Peter, Richard; Swart, Enno; March, Stefanie

2018-04-17

Due to demographic changes, the employee structure in companies is changing dramatically. It will be necessary to offer employees suitable, age-adequate jobs. As one of its foremost goals, optimized business management strategies must create conditions for guaranteeing a person’s health, work ability, and work motivation. In the context of corporate age management concepts, the literature recommends to retain and integrate older employees in the organization. This paper aims at developing an extended model of the relation between work motivation and health as affected by work ability and at deriving a host of measures that enterprises can apply as part of a corporate age management policy to counteract the impact of demographic changes. The model also takes into consideration factors influencing the relation between work motivation and health as affected by work ability (socio-demographic parameters, occupation, work-related stress). Additionally, the extended model translates the literature-based results into a corporate setting by way of a corporate age management program. The model comprises a process focusing on retaining and promoting work ability in order to maintain or boost work motivation and health. The host of measures presented serves as a basis to preventively counter demographic change on an individual, interpersonal, and structural level.

Rethinking plant functional types in Earth System Models: pan-tropical analysis of tree survival across environmental gradients

NASA Astrophysics Data System (ADS)

Johnson, D. J.; Needham, J.; Xu, C.; Davies, S. J.; Bunyavejchewin, S.; Giardina, C. P.; Condit, R.; Cordell, S.; Litton, C. M.; Hubbell, S.; Kassim, A. R. B.; Shawn, L. K. Y.; Nasardin, M. B.; Ong, P.; Ostertag, R.; Sack, L.; Tan, S. K. S.; Yap, S.; McDowell, N. G.; McMahon, S.

2016-12-01

Terrestrial carbon cycling is a function of the growth and survival of trees. Current model representations of tree growth and survival at a global scale rely on coarse plant functional traits that are parameterized very generally. In view of the large biodiversity in the tropical forests, it is important that we account for the functional diversity in order to better predict tropical forest responses to future climate changes. Several next generation Earth System Models are moving towards a size-structured, trait-based approach to modelling vegetation globally, but the challenge of which and how many traits are necessary to capture forest complexity remains. Additionally, the challenge of collecting sufficient trait data to describe the vast species richness of tropical forests is enormous. We propose a more fundamental approach to these problems by characterizing forests by their patterns of survival. We expect our approach to distill real-world tree survival into a reasonable number of functional types. Using 10 large-area tropical forest plots that span geographic, edaphic and climatic gradients, we model tree survival as a function of tree size for hundreds of species. We found surprisingly few categories of size-survival functions emerge. This indicates some fundamental strategies at play across diverse forests to constrain the range of possible size-survival functions. Initial cluster analysis indicates that four to eight functional forms are necessary to describe variation in size-survival relations. Temporal variation in size-survival functions can be related to local environmental variation, allowing us to parameterize how demographically similar groups of species respond to perturbations in the ecosystem. We believe this methodology will yield a synthetic approach to classifying forest systems that will greatly reduce uncertainty and complexity in global vegetation models.

Involving older people in a multi-centre randomised trial of a complex intervention in pre-hospital emergency care: implementation of a collaborative model.

PubMed

Koniotou, Marina; Evans, Bridie Angela; Chatters, Robin; Fothergill, Rachael; Garnsworthy, Christopher; Gaze, Sarah; Halter, Mary; Mason, Suzanne; Peconi, Julie; Porter, Alison; Siriwardena, A Niroshan; Toghill, Alun; Snooks, Helen

2015-07-10

Health services research is expected to involve service users as active partners in the research process, but few examples report how this has been achieved in practice in trials. We implemented a model to involve service users in a multi-centre randomised controlled trial in pre-hospital emergency care. We used the generic Standard Operating Procedure (SOP) from our Clinical Trials Unit (CTU) as the basis for creating a model to fit the context and population of the SAFER 2 trial. In our model, we planned to involve service users at all stages in the trial through decision-making forums at 3 levels: 1) strategic; 2) site (e.g. Wales; London; East Midlands); 3) local. We linked with charities and community groups to recruit people with experience of our study population. We collected notes of meetings alongside other documentary evidence such as attendance records and study documentation to track how we implemented our model. We involved service users at strategic, site and local level. We also added additional strategic level forums (Task and Finish Groups and Writing Days) where we included service users. Service user involvement varied in frequency and type across meetings, research stages and locations but stabilised and increased as the trial progressed. Involving service users in the SAFER 2 trial showed how it is feasible and achievable for patients, carers and potential patients sharing the demographic characteristics of our study population to collaborate in a multi-centre trial at the level which suited their health, location, skills and expertise. A standard model of involvement can be tailored by adopting a flexible approach to take account of the context and complexities of a multi-site trial. Current Controlled Trials ISRCTN60481756. Registered: 13 March 2009.

Demographic and genetic connectivity: the role and consequences of reproduction, dispersal and recruitment in seagrasses.

PubMed

Kendrick, Gary A; Orth, Robert J; Statton, John; Hovey, Renae; Ruiz Montoya, Leonardo; Lowe, Ryan J; Krauss, Siegfried L; Sinclair, Elizabeth A

2017-05-01

Accurate estimation of connectivity among populations is fundamental for determining the drivers of population resilience, genetic diversity, adaptation and speciation. However the separation and quantification of contemporary versus historical connectivity remains a major challenge. This review focuses on marine angiosperms, seagrasses, that are fundamental to the health and productivity of temperate and tropical coastal marine environments globally. Our objective is to understand better the role of sexual reproduction and recruitment in influencing demographic and genetic connectivity among seagrass populations through an integrated multidisciplinary assessment of our present ecological, genetic, and demographic understanding, with hydrodynamic modelling of transport. We investigate (i) the demographic consequences of sexual reproduction, dispersal and recruitment in seagrasses, (ii) contemporary transport of seagrass pollen, fruits and seed, and vegetative fragments with a focus on hydrodynamic and particle transport models, and (iii) contemporary genetic connectivity among seagrass meadows as inferred through the application of genetic markers. New approaches are reviewed, followed by a summary outlining future directions for research: integrating seascape genetic approaches; incorporating hydrodynamic modelling for dispersal of pollen, seeds and vegetative fragments; integrating studies across broader geographic ranges; and incorporating non-equilibrium modelling. These approaches will lead to a more integrated understanding of the role of contemporary dispersal and recruitment in the persistence and evolution of seagrasses. © 2016 Cambridge Philosophical Society.

Demographic factors and traffic crashes. Part 1, descriptive statistics and models

DOT National Transportation Integrated Search

1998-08-01

This research analyzes the Department of Highway Safety and Motor Vehicle's (DHSMV) 1993 to 1995 crash data. There are four demographic variables investigated throughout the research, which are age, gender, race, and residency. To show general trends...

An evaluation of the relations between flow regime components, stream characteristics, species traits and meta-demographic rates of warmwater stream fishes: Implications for aquatic resource management

USGS Publications Warehouse

Peterson, James T.; Shea, C.P.

2015-01-01

Fishery biologists are increasingly recognizing the importance of considering the dynamic nature of streams when developing streamflow policies. Such approaches require information on how flow regimes influence the physical environment and how those factors, in turn, affect species-specific demographic rates. A more cost-effective alternative could be the use of dynamic occupancy models to predict how species are likely to respond to changes in flow. To appraise the efficacy of this approach, we evaluated relative support for hypothesized effects of seasonal streamflow components, stream channel characteristics, and fish species traits on local extinction, colonization, and recruitment (meta-demographic rates) of stream fishes. We used 4 years of seasonal fish collection data from 23 streams to fit multistate, multiseason occupancy models for 42 fish species in the lower Flint River Basin, Georgia. Modelling results suggested that meta-demographic rates were influenced by streamflows, particularly short-term (10-day) flows. Flow effects on meta-demographic rates also varied with stream size, channel morphology, and fish species traits. Small-bodied species with generalized life-history characteristics were more resilient to flow variability than large-bodied species with specialized life-history characteristics. Using this approach, we simplified the modelling framework, thereby facilitating the development of dynamic, spatially explicit evaluations of the ecological consequences of water resource development activities over broad geographic areas. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

The evolutionary time machine: forecasting how populations can adapt to changing environments using dormant propagules

PubMed Central

Orsini, Luisa; Schwenk, Klaus; De Meester, Luc; Colbourne, John K.; Pfrender, Michael E.; Weider, Lawrence J.

2013-01-01

Evolutionary changes are determined by a complex assortment of ecological, demographic and adaptive histories. Predicting how evolution will shape the genetic structures of populations coping with current (and future) environmental challenges has principally relied on investigations through space, in lieu of time, because long-term phenotypic and molecular data are scarce. Yet, dormant propagules in sediments, soils and permafrost are convenient natural archives of population-histories from which to trace adaptive trajectories along extended time periods. DNA sequence data obtained from these natural archives, combined with pioneering methods for analyzing both ecological and population genomic time-series data, are likely to provide predictive models to forecast evolutionary responses of natural populations to environmental changes resulting from natural and anthropogenic stressors, including climate change. PMID:23395434

Contextualizing Gay-Straight Alliances: Student, Advisor, and Structural Factors Related to Positive Youth Development Among Members

PubMed Central

Poteat, V. Paul; Yoshikawa, Hirokazu; Calzo, Jerel P.; Gray, Mary L.; DiGiovanni, Craig. D.; Lipkin, Arthur; Mundy-Shephard, Adrienne; Perrotti, Jeff; Scheer, Jillian R.; Shaw, Mathew P.

2014-01-01

Gay-Straight Alliances (GSAs) may promote resilience. Yet, what GSA components predict wellbeing? Among 146 youth and advisors in 13 GSAs (58% lesbian, gay, bisexual, or questioning; 64% white; 38% received free/reduced-cost lunch), student (demographics, victimization, attendance frequency, leadership, support, control), advisor (years served, training, control) and contextual factors (overall support or advocacy, outside support for the GSA) that predicted purpose, mastery, and self-esteem were tested. In multilevel models, GSA support predicted all outcomes. Racial/ethnic minority youth reported greater wellbeing, yet lower support. Youth in GSAs whose advisors served longer and perceived more control and were in more supportive school contexts reported healthier outcomes. GSA advocacy also predicted purpose. Ethnographic notes elucidated complex associations and variability in how GSAs operated. PMID:25176579

The investigation of vertebral injury sustained during aircrew ejection

NASA Technical Reports Server (NTRS)

Benedict, J. V.

1972-01-01

A series of tests were performed on excised human vertebral segments to determine the static and dynamic response of the thoraco-lumbar spine when loaded in flexion. A total of fifteen tests were performed on eleven specimens. Specimens were obtained from male donors ranging in age from 34 to 60 years. Demographic data pertinent to each specimen and the elapsed time between death of the donor and testing of each corresponding specimen are presented. Only spinal segments comprised of lower thoracic and upper lumbar vertebrae were tested because in aircraft ejection injuries clinical complications in this anatomical region predominate. A complex continuum mathematical model describing the dynamic response of the human spine was formulated, solved, and verified experimentally. Detailed results are presented in figures, tables, and equations.

Complex Biventricular Pacing - A Case Series

PubMed Central

Hodkinson, Emily Catherine; Morrice, Keith; Loan, William; Nicholas, Jacob; Chew, EngWooi

2014-01-01

It is established that cardiac resynchronisation therapy (CRT) reduces mortality and hospitalisation and improves functional class in patients with NYHA class 3-4 heart failure, an ejection fraction of ≤ 35% and a QRS duration of ≥ 120ms. Recent updates in the American guidelines have expanded the demographic of patients in whom CRT may be appropriate. Here we present two cases of complex CRT; one with a conventional indication but occluded central veins and the second with a novel indication for CRT post cardiac transplant. PMID:24493915

Integrating Demographic, Clinical,and Environmental Exposure Information to Identify Genomic Biomarkers Associated With Subtypes of Childhood Asthma

EPA Science Inventory

Childhood asthma is a multifactorial disease with a disturbingly high incidence in urbanized areas. The pathogenesis of asthma is poorly understood due to the complex relationship between genetic susceptibility and modulating environmental factors. The Mechanistic Indicators of C...

Molecular hyperdiversity and evolution in very large populations.

PubMed

Cutter, Asher D; Jovelin, Richard; Dey, Alivia

2013-04-01

The genomic density of sequence polymorphisms critically affects the sensitivity of inferences about ongoing sequence evolution, function and demographic history. Most animal and plant genomes have relatively low densities of polymorphisms, but some species are hyperdiverse with neutral nucleotide heterozygosity exceeding 5%. Eukaryotes with extremely large populations, mimicking bacterial and viral populations, present novel opportunities for studying molecular evolution in sexually reproducing taxa with complex development. In particular, hyperdiverse species can help answer controversial questions about the evolution of genome complexity, the limits of natural selection, modes of adaptation and subtleties of the mutation process. However, such systems have some inherent complications and here we identify topics in need of theoretical developments. Close relatives of the model organisms Caenorhabditis elegans and Drosophila melanogaster provide known examples of hyperdiverse eukaryotes, encouraging functional dissection of resulting molecular evolutionary patterns. We recommend how best to exploit hyperdiverse populations for analysis, for example, in quantifying the impact of noncrossover recombination in genomes and for determining the identity and micro-evolutionary selective pressures on noncoding regulatory elements. © 2013 Blackwell Publishing Ltd.

Prescription Drug Misuse and Sexual Behavior among Young Adults

PubMed Central

Wells, Brooke E.; Kelly, Brian C.; Rendina, H. Jonathon; Parsons, Jeffrey T.

2015-01-01

Though research indicates a complex link between substance use and sexual risk behavior, there is limited research on the association between sexual risk behavior and prescription drug misuse. In light of the alarming increases in prescription drug misuse and the role of demographic characteristics in sexual risk behavior and outcomes, the current study examines demographic differences (gender, sexual identity, age, relationship status, parental class background, and race/ethnicity) in sexual risk behavior, sexual behavior under the influence of prescription drugs, and sexual risk behavior under the influence of prescription drugs in a sample of 402 young adults (18–29) who misuse prescription drugs. Nearly half of the sexually active young adult prescription drug misusers in this sample reported recent sex under the influence of prescription drugs, more than three quarters reported recent sex without a condom, and more than one-third reported recent sex without a condom after using prescription drugs. Zero-inflated Poisson regression models indicated that white race, younger age, higher parental class, and being a heterosexual man were all associated with sexual risk behavior, sex under the influence of prescription drugs, and sexual risk under the influence of prescription drugs. Findings have implications for the targeting of prevention and intervention efforts. PMID:25569204

Influence of hospital-level practice patterns on variation in the application of minimally invasive surgery in United States pediatric patients.

PubMed

Train, Arianne T; Harmon, Carroll M; Rothstein, David H

2017-10-01

Although disparities in access to minimally invasive surgery are thought to exist in pediatric surgical patients in the United States, hospital-level practice patterns have not been evaluated as a possible contributing factor. Retrospective cohort study using the Kids' Inpatient Database, 2012. Odds ratios of undergoing a minimally invasive compared to open operation were calculated for six typical pediatric surgical operations after adjustment for multiple patient demographic and hospital-level variables. Further adjustment to the regression model was made by incorporating hospital practice patterns, defined as operation-specific minimally invasive frequency and volume. Age was the most significant patient demographic factor affecting application of minimally invasive surgery for all procedures. For several procedures, adjusting for individual hospital practice patterns removed race- and income-based disparities seen in performance of minimally invasive operations. Disparities related to insurance status were not affected by the same adjustment. Variation in the application of minimally invasive surgery in pediatric surgical patients is primarily influenced by patient age and the type of procedure performed. Perceived disparities in access related to some socioeconomic factors are decreased but not eliminated by accounting for individual hospital practice patterns, suggesting that complex underlying factors influence application of advanced surgical techniques. II. Copyright © 2017 Elsevier Inc. All rights reserved.

Association between domestic violence and HIV serostatus among married and formerly married women in Kenya

PubMed Central

Abuya, Benta A; Okech, Irene N; Rosen, David L; Duren-Winfield, Vanessa; Simmons, Amber C

2014-01-01

The prevalence of both domestic violence (DV) and HIV among Kenyan women is known to be high, but the relationship between them is unknown. Nationally representative cross-sectional data from married and formerly married (MFM) women responding to the Kenya Demographic and Health Survey 2008/2009 were analyzed adjusting for complex survey design. Multivariable logistic regressions were used to assess the covariate-adjusted associations between HIV serostatus and any reported DV as well as four constituent DV measures: physical, emotional, sexual, and aggravated bodily harm, adjusting for co-variates entered into each model using a forward stepwise selection process. Co-variates of a priori interest included those representing marriage history, risky sexual behavior, substance use, perceived HIV risk, and socio-demographic characteristics. The prevalence of HIV among MFM women was 10.7% (any DV: 13.1%, no DV: 8.6%); overall prevalence of DV was 43.4%. Among all DV measures, only physical DV was associated with HIV (11.9%; adjusted odds ratio: 2.01, p < 0.05). Efforts by the government and women's groups to monitor and improve policies to reduce DV, such as the Sexual Offences Act of 2006, are urgently needed to curb HIV, as are policies that seek to provide DV counseling and treatment to MFM women. PMID:25127397

Institutional delivery in public and private sectors in South Asia: a comparative analysis of prospective data from four demographic surveillance sites.

PubMed

Das, Sushmita; Alcock, Glyn; Azad, Kishwar; Kuddus, Abdul; Manandhar, Dharma S; Shrestha, Bhim Prasad; Nair, Nirmala; Rath, Shibanand; More, Neena Shah; Saville, Naomi; Houweling, Tanja A J; Osrin, David

2016-09-20

Maternity care in South Asia is available in both public and private sectors. Using data from demographic surveillance sites in Bangladesh, Nepal and rural and urban India, we aimed to compare institutional delivery rates and public-private share. We used records of maternity care collected in socio-economically disadvantaged communities between 2005 and 2011. Institutional delivery was summarized by four potential determinants: household asset index, maternal schooling, maternal age, and parity. We developed logistic regression models for private sector institutional delivery with these as independent covariates. The data described 52 750 deliveries. Institutional delivery proportion varied and there were differences in public-private split. In Bangladesh and urban India, the proportion of deliveries in the private sector increased with wealth, maternal education, and age. The opposite was observed in rural India and Nepal. The proportion of institutional delivery increased with economic status and education. The choice of sector is more complex and provision and perceived quality of public sector services is likely to play a role. Choices for safe maternity are influenced by accessibility, quantity and perceived quality of care. Along with data linkage between private and public sectors, increased regulation should be part of the development of the pluralistic healthcare systems that characterize south Asia.

Associations between sexual habits, menstrual hygiene practices, demographics and the vaginal microbiome as revealed by Bayesian network analysis

PubMed Central

Noyes, Noelle; Cho, Kyu-Chul; Ravel, Jacques; Forney, Larry J.

2018-01-01

The vaginal microbiome plays an influential role in several disease states in reproductive age women, including bacterial vaginosis (BV). While demographic characteristics are associated with differences in vaginal microbiome community structure, little is known about the influence of sexual and hygiene habits. Furthermore, associations between the vaginal microbiome and risk symptoms of bacterial vaginosis have not been fully elucidated. Using Bayesian network (BN) analysis of 16S rRNA gene sequence results, demographic and extensive questionnaire data, we describe both novel and previously documented associations between habits of women and their vaginal microbiome. The BN analysis approach shows promise in uncovering complex associations between disparate data types. Our findings based on this approach support published associations between specific microbiome members (e.g., Eggerthella, Gardnerella, Dialister, Sneathia and Ruminococcaceae), the Nugent score (a BV diagnostic) and vaginal pH (a risk symptom of BV). Additionally, we found that several microbiome members were directly connected to other risk symptoms of BV (such as vaginal discharge, odor, itch, irritation, and yeast infection) including L. jensenii, Corynebacteria, and Proteobacteria. No direct connections were found between the Nugent Score and risk symptoms of BV other than pH, indicating that the Nugent Score may not be the most useful criteria for assessment of clinical BV. We also found that demographics (i.e., age, ethnicity, previous pregnancy) were associated with the presence/absence of specific vaginal microbes. The resulting BN revealed several as-yet undocumented associations between birth control usage, menstrual hygiene practices and specific microbiome members. Many of these complex relationships were not identified using common analytical methods, i.e., ordination and PERMANOVA. While these associations require confirmatory follow-up study, our findings strongly suggest that future studies of the vaginal microbiome and vaginal pathologies should include detailed surveys of participants’ sanitary, sexual and birth control habits, as these can act as confounders in the relationship between the microbiome and disease. Although the BN approach is powerful in revealing complex associations within multidimensional datasets, the need in some cases to discretize the data for use in BN analysis can result in loss of information. Future research is required to alleviate such limitations in constructing BN networks. Large sample sizes are also required in order to allow for the incorporation of a large number of variables (nodes) into the BN, particularly when studying associations between metadata and the microbiome. We believe that this approach is of great value, complementing other methods, to further our understanding of complex associations characteristic of microbiome research. PMID:29364944

Associations between sexual habits, menstrual hygiene practices, demographics and the vaginal microbiome as revealed by Bayesian network analysis.

PubMed

Noyes, Noelle; Cho, Kyu-Chul; Ravel, Jacques; Forney, Larry J; Abdo, Zaid

2018-01-01

The vaginal microbiome plays an influential role in several disease states in reproductive age women, including bacterial vaginosis (BV). While demographic characteristics are associated with differences in vaginal microbiome community structure, little is known about the influence of sexual and hygiene habits. Furthermore, associations between the vaginal microbiome and risk symptoms of bacterial vaginosis have not been fully elucidated. Using Bayesian network (BN) analysis of 16S rRNA gene sequence results, demographic and extensive questionnaire data, we describe both novel and previously documented associations between habits of women and their vaginal microbiome. The BN analysis approach shows promise in uncovering complex associations between disparate data types. Our findings based on this approach support published associations between specific microbiome members (e.g., Eggerthella, Gardnerella, Dialister, Sneathia and Ruminococcaceae), the Nugent score (a BV diagnostic) and vaginal pH (a risk symptom of BV). Additionally, we found that several microbiome members were directly connected to other risk symptoms of BV (such as vaginal discharge, odor, itch, irritation, and yeast infection) including L. jensenii, Corynebacteria, and Proteobacteria. No direct connections were found between the Nugent Score and risk symptoms of BV other than pH, indicating that the Nugent Score may not be the most useful criteria for assessment of clinical BV. We also found that demographics (i.e., age, ethnicity, previous pregnancy) were associated with the presence/absence of specific vaginal microbes. The resulting BN revealed several as-yet undocumented associations between birth control usage, menstrual hygiene practices and specific microbiome members. Many of these complex relationships were not identified using common analytical methods, i.e., ordination and PERMANOVA. While these associations require confirmatory follow-up study, our findings strongly suggest that future studies of the vaginal microbiome and vaginal pathologies should include detailed surveys of participants' sanitary, sexual and birth control habits, as these can act as confounders in the relationship between the microbiome and disease. Although the BN approach is powerful in revealing complex associations within multidimensional datasets, the need in some cases to discretize the data for use in BN analysis can result in loss of information. Future research is required to alleviate such limitations in constructing BN networks. Large sample sizes are also required in order to allow for the incorporation of a large number of variables (nodes) into the BN, particularly when studying associations between metadata and the microbiome. We believe that this approach is of great value, complementing other methods, to further our understanding of complex associations characteristic of microbiome research.

Effects of demographic and health variables on Rasch scaled cognitive scores.

PubMed

Zelinski, Elizabeth M; Gilewski, Michael J

2003-08-01

To determine whether demographic and health variables interact to predict cognitive scores in Asset and Health Dynamics of the Oldest-Old (AHEAD), a representative survey of older Americans, as a test of the developmental discontinuity hypothesis. Rasch modeling procedures were used to rescale cognitive measures into interval scores, equating scales across measures, making it possible to compare predictor effects directly. Rasch scaling also reduces the likelihood of obtaining spurious interactions. Tasks included combined immediate and delayed recall, the Telephone Interview for Cognitive Status (TICS), Series 7, and an overall cognitive score. Demographic variables most strongly predicted performance on all scores, with health variables having smaller effects. Age interacted with both demographic and health variables, but patterns of effects varied. Demographic variables have strong effects on cognition. The developmental discontinuity hypothesis that health variables have stronger effects than demographic ones on cognition in older adults was not supported.

The Earth’s Population Can Reach 14 Billion in the 23rd Century without Significant Adverse Effects on Survivability

PubMed Central

Krapivin, Vladimir F.; Varotsos, Costas A.; Soldatov, Vladimir Yu.

2017-01-01

This paper presents the results obtained from the study of the sustainable state between nature and human society on a global scale, focusing on the most critical interactions between the natural and anthropogenic processes. Apart from the conventional global models, the basic tool employed herein is the newly proposed complex model entitled “nature-society system (NSS) model”, through which a reliable modeling of the processes taking place in the global climate-nature-society system (CNSS) is achieved. This universal tool is mainly based on the information technology that allows the adaptive conformance of the parametric and functional space of this model. The structure of this model includes the global biogeochemical cycles, the hydrological cycle, the demographic processes and a simple climate model. In this model, the survivability indicator is used as a criterion for the survival of humanity, which defines a trend in the dynamics of the total biomass of the biosphere, taking into account the trends of the biocomplexity dynamics of the land and hydrosphere ecosystems. It should be stressed that there are no other complex global models comparable to those of the CNSS model developed here. The potential of this global model is demonstrated through specific examples in which the classification of the terrestrial ecosystem is accomplished by separating 30 soil-plant formations for geographic pixels 4° × 5°. In addition, humanity is considered to be represented by three groups of economic development status (high, transition, developing) and the World Ocean is parameterized by three latitude zones (low, middle, high). The modelling results obtained show the dynamics of the CNSS at the beginning of the 23rd century, according to which the world population can reach the level of 14 billion without the occurrence of major negative impacts. PMID:28783136

Analytical properties of a three-compartmental dynamical demographic model

NASA Astrophysics Data System (ADS)

Postnikov, E. B.

2015-07-01

The three-compartmental demographic model by Korotaeyv-Malkov-Khaltourina, connecting population size, economic surplus, and education level, is considered from the point of view of dynamical systems theory. It is shown that there exist two integrals of motion, which enables the system to be reduced to one nonlinear ordinary differential equation. The study of its structure provides analytical criteria for the dominance ranges of the dynamics of Malthus and Kremer. Additionally, the particular ranges of parameters enable the derived general ordinary differential equations to be reduced to the models of Gompertz and Thoularis-Wallace.

Do we need demographic data to forecast plant population dynamics?

USGS Publications Warehouse

Tredennick, Andrew T.; Hooten, Mevin B.; Adler, Peter B.

2017-01-01

Rapid environmental change has generated growing interest in forecasts of future population trajectories. Traditional population models built with detailed demographic observations from one study site can address the impacts of environmental change at particular locations, but are difficult to scale up to the landscape and regional scales relevant to management decisions. An alternative is to build models using population-level data that are much easier to collect over broad spatial scales than individual-level data. However, it is unknown whether models built using population-level data adequately capture the effects of density-dependence and environmental forcing that are necessary to generate skillful forecasts.Here, we test the consequences of aggregating individual responses when forecasting the population states (percent cover) and trajectories of four perennial grass species in a semi-arid grassland in Montana, USA. We parameterized two population models for each species, one based on individual-level data (survival, growth and recruitment) and one on population-level data (percent cover), and compared their forecasting accuracy and forecast horizons with and without the inclusion of climate covariates. For both models, we used Bayesian ridge regression to weight the influence of climate covariates for optimal prediction.In the absence of climate effects, we found no significant difference between the forecast accuracy of models based on individual-level data and models based on population-level data. Climate effects were weak, but increased forecast accuracy for two species. Increases in accuracy with climate covariates were similar between model types.In our case study, percent cover models generated forecasts as accurate as those from a demographic model. For the goal of forecasting, models based on aggregated individual-level data may offer a practical alternative to data-intensive demographic models. Long time series of percent cover data already exist for many plant species. Modelers should exploit these data to predict the impacts of environmental change.

Impact of Sampling Schemes on Demographic Inference: An Empirical Study in Two Species with Different Mating Systems and Demographic Histories

PubMed Central

St. Onge, K. R.; Palmé, A. E.; Wright, S. I.; Lascoux, M.

2012-01-01

Most species have at least some level of genetic structure. Recent simulation studies have shown that it is important to consider population structure when sampling individuals to infer past population history. The relevance of the results of these computer simulations for empirical studies, however, remains unclear. In the present study, we use DNA sequence datasets collected from two closely related species with very different histories, the selfing species Capsella rubella and its outcrossing relative C. grandiflora, to assess the impact of different sampling strategies on summary statistics and the inference of historical demography. Sampling strategy did not strongly influence the mean values of Tajima’s D in either species, but it had some impact on the variance. The general conclusions about demographic history were comparable across sampling schemes even when resampled data were analyzed with approximate Bayesian computation (ABC). We used simulations to explore the effects of sampling scheme under different demographic models. We conclude that when sequences from modest numbers of loci (<60) are analyzed, the sampling strategy is generally of limited importance. The same is true under intermediate or high levels of gene flow (4Nm > 2–10) in models in which global expansion is combined with either local expansion or hierarchical population structure. Although we observe a less severe effect of sampling than predicted under some earlier simulation models, our results should not be seen as an encouragement to neglect this issue. In general, a good coverage of the natural range, both within and between populations, will be needed to obtain a reliable reconstruction of a species’s demographic history, and in fact, the effect of sampling scheme on polymorphism patterns may itself provide important information about demographic history. PMID:22870403

Estimating under-five mortality in space and time in a developing world context.

PubMed

Wakefield, Jon; Fuglstad, Geir-Arne; Riebler, Andrea; Godwin, Jessica; Wilson, Katie; Clark, Samuel J

2018-01-01

Accurate estimates of the under-five mortality rate in a developing world context are a key barometer of the health of a nation. This paper describes a new model to analyze survey data on mortality in this context. We are interested in both spatial and temporal description, that is wishing to estimate under-five mortality rate across regions and years and to investigate the association between the under-five mortality rate and spatially varying covariate surfaces. We illustrate the methodology by producing yearly estimates for subnational areas in Kenya over the period 1980-2014 using data from the Demographic and Health Surveys, which use stratified cluster sampling. We use a binomial likelihood with fixed effects for the urban/rural strata and random effects for the clustering to account for the complex survey design. Smoothing is carried out using Bayesian hierarchical models with continuous spatial and temporally discrete components. A key component of the model is an offset to adjust for bias due to the effects of HIV epidemics. Substantively, there has been a sharp decline in Kenya in the under-five mortality rate in the period 1980-2014, but large variability in estimated subnational rates remains. A priority for future research is understanding this variability. In exploratory work, we examine whether a variety of spatial covariate surfaces can explain the variability in under-five mortality rate. Temperature, precipitation, a measure of malaria infection prevalence, and a measure of nearness to cities were candidates for inclusion in the covariate model, but the interplay between space, time, and covariates is complex.

The aggregate site frequency spectrum for comparative population genomic inference.

PubMed

Xue, Alexander T; Hickerson, Michael J

2015-12-01

Understanding how assemblages of species responded to past climate change is a central goal of comparative phylogeography and comparative population genomics, an endeavour that has increasing potential to integrate with community ecology. New sequencing technology now provides the potential to perform complex demographic inference at unprecedented resolution across assemblages of nonmodel species. To this end, we introduce the aggregate site frequency spectrum (aSFS), an expansion of the site frequency spectrum to use single nucleotide polymorphism (SNP) data sets collected from multiple, co-distributed species for assemblage-level demographic inference. We describe how the aSFS is constructed over an arbitrary number of independent population samples and then demonstrate how the aSFS can differentiate various multispecies demographic histories under a wide range of sampling configurations while allowing effective population sizes and expansion magnitudes to vary independently. We subsequently couple the aSFS with a hierarchical approximate Bayesian computation (hABC) framework to estimate degree of temporal synchronicity in expansion times across taxa, including an empirical demonstration with a data set consisting of five populations of the threespine stickleback (Gasterosteus aculeatus). Corroborating what is generally understood about the recent postglacial origins of these populations, the joint aSFS/hABC analysis strongly suggests that the stickleback data are most consistent with synchronous expansion after the Last Glacial Maximum (posterior probability = 0.99). The aSFS will have general application for multilevel statistical frameworks to test models involving assemblages and/or communities, and as large-scale SNP data from nonmodel species become routine, the aSFS expands the potential for powerful next-generation comparative population genomic inference. © 2015 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

Cryptic herbivores mediate the strength and form of ungulate impacts on a long-lived savanna tree.

PubMed

Maclean, Janet E; Goheen, Jacob R; Doak, Daniel F; Palmer, Todd M; Young, Truman P

2011-08-01

Plant populations are regulated by a diverse array of herbivores that impose demographic filters throughout their life cycle. Few studies, however, simultaneously quantify the impacts of multiple herbivore guilds on the lifetime performance or population growth rate of plants. In African savannas, large ungulates (such as elephants) are widely regarded as important drivers of woody plant population dynamics, while the potential impacts of smaller, more cryptic herbivores (such as rodents) have largely been ignored. We combined a large-scale ungulate exclusion experiment with a five-year manipulation of rodent densities to quantify the impacts of three herbivore guilds (wild ungulates, domestic cattle, and rodents) on all life stages of a widespread savanna tree. We utilized demographic modeling to reveal the overall role of each guild in regulating tree population dynamics, and to elucidate the importance of different demographic hurdles in driving population growth under contrasting consumer communities. We found that wild ungulates dramatically reduced population growth, shifting the population trajectory from increase to decline, but that the mechanisms driving these effects were strongly mediated by rodents. The impact of wild ungulates on population growth was predominantly driven by their negative effect on tree reproduction when rodents were excluded, and on adult tree survival when rodents were present. By limiting seedling survival, rodents also reduced population growth; however, this effect was strongly dampened where wild ungulates were present. We suggest that these complex interactions between disparate consumer guilds can have important consequences for the population demography of long-lived species, and that the effects of a single consumer group are often likely to vary dramatically depending on the larger community in which interactions are embedded.

Definition, Management, and Outcomes of Acute Kidney Injury: An International Survey of Nephrologists.

PubMed

Farooq, Umar; Tober, Aaron; Chinchilli, Vernon; Reeves, W Brian; Ghahramani, Nasrollah

2017-12-01

Acute kidney injury (AKI) is a complex disease burdened by uncertainties of definition, management strategies, and prognosis. This study explores the relationship between demographic characteristics of nephrologists and their perceptions about the definition, management, and follow-up of AKI. We developed a Web-based survey, the International Survey on Acute Kidney Injury (ISAKI), consisting of 29 items in 4 categories: (1) demographic and practice characteristics, (2) definition of AKI, (3) management of renal replacement therapy (RRT) in AKI, and (4) sequelae of AKI. A multivariable stepwise logistic regression model was used to examine relationships between the dependent variables and the demographic characteristics of the respondents. Responses from 743 nephrologists from 90 countries were analyzed. The majority (60%) of respondents reported using RIFLE and/or AKIN criteria regularly to define AKI, although US nephrologists were less likely to do so (OR: 0.58; 95% CI: 0.42-0.85). The most common initial RRT modality was intermittent hemodialysis (63.5%), followed by continuous RRT (23.8%). Faculty affiliation was associated with a higher likelihood of using a dialysis schedule of ≥4 times a week (OR: 1.75; 95% CI: 1.20-2.55). The respondents believed that a single episode of AKI increases the likelihood of development of chronic kidney disease (CKD) (55%), subsequent AKI (36%), and rapid progression of preexisting CKD (87%). US nephrologists were less likely to recommend follow-up after resolution of AKI (OR: 0.15; 95% CI: 0.07-0.33). Our findings highlight the need for a widely accepted consensus definition of AKI, a uniform approach to management, and improved follow-up after resolution of AKI episodes.

Lactate dehydrogenase and caspase activity in nasopharyngeal secretions are predictors of bronchiolitis severity.

PubMed

Mehta, Reena; Scheffler, Margaret; Tapia, Lorena; Aideyan, Letisha; Patel, Kirtida D; Jewell, Alan M; Avadhanula, Vasanthi; Mei, Minghua; Garofalo, Roberto P; Piedra, Pedro A

2014-11-01

Bronchiolitis is the leading cause of hospitalization in infants. Biomarkers of disease severity might help in clinical management. To determine the clinical predictiveness of NW-LDH, NW-caspase 3/7, and NW-LDH/NW-caspase 3/7 ratio in bronchiolitis. Previously healthy children less than 24 months of age with bronchiolitis were recruited from the Texas Children's emergency room and intensive care unit from October 2010 to April 2011. Demographic, clinical information, and NW samples were obtained at enrollment. NW samples were analyzed for respiratory viruses, caspase 3/7, and LDH. A viral pathogen was detected in 91·6% of 131 children, with the most common being respiratory syncytial virus and human rhinovirus. A single infection was found in 61·8% of subjects and co-infection in 29·8%. Children admitted to ICU had significantly higher NW-LDH than children sent home from the ER or admitted to the general floor (P = 0·02). Children infected with RSV had the highest NW-LDH concentration (P = 0·03) compared with other viral infections. NW-LDH and NW-caspase were significantly correlated (r = 0·77, P < 0·0001). The univariate models showed NW-LDH and NW-LDH/NW- caspase 3/7 ratio were directly associated with hospitalization. Mutivariate regression analyses suggested a complex interaction between the biomarkers, demographics, and disposition. NW-LDH, NW-caspase 3/7 and NW-LDH/NW-caspase 3/7 ratio and their interactions with demographic factors are predictive of bronchiolitis severity and can help distinguish children requiring ICU-level care from those admitted to the general floor, or discharged home from the emergency center. © 2014 The Authors. Influenza and Other Respiratory Viruses Published by John Wiley & Sons Ltd.

Lactate dehydrogenase and caspase activity in nasopharyngeal secretions are predictors of bronchiolitis severity

PubMed Central

Mehta, Reena; Scheffler, Margaret; Tapia, Lorena; Aideyan, Letisha; Patel, Kirtida D; Jewell, Alan M; Avadhanula, Vasanthi; Mei, Minghua; Garofalo, Roberto P; Piedra, Pedro A

2014-01-01

Background Bronchiolitis is the leading cause of hospitalization in infants. Biomarkers of disease severity might help in clinical management. Objective To determine the clinical predictiveness of NW-LDH, NW-caspase 3/7, and NW-LDH/NW-caspase 3/7 ratio in bronchiolitis. Methods Previously healthy children less than 24 months of age with bronchiolitis were recruited from the Texas Children's emergency room and intensive care unit from October 2010 to April 2011. Demographic, clinical information, and NW samples were obtained at enrollment. NW samples were analyzed for respiratory viruses, caspase 3/7, and LDH. Results A viral pathogen was detected in 91·6% of 131 children, with the most common being respiratory syncytial virus and human rhinovirus. A single infection was found in 61·8% of subjects and co-infection in 29·8%. Children admitted to ICU had significantly higher NW-LDH than children sent home from the ER or admitted to the general floor (P = 0·02). Children infected with RSV had the highest NW-LDH concentration (P = 0·03) compared with other viral infections. NW-LDH and NW-caspase were significantly correlated (r = 0·77, P < 0·0001). The univariate models showed NW-LDH and NW-LDH/NW- caspase 3/7 ratio were directly associated with hospitalization. Mutivariate regression analyses suggested a complex interaction between the biomarkers, demographics, and disposition. Conclusions NW-LDH, NW-caspase 3/7 and NW-LDH/NW-caspase 3/7 ratio and their interactions with demographic factors are predictive of bronchiolitis severity and can help distinguish children requiring ICU-level care from those admitted to the general floor, or discharged home from the emergency center. PMID:25132512

Typology of religiosity/spirituality in relation to perceived health, depression, and life satisfaction among older Korean immigrants.

PubMed

Roh, Soonhee; Lee, Yeon-Shim; Lee, Jae Hoon; Martin, James I

2014-05-01

The objectives of this study were (1) to identify distinct subtypes of older Korean immigrants based on their levels of religiosity/spirituality (R/S) and (2) to determine if the identified subtypes differed by demographic characteristics, perceived health, depression, and life satisfaction. Factor mixture models were evaluated with a nonprobability sample of older Korean immigrants (N=200) residing in the New York City area in 2009 to classify typologies of R/S. Multiple regression was used to test the associations between the R/S subtypes and outcomes (perceived health, depression, and life satisfaction) while controlling for demographics. Two substantively distinct latent profiles were identified: normally religious/spiritual ('average R/S') and minimally religious/spiritual ('low R/S'). The average R/S subgroup (74.4%) showed higher means than those in the low R/S subgroup (25.6%) on all six R/S class indicators. Subtypes did not differ on age, education, income, marital status, living arrangements, or years in the USA. However, males were more likely than females to be 'average R/S.' The 'average R/S' subtype had significantly greater life satisfaction than their 'low R/S' counterpart. No differences between the two subtypes were found on perceived health or depression. Findings highlight the importance of the classifications of R/S for mental health outcomes, and they indicate that relationships among R/S, various demographic characteristics, and physical/mental health are complex. Future research should validate and refine this classification of R/S in order to help identify particular sources of health risks/behaviors, relevant treatments, and health-promoting interventions within homogenous subtypes of older Korean immigrants.

Genomic Insights into the Ancestry and Demographic History of South America

PubMed Central

Homburger, Julian R.; Moreno-Estrada, Andrés; Gignoux, Christopher R.; Nelson, Dominic; Sanchez, Elena; Ortiz-Tello, Patricia; Pons-Estel, Bernardo A.; Acevedo-Vasquez, Eduardo; Miranda, Pedro; Langefeld, Carl D.; Gravel, Simon; Alarcón-Riquelme, Marta E.; Bustamante, Carlos D.

2015-01-01

South America has a complex demographic history shaped by multiple migration and admixture events in pre- and post-colonial times. Settled over 14,000 years ago by Native Americans, South America has experienced migrations of European and African individuals, similar to other regions in the Americas. However, the timing and magnitude of these events resulted in markedly different patterns of admixture throughout Latin America. We use genome-wide SNP data for 437 admixed individuals from 5 countries (Colombia, Ecuador, Peru, Chile, and Argentina) to explore the population structure and demographic history of South American Latinos. We combined these data with population reference panels from Africa, Asia, Europe and the Americas to perform global ancestry analysis and infer the subcontinental origin of the European and Native American ancestry components of the admixed individuals. By applying ancestry-specific PCA analyses we find that most of the European ancestry in South American Latinos is from the Iberian Peninsula; however, many individuals trace their ancestry back to Italy, especially within Argentina. We find a strong gradient in the Native American ancestry component of South American Latinos associated with country of origin and the geography of local indigenous populations. For example, Native American genomic segments in Peruvians show greater affinities with Andean indigenous peoples like Quechua and Aymara, whereas Native American haplotypes from Colombians tend to cluster with Amazonian and coastal tribes from northern South America. Using ancestry tract length analysis we modeled post-colonial South American migration history as the youngest in Latin America during European colonization (9–14 generations ago), with an additional strong pulse of European migration occurring between 3 and 9 generations ago. These genetic footprints can impact our understanding of population-level differences in biomedical traits and, thus, inform future medical genetic studies in the region. PMID:26636962

Genomic Insights into the Ancestry and Demographic History of South America.

PubMed

Homburger, Julian R; Moreno-Estrada, Andrés; Gignoux, Christopher R; Nelson, Dominic; Sanchez, Elena; Ortiz-Tello, Patricia; Pons-Estel, Bernardo A; Acevedo-Vasquez, Eduardo; Miranda, Pedro; Langefeld, Carl D; Gravel, Simon; Alarcón-Riquelme, Marta E; Bustamante, Carlos D

2015-12-01

South America has a complex demographic history shaped by multiple migration and admixture events in pre- and post-colonial times. Settled over 14,000 years ago by Native Americans, South America has experienced migrations of European and African individuals, similar to other regions in the Americas. However, the timing and magnitude of these events resulted in markedly different patterns of admixture throughout Latin America. We use genome-wide SNP data for 437 admixed individuals from 5 countries (Colombia, Ecuador, Peru, Chile, and Argentina) to explore the population structure and demographic history of South American Latinos. We combined these data with population reference panels from Africa, Asia, Europe and the Americas to perform global ancestry analysis and infer the subcontinental origin of the European and Native American ancestry components of the admixed individuals. By applying ancestry-specific PCA analyses we find that most of the European ancestry in South American Latinos is from the Iberian Peninsula; however, many individuals trace their ancestry back to Italy, especially within Argentina. We find a strong gradient in the Native American ancestry component of South American Latinos associated with country of origin and the geography of local indigenous populations. For example, Native American genomic segments in Peruvians show greater affinities with Andean indigenous peoples like Quechua and Aymara, whereas Native American haplotypes from Colombians tend to cluster with Amazonian and coastal tribes from northern South America. Using ancestry tract length analysis we modeled post-colonial South American migration history as the youngest in Latin America during European colonization (9-14 generations ago), with an additional strong pulse of European migration occurring between 3 and 9 generations ago. These genetic footprints can impact our understanding of population-level differences in biomedical traits and, thus, inform future medical genetic studies in the region.

Effects of complex life cycles on genetic diversity: cyclical parthenogenesis.

PubMed

Rouger, R; Reichel, K; Malrieu, F; Masson, J P; Stoeckel, S

2016-11-01

Neutral patterns of population genetic diversity in species with complex life cycles are difficult to anticipate. Cyclical parthenogenesis (CP), in which organisms undergo several rounds of clonal reproduction followed by a sexual event, is one such life cycle. Many species, including crop pests (aphids), human parasites (trematodes) or models used in evolutionary science (Daphnia), are cyclical parthenogens. It is therefore crucial to understand the impact of such a life cycle on neutral genetic diversity. In this paper, we describe distributions of genetic diversity under conditions of CP with various clonal phase lengths. Using a Markov chain model of CP for a single locus and individual-based simulations for two loci, our analysis first demonstrates that strong departures from full sexuality are observed after only a few generations of clonality. The convergence towards predictions made under conditions of full clonality during the clonal phase depends on the balance between mutations and genetic drift. Second, the sexual event of CP usually resets the genetic diversity at a single locus towards predictions made under full sexuality. However, this single recombination event is insufficient to reshuffle gametic phases towards full-sexuality predictions. Finally, for similar levels of clonality, CP and acyclic partial clonality (wherein a fixed proportion of individuals are clonally produced within each generation) differentially affect the distribution of genetic diversity. Overall, this work provides solid predictions of neutral genetic diversity that may serve as a null model in detecting the action of common evolutionary or demographic processes in cyclical parthenogens (for example, selection or bottlenecks).

Household and Family Characteristics: March 1985.

ERIC Educational Resources Information Center

Rawlings, Steve W.

1986-01-01

This annual report summarizes some of the notable recent trends in household and family characteristics and contains detailed demographic data from the March, 1985 "Current Population Survey." The households vary greatly in size and complexity. Some of the aspects of household demography that have important consequences for both consumer demand…

Learner Differences in Theory and Practice

ERIC Educational Resources Information Center

Kalantzis, Mary; Cope, Bill

2016-01-01

This paper explores the complex and shifting dimensions of the social, cultural and bodily differences that impact on learners and their learning. Our theoretical argument proceeds in five stages. First, we build a typology of terms used to classify demographic differences for the purposes of designing, implementing and evaluating the…

Catholic Ed., K-12 Charters Squaring Off

ERIC Educational Resources Information Center

Cavanagh, Sean

2012-01-01

The nation's Roman Catholic schools have labored for decades under increasingly adverse economic and demographic conditions, which have undermined their finances and sapped their enrollment. Today, researchers and supporters say those schools face one of their most complex challenges yet: the continued growth of charter schools. Since they first…

Rural Sociology at the Crossroads

ERIC Educational Resources Information Center

Krannich, Richard S.

2008-01-01

A complex array of socio-historical, demographic, and organizational factors have combined in recent years to threaten both the current status of and future prospects for the discipline of rural sociology, and for the Rural Sociological Society (RSS). This paper examines the somewhat problematic recent trajectories of the RSS as a professional…

The Balancing Act of Adult Life. ERIC Digest.

ERIC Educational Resources Information Center

Kerka, Sandra

Life is more complex than ever for adults in the 21st century as a result of technological advances; the changing nature of work, workplaces, and working relationships; international economic competition; the changing demographics of workers, families, and communities; and longer life spans. Learning to cope with all these changing…

Preparing Bilingual Teachers for the Future: Developing Culture and Linguistic Global Competence

ERIC Educational Resources Information Center

Alfaro, Cristina

2008-01-01

Increasing diversity and linguistics complexity in classrooms is occurring in schools throughout the world. Bilingual teachers need to develop knowledge and skills to succees in teaching diverse students. Demographic shifts are bringing increasing numbers of international students from diverse racial, ethnic, religious, class, and linguistic…

A pragmatic randomized comparative effectiveness trial of transitional care for a socioeconomically diverse population: Design, rationale and baseline characteristics.

PubMed

Schaeffer, Christine; Teter, Caroline; Finch, Emily A; Hurt, Courtney; Keeter, Mary Kate; Liss, David T; Rogers, Angela; Sheth, Avani; Ackermann, Ronald

2018-02-01

Transitional care programs have been widely used to reduce readmissions and improve the quality and safety of the handoff process between hospital and outpatient providers. Very little is known about effective transitional care interventions among patients who are uninsured or with Medicaid. This paper describes the design and baseline characteristics of a pragmatic randomized comparative effectiveness trial of transitional care. Northwestern Medical Group- Transitional Care (NMG-TC) care model was developed to address the needs of patients with multiple medical problems that required lifestyle changes and were amenable to office-based management. We present the design, evaluation methods and baseline characteristics of NMG-TC trial patients. Baseline demographic characteristics indicate that our patient population is predominantly male, Medicaid insured and non-white. This study will evaluate two methods for implementing an effective transitional care model in a medically complex and socioeconomically diverse population. Copyright © 2017 Elsevier Inc. All rights reserved.

A systematic literature review of sport and physical activity participation in culturally and linguistically diverse (CALD) migrant populations.

PubMed

O'Driscoll, Téa; Banting, Lauren Kate; Borkoles, Erika; Eime, Rochelle; Polman, Remco

2014-06-01

Culturally and linguistically diverse (CALD) migrants face significant health risks as they adapt to new cultures. These risks are exacerbated by their limited participation in preventative behaviours such as sports and physical activity. The review aimed to identify studies that examined the correlates of sport and physical activity participation in migrants. The systematic review identified 72 papers, including 6 interventions, 18 qualitative and 48 quantitative studies. The 44 identified correlates highlight the complexities involved in working with migrants. The correlates were grouped in four themes using the social ecological model; acculturation, demographic, psychosocial and environmental/organisational. The social ecological model identified general correlates such as social support and safety. However, there were unique correlates relating to individuals who are facing cultural changes such as acculturation and language. Overall, there is a lack of contextualisation of CALD migrants' sport and physical activity experiences because many studies fail to consider acculturation comprehensively.

Effects of familial climate on the adolescents' driving habits: a recent literature.

PubMed

Foo, K Y

2015-01-01

Driving is a functional task that requires a complex interaction of visual perception, cognitive and motor skills. Next to circulatory diseases and cancer, road accidents remain the third epidemic cause of death internationally, with approximately half a million teen drivers killed annually. Driver behaviour has been cited as the pervasive marker of automotive crashes. A reliable and firm relationship between the positive parental model, message, and communication has been established. Specifically, the familial climate is proposed to be an important element of reinforcement, modelling, support and environmental determinant in interpreting personal perceptions, habits, values, and belief system. Confirming the assertion, this bibliographic review presents the most recent research findings on the contributions of families to the driving habits of teens. The emphasis is speculated on parental alcohol use, aggressiveness, attention-deficit/hyperactivity disorder, relationship, and intergenerational transmission of driving styles. Besides, the effects of familial supervision, monitoring, education and awareness, and genders, partners, and demographic influence on the driving habits are discussed and outlined.

Exploratory of society

NASA Astrophysics Data System (ADS)

Cederman, L.-E.; Conte, R.; Helbing, D.; Nowak, A.; Schweitzer, F.; Vespignani, A.

2012-11-01

A huge flow of quantitative social, demographic and behavioral data is becoming available that traces the activities and interactions of individuals, social patterns, transportation infrastructures and travel fluxes. This has caused, together with innovative computational techniques and methods for modeling social actions in hybrid (natural and artificial) societies, a qualitative change in the ways we model socio-technical systems. For the first time, society can be studied in a comprehensive fashion that addresses social and behavioral complexity. In other words we are in the position to envision the development of large data and computational cyber infrastructure defining an exploratory of society that provides quantitative anticipatory, explanatory and scenario analysis capabilities ranging from emerging infectious disease to conflict and crime surges. The goal of the exploratory of society is to provide the basic infrastructure embedding the framework of tools and knowledge needed for the design of forecast/anticipatory/crisis management approaches to socio technical systems, supporting future decision making procedures by accelerating the scientific cycle that goes from data generation to predictions.

Factors of interpersonal communication and behavioral health on medication self-efficacy and medication adherence.

PubMed

Archiopoli, Ashley; Ginossar, Tamar; Wilcox, Bryan; Avila, Magdalena; Hill, Ricky; Oetzel, John

2016-12-01

Despite devastating effects on health outcomes and disease progression, many people living with HIV (PLWH) are non-adherent to their medications. Medication self-efficacy is a pivotal factor in medication adherence, yet its formation and relationship with other factors are understudied. This study examines a model that considers the role of three communicative factors (patient-provider communication, social support, and social undermining) and two behavioral health factors (depression and alcohol abuse) and medication self-efficacy impacting medication adherence. Methods included a cross-sectional design using a survey questionnaire of 344 PLWH. Findings indicated that 25% of variance in medication adherence can be explained by a mediation model where depression (B = -.18) and provider-patient communication (B = .21) affect medication self-efficacy, which in turn impacts medication adherence (B = .64). Other variables, including demographics, did not add any explanatory power. These findings demonstrate the complex nature of medication adherence and the formation of medication self-efficacy.

Predicting animal home-range structure and transitions using a multistate Ornstein-Uhlenbeck biased random walk

USGS Publications Warehouse

Breed, Greg A.; Golson, Emily A.; Tinker, M. Tim

2017-01-01

The home‐range concept is central in animal ecology and behavior, and numerous mechanistic models have been developed to understand home range formation and maintenance. These mechanistic models usually assume a single, contiguous home range. Here we describe and implement a simple home‐range model that can accommodate multiple home‐range centers, form complex shapes, allow discontinuities in use patterns, and infer how external and internal variables affect movement and use patterns. The model assumes individuals associate with two or more home‐range centers and move among them with some estimable probability. Movement in and around home‐range centers is governed by a two‐dimensional Ornstein‐Uhlenbeck process, while transitions between centers are modeled as a stochastic state‐switching process. We augmented this base model by introducing environmental and demographic covariates that modify transition probabilities between home‐range centers and can be estimated to provide insight into the movement process. We demonstrate the model using telemetry data from sea otters (Enhydra lutris) in California. The model was fit using a Bayesian Markov Chain Monte Carlo method, which estimated transition probabilities, as well as unique Ornstein‐Uhlenbeck diffusion and centralizing tendency parameters. Estimated parameters could then be used to simulate movement and space use that was virtually indistinguishable from real data. We used Deviance Information Criterion (DIC) scores to assess model fit and determined that both wind and reproductive status were predictive of transitions between home‐range centers. Females were less likely to move between home‐range centers on windy days, less likely to move between centers when tending pups, and much more likely to move between centers just after weaning a pup. These tendencies are predicted by theoretical movement rules but were not previously known and show that our model can extract meaningful behavioral insight from complex movement data.

Integrated modeling of land-use change: the role of coupling, interactions and feedbacks between the human and Earth systems

NASA Astrophysics Data System (ADS)

Monier, E.; Kicklighter, D. W.; Ejaz, Q.; Winchester, N.; Paltsev, S.; Reilly, J. M.

2016-12-01

Land-use change integrates a large number of components of the human and Earth systems, including climate, energy, water, and land. These complex coupling elements, interactions and feedbacks take place on a variety of space and time scales, thus increasing the complexity of land-use change modeling frameworks. In this study, we aim to identify which coupling elements, interactions and feedbacks are important for modeling land-use change, both at the global and regional level. First, we review the existing land-use change modeling framework used to develop land-use change projections for the Representative Concentration Pathways (RCP) scenarios. In such framework, land-use change is simulated by Integrated Assessment Models (IAMs) and mainly influenced by economic, energy, demographic and policy drivers. IAMs focus on representing the demand for agriculture and forestry goods (crops for food and bioenergy, forest products for construction and bioenergy), the interactions with other sectors of the economy and trade between various regions of the world. Then, we investigate how important various coupling elements and feedbacks with the Earth system are for projections of land-use change at the global and regional level. We focus on the following: i) the climate impacts on land productivity and greenhouse gas emissions, which requires climate change information and coupling to a terrestrial ecosystem model/crop model; ii) the climate and economic impacts on irrigation availability, which requires coupling the LUC modeling framework to a water resources management model and disaggregating rainfed and irrigated croplands; iii) the feedback of land-use change on the global and regional climate system through land-use change emissions and changes in the surface albedo and hydrology, which requires coupling to an Earth system model. Finally, we conclude our study by highlighting the current lack of clarity in how various components of the human and Earth systems are coupled in IAMs , and the need for a lexicon that is agreed upon by the IAM community.

Demographic Predictors of Event-Level Associations between Alcohol Consumption and Sexual Behavior.

PubMed

Wells, Brooke E; Rendina, H Jonathon; Kelly, Brian C; Golub, Sarit A; Parsons, Jeffrey T

2016-02-01

Alcohol consumption is associated with sexual behavior and outcomes, though research indicates a variety of moderating factors, including demographic characteristics. To better target interventions aimed at alcohol-related sexual risk behavior, our analyses simultaneously examine demographic predictors of both day- and event-level associations between alcohol consumption and sexual behavior in a sample of young adults (N = 301) who are sexually active and consume alcohol. Young adults (aged 18-29) recruited using time-space sampling and incentivized snowball sampling completed a survey and a timeline follow-back calendar reporting alcohol consumption and sexual behavior in the past 30 days. On a given day, a greater number of drinks consumed was associated with higher likelihood of sex occurring, particularly for women and single participants. During a given sexual event, number of drinks consumed was not associated with condom use, nor did any demographic predictors predict that association. Findings highlight associations between alcohol and sexual behavior, though not between alcohol and sexual risk behavior, highlighting the need for additional research exploring the complex role of alcohol in sexual risk behavior and the need to develop prevention efforts to minimize the role of alcohol in the initiation of sexual encounters.

Psychosocial factors affecting resilience in Nepalese individuals with earthquake-related spinal cord injury: a cross-sectional study.

PubMed

Bhattarai, Muna; Maneewat, Khomapak; Sae-Sia, Wipa

2018-03-02

One of many types of injuries following an earthquake is spinal cord injury (SCI) which is a life-long medically complex injury and high-cost health problem. Despite several negative consequences, some persons with SCI are resilient enough to achieve positive adjustment, greater acceptance, and better quality of life. Since resilience is influenced by several factors and can vary by context, it is beneficial to explore factors that affect the resilience of people who sustained spinal cord injury from the 2015 earthquake in Nepal. A descriptive cross-sectional study included 82 participants from the Spinal Injury Rehabilitation Center and communities in Nepal. Participants completed the Demographic and Injury-related Questionnaire, Connor-Davidson Resilience Scale, Multidimensional Scale of Perceived Social Support, Moorong Self-efficacy Scale, Intrinsic Spirituality Scale, and Patient Health Questionnaire-9. Pearson's correlation and point biserial correlation analyses were performed to examine associations between resilience and independent variables. A hierarchical regression analysis was used to identify the influence of certain factors. Findings indicated significant associations between resilience and social support (r = 0.42, p < 0.001), self-efficacy (r = 0.53, p < 0.001), depressive mood (r = - 0.50, p < 0.001) and demographic variables which included sex (r = 0.47, p < 0.001), employment (r = 0.27, p = 0.016), and current living location (r = 0.24, p = 0.029). There was a non-significant association between resilience and spirituality (r = - 0.12, p > 0.05). In hierarchical regression analysis, an overall regression model explained 46% of the variance in resilience. Self-efficacy (β = 0.28, p = 0.007) and depressive mood (β = - 0.24, p = 0.016) significantly determined resilience after controlling the effect of demographic variables. Among the demographic factors, being male significantly explained the variance in resilience (β = 0.31, p = 0.001). Multiple psychosocial and demographic factors were associated with resilience in people who sustained an earthquake-related SCI. Mental health professionals should demonstrate concern and consider such factors in allocating care in this group. Development of intervention research concerning resilience is recommended to strengthen resilience in order to improve rehabilitation outcomes and enhance reintegration of individuals with SCI into their communities.

[Knowledge of pregnant adolescents about reproductive anatomy and physiology in a municipality of Southern Brazil].

PubMed

Carvacho, Ingrid Espejo; Pinto E Silva, João Luiz; Mello, Maeve Brito de

2008-01-01

To study knowledge of some aspects of the female reproductive anatomy and physiology and their association with socio-demographic and reproductive "choices" of pregnant adolescents. A cross-sectional study was performed with 200 first time pregnant adolescents who attended a public women's health clinic in the municipality of Indaiatuba, Sao Paulo, Brazil. During their first prenatal care visit, face-to-face interviews were conducted using a structured questionnaire and a three-dimensional handmade female model. Bivariate data analyses were performed using Pearson's Chi-square or Fisher's Exact test. Data were also analyzed using multivariate logistic regression models to test for associations of indicators of knowledge of female reproductive anatomy, physiology of female reproductive organs and physiology of reproduction with socio-demographic characteristics and reproductive "choices". The majority had little knowledge of anatomy (55.5%), with external organs more easily identified and placed than the internal; of physiology of reproductive organs (61.0%), and of physiology of reproduction (76.5%). Associations were found between knowledge and age of partner, couple difference of age, maintenance of the relationship with partner after pregnancy, religious affiliation, and level of education. No association was found between indicators of knowledge with use of contraceptives at first intercourse and with intention of having the baby at that time. This study addressed the complexity of the relationship between knowledge of reproductive anatomy and physiology and the theme of adolescent pregnancy, and emphasized the need for more contextualized approaches of programmatic contents on sexual education, in view of the intention to reduce early pregnancy.

Conservation biology for suites of species: Demographic modeling for Pacific island kingfishers

USGS Publications Warehouse

Kesler, D.C.; Haig, S.M.

2007-01-01

Conservation practitioners frequently extrapolate data from single-species investigations when managing critically endangered populations. However, few researchers initiate work with the intent of making findings useful to conservation efforts for other species. We presented and explored the concept of conducting conservation-oriented research for suites of geographically separated populations with similar natural histories, resource needs, and extinction threats. An example was provided in the form of an investigation into the population demography of endangered Micronesian kingfishers (Todiramphus cinnamominus). We provided the first demographic parameter estimates for any of the 12 endangered Pacific Todiramphus species, and used results to develop a population projection matrix model for management throughout the insular Pacific. Further, we used the model for elasticity and simulation analyses with demographic values that randomly varied across ranges that might characterize congener populations. Results from elasticity and simulation analyses indicated that changes in breeding adult survival exerted the greatest magnitude of influence on population dynamics. However, changes in nestling survival were more consistently correlated with population dynamics as demographic rates were randomly altered. We concluded that conservation practitioners working with endangered Pacific kingfishers should primarily focus efforts on factors affecting nestling and breeder survival, and secondarily address fledgling juveniles and helpers. Further, we described how the generalized base model might be changed to focus on individual populations and discussed the potential application of multi-species models to other conservation situations. ?? 2007 Elsevier Ltd. All rights reserved.

Bayesian Analysis of Evolutionary Divergence with Genomic Data under Diverse Demographic Models.

PubMed

Chung, Yujin; Hey, Jody

2017-06-01

We present a new Bayesian method for estimating demographic and phylogenetic history using population genomic data. Several key innovations are introduced that allow the study of diverse models within an Isolation-with-Migration framework. The new method implements a 2-step analysis, with an initial Markov chain Monte Carlo (MCMC) phase that samples simple coalescent trees, followed by the calculation of the joint posterior density for the parameters of a demographic model. In step 1, the MCMC sampling phase, the method uses a reduced state space, consisting of coalescent trees without migration paths, and a simple importance sampling distribution without the demography of interest. Once obtained, a single sample of trees can be used in step 2 to calculate the joint posterior density for model parameters under multiple diverse demographic models, without having to repeat MCMC runs. Because migration paths are not included in the state space of the MCMC phase, but rather are handled by analytic integration in step 2 of the analysis, the method is scalable to a large number of loci with excellent MCMC mixing properties. With an implementation of the new method in the computer program MIST, we demonstrate the method's accuracy, scalability, and other advantages using simulated data and DNA sequences of two common chimpanzee subspecies: Pan troglodytes (P. t.) troglodytes and P. t. verus. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

[Demographic pressure, "informal sector" and technological choices in Third World countries].

PubMed

Hugon, P

1983-01-01

Trisectorial models of economic functioning have been proposed to replace the dualistic models that proved incapable of illuminating postwar employment trends in developing countries. The new models propose 3 sectors: the subsistence sector, where average productivity corresponds to the subsistence minimum and which is thus incapable of generating a surplus for savings; the intermediate sector, weakly capitalistic, characterized by the absence of a permanent salaried work force or codified labor relations, in which precariousness of employment and the exploitation of specific social relations allow a low wage rate, with a concommitant mode of regulation that largely escapes state control; and the intensely capitalistic sector, with a salaried work force, codified labor relations, existence of administered prices, various state subventions and protections and a monopolistic type of regulation. The 3 sectors are described in greater detail and represented graphically, along with a critique of the limitations of most studies employing a trisectorial perspective. A study of the impact of demographic pressure at different levels of technology embedded in specific sociohistoric systems follows. The final section contains an analysis of 3 types of effects which may mediate the role of demographic pressure in the choice of technologies: effects of demographic pressure on structures of production and consumption, on segments of the labor force, and on involutive and evolutive processes. It is argued that the links between demographic pressure, technologic choices, and the productive sector can only be analyzed in specific social systems.

Modeling socio-demography to capture tuberculosis transmission dynamics in a low burden setting

PubMed Central

Ajelli, Marco; Yang, Zhenhua; Merler, Stefano; Furlanello, Cesare; Kirschner, Denise

2011-01-01

Evidence of preferential mixing through selected social routes has been suggested for the transmission of tuberculosis (TB) infection in low burden settings. A realistic modelization of these contact routes is needed to appropriately assess the impact of individually targeted control strategies, such as contact network investigation of index cases and treatment of latent TB infection (LTBI). We propose an age-structured, socio-demographic individual based model (IBM) with a realistic, time-evolving structure of preferential contacts in a population. In particular, transmission within households, schools and work-places, together with a component of casual, distance-dependent contacts are considered. We also compared the model against two other formulations having no social structure of contacts (homogeneous mixing transmission): a baseline deterministic model without age structure and an age-structured IBM. The socio-demographic IBM better fitted recent longitudinal data on TB epidemiology in Arkansas, USA, which serves as an example of a low burden setting. Inclusion of age structure in the model proved fundamental to capturing actual proportions of reactivated TB cases (as opposed to recently transmitted) as well as profiling age-group specific incidence. The socio-demographic structure additionally provides a prediction of TB transmission rates (the rate of infection in household contacts and the rate of secondary cases in household and workplace contacts). These results suggest that the socio-demographic IBM is an optimal choice for evaluating current control strategies, including contact network investigation of index cases, and the simulation of alternative scenarios, particularly for TB eradication targets. PMID:21906603

Estimating synchronous demographic changes across populations using hABC and its application for a herpetological community from northeastern Brazil.

PubMed

Gehara, Marcelo; Garda, Adrian A; Werneck, Fernanda P; Oliveira, Eliana F; da Fonseca, Emanuel M; Camurugi, Felipe; Magalhães, Felipe de M; Lanna, Flávia M; Sites, Jack W; Marques, Ricardo; Silveira-Filho, Ricardo; São Pedro, Vinícius A; Colli, Guarino R; Costa, Gabriel C; Burbrink, Frank T

2017-09-01

Many studies propose that Quaternary climatic cycles contracted and/or expanded the ranges of species and biomes. Strong expansion-contraction dynamics of biomes presume concerted demographic changes of associated fauna. The analysis of temporal concordance of demographic changes can be used to test the influence of Quaternary climate on diversification processes. Hierarchical approximate Bayesian computation (hABC) is a powerful and flexible approach that models genetic data from multiple species, and can be used to estimate the temporal concordance of demographic processes. Using available single-locus data, we can now perform large-scale analyses, both in terms of number of species and geographic scope. Here, we first compared the power of four alternative hABC models for a collection of single-locus data. We found that the model incorporating an a priori hypothesis about the timing of simultaneous demographic change had the best performance. Second, we applied the hABC models to a data set of seven squamate and four amphibian species occurring in the Seasonally Dry Tropical Forests (Caatinga) in northeastern Brazil, which, according to paleoclimatic evidence, experienced an increase in aridity during the Pleistocene. If this increase was important for the diversification of associated xeric-adapted species, simultaneous population expansions should be evident at the community level. We found a strong signal of synchronous population expansion in the Late Pleistocene, supporting the increase of the Caatinga during this time. This expansion likely enhanced the formation of communities adapted to high aridity and seasonality and caused regional extirpation of taxa adapted to wet forest. © 2017 John Wiley & Sons Ltd.

Impact of Demographic Trends on Future Development Patterns and the Loss of Open Space in the California Mojave Desert

NASA Astrophysics Data System (ADS)

Gomben, Peter; Lilieholm, Robert; Gonzalez-Guillen, Manuel

2012-02-01

During the post-World War II era, the Mojave Desert Region of San Bernardino County, California, has experienced rapid levels of population growth. Over the past several decades, growth has accelerated, accompanied by significant shifts in ethnic composition, most notably from predominantly White non-Hispanic to Hispanic. This study explores the impacts of changing ethnicity on future development and the loss of open space by modeling ethnic propensities regarding family size and settlement preferences reflected by U.S. Census Bureau data. Demographic trends and land conversion data were obtained for seven Mojave Desert communities for the period between 1990 and 2001. Using a spatially explicit, logistic regression-based urban growth model, these data and trends were used to project community-specific future growth patterns from 2000 to 2020 under three future settlement scenarios: (1) an "historic" scenario reported in earlier research that uses a Mojave-wide average settlement density of 3.76 persons/ha; (2) an "existing" scenario based on community-specific settlement densities as of 2001; and (3) a "demographic futures" scenario based on community-specific settlement densities that explicitly model the Region's changing ethnicity. Results found that under the demographic futures scenario, by 2020 roughly 53% of within-community open space would remain, under the existing scenario only 40% would remain, and under the historic scenario model the communities would have what amounts to a deficit of open space. Differences in the loss of open space across the scenarios demonstrate the importance of considering demographic trends that are reflective of the residential needs and preferences of projected future populations.

Impact of demographic trends on future development patterns and the loss of open space in the California Mojave Desert.

PubMed

Gomben, Peter; Lilieholm, Robert; Gonzalez-Guillen, Manuel

2012-02-01

During the post-World War II era, the Mojave Desert Region of San Bernardino County, California, has experienced rapid levels of population growth. Over the past several decades, growth has accelerated, accompanied by significant shifts in ethnic composition, most notably from predominantly White non-Hispanic to Hispanic. This study explores the impacts of changing ethnicity on future development and the loss of open space by modeling ethnic propensities regarding family size and settlement preferences reflected by U.S. Census Bureau data. Demographic trends and land conversion data were obtained for seven Mojave Desert communities for the period between 1990 and 2001. Using a spatially explicit, logistic regression-based urban growth model, these data and trends were used to project community-specific future growth patterns from 2000 to 2020 under three future settlement scenarios: (1) an "historic" scenario reported in earlier research that uses a Mojave-wide average settlement density of 3.76 persons/ha; (2) an "existing" scenario based on community-specific settlement densities as of 2001; and (3) a "demographic futures" scenario based on community-specific settlement densities that explicitly model the Region's changing ethnicity. Results found that under the demographic futures scenario, by 2020 roughly 53% of within-community open space would remain, under the existing scenario only 40% would remain, and under the historic scenario model the communities would have what amounts to a deficit of open space. Differences in the loss of open space across the scenarios demonstrate the importance of considering demographic trends that are reflective of the residential needs and preferences of projected future populations.

The Use of Surrogate Data in Demographic Population Viability Analysis: A Case Study of California Sea Lions

PubMed Central

2015-01-01

Reliable data necessary to parameterize population models are seldom available for imperiled species. As an alternative, data from populations of the same species or from ecologically similar species have been used to construct models. In this study, we evaluated the use of demographic data collected at one California sea lion colony (Los Islotes) to predict the population dynamics of the same species from two other colonies (San Jorge and Granito) in the Gulf of California, Mexico, for which demographic data are lacking. To do so, we developed a stochastic demographic age-structured matrix model and conducted a population viability analysis for each colony. For the Los Islotes colony we used site-specific pup, juvenile, and adult survival probabilities, as well as birth rates for older females. For the other colonies, we used site-specific pup and juvenile survival probabilities, but used surrogate data from Los Islotes for adult survival probabilities and birth rates. We assessed these models by comparing simulated retrospective population trajectories to observed population trends based on count data. The projected population trajectories approximated the observed trends when surrogate data were used for one colony but failed to match for a second colony. Our results indicate that species-specific and even region-specific surrogate data may lead to erroneous conservation decisions. These results highlight the importance of using population-specific demographic data in assessing extinction risk. When vital rates are not available and immediate management actions must be taken, in particular for imperiled species, we recommend the use of surrogate data only when the populations appear to have similar population trends. PMID:26413746

Survival models for harvest management of mourning dove populations

USGS Publications Warehouse

Otis, D.L.

2002-01-01

Quantitative models of the relationship between annual survival and harvest rate of migratory game-bird populations are essential to science-based harvest management strategies. I used the best available band-recovery and harvest data for mourning doves (Zenaida macroura) to build a set of models based on different assumptions about compensatory harvest mortality. Although these models suffer from lack of contemporary data, they can be used in development of an initial set of population models that synthesize existing demographic data on a management-unit scale, and serve as a tool for prioritization of population demographic information needs. Credible harvest management plans for mourning dove populations will require a long-term commitment to population monitoring and iterative population analysis.

Cognitive functioning and social problem-solving skills in schizophrenia.

PubMed

Hatashita-Wong, Michi; Smith, Thomas E; Silverstein, Steven M; Hull, James W; Willson, Deborah F

2002-05-01

This study examined the relationships between symptoms, cognitive functioning, and social skill deficits in schizophrenia. Few studies have incorporated measures of cognitive functioning and symptoms in predictive models for social problem solving. For our study, 44 participants were recruited from consecutive outpatient admissions. Neuropsychological tests were given to assess cognitive function, and social problem solving was assessed using structured vignettes designed to evoke the participant's ability to generate, evaluate, and apply solutions to social problems. A sequential model-fitting method of analysis was used to incorporate social problem solving, symptom presentation, and cognitive impairment into linear regression models. Predictor variables were drawn from demographic, cognitive, and symptom domains. Because this method of analysis was exploratory and not intended as hierarchical modelling, no a priori hypotheses were proposed. Participants with higher scores on tests of cognitive flexibility were better able to generate accurate, appropriate, and relevant responses to the social problem-solving vignettes. The results suggest that cognitive flexibility is a potentially important mediating factor in social problem-solving competence. While other factors are related to social problem-solving skill, this study supports the importance of cognition and understanding how it relates to the complex and multifaceted nature of social functioning.

Work Ability: using structural equation modeling to assess the effects of aging, health and work on the population of Brazilian municipal employees.

PubMed

Alcântara, Marcus A; Sampaio, Rosana F; Assunção, Ada Ávila; Silva, Fabiana C Martins

2014-01-01

The Work Ability Model has a holistic structure that incorporates individual characteristics, work-related factors and life outside of work. The model has been explored in the context of Finland but still needs to be applied in other countries. The aim of this study was to examine the relationships between age, health, work and work ability in a sample of Brazilian municipal employees. A sample of 5,646 workers answered a web-survey questionnaire that collected information about socio-demographics, health, work characteristics and work ability. Structural equation modeling (SEM) was used to examine the simultaneous relationships between the variables that comprise the Work Ability Model. The sample was predominantly female (68.0%), between 30 and 49 years old (60.0%) and highly educated (66.0%). SEM produced good fit indexes that supported the Work Ability Model. Age was positively related to work ability and negatively related to health. Health and work characteristics positively influenced work ability. The results produced additional support for the conceptualization of work ability as a complex and dynamic phenomenon: a system composed of an individual and various elements of his/her work interact in time and space in a nonlinear way.

Association between latent toxoplasmosis and cognition in adults: a cross-sectional study.

PubMed

Gale, S D; Brown, B L; Erickson, L D; Berrett, A; Hedges, D W

2015-04-01

Latent infection from Toxoplasma gondii (T. gondii) is widespread worldwide and has been associated with cognitive deficits in some but not all animal models and in humans. We tested the hypothesis that latent toxoplasmosis is associated with decreased cognitive function in a large cross-sectional dataset, the National Health and Nutrition Examination Survey (NHANES). There were 4178 participants aged 20-59 years, of whom 19.1% had IgG antibodies against T. gondii. Two ordinary least squares (OLS) regression models adjusted for the NHANES complex sampling design and weighted to represent the US population were estimated for simple reaction time, processing speed and short-term memory or attention. The first model included only main effects of latent toxoplasmosis and demographic control variables, and the second added interaction terms between latent toxoplasmosis and the poverty-to-income ratio (PIR), educational attainment and race-ethnicity. We also used multivariate models to assess all three cognitive outcomes in the same model. Although the models evaluating main effects only demonstrated no association between latent toxoplasmosis and the cognitive outcomes, significant interactions between latent toxoplasmosis and the PIR, between latent toxoplasmosis and educational attainment, and between latent toxoplasmosis and race-ethnicity indicated that latent toxoplasmosis may adversely affect cognitive function in certain groups.

Does Litter Size Variation Affect Models of Terrestrial Carnivore Extinction Risk and Management?

PubMed Central

Devenish-Nelson, Eleanor S.; Stephens, Philip A.; Harris, Stephen; Soulsbury, Carl; Richards, Shane A.

2013-01-01

Background Individual variation in both survival and reproduction has the potential to influence extinction risk. Especially for rare or threatened species, reliable population models should adequately incorporate demographic uncertainty. Here, we focus on an important form of demographic stochasticity: variation in litter sizes. We use terrestrial carnivores as an example taxon, as they are frequently threatened or of economic importance. Since data on intraspecific litter size variation are often sparse, it is unclear what probability distribution should be used to describe the pattern of litter size variation for multiparous carnivores. Methodology/Principal Findings We used litter size data on 32 terrestrial carnivore species to test the fit of 12 probability distributions. The influence of these distributions on quasi-extinction probabilities and the probability of successful disease control was then examined for three canid species – the island fox Urocyon littoralis, the red fox Vulpes vulpes, and the African wild dog Lycaon pictus. Best fitting probability distributions differed among the carnivores examined. However, the discretised normal distribution provided the best fit for the majority of species, because variation among litter-sizes was often small. Importantly, however, the outcomes of demographic models were generally robust to the distribution used. Conclusion/Significance These results provide reassurance for those using demographic modelling for the management of less studied carnivores in which litter size variation is estimated using data from species with similar reproductive attributes. PMID:23469140

Does litter size variation affect models of terrestrial carnivore extinction risk and management?

PubMed

Devenish-Nelson, Eleanor S; Stephens, Philip A; Harris, Stephen; Soulsbury, Carl; Richards, Shane A

2013-01-01

Individual variation in both survival and reproduction has the potential to influence extinction risk. Especially for rare or threatened species, reliable population models should adequately incorporate demographic uncertainty. Here, we focus on an important form of demographic stochasticity: variation in litter sizes. We use terrestrial carnivores as an example taxon, as they are frequently threatened or of economic importance. Since data on intraspecific litter size variation are often sparse, it is unclear what probability distribution should be used to describe the pattern of litter size variation for multiparous carnivores. We used litter size data on 32 terrestrial carnivore species to test the fit of 12 probability distributions. The influence of these distributions on quasi-extinction probabilities and the probability of successful disease control was then examined for three canid species - the island fox Urocyon littoralis, the red fox Vulpes vulpes, and the African wild dog Lycaon pictus. Best fitting probability distributions differed among the carnivores examined. However, the discretised normal distribution provided the best fit for the majority of species, because variation among litter-sizes was often small. Importantly, however, the outcomes of demographic models were generally robust to the distribution used. These results provide reassurance for those using demographic modelling for the management of less studied carnivores in which litter size variation is estimated using data from species with similar reproductive attributes.

Prospective impact of illness uncertainty on outcomes in chronic lung disease.

PubMed

Hoth, Karin F; Wamboldt, Frederick S; Strand, Matthew; Ford, Dee W; Sandhaus, Robert A; Strange, Charlie; Bekelman, David B; Holm, Kristen E

2013-11-01

To determine which aspect of illness uncertainty (i.e., ambiguity or complexity) has a stronger association with psychological and clinical outcomes over a 2-year period among individuals with a genetic subtype of chronic obstructive pulmonary disease (COPD). Ambiguity reflects uncertainty about physical cues and symptoms, and complexity reflects uncertainty about treatment and the medical system. Four-hundred and 7 individuals with alpha-1 antitrypsin deficiency-associated COPD completed questionnaires at baseline, 1- and 2-year follow-up. Uncertainty was measured using the Mishel Uncertainty in Illness Scale. Outcomes were measured using the Hospital Anxiety and Depression Scale, St. George's Respiratory Questionnaire, and MMRC Dyspnea Scale. Ambiguity and complexity were examined as predictors of depressive symptoms, anxiety, quality of life, and breathlessness using linear mixed models adjusting for demographic and health characteristics. Ambiguity was associated with more depressive symptoms (b = 0.09, SE = 0.02, p < .001) and anxiety (b = 0.13, SE = 0.02, p < .001), worse quality of life (b = 0.57, SE = 0.10, p < .001), and more breathlessness (b = 0.02, SE = 0.006, p < .001). Complexity did not have an independent effect on any outcome. Interactions between ambiguity and time since diagnosis were not statistically significant. Ambiguity was prospectively associated with worse mood, quality of life, and breathlessness. Thus, ambiguity should be targeted in psychosocial interventions. Time since diagnosis did not affect the association between ambiguity and outcomes, suggesting that the impact of ambiguity is equally strong throughout the course of COPD.

The changing demographic, legal, and technological contexts of political representation

PubMed Central

Forest, Benjamin

2005-01-01

Three developments have created challenges for political representation in the U.S. and particularly for the use of territorially based representation (election by district). First, the demographic complexity of the U.S. population has grown both in absolute terms and in terms of residential patterns. Second, legal developments since the 1960s have recognized an increasing number of groups as eligible for voting rights protection. Third, the growing technical capacities of computer technology, particularly Geographic Information Systems, have allowed political parties and other organizations to create election districts with increasingly precise political and demographic characteristics. Scholars have made considerable progress in measuring and evaluating the racial and partisan biases of districting plans, and some states have tried to use Geographic Information Systems technology to produce more representative districts. However, case studies of Texas and Arizona illustrate that such analytic and technical advances have not overcome the basic contradictions that underlie the American system of territorial political representation. PMID:16230615

Baby boomers' food shopping habits. Relationships with demographics and personal values.

PubMed

Worsley, Anthony; Wang, Wei C; Hunter, Wendy

2010-12-01

The purpose of this study was to examine baby boomers' food shopping behaviours and to investigate their relationships with demographics and personal values. A questionnaire concerning food shopping behaviours, personal values and demographics was mailed to a random sample of 2975 people aged 40-70 years in Victoria, Australia. Usable questionnaires of 1031 were obtained. Structural equation modelling was employed for data analyses. The analyses revealed that demographics and personal values influenced shopping behaviours via different pathways among male and female baby boomers. For example, self-direction positively impacted on shopping planning for men but negatively influenced price minimization for women. Among women only, age was positively related to shopping planning and negatively to price minimization. Thus, both personal values and demographics influenced baby boomers' shopping behaviours. Since values are more likely to be amenable to change than demographics, segmentation of the population via value orientations would facilitate targeted interventions to promote healthy food shopping. Copyright © 2010 Elsevier Ltd. All rights reserved.

Demographic Analysis and Planning for the Future. No. 13.

ERIC Educational Resources Information Center

Efird, Cathy M.

The basic sources and types of demographic data available for future planning for the developmentally disabled are reviewed and a frame work for data organization is suggested. It is explained that future forecasts may be undertaken by the following principles: trend forecasting or extrapolation; scenario construction; models, games, and…

Temporal, spatial, and environmental influences on the demographics of grizzly bears in the Greater Yellowstone Ecosystem

USGS Publications Warehouse

Schwartz, Charles C.; Haroldson, Mark A.; White, Gary C.; Harris, Richard B.; Cherry, Steve; Keating, Kim A.; Moody, Dave; Servheen, Christopher

2006-01-01

During the past 2 decades, the grizzly bear (Ursus arctos) population in the Greater Yellowstone Ecosystem (GYE) has increased in numbers and expanded in range. Understanding temporal, environmental, and spatial variables responsible for this change is useful in evaluating what likely influenced grizzly bear demographics in the GYE and where future management efforts might benefit conservation and management. We used recent data from radio-marked bears to estimate reproduction (1983–2002) and survival (1983–2001); these we combined into models to evaluate demographic vigor (lambda [λ]). We explored the influence of an array of individual, temporal, and spatial covariates on demographic vigor.

Decision tree-based method for integrating gene expression, demographic, and clinical data to determine disease endotypes

EPA Science Inventory

Complex diseases are often difficult to diagnose, treat, and study due to the multi-factorial nature of the etiology. Significant challenges exist with regard to how to segregate indivdiuals into suitable subtypes of the disease. Here, we examine a range of methods for evaluati...

Remarriage and Stepfamilies: Strategic Sites for Family Scholarship in the 21st Century

ERIC Educational Resources Information Center

Sweeney, Megan M.

2010-01-01

This article reviews areas of advancement over the past decade in our understanding of remarriage and stepfamilies and suggests promising new directions for future work. Profound shifts in the demographic context of family life motivate central themes in recent scholarship on remarriage and stepfamilies, including the diversity and complexity of…

Investigating Syntactical and Lexical Complexity in Gendered and Same-Sex Interactions

ERIC Educational Resources Information Center

Long, Robert W., III.

2018-01-01

For many sociolinguists, the issue of shyness and hesitation phenomenon has been problematic for Japanese L1 and L2 speakers, particularly in gendered interactions. Over the past decade, more Japanese are shunning conversations, relationships, and isolating themselves, which is accelerating the demographic crisis in Japan. Thus, this paper focuses…

Psychiatric Services in Dubai (A Short Descriptive Report)

ERIC Educational Resources Information Center

Al Mualla, Saoud

2011-01-01

The paper gives an account of psychiatric services in Dubai (U.A.E). It describes the unique demographic constitution of Dubai and its complex health system. It also discusses the reasons behind the primitiveness of psychiatry in comparison to other medical specialties and services, especially considering the wealth of Dubai. The paper then goes…

Preparing Young Adolescents for a Bright Future--Right Now!

ERIC Educational Resources Information Center

Deering, Paul D.; Martin, Kathryn L.; Buelow, Stephanie M.; Hoffman, Jennifer T.; Cameli, Sandy; Martin, Matt; Walker, Robert E.; O'Neill, Tara B.

2016-01-01

We must prepare young adolescents for a bright future by examining all of our educational practices in terms of their current and future relevance. The education we provide our students must prepare them to address enormously complex issues involving demographics and international relations, environmental and human health, and the development and…

The Western Sydney Rustbelt: Recognizing and Building on Strengths in Pre-Service Teacher Education

ERIC Educational Resources Information Center

Naidoo, Loshini; D'warte, Jacqueline Ann

2017-01-01

Preparing pre-service teachers to address the disparities in educational attainment that occur in settings with complex demographics such as high poverty and super diversity (Vertovec, 2007) require a theoretically driven contextual and spacial (Soja, 1996) understanding of disadvantage. This understanding highlights the structural and systemic…

Identifying Predictors of Academic Success for Part-Time Students at Polytechnic Institutes in Malaysia

ERIC Educational Resources Information Center

Ibrahim, Norhayati; Freeman, Steven A.; Shelley, Mack C.

2011-01-01

A central challenge for higher education today is to understand the diversity and complexity of nontraditional students' life experiences and how these factors influence their academic success. To better understand these issues, this study explored the role of demographic characteristics and employment variables in predicting the academic success…

The Politics of Diversity: Integration in an Era of Political and Legal Uncertainty

ERIC Educational Resources Information Center

Diem, Sarah; Frankenberg, Erica

2013-01-01

Background: The demographic landscape in the United States has shifted dramatically since "Brown v. Board of Education," leading to more complex diversity in many school districts than the diversity contemplated nearly 60 years ago. Desegregation research has shown that countywide districts are better able to maintain diverse schools,…

New Realities in the Management of Student Affairs: Emerging Specialist Roles and Structures for Changing Times

ERIC Educational Resources Information Center

Tull, Ashley, Ed.; Kuk, Linda, Ed.

2012-01-01

Student affairs organizations are at a crossroads. They face expanding enrollments; a concomitant increase need for often more complex services; changing demographics; a growing cohort of non-traditional and first-generation students; shifting and more demanding responsibilities; and increased expectations from the greater campus community,…

Estimating demographic parameters using a combination of known-fate and open N-mixture models

USGS Publications Warehouse

Schmidt, Joshua H.; Johnson, Devin S.; Lindberg, Mark S.; Adams, Layne G.

2015-01-01

Accurate estimates of demographic parameters are required to infer appropriate ecological relationships and inform management actions. Known-fate data from marked individuals are commonly used to estimate survival rates, whereas N-mixture models use count data from unmarked individuals to estimate multiple demographic parameters. However, a joint approach combining the strengths of both analytical tools has not been developed. Here we develop an integrated model combining known-fate and open N-mixture models, allowing the estimation of detection probability, recruitment, and the joint estimation of survival. We demonstrate our approach through both simulations and an applied example using four years of known-fate and pack count data for wolves (Canis lupus). Simulation results indicated that the integrated model reliably recovered parameters with no evidence of bias, and survival estimates were more precise under the joint model. Results from the applied example indicated that the marked sample of wolves was biased toward individuals with higher apparent survival rates than the unmarked pack mates, suggesting that joint estimates may be more representative of the overall population. Our integrated model is a practical approach for reducing bias while increasing precision and the amount of information gained from mark–resight data sets. We provide implementations in both the BUGS language and an R package.

Estimating demographic parameters using a combination of known-fate and open N-mixture models.

PubMed

Schmidt, Joshua H; Johnson, Devin S; Lindberg, Mark S; Adams, Layne G

2015-10-01

Accurate estimates of demographic parameters are required to infer appropriate ecological relationships and inform management actions. Known-fate data from marked individuals are commonly used to estimate survival rates, whereas N-mixture models use count data from unmarked individuals to estimate multiple demographic parameters. However, a joint approach combining the strengths of both analytical tools has not been developed. Here we develop an integrated model combining known-fate and open N-mixture models, allowing the estimation of detection probability, recruitment, and the joint estimation of survival. We demonstrate our approach through both simulations and an applied example using four years of known-fate and pack count data for wolves (Canis lupus). Simulation results indicated that the integrated model reliably recovered parameters with no evidence of bias, and survival estimates were more precise under the joint model. Results from the applied example indicated that the marked sample of wolves was biased toward individuals with higher apparent survival rates than the unmarked pack mates, suggesting that joint estimates may be more representative of the overall population. Our integrated model is a practical approach for reducing bias while increasing precision and the amount of information gained from mark-resight data sets. We provide implementations in both the BUGS language and an R package.

Principles of Precision Prevention Science for Improving Recruitment and Retention of Participants.

PubMed

Supplee, Lauren H; Parekh, Jenita; Johnson, Makedah

2018-03-12

Precision medicine and precision public health focus on identifying and providing the right intervention to the right population at the right time. Expanding on the concept, precision prevention science could allow the field to examine prevention programs to identify ways to make them more efficient and effective at scale, including addressing issues related to engagement and retention of participants. Research to date on engagement and retention has often focused on demographics and risk factors. The current paper proposes using McCurdy and Daro (Family Relations, 50, 113-121, 2001) model that posits a complex mixture of individual, provider, program, and community-level factors synergistically affect enrollment, engagement, and retention. The paper concludes recommending the use of research-practice partnerships and innovative, rapid cycle methods to design and improve prevention programs related to participant engagement and retention at scale.

Human mobility in an emerging epidemic: a key aspect for response planning

NASA Astrophysics Data System (ADS)

Poletto, Chiara; Bajardi, Paolo; Colizza, Vittoria; Ramasco, Jose J.; Tizzoni, Michele; Vespignani, Alessandro

2010-03-01

Human mobility and interactions represent key ingredients in the spreading dynamics of an infectious disease. The flows of traveling people form a network characterized by complex features, such as strong topological and traffic heterogeneities, that unfolds at different temporal and spatial scales, from short ranges to the global scale. Computational models can be developed that integrate detailed network structures based on demographic and mobility data, in order to simulate the spatial evolution of an epidemic. Focusing on the recent A(H1N1) influenza pandemic as a paradigmatic example, these approaches allow the assessment of the interplay between individual mobility and epidemic dynamics, quantifying the effects of travel restrictions in delaying the epidemic spread and the role of mobility as an additional source of information for the understanding of the early outbreak.

An integrated modeling approach to estimating Gunnison Sage-Grouse population dynamics: combining index and demographic data.

USGS Publications Warehouse

Davis, Amy J.; Hooten, Mevin B.; Phillips, Michael L.; Doherty, Paul F.

2014-01-01

Evaluation of population dynamics for rare and declining species is often limited to data that are sparse and/or of poor quality. Frequently, the best data available for rare bird species are based on large-scale, population count data. These data are commonly based on sampling methods that lack consistent sampling effort, do not account for detectability, and are complicated by observer bias. For some species, short-term studies of demographic rates have been conducted as well, but the data from such studies are typically analyzed separately. To utilize the strengths and minimize the weaknesses of these two data types, we developed a novel Bayesian integrated model that links population count data and population demographic data through population growth rate (λ) for Gunnison sage-grouse (Centrocercus minimus). The long-term population index data available for Gunnison sage-grouse are annual (years 1953–2012) male lek counts. An intensive demographic study was also conducted from years 2005 to 2010. We were able to reduce the variability in expected population growth rates across time, while correcting for potential small sample size bias in the demographic data. We found the population of Gunnison sage-grouse to be variable and slightly declining over the past 16 years.

[Impact of demographic changes on health care expenditure in Germany: an analysis considering the expenditures of decedents].

PubMed

Gandjour, A; Ihle, P; Schubert, I

2008-02-01

The purpose of this study was to evaluate the impact of demographic changes on future health care expenditure of the German social health insurances considering the expenditures of survivors and decedents by age. The study analysed data from 269,646 members up to the age of 99 years of the AOK - one of Germany's largest social health insurers - in the State of Hesse in 2000/2001. In order to determine future health care expenditures, per-capita expenditures by age for outpatient, inpatient, rehabilitation, and nursing services of survivors and decedents (death within the next 12 months) were multiplied by the estimated number of survivors and decedents by age in Germany in 2020, 2035 und 2050. Expenditures for all ages were summed together. The paper shows that demographic changes until 2050 will lead to an increase of health care expenditures by 20% in total or less than 1% annually. Considering the future re-duction in workforce, demographic changes until 2050 will result in an estimated increase in health care expenditures per employee by about 57% (undifferentiated model). Considering the cost of survivors and decedents separately, this increase will amount to 50%. Hence, undifferentiated models overestimate the impact of demographic changes by about 10%.

Work stress, role conflict, social support, and psychological burnout among teachers.

PubMed

Burke, R J; Greenglass, E

1993-10-01

This study examined a research model developed to understand psychological burnout among school-based educators. Data were collected from 833 school-based educators using questionnaires completed anonymously. Four groups of predictor variables identified in previous research were considered: individual demographic and situational variables, work stressors, role conflict, and social support. Some support for the model was found. Work stressors were strong predictors of psychological burnout. Individual demographic characteristics, role conflict, and social support had little effect on psychological burnout.

Using a Hierarchical Approach to Model Regional Source Sink Dynamics for Neotropical Nearctic Songbirds to Inform Management Practices on Department of Defense Installations

DTIC Science & Technology

2017-03-20

comparison with the more intensive demographic study . We found support for spatial variation in productivity at both location and station scales. At location...the larger intensive demographic monitoring study , we also fit a productivity model that included a covariate calculated for the 12 stations included...Reference herein to any specific commercial product , process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily

AFRICAN GENETIC DIVERSITY: Implications for Human Demographic History, Modern Human Origins, and Complex Disease Mapping

PubMed Central

Campbell, Michael C.; Tishkoff, Sarah A.

2010-01-01

Comparative studies of ethnically diverse human populations, particularly in Africa, are important for reconstructing human evolutionary history and for understanding the genetic basis of phenotypic adaptation and complex disease. African populations are characterized by greater levels of genetic diversity, extensive population substructure, and less linkage disequilibrium (LD) among loci compared to non-African populations. Africans also possess a number of genetic adaptations that have evolved in response to diverse climates and diets, as well as exposure to infectious disease. This review summarizes patterns and the evolutionary origins of genetic diversity present in African populations, as well as their implications for the mapping of complex traits, including disease susceptibility. PMID:18593304

[To educate and to inform the population about population].

PubMed

Levy, M L

1993-03-01

Each society has multiple institutions that inform members about themselves and their world. The quality of the information received depends on the balance between the political, religious, intellectual, educational, and media institutions that supply information. Population questions are almost always absent from public education programs, because they deal with themes traditionally reserved for family and religious education. But the contemporary world has changed so much that families and the clerical world are no longer necessarily the best sources of instruction. The ignorance and passivity of many families leave a void that is difficult to fill. The difficulty arises because the need is to assist families in filling their role, and not to substitute for them. Educators, development technicians, psychologists, physicians, and sociologists should not be allowed to monopolize the task of educating children in areas related to population, and morality any more than priests should. The central discipline for questions of population is demography. The use of figures and quantitative categories such as age cohorts gives a "scientific" air to demographic discourse which masks the arbitrariness of many terms. At what age, for example, does one became single, or when does one cease to be an orphan? Explaining the European term "household" to Africans, or the African term "concession" to Europeans, illustrates the semantic problems impeding, understanding and communication. The diffusion of demographic information, like that of all numeric information, assumes that the complexity of data gathering and the conventions of calculation are understood. The risk of error and misunderstanding is greater in population than, for example, for the economy, because of the simple and universal nature of demographic subjects: birth, death, illness. Good understanding of demographic information should lead to a deeper understanding of apparently evident notions such as age, duration of life, households, couples and parenthood. Demography is the statistical study of intimate life. Demography should play the same role in relation to social information that national accounts play in relation to economic information, that of a model requiring careful collection of statistics and mathematical rigor, without discouraging evaluation of sources and questioning of theories by the statistical administrators, the press, or the educational institutions.

Uncertainty in Population Growth Rates: Determining Confidence Intervals from Point Estimates of Parameters

PubMed Central

Devenish Nelson, Eleanor S.; Harris, Stephen; Soulsbury, Carl D.; Richards, Shane A.; Stephens, Philip A.

2010-01-01

Background Demographic models are widely used in conservation and management, and their parameterisation often relies on data collected for other purposes. When underlying data lack clear indications of associated uncertainty, modellers often fail to account for that uncertainty in model outputs, such as estimates of population growth. Methodology/Principal Findings We applied a likelihood approach to infer uncertainty retrospectively from point estimates of vital rates. Combining this with resampling techniques and projection modelling, we show that confidence intervals for population growth estimates are easy to derive. We used similar techniques to examine the effects of sample size on uncertainty. Our approach is illustrated using data on the red fox, Vulpes vulpes, a predator of ecological and cultural importance, and the most widespread extant terrestrial mammal. We show that uncertainty surrounding estimated population growth rates can be high, even for relatively well-studied populations. Halving that uncertainty typically requires a quadrupling of sampling effort. Conclusions/Significance Our results compel caution when comparing demographic trends between populations without accounting for uncertainty. Our methods will be widely applicable to demographic studies of many species. PMID:21049049

Prediction of thoracic injury severity in frontal impacts by selected anatomical morphomic variables through model-averaged logistic regression approach.

PubMed

Zhang, Peng; Parenteau, Chantal; Wang, Lu; Holcombe, Sven; Kohoyda-Inglis, Carla; Sullivan, June; Wang, Stewart

2013-11-01

This study resulted in a model-averaging methodology that predicts crash injury risk using vehicle, demographic, and morphomic variables and assesses the importance of individual predictors. The effectiveness of this methodology was illustrated through analysis of occupant chest injuries in frontal vehicle crashes. The crash data were obtained from the International Center for Automotive Medicine (ICAM) database for calendar year 1996 to 2012. The morphomic data are quantitative measurements of variations in human body 3-dimensional anatomy. Morphomics are obtained from imaging records. In this study, morphomics were obtained from chest, abdomen, and spine CT using novel patented algorithms. A NASS-trained crash investigator with over thirty years of experience collected the in-depth crash data. There were 226 cases available with occupants involved in frontal crashes and morphomic measurements. Only cases with complete recorded data were retained for statistical analysis. Logistic regression models were fitted using all possible configurations of vehicle, demographic, and morphomic variables. Different models were ranked by the Akaike Information Criteria (AIC). An averaged logistic regression model approach was used due to the limited sample size relative to the number of variables. This approach is helpful when addressing variable selection, building prediction models, and assessing the importance of individual variables. The final predictive results were developed using this approach, based on the top 100 models in the AIC ranking. Model-averaging minimized model uncertainty, decreased the overall prediction variance, and provided an approach to evaluating the importance of individual variables. There were 17 variables investigated: four vehicle, four demographic, and nine morphomic. More than 130,000 logistic models were investigated in total. The models were characterized into four scenarios to assess individual variable contribution to injury risk. Scenario 1 used vehicle variables; Scenario 2, vehicle and demographic variables; Scenario 3, vehicle and morphomic variables; and Scenario 4 used all variables. AIC was used to rank the models and to address over-fitting. In each scenario, the results based on the top three models and the averages of the top 100 models were presented. The AIC and the area under the receiver operating characteristic curve (AUC) were reported in each model. The models were re-fitted after removing each variable one at a time. The increases of AIC and the decreases of AUC were then assessed to measure the contribution and importance of the individual variables in each model. The importance of the individual variables was also determined by their weighted frequencies of appearance in the top 100 selected models. Overall, the AUC was 0.58 in Scenario 1, 0.78 in Scenario 2, 0.76 in Scenario 3 and 0.82 in Scenario 4. The results showed that morphomic variables are as accurate at predicting injury risk as demographic variables. The results of this study emphasize the importance of including morphomic variables when assessing injury risk. The results also highlight the need for morphomic data in the development of human mathematical models when assessing restraint performance in frontal crashes, since morphomic variables are more "tangible" measurements compared to demographic variables such as age and gender. Copyright © 2013 Elsevier Ltd. All rights reserved.

Effects of climate change on an emperor penguin population: analysis of coupled demographic and climate models.

PubMed

Jenouvrier, Stéphanie; Holland, Marika; Stroeve, Julienne; Barbraud, Christophe; Weimerskirch, Henri; Serreze, Mark; Caswell, Hal

2012-09-01

Sea ice conditions in the Antarctic affect the life cycle of the emperor penguin (Aptenodytes forsteri). We present a population projection for the emperor penguin population of Terre Adélie, Antarctica, by linking demographic models (stage-structured, seasonal, nonlinear, two-sex matrix population models) to sea ice forecasts from an ensemble of IPCC climate models. Based on maximum likelihood capture-mark-recapture analysis, we find that seasonal sea ice concentration anomalies (SICa ) affect adult survival and breeding success. Demographic models show that both deterministic and stochastic population growth rates are maximized at intermediate values of annual SICa , because neither the complete absence of sea ice, nor heavy and persistent sea ice, would provide satisfactory conditions for the emperor penguin. We show that under some conditions the stochastic growth rate is positively affected by the variance in SICa . We identify an ensemble of five general circulation climate models whose output closely matches the historical record of sea ice concentration in Terre Adélie. The output of this ensemble is used to produce stochastic forecasts of SICa , which in turn drive the population model. Uncertainty is included by incorporating multiple climate models and by a parametric bootstrap procedure that includes parameter uncertainty due to both model selection and estimation error. The median of these simulations predicts a decline of the Terre Adélie emperor penguin population of 81% by the year 2100. We find a 43% chance of an even greater decline, of 90% or more. The uncertainty in population projections reflects large differences among climate models in their forecasts of future sea ice conditions. One such model predicts population increases over much of the century, but overall, the ensemble of models predicts that population declines are far more likely than population increases. We conclude that climate change is a significant risk for the emperor penguin. Our analytical approach, in which demographic models are linked to IPCC climate models, is powerful and generally applicable to other species and systems. © 2012 Blackwell Publishing Ltd.

Computer models of social processes: the case of migration.

PubMed

Beshers, J M

1967-06-01

The demographic model is a program for representing births, deaths, migration, and social mobility as social processes in a non-stationary stochastic process (Markovian). Transition probabilities for each age group are stored and then retrieved at the next appearance of that age cohort. In this way new transition probabilities can be calculated as a function of the old transition probabilities and of two successive distribution vectors.Transition probabilities can be calculated to represent effects of the whole age-by-state distribution at any given time period, too. Such effects as saturation or queuing may be represented by a market mechanism; for example, migration between metropolitan areas can be represented as depending upon job supplies and labor markets. Within metropolitan areas, migration can be represented as invasion and succession processes with tipping points (acceleration curves), and the market device has been extended to represent this phenomenon.Thus, the demographic model makes possible the representation of alternative classes of models of demographic processes. With each class of model one can deduce implied time series (varying parame-terswithin the class) and the output of the several classes can be compared to each other and to outside criteria, such as empirical time series.

Naturally rare versus newly rare: demographic inferences on two timescales inform conservation of Galápagos giant tortoises

PubMed Central

Garrick, Ryan C; Kajdacsi, Brittney; Russello, Michael A; Benavides, Edgar; Hyseni, Chaz; Gibbs, James P; Tapia, Washington; Caccone, Adalgisa

2015-01-01

Long-term population history can influence the genetic effects of recent bottlenecks. Therefore, for threatened or endangered species, an understanding of the past is relevant when formulating conservation strategies. Levels of variation at neutral markers have been useful for estimating local effective population sizes (Ne) and inferring whether population sizes increased or decreased over time. Furthermore, analyses of genotypic, allelic frequency, and phylogenetic information can potentially be used to separate historical from recent demographic changes. For 15 populations of Galápagos giant tortoises (Chelonoidis sp.), we used 12 microsatellite loci and DNA sequences from the mitochondrial control region and a nuclear intron, to reconstruct demographic history on shallow (past ∽100 generations, ∽2500 years) and deep (pre-Holocene, >10 thousand years ago) timescales. At the deep timescale, three populations showed strong signals of growth, but with different magnitudes and timing, indicating different underlying causes. Furthermore, estimated historical Ne of populations across the archipelago showed no correlation with island age or size, underscoring the complexity of predicting demographic history a priori. At the shallow timescale, all populations carried some signature of a genetic bottleneck, and for 12 populations, point estimates of contemporary Ne were very small (i.e., < 50). On the basis of the comparison of these genetic estimates with published census size data, Ne generally represented ∽0.16 of the census size. However, the variance in this ratio across populations was considerable. Overall, our data suggest that idiosyncratic and geographically localized forces shaped the demographic history of tortoise populations. Furthermore, from a conservation perspective, the separation of demographic events occurring on shallow versus deep timescales permits the identification of naturally rare versus newly rare populations; this distinction should facilitate prioritization of management action. PMID:25691990

Mixing times towards demographic equilibrium in insect populations with temperature variable age structures.

PubMed

Damos, Petros

2015-08-01

In this study, we use entropy related mixing rate modules to measure the effects of temperature on insect population stability and demographic breakdown. The uncertainty in the age of the mother of a randomly chosen newborn, and how it is moved after a finite act of time steps, is modeled using a stochastic transformation of the Leslie matrix. Age classes are represented as a cycle graph and its transitions towards the stable age distribution are brought forth as an exact Markov chain. The dynamics of divergence, from a non equilibrium state towards equilibrium, are evaluated using the Kolmogorov-Sinai entropy. Moreover, Kullback-Leibler distance is applied as information-theoretic measure to estimate exact mixing times of age transitions probabilities towards equilibrium. Using empirically data, we show that on the initial conditions and simulated projection's trough time, that population entropy can effectively be applied to detect demographic variability towards equilibrium under different temperature conditions. Changes in entropy are correlated with the fluctuations of the insect population decay rates (i.e. demographic stability towards equilibrium). Moreover, shorter mixing times are directly linked to lower entropy rates and vice versa. This may be linked to the properties of the insect model system, which in contrast to warm blooded animals has the ability to greatly change its metabolic and demographic rates. Moreover, population entropy and the related distance measures that are applied, provide a means to measure these rates. The current results and model projections provide clear biological evidence why dynamic population entropy may be useful to measure population stability. Copyright © 2015 Elsevier Inc. All rights reserved.

An analytics approach to designing patient centered medical homes.

PubMed

Ajorlou, Saeede; Shams, Issac; Yang, Kai

2015-03-01

Recently the patient centered medical home (PCMH) model has become a popular team based approach focused on delivering more streamlined care to patients. In current practices of medical homes, a clinical based prediction frame is recommended because it can help match the portfolio capacity of PCMH teams with the actual load generated by a set of patients. Without such balances in clinical supply and demand, issues such as excessive under and over utilization of physicians, long waiting time for receiving the appropriate treatment, and non-continuity of care will eliminate many advantages of the medical home strategy. In this paper, by using the hierarchical generalized linear model with multivariate responses, we develop a clinical workload prediction model for care portfolio demands in a Bayesian framework. The model allows for heterogeneous variances and unstructured covariance matrices for nested random effects that arise through complex hierarchical care systems. We show that using a multivariate approach substantially enhances the precision of workload predictions at both primary and non primary care levels. We also demonstrate that care demands depend not only on patient demographics but also on other utilization factors, such as length of stay. Our analyses of a recent data from Veteran Health Administration further indicate that risk adjustment for patient health conditions can considerably improve the prediction power of the model.

Multistate modelling extended by behavioural rules: An application to migration.

PubMed

Klabunde, Anna; Zinn, Sabine; Willekens, Frans; Leuchter, Matthias

2017-10-01

We propose to extend demographic multistate models by adding a behavioural element: behavioural rules explain intentions and thus transitions. Our framework is inspired by the Theory of Planned Behaviour. We exemplify our approach with a model of migration from Senegal to France. Model parameters are determined using empirical data where available. Parameters for which no empirical correspondence exists are determined by calibration. Age- and period-specific migration rates are used for model validation. Our approach adds to the toolkit of demographic projection by allowing for shocks and social influence, which alter behaviour in non-linear ways, while sticking to the general framework of multistate modelling. Our simulations yield that higher income growth in Senegal leads to higher emigration rates in the medium term, while a decrease in fertility yields lower emigration rates.

Demographics, political power and economic growth.

PubMed

Holtz-eakin, D

1993-01-01

"Growth theory may be used to predict the response of saving, capital formation, and output growth to large demographic shifts. Such large shifts would also be expected to alter the demand for government services and the desired levels of taxation in the population. This paper extends the overlapping-generations model of economic growth to predict the evolution of government tax and spending policy through the course of a major demographic shift. Simulations suggest that this approach may yield valuable insights into the evolution of policy in the United States and other industrialized economies." excerpt

Do Online Learning Patterns Exhibit Regional and Demographic Differences?

ERIC Educational Resources Information Center

Hsieh, Tsui-Chuan; Yang, Chyan

2012-01-01

This paper used a multi-level latent class model to evaluate whether online learning patterns exhibit regional differences and demographics. This study discovered that the Internet learning pattern consists of five segments, and the region of Taiwan is divided into two segments and further found that both the user and the regional segments are…

False Accusations: A Growing Fear in the Classroom

ERIC Educational Resources Information Center

Bradley, Jon

2011-01-01

Male role models are becoming increasingly scarce in Canadian classrooms, and the demographics indicate that the current low numbers will continue to decline. New teachers are quite prepared to take up the pedagogical issues raised by changing standards and a changing demographic; however, the spectre of violence and false accusations adds a level…

Tobacco Sales in Community Pharmacies: Remote Decisions and Demographic Targets

ERIC Educational Resources Information Center

Morton, Cory M.; Peterson, N. Andrew; Schneider, John E.; Smith, Brian J.; Armstead, Theresa L.

2010-01-01

This study applied multilevel modeling procedures with data from 678 community pharmacies and 382 residential census tracts in a Midwestern U.S. state to determine if two sets of variables: retail type (e.g., remotely owned, independently owned) and population demographics of the tracts in which outlets were located were associated with retail…

Perspectives on Population in AP® Human Geography

ERIC Educational Resources Information Center

Lu, Max; Keller, Kenneth

2016-01-01

A study of human geography begins with the human population. In fact, demographic topics frequently relate to other units in the AP Human Geography course. The three main concepts elaborated upon in this article are (1) the demographic transition model, (2) Malthusian theory and its critics, and (3) pronatalist and antinatalist policies that might…

Chapter 8: Demographic characteristics and population modeling

Treesearch

Scott H. Stoleson; Mary J. Whitfield; Mark K. Sogge

2000-01-01

An understanding of the basic demography of a species is necessary to estimate and evaluate population trends. The relative impact of different demographic parameters on growth rates can be assessed through a sensitivity analysis, in which different parameters are altered singly to assess the effect on population growth. Identification of critical parameters can allow...

The Associations between Socio-Demographic Factors and Environmental Knowledge in the City of Toyota, Japan

ERIC Educational Resources Information Center

Ito, Hiroshi; Kawazoe, Nobuo

2018-01-01

This study analyzes relationships between socio-demographic factors (age, sex, education, and household income) and environmental awareness related to the eco-policy in Toyota City, Japan. Previous research has shown that citizens' environmental awareness improved significantly after the city was designated as an environmental model city by the…

Demography of a reintroduced population: moving toward management models for an endangered species, the whooping crane

USGS Publications Warehouse

Servanty, Sabrina; Converse, Sarah J.; Bailey, Larissa L.

2014-01-01

The reintroduction of threatened and endangered species is now a common method for reestablishing populations. Typically, a fundamental objective of reintroduction is to establish a self-sustaining population. Estimation of demographic parameters in reintroduced populations is critical, as these estimates serve multiple purposes. First, they support evaluation of progress toward the fundamental objective via construction of population viability analyses (PVAs) to predict metrics such as probability of persistence. Second, PVAs can be expanded to support evaluation of management actions, via management modeling. Third, the estimates themselves can support evaluation of the demographic performance of the reintroduced population, e.g., via comparison with wild populations. For each of these purposes, thorough treatment of uncertainties in the estimates is critical. Recently developed statistical methods - namely, hierarchical Bayesian implementations of state-space models - allow for effective integration of different types of uncertainty in estimation. We undertook a demographic estimation effort for a reintroduced population of endangered whooping cranes with the purpose of ultimately developing a Bayesian PVA for determining progress toward establishing a self-sustaining population, and for evaluating potential management actions via a Bayesian PVA-based management model. We evaluated individual and temporal variation in demographic parameters based upon a multi-state mark-recapture model. We found that survival was relatively high across time and varied little by sex. There was some indication that survival varied by release method. Survival was similar to that observed in the wild population. Although overall reproduction in this reintroduced population is poor, birds formed social pairs when relatively young, and once a bird was in a social pair, it had a nearly 50% chance of nesting the following breeding season. Also, once a bird had nested, it had a high probability of nesting again. These results are encouraging considering that survival and reproduction have been major challenges in past reintroductions of this species. The demographic estimates developed will support construction of a management model designed to facilitate exploration of management actions of interest, and will provide critical guidance in future planning for this reintroduction. An approach similar to what we describe could be usefully applied to many reintroduced populations.

Contrasted demographic responses facing future climate change in Southern Ocean seabirds.

PubMed

Barbraud, Christophe; Rivalan, Philippe; Inchausti, Pablo; Nevoux, Marie; Rolland, Virginie; Weimerskirch, Henri

2011-01-01

1. Recent climate change has affected a wide range of species, but predicting population responses to projected climate change using population dynamics theory and models remains challenging, and very few attempts have been made. The Southern Ocean sea surface temperature and sea ice extent are projected to warm and shrink as concentrations of atmospheric greenhouse gases increase, and several top predator species are affected by fluctuations in these oceanographic variables. 2. We compared and projected the population responses of three seabird species living in sub-tropical, sub-Antarctic and Antarctic biomes to predicted climate change over the next 50 years. Using stochastic population models we combined long-term demographic datasets and projections of sea surface temperature and sea ice extent for three different IPCC emission scenarios (from most to least severe: A1B, A2, B1) from general circulation models of Earth's climate. 3. We found that climate mostly affected the probability to breed successfully, and in one case adult survival. Interestingly, frequent nonlinear relationships in demographic responses to climate were detected. Models forced by future predicted climatic change provided contrasted population responses depending on the species considered. The northernmost distributed species was predicted to be little affected by a future warming of the Southern Ocean, whereas steep declines were projected for the more southerly distributed species due to sea surface temperature warming and decrease in sea ice extent. For the most southerly distributed species, the A1B and B1 emission scenarios were respectively the most and less damaging. For the two other species, population responses were similar for all emission scenarios. 4. This is among the first attempts to study the demographic responses for several populations with contrasted environmental conditions, which illustrates that investigating the effects of climate change on core population dynamics is feasible for different populations using a common methodological framework. Our approach was limited to single populations and have neglected population settlement in new favourable habitats or changes in inter-specific relations as a potential response to future climate change. Predictions may be enhanced by merging demographic population models and climatic envelope models. © 2010 The Authors. Journal compilation © 2010 British Ecological Society.

Path analysis and multi-criteria decision making: an approach for multivariate model selection and analysis in health.

PubMed

Vasconcelos, A G; Almeida, R M; Nobre, F F

2001-08-01

This paper introduces an approach that includes non-quantitative factors for the selection and assessment of multivariate complex models in health. A goodness-of-fit based methodology combined with fuzzy multi-criteria decision-making approach is proposed for model selection. Models were obtained using the Path Analysis (PA) methodology in order to explain the interrelationship between health determinants and the post-neonatal component of infant mortality in 59 municipalities of Brazil in the year 1991. Socioeconomic and demographic factors were used as exogenous variables, and environmental, health service and agglomeration as endogenous variables. Five PA models were developed and accepted by statistical criteria of goodness-of fit. These models were then submitted to a group of experts, seeking to characterize their preferences, according to predefined criteria that tried to evaluate model relevance and plausibility. Fuzzy set techniques were used to rank the alternative models according to the number of times a model was superior to ("dominated") the others. The best-ranked model explained above 90% of the endogenous variables variation, and showed the favorable influences of income and education levels on post-neonatal mortality. It also showed the unfavorable effect on mortality of fast population growth, through precarious dwelling conditions and decreased access to sanitation. It was possible to aggregate expert opinions in model evaluation. The proposed procedure for model selection allowed the inclusion of subjective information in a clear and systematic manner.

Exploring the Framing of Animal Farming and Meat Consumption: On the Diversity of Topics Used and Qualitative Patterns in Selected Demographic Contexts.

PubMed

Nijland, Hanneke J; Aarts, Noelle; van Woerkum, Cees M J

2018-01-24

In various contexts, people talk about animal farming and meat consumption using different arguments to construct and justify their (non-)acceptability. This article presents the results of an in-depth qualitative inquiry into the content of and contextual patterns in the everyday-life framing regarding this issue, performed among consumers in various settings in two extremes in the European sphere: the Netherlands and Turkey. We describe the methodological steps of collecting, coding, and organizing the variety of encountered framing topics, as well as our search for symbolic convergence in groups of consumers from different selected demographic contexts (country, urban-rural areas, gender, age, and education level). The framing of animal farming and meat consumption in everyday-life is not a simple one-issue rational display of facts; people referred to a vast range of topics in the categories knowledge, convictions, pronounced behaviour, values, norms, interests, and feelings. Looking at framing in relation to the researched demographic contexts, most patterns were found on the level of topics; symbolic convergence in lines of reasoning and composite framing was less prominent in groups based on single demographic contexts than anticipated. An explanation for this lies in the complexity of frame construction, happening in relation with multiple interdependent contextual features.

Rural Household Demographics, Livelihoods and the Environment

PubMed Central

de Sherbinin, Alex; VanWey, Leah; McSweeney, Kendra; Aggarwal, Rimjhim; Barbieri, Alisson; Henry, Sabina; Hunter, Lori M.; Twine, Wayne

2008-01-01

This paper reviews and synthesizes findings from scholarly work on linkages among rural household demographics, livelihoods and the environment. Using the livelihood approach as an organizing framework, we examine evidence on the multiple pathways linking environmental variables and the following demographic variables: fertility, migration, morbidity and mortality, and lifecycles. Although the review draws on studies from the entire developing world, we find the majority of micro-level studies have been conducted in either marginal (mountainous or arid) or frontier environments, especially Amazonia. Though the linkages are mediated by many complex and often context-specific factors, there is strong evidence that dependence on natural resources intensifies when households lose human and social capital through adult morbidity and mortality, and qualified evidence for the influence of environmental factors on household decision-making regarding fertility and migration. Two decades of research on lifecycles and land-cover change at the farm level have yielded a number of insights about how households make use of different land-use and natural resource management strategies at different stages. A thread running throughout the review is the importance of managing risk through livelihood diversification, ensuring future income security, and culture-specific norms regarding appropriate and desirable activities and demographic responses. Recommendations for future research are provided. PMID:19190718

The ecology of avian influenza viruses in wild dabbling ducks (Anas spp.) in Canada

PubMed Central

Papp, Zsuzsanna; Clark, Robert G.; Parmley, E. Jane; Leighton, Frederick A.; Waldner, Cheryl

2017-01-01

Avian influenza virus (AIV) occurrence and transmission remain important wildlife and human health issues in much of the world, including in North America. Through Canada’s Inter-Agency Wild Bird Influenza Survey, close to 20,000 apparently healthy, wild dabbling ducks (of seven species) were tested for AIV between 2005 and 2011. We used these data to identify and evaluate ecological and demographic correlates of infection with low pathogenic AIVs in wild dabbling ducks (Anas spp.) across Canada. Generalized linear mixed effects model analyses revealed that risk of AIV infection was higher in hatch-year birds compared to adults, and was positively associated with a high proportion of hatch-year birds in the population. Males were more likely to be infected than females in British Columbia and in Eastern Provinces of Canada, but more complex relationships among age and sex cohorts were found in the Prairie Provinces. A species effect was apparent in Eastern Canada and British Columbia, where teal (A. discors and/or A. carolinensis) were less likely to be infected than mallards (A. platyrhynchos). Risk of AIV infection increased with the density of the breeding population, in both Eastern Canada and the Prairie Provinces, and lower temperatures preceding sampling were associated with a higher probability of AIV infection in Eastern Canada. Our results provide new insights into the ecological and demographic factors associated with AIV infection in waterfowl. PMID:28475626

Sitting occupations are an independent risk factor for Ischemic stroke in North Indian population.

PubMed

Kumar, A; Prasad, M; Kathuria, P

2014-10-01

Stroke is a multi-factorial disease and is influenced by complex environmental interactions. The purpose of this case-control study was to determine the relationship of sitting occupations with ischemic stroke in the North Indian population. In a hospital-based case-control study, age- and sex-matched controls were recruited from the outpatient department and the neurology ward of All India Institute of Medical Sciences, New Delhi. Occupation along with other demographic and risk factor variables was measured in-person interview in standardized case record form. The multivariate logistic regression model was used to estimate the odds ratio associated with ischemic stroke. Two hundred and twenty-four people post-stroke and 224 control participants were recruited from the period of February 2009 to February 2012. Mean age of cases and controls was 53.47 ± 14 and 52.92 ± 13.4, respectively. The occupations which involve sitting at work were independently associated with the risk of ischemic stroke after adjustment for demographic and risk factor variables (OR 2.2, 95% CI 1.12-3.8). The result of this study has shown an independent association between the sitting occupations and ischemic stroke in North Indian population. The present study supports the workplace health initiative to implement workplace physical activity policy and encourages employee to reduce the amount of time they spend sitting throughout the day.

The ecology of avian influenza viruses in wild dabbling ducks (Anas spp.) in Canada.

PubMed

Papp, Zsuzsanna; Clark, Robert G; Parmley, E Jane; Leighton, Frederick A; Waldner, Cheryl; Soos, Catherine

2017-01-01

Avian influenza virus (AIV) occurrence and transmission remain important wildlife and human health issues in much of the world, including in North America. Through Canada's Inter-Agency Wild Bird Influenza Survey, close to 20,000 apparently healthy, wild dabbling ducks (of seven species) were tested for AIV between 2005 and 2011. We used these data to identify and evaluate ecological and demographic correlates of infection with low pathogenic AIVs in wild dabbling ducks (Anas spp.) across Canada. Generalized linear mixed effects model analyses revealed that risk of AIV infection was higher in hatch-year birds compared to adults, and was positively associated with a high proportion of hatch-year birds in the population. Males were more likely to be infected than females in British Columbia and in Eastern Provinces of Canada, but more complex relationships among age and sex cohorts were found in the Prairie Provinces. A species effect was apparent in Eastern Canada and British Columbia, where teal (A. discors and/or A. carolinensis) were less likely to be infected than mallards (A. platyrhynchos). Risk of AIV infection increased with the density of the breeding population, in both Eastern Canada and the Prairie Provinces, and lower temperatures preceding sampling were associated with a higher probability of AIV infection in Eastern Canada. Our results provide new insights into the ecological and demographic factors associated with AIV infection in waterfowl.

Final anatomic and visual outcomes appear independent of duration of silicone oil intraocular tamponade in complex retinal detachment surgery.

PubMed

Rhatigan, Maedbh; McElnea, Elizabeth; Murtagh, Patrick; Stephenson, Kirk; Harris, Elaine; Connell, Paul; Keegan, David

2018-01-01

To report anatomic and visual outcomes following silicone oil removal in a cohort of patients with complex retinal detachment, to determine association between duration of tamponade and outcomes and to compare patients with oil removed and those with oil in situ in terms of demographic, surgical and visual factors. We reported a four years retrospective case series of 143 patients with complex retinal detachments who underwent intraocular silicone oil tamponade. Analysis between anatomic and visual outcomes, baseline demographics, duration of tamponade and number of surgical procedures were carried out using Fisher's exact test and unpaired two-tailed t -test. One hundred and six patients (76.2%) had undergone silicone oil removal at the time of review with 96 patients (90.6%) showing retinal reattachment following oil removal. Duration of tamponade was not associated with final reattachment rate or with a deterioration in best corrected visual acuity (BCVA). Patients with oil removed had a significantly better baseline and final BCVA compared to those under oil tamponade ( P =0.0001, <0.0001 respectively). Anatomic and visual outcomes in this cohort are in keeping with those reported in the literature. Favorable outcomes were seen with oil removal but duration of oil tamponade does not affect final attachment rate with modern surgical techniques and should be managed on a case by case basis.

Dairy goat demography and Q fever infection dynamics

PubMed Central

2013-01-01

Between 2007 and 2009, the largest human Q fever epidemic ever described occurred in the Netherlands. The source was traced back to dairy goat farms, where abortion storms had been observed since 2005. Since one putative cause of these abortion storms is the intensive husbandry systems in which the goats are kept, the objective of this study was to assess whether these could be explained by herd size, reproductive pattern and other demographic aspects of Dutch dairy goat herds alone. We adapted an existing, fully parameterized simulation model for Q fever transmission in French dairy cattle herds to represent the demographics typical for Dutch dairy goat herds. The original model represents the infection dynamics in a herd of 50 dairy cows after introduction of a single infected animal; the adapted model has 770 dairy goats. For a full comparison, herds of 770 cows and 50 goats were also modeled. The effects of herd size and goat versus cattle demographics on the probability of and time to extinction of the infection, environmental bacterial load and abortion rate were studied by simulation. The abortion storms could not be fully explained by demographics alone. Adequate data were lacking at the moment to attribute the difference to characteristics of the pathogen, host, within-herd environment, or a combination thereof. The probability of extinction was higher in goat herds than in cattle herds of the same size. The environmental contamination was highest within cattle herds, which may be taken into account when enlarging cattle farming systems. PMID:23621908

Dairy goat demography and Q fever infection dynamics.

PubMed

Hogerwerf, Lenny; Courcoul, Aurélie; Klinkenberg, Don; Beaudeau, François; Vergu, Elisabeta; Nielen, Mirjam

2013-04-26

Between 2007 and 2009, the largest human Q fever epidemic ever described occurred in the Netherlands. The source was traced back to dairy goat farms, where abortion storms had been observed since 2005. Since one putative cause of these abortion storms is the intensive husbandry systems in which the goats are kept, the objective of this study was to assess whether these could be explained by herd size, reproductive pattern and other demographic aspects of Dutch dairy goat herds alone. We adapted an existing, fully parameterized simulation model for Q fever transmission in French dairy cattle herds to represent the demographics typical for Dutch dairy goat herds. The original model represents the infection dynamics in a herd of 50 dairy cows after introduction of a single infected animal; the adapted model has 770 dairy goats. For a full comparison, herds of 770 cows and 50 goats were also modeled. The effects of herd size and goat versus cattle demographics on the probability of and time to extinction of the infection, environmental bacterial load and abortion rate were studied by simulation. The abortion storms could not be fully explained by demographics alone. Adequate data were lacking at the moment to attribute the difference to characteristics of the pathogen, host, within-herd environment, or a combination thereof. The probability of extinction was higher in goat herds than in cattle herds of the same size. The environmental contamination was highest within cattle herds, which may be taken into account when enlarging cattle farming systems.

Beyond Population and Environment: Household Life Cycle Demography and Land Use Allocation among Small Farm Colonists in the Amazon

NASA Technical Reports Server (NTRS)

Perz, Stephen G.; Walker, Robert T.; Caldas, Marcellus M.

2006-01-01

Most research featuring demographic factors in environmental change has focused on processes operating at the level of national or global populations. This paper focuses on household-level demographic life cycles among colonists in the Amazon, and evaluates the impacts on land use allocation. The analysis goes beyond prior research by including a broader suite of demographic variables, and by simultaneously assessing their impacts on multiple land uses with different economic and ecological implications. We estimate a system of structural equations that accounts for endogeneity among land uses, and the findings indicate stronger demographic effects than previous work. These findings bear implications for modeling land use, and the place of demography in environmental research.

Spatially explicit inference for open populations: estimating demographic parameters from camera-trap studies

USGS Publications Warehouse

Gardner, Beth; Reppucci, Juan; Lucherini, Mauro; Royle, J. Andrew

2010-01-01

We develop a hierarchical capture–recapture model for demographically open populations when auxiliary spatial information about location of capture is obtained. Such spatial capture–recapture data arise from studies based on camera trapping, DNA sampling, and other situations in which a spatial array of devices records encounters of unique individuals. We integrate an individual-based formulation of a Jolly-Seber type model with recently developed spatially explicit capture–recapture models to estimate density and demographic parameters for survival and recruitment. We adopt a Bayesian framework for inference under this model using the method of data augmentation which is implemented in the software program WinBUGS. The model was motivated by a camera trapping study of Pampas cats Leopardus colocolo from Argentina, which we present as an illustration of the model in this paper. We provide estimates of density and the first quantitative assessment of vital rates for the Pampas cat in the High Andes. The precision of these estimates is poor due likely to the sparse data set. Unlike conventional inference methods which usually rely on asymptotic arguments, Bayesian inferences are valid in arbitrary sample sizes, and thus the method is ideal for the study of rare or endangered species for which small data sets are typical.

Spatially explicit inference for open populations: estimating demographic parameters from camera-trap studies.

PubMed

Gardner, Beth; Reppucci, Juan; Lucherini, Mauro; Royle, J Andrew

2010-11-01

We develop a hierarchical capture-recapture model for demographically open populations when auxiliary spatial information about location of capture is obtained. Such spatial capture-recapture data arise from studies based on camera trapping, DNA sampling, and other situations in which a spatial array of devices records encounters of unique individuals. We integrate an individual-based formulation of a Jolly-Seber type model with recently developed spatially explicit capture-recapture models to estimate density and demographic parameters for survival and recruitment. We adopt a Bayesian framework for inference under this model using the method of data augmentation which is implemented in the software program WinBUGS. The model was motivated by a camera trapping study of Pampas cats Leopardus colocolo from Argentina, which we present as an illustration of the model in this paper. We provide estimates of density and the first quantitative assessment of vital rates for the Pampas cat in the High Andes. The precision of these estimates is poor due likely to the sparse data set. Unlike conventional inference methods which usually rely on asymptotic arguments, Bayesian inferences are valid in arbitrary sample sizes, and thus the method is ideal for the study of rare or endangered species for which small data sets are typical.

Fatal disease and demographic Allee effect: population persistence and extinction.

PubMed

Friedman, Avner; Yakubu, Abdul-Aziz

2012-01-01

If a healthy stable host population at the disease-free equilibrium is subject to the Allee effect, can a small number of infected individuals with a fatal disease cause the host population to go extinct? That is, does the Allee effect matter at high densities? To answer this question, we use a susceptible-infected epidemic model to obtain model parameters that lead to host population persistence (with or without infected individuals) and to host extinction. We prove that the presence of an Allee effect in host demographics matters even at large population densities. We show that a small perturbation to the disease-free equilibrium can eventually lead to host population extinction. In addition, we prove that additional deaths due to a fatal infectious disease effectively increase the Allee threshold of the host population demographics.

Effects of complex life cycles on genetic diversity: cyclical parthenogenesis

PubMed Central

Rouger, R; Reichel, K; Malrieu, F; Masson, J P; Stoeckel, S

2016-01-01

Neutral patterns of population genetic diversity in species with complex life cycles are difficult to anticipate. Cyclical parthenogenesis (CP), in which organisms undergo several rounds of clonal reproduction followed by a sexual event, is one such life cycle. Many species, including crop pests (aphids), human parasites (trematodes) or models used in evolutionary science (Daphnia), are cyclical parthenogens. It is therefore crucial to understand the impact of such a life cycle on neutral genetic diversity. In this paper, we describe distributions of genetic diversity under conditions of CP with various clonal phase lengths. Using a Markov chain model of CP for a single locus and individual-based simulations for two loci, our analysis first demonstrates that strong departures from full sexuality are observed after only a few generations of clonality. The convergence towards predictions made under conditions of full clonality during the clonal phase depends on the balance between mutations and genetic drift. Second, the sexual event of CP usually resets the genetic diversity at a single locus towards predictions made under full sexuality. However, this single recombination event is insufficient to reshuffle gametic phases towards full-sexuality predictions. Finally, for similar levels of clonality, CP and acyclic partial clonality (wherein a fixed proportion of individuals are clonally produced within each generation) differentially affect the distribution of genetic diversity. Overall, this work provides solid predictions of neutral genetic diversity that may serve as a null model in detecting the action of common evolutionary or demographic processes in cyclical parthenogens (for example, selection or bottlenecks). PMID:27436524

How many tigers Panthera tigris are there in Huai Kha Khaeng Wildlife Sanctuary, Thailand? An estimate using photographic capture-recapture sampling

USGS Publications Warehouse

Simcharoen, S.; Pattanavibool, A.; Karanth, K.U.; Nichols, J.D.; Kumar, N.S.

2007-01-01

We used capture-recapture analyses to estimate the density of a tiger Panthera tigris population in the tropical forests of Huai Kha Khaeng Wildlife Sanctuary, Thailand, from photographic capture histories of 15 distinct individuals. The closure test results (z = 0.39, P = 0.65) provided some evidence in support of the demographic closure assumption. Fit of eight plausible closed models to the data indicated more support for model Mh, which incorporates individual heterogeneity in capture probabilities. This model generated an average capture probability $\\hat p$ = 0.42 and an abundance estimate of $\\widehat{N}(\\widehat{SE}[\\widehat{N}])$ = 19 (9.65) tigers. The sampled area of $\\widehat{A}(W)(\\widehat{SE}[\\widehat{A}(W)])$ = 477.2 (58.24) km2 yielded a density estimate of $\\widehat{D}(\\widehat{SE}[\\widehat{D}])$ = 3.98 (0.51) tigers per 100 km2. Huai Kha Khaeng Wildlife Sanctuary could therefore hold 113 tigers and the entire Western Forest Complex c. 720 tigers. Although based on field protocols that constrained us to use sub-optimal analyses, this estimated tiger density is comparable to tiger densities in Indian reserves that support moderate prey abundances. However, tiger densities in well-protected Indian reserves with high prey abundances are three times higher. If given adequate protection we believe that the Western Forest Complex of Thailand could potentially harbour >2,000 wild tigers, highlighting its importance for global tiger conservation. The monitoring approaches we recommend here would be useful for managing this tiger population.

Spatially explicit dynamic N-mixture models

USGS Publications Warehouse

Zhao, Qing; Royle, Andy; Boomer, G. Scott

2017-01-01

Knowledge of demographic parameters such as survival, reproduction, emigration, and immigration is essential to understand metapopulation dynamics. Traditionally the estimation of these demographic parameters requires intensive data from marked animals. The development of dynamic N-mixture models makes it possible to estimate demographic parameters from count data of unmarked animals, but the original dynamic N-mixture model does not distinguish emigration and immigration from survival and reproduction, limiting its ability to explain important metapopulation processes such as movement among local populations. In this study we developed a spatially explicit dynamic N-mixture model that estimates survival, reproduction, emigration, local population size, and detection probability from count data under the assumption that movement only occurs among adjacent habitat patches. Simulation studies showed that the inference of our model depends on detection probability, local population size, and the implementation of robust sampling design. Our model provides reliable estimates of survival, reproduction, and emigration when detection probability is high, regardless of local population size or the type of sampling design. When detection probability is low, however, our model only provides reliable estimates of survival, reproduction, and emigration when local population size is moderate to high and robust sampling design is used. A sensitivity analysis showed that our model is robust against the violation of the assumption that movement only occurs among adjacent habitat patches, suggesting wide applications of this model. Our model can be used to improve our understanding of metapopulation dynamics based on count data that are relatively easy to collect in many systems.

Team Learning for Healthcare Quality Improvement

PubMed Central

Eppstein, Margaret J.; Horbar, Jeffrey D.

2014-01-01

In organized healthcare quality improvement collaboratives (QICs), teams of practitioners from different hospitals exchange information on clinical practices with the aim of improving health outcomes at their own institutions. However, what works in one hospital may not work in others with different local contexts because of nonlinear interactions among various demographics, treatments, and practices. In previous studies of collaborations where the goal is a collective problem solving, teams of diverse individuals have been shown to outperform teams of similar individuals. However, when the purpose of collaboration is knowledge diffusion in complex environments, it is not clear whether team diversity will help or hinder effective learning. In this paper, we first use an agent-based model of QICs to show that teams comprising similar individuals outperform those with more diverse individuals under nearly all conditions, and that this advantage increases with the complexity of the landscape and level of noise in assessing performance. Examination of data from a network of real hospitals provides encouraging evidence of a high degree of similarity in clinical practices, especially within teams of hospitals engaging in QIC teams. However, our model also suggests that groups of similar hospitals could benefit from larger teams and more open sharing of details on clinical outcomes than is currently the norm. To facilitate this, we propose a secure virtual collaboration system that would allow hospitals to efficiently identify potentially better practices in use at other institutions similar to theirs without any institutions having to sacrifice the privacy of their own data. Our results may also have implications for other types of data-driven diffusive learning such as in personalized medicine and evolutionary search in noisy, complex combinatorial optimization problems. PMID:25360395

Educational Provision in Sparsely Populated Areas of Western Australia. Studies in Rural Education No. 1.

ERIC Educational Resources Information Center

Brown, Sandra; Williams, Michael

This study of educational provisions in Western Australia, an area of 2.5 million square kilometers with a mere 1.2 million inhabitants, provides a broad picture of the complex, difficult, and expensive undertaking of providing education to a small, widely-spread population which differs in demographic, economic, and cultural characteristics. The…

Future Skill Needs in Europe: Critical Labour Force Trends. Cedefop Research Paper. No 59

ERIC Educational Resources Information Center

Cedefop - European Centre for the Development of Vocational Training, 2016

2016-01-01

The European labour market is challenged by changes in the demographic composition of the labour force and increasing work complexities and processes. Skills forecasting makes useful contribution to decisions by policy-makers, experts and individuals. In this publication, Cedefop presents the latest results of skills supply and demand forecasts.…

Relationship between Prior Legal Involvement and Current Crisis for Adults with Intellectual Disability

ERIC Educational Resources Information Center

Lunsky, Yona; Raina, Poonam; Jones, Jessica

2012-01-01

Background: Individuals with intellectual disability (ID) and legal involvement are a unique population with complex needs. To date, there has been limited research exploring the demographic and clinical profiles of individuals with ID and legal involvement that are in crisis and how they differ to individuals with ID without legal involvement.…

Challenges in an Aging Society: Presidential Address to APPAM

ERIC Educational Resources Information Center

Swartz, Katherine

2010-01-01

The United States is at a critical crossroads in its history right now. The public policy problems that the people are facing are complex and interrelated, and the demographic changes that are about to significantly change their country are not well understood by large numbers of people. In this presidential address to the Association for Public…

Science, Technology and Society in Contemporary Egypt: Background Information for Social Studies Teachers.

ERIC Educational Resources Information Center

1989

Egypt is having a very difficult time supplying enough food to meet the demands of its swelling population. This complex problem is analyzed and discussed from a variety of perspectives. Factors such as foreign aid, family planning, agriculture, demographics, and religious and social culture are examined, as well as more specific issues such as…

Fostering Culturally Relevant/Responsive Pedagogy and Global Awareness through the Integration of International Service-Learning in Courses

ERIC Educational Resources Information Center

Mbugua, Tata

2010-01-01

Educators are being asked to respond to the forces of globalization and human interconnectedness that characterize the 21st century. These forces are resulting in changing population demographics and increased migration which is bringing a new complexity to cultural and ethnic diversity within regions, local communities and ultimately in…

Impact Of Selfing On The Inference Of Demographic History From Whole Genomes In Theobroma cacao L.

USDA-ARS?s Scientific Manuscript database

Theobroma cacao L (cacao: Malvaceae) is a small tree found naturally in the Amazonian rain forest. An interesting feature of cacao is that it persists in populations of naturally outcrossing and inbreeding plants, as it is a species with a complex system of self-incompatibility, where a fraction of...

An emerging paradigm for managing protected areas with examples from Europe and the United States

Treesearch

James Absher; Carsten Mann

2010-01-01

Parks and Protected Areas (PPA) have become increasingly important for societal well-being in Europe and the United States. Urbanization, detachment from nature, and demographic changes are fostering discussions about strengthening the social and cultural dimensions of management. The complexities and subtleties of incorporating PPAs into existing government and...

American Indian Tribal Values: A Critical Consideration in the Education of American Indians/Alaska Natives Today

ERIC Educational Resources Information Center

Tippeconnic, John W., III; Tippeconnic Fox, Mary Jo

2012-01-01

The education of American Indians and Alaska Natives has increasingly become more complex given the differences in tribal languages and cultures, especially as changing demographics and issues of Indian identity are considered. There are over 200 languages and vast cultural differences between and within the 565 federally recognized tribes in…

Global Skills and Mobility Challenges and Possibilities for VET: A Crossborder Cross-Sectoral Case Study

ERIC Educational Resources Information Center

Cameron, Roslyn; O'Hanlon-Rose, Terry

2011-01-01

The complex interplay of technological advances, global demographic trends and macroeconomic forces has seen the emergence of global markets, economies, supply chains and labour markets. The use of skilled migration policy and initiatives for many countries feeling the effects of aging populations and skill shortages adds another dimension to this…

Relationships between Hong Kong Students' Perceptions of the Learning Environment and Their Learning Patterns in Post-Secondary Education

ERIC Educational Resources Information Center

Law, Dennis C. S.; Meyer, Jan H. F.

2011-01-01

The present study aims to analyse the complex relationships between the relevant constructs of students' demographic background, perceptions, learning patterns and (proxy measures of) learning outcomes in order to delineate the possible direct, indirect, or spurious effects among them. The analytical methodology is substantively framed against the…

Multidimensional Evaluation of Longterm-Effects of Complex Teaching-Learning Arrangements - in the Context of Commercial Education.

ERIC Educational Resources Information Center

Achtenhagen, Frank

The effects of various megatrends in social and economic life on vocational education in Germany and other countries are discussed, and the evaluation of one approach to facing these megatrends is described. Trends include demographic changes and the conditions resulting from new technologies and environmental concerns. Such megatrends are…

The Coming Revolution in Public Services, and What It Means for Cities and Universities

ERIC Educational Resources Information Center

Konvitz, Josef

2016-01-01

Long-term demographic trends, combined with low productivity and pressure on public finances have set in place the preconditions for a major revolution in public services. Governments face new demands including for security which will lead to more centralization, but social and environmental services for a more complex society call for greater…

Modeling time-location patterns of inner-city high school students in New York and Los Angeles using a longitudinal approach with generalized estimating equations.

PubMed

Decastro, B Rey; Sax, Sonja N; Chillrud, Steven N; Kinney, Patrick L; Spengler, John D

2007-05-01

The TEACH Project obtained subjects' time-location information as part of its assessment of personal exposures to air toxics for high school students in two major urban areas. This report uses a longitudinal modeling approach to characterize the association between demographic and temporal predictors and the subjects' time-location behavior for three microenvironments--indoor-home, indoor-school, and outdoors. Such a longitudinal approach has not, to the knowledge of the authors, been previously applied to time-location data. Subjects were 14- to 19-year-old, self reported non-smokers, and were recruited from high schools in New York, NY (31 subjects: nine male, 22 female) and Los Angeles, CA (31 subjects: eight male, 23 female). Subjects reported their time-location in structured 24-h diaries with 15-min intervals for three consecutive weekdays in each of winter and summer-fall seasons in New York and Los Angeles during 1999-2000. The data set contained 15,009 observations. A longitudinal logistic regression model was run for each microenvironment where the binary outcome indicated the subject's presence in a microenvironment during a 15-min period. The generalized estimating equation (GEE) technique with alternating logistic regressions was used to account for the correlation of observations within each subject. The multivariate models revealed complex time-location patterns, with subjects predominantly in the indoor-home microenvironment, but also with a clear influence of the school schedule. The models also found that a subject's presence in a particular microenvironment may be significantly positively correlated for as long as 45 min before the current observation. Demographic variables were also predictive of time-location behavior: for the indoor-home microenvironment, having an after school job (OR=0.67 [95% confidence interval: 0.54:0.85]); for indoor-school, living in New York (0.42 [0.29:0.59]); and for outdoor, being 16-year-old (0.80 [0.67:0.96]), 17-year-old (0.71 [0.54:0.92]), and having an after school job (1.29 [1.07:1.56]).

Is bad living better than good death? Impact of demographic and cultural factors on health state preference.

PubMed

Jin, Xuejing; Liu, Gordon Guoen; Luo, Nan; Li, Hongchao; Guan, Haijing; Xie, Feng

2016-04-01

The aim of this study was to examine the impact of demographic and cultural factors on health preferences among Chinese general population. The Chinese EQ-5D-5L valuation study was conducted between December 2012 and January 2013. A total of 1296 participants were recruited from the general public at Beijing, Chengdu, Guiyang, Nanjing, and Shenyang. Each participant was interviewed to measure preferences for ten EQ-5D-5L health states using composite time trade-off and seven pairs of states using discrete choice experiment (data were not included in this study). At the end of the interview, each participant was also asked to provide their demographic information and answers to two questions about their attitudes towards whether bad living is better than good death (LBD) and whether they believe in an afterlife. Generalized linear model and random effects logistic models were used to examine the impact of demographic and cultural factors on health preferences. Participants who had serious illness experience received college or higher education, or agree with LBD were more likely to value health states positively and have a narrower score range. Participants at Beijing were more likely to be non-traders, value health states positively, less likely to reach the lowest possible score, and have narrower score range compared with all other four cities after controlling for all other demographic and culture factors. Health state preference is significantly affected by factors beyond demographics. These factors should be considered in achieving a representative sample in valuation studies in China.

Coupled Socio-Environmental Changes Triggered Indigenous Aymara Depopulation of the Semiarid Andes of Tarapacá-Chile during the Late 19th-20th Centuries.

PubMed

Lima, Mauricio; Christie, Duncan A; Santoro, M Calogero; Latorre, Claudio

2016-01-01

Socio-economic and environmental changes are well known causes of demographic collapse of agrarian cultures. The collapse of human societies is a complex phenomenon where historical and cultural dimensions play a key role, and they may interact with the environmental context. However, the importance of the interaction between socio-economic and climatic factors in explaining possible breakdowns in Native American societies has been poorly explored. The aim of this study is to test the role of socio-economic causes and rainfall variability in the collapse suffered by the Aymara people of the semiarid Andean region of Tarapacá during the period 1820-1970. Our motivation is to demonstrate that simple population dynamic models can be helpful in understanding the causes and relative importance of population changes in Andean agro-pastoral societies in responses to socio-environmental variability. Simple logistic models that combine the effects of external socio-economic causes and past rainfall variability (inferred from Gross Domestic Product [GDP] and tree-rings, respectively) were quite accurate in predicting the sustained population decline of the Aymara people. Our results suggest that the depopulation in the semiarid Tarapacá province was caused by the interaction among external socio-economic pressures given by the economic growth of the lowlands and demands for labor coupled with a persistent decline in rainfall. This study constitutes an example of how applied ecological knowledge, in particular the application of the logistic equation and theories pertaining to nonlinear population dynamics and exogenous perturbations, can be used to better understand major demographic changes in human societies.

Coupled Socio-Environmental Changes Triggered Indigenous Aymara Depopulation of the Semiarid Andes of Tarapacá-Chile during the Late 19th-20th Centuries

PubMed Central

Lima, Mauricio; Christie, Duncan A.; Santoro, M. Calogero; Latorre, Claudio

2016-01-01

Socio-economic and environmental changes are well known causes of demographic collapse of agrarian cultures. The collapse of human societies is a complex phenomenon where historical and cultural dimensions play a key role, and they may interact with the environmental context. However, the importance of the interaction between socio-economic and climatic factors in explaining possible breakdowns in Native American societies has been poorly explored. The aim of this study is to test the role of socio-economic causes and rainfall variability in the collapse suffered by the Aymara people of the semiarid Andean region of Tarapacá during the period 1820–1970. Our motivation is to demonstrate that simple population dynamic models can be helpful in understanding the causes and relative importance of population changes in Andean agro-pastoral societies in responses to socio-environmental variability. Simple logistic models that combine the effects of external socio-economic causes and past rainfall variability (inferred from Gross Domestic Product [GDP] and tree-rings, respectively) were quite accurate in predicting the sustained population decline of the Aymara people. Our results suggest that the depopulation in the semiarid Tarapacá province was caused by the interaction among external socio-economic pressures given by the economic growth of the lowlands and demands for labor coupled with a persistent decline in rainfall. This study constitutes an example of how applied ecological knowledge, in particular the application of the logistic equation and theories pertaining to nonlinear population dynamics and exogenous perturbations, can be used to better understand major demographic changes in human societies. PMID:27560499

Rule-Mining for the Early Prediction of Chronic Kidney Disease Based on Metabolomics and Multi-Source Data

PubMed Central

Luck, Margaux; Bertho, Gildas; Bateson, Mathilde; Karras, Alexandre; Yartseva, Anastasia; Thervet, Eric

2016-01-01

1H Nuclear Magnetic Resonance (NMR)-based metabolic profiling is very promising for the diagnostic of the stages of chronic kidney disease (CKD). Because of the high dimension of NMR spectra datasets and the complex mixture of metabolites in biological samples, the identification of discriminant biomarkers of a disease is challenging. None of the widely used chemometric methods in NMR metabolomics performs a local exhaustive exploration of the data. We developed a descriptive and easily understandable approach that searches for discriminant local phenomena using an original exhaustive rule-mining algorithm in order to predict two groups of patients: 1) patients having low to mild CKD stages with no renal failure and 2) patients having moderate to established CKD stages with renal failure. Our predictive algorithm explores the m-dimensional variable space to capture the local overdensities of the two groups of patients under the form of easily interpretable rules. Afterwards, a L2-penalized logistic regression on the discriminant rules was used to build predictive models of the CKD stages. We explored a complex multi-source dataset that included the clinical, demographic, clinical chemistry, renal pathology and urine metabolomic data of a cohort of 110 patients. Given this multi-source dataset and the complex nature of metabolomic data, we analyzed 1- and 2-dimensional rules in order to integrate the information carried by the interactions between the variables. The results indicated that our local algorithm is a valuable analytical method for the precise characterization of multivariate CKD stage profiles and as efficient as the classical global model using chi2 variable section with an approximately 70% of good classification level. The resulting predictive models predominantly identify urinary metabolites (such as 3-hydroxyisovalerate, carnitine, citrate, dimethylsulfone, creatinine and N-methylnicotinamide) as relevant variables indicating that CKD significantly affects the urinary metabolome. In addition, the simple knowledge of the concentration of urinary metabolites classifies the CKD stage of the patients correctly. PMID:27861591

Resource utilization in children with tuberous sclerosis complex and associated seizures: a retrospective chart review study.

PubMed

Lennert, Barb; Farrelly, Eileen; Sacco, Patricia; Pira, Geraldine; Frost, Michael

2013-04-01

Seizures are a hallmark manifestation of tuberous sclerosis complex, yet data characterizing resource utilization are lacking. This retrospective chart review was performed to assess the economic burden of tuberous sclerosis complex with neurologic manifestations. Demographic and resource utilization data were collected for 95 patients for up to 5 years after tuberous sclerosis complex diagnosis. Mean age at diagnosis was 3.1 years, with complex partial and infantile spasms as the most common seizure types. In the first 5 years post-diagnosis, 83.2% required hospitalization, 30.5% underwent surgery, and the majority of patients (90.5%) underwent ≥3 testing procedures. In 79 patients with a full 5 years of data, hospitalizations, intensive care unit stays, diagnostic testing, and rehabilitation services decreased over the 5-year period. Resource utilization is cost-intensive in children with tuberous sclerosis complex and associated seizures during the first few years following diagnosis. Improving seizure control and reducing health care costs in this population remain unmet needs.

Self-Construal and Demographic Variables as Predictors of Blind and Constructive Patriotism in University Students

ERIC Educational Resources Information Center

Ercan, Hülya

2017-01-01

The aim of this study is to investigate the blind and constructive patriotism tendencies of university students in light of the demographic structure and variables. The investigation is performed by using the correlational descriptive model. The purposeful sampling technique has been used and data was collected from a total of 390 university…

Wilderness and primitive area recreation participation and consumption: an examination of demographic and spatial factors

Treesearch

J. Michael Bowker; D. Murphy; H. Ken Cordell; Donald B.K. English; J.C. Bergstrom; C.M. Starbuck; C.J. Betz; G.T. Green

2006-01-01

This paper explores the influence of demographic and spatial variables on individual participation and consumption of wildland area recreation. Data from the National Survey on Recreation and the Environment are combined with geographical information systembased distance measures to develop nonlinear regression models used to predict both participation and the number...

Convoys of Social Support in Mexico: Examining Socio-Demographic Variation

ERIC Educational Resources Information Center

Fuller-Iglesias, Heather R.; Antonucci, Toni

2016-01-01

The Convoy Model suggests that at different stages of the lifespan the makeup of the social support network varies in step with developmental and contextual needs. Cultural norms may shape the makeup of social convoys as well as denote socio-demographic differences in social support. This study examines the social convoys of adults in Mexico.…

A demographic study of the exponential distribution applied to uneven-aged forests

Treesearch

Jeffrey H. Gove

2016-01-01

A demographic approach based on a size-structured version of the McKendrick-Von Foerster equation is used to demonstrate a theoretical link between the population size distribution and the underlying vital rates (recruitment, mortality and diameter growth) for the population of individuals whose diameter distribution is negative exponential. This model supports the...

The Relation of Student Behavior, Peer Status, Race, and Gender to Decisions about School Discipline Using CHAID Decision Trees and Regression Modeling

ERIC Educational Resources Information Center

Horner, Stacy B.; Fireman, Gary D.; Wang, Eugene W.

2010-01-01

Peer nominations and demographic information were collected from a diverse sample of 1493 elementary school participants to examine behavior (overt and relational aggression, impulsivity, and prosociality), context (peer status), and demographic characteristics (race and gender) as predictors of teacher and administrator decisions about…

Using Machine Learning to Discover Latent Social Phenotypes in Free-Ranging Macaques

PubMed Central

Madlon-Kay, Seth; Brent, Lauren J. N.; Heller, Katherine A.; Platt, Michael L.

2017-01-01

Investigating the biological bases of social phenotypes is challenging because social behavior is both high-dimensional and richly structured, and biological factors are more likely to influence complex patterns of behavior rather than any single behavior in isolation. The space of all possible patterns of interactions among behaviors is too large to investigate using conventional statistical methods. In order to quantitatively define social phenotypes from natural behavior, we developed a machine learning model to identify and measure patterns of behavior in naturalistic observational data, as well as their relationships to biological, environmental, and demographic sources of variation. We applied this model to extensive observations of natural behavior in free-ranging rhesus macaques, and identified behavioral states that appeared to capture periods of social isolation, competition over food, conflicts among groups, and affiliative coexistence. Phenotypes, represented as the rate of being in each state for a particular animal, were strongly and broadly influenced by dominance rank, sex, and social group membership. We also identified two states for which variation in rates had a substantial genetic component. We discuss how this model can be extended to identify the contributions to social phenotypes of particular genetic pathways. PMID:28754001

Univariate and multivariate spatial models of health facility utilisation for childhood fevers in an area on the coast of Kenya.

PubMed

Ouma, Paul O; Agutu, Nathan O; Snow, Robert W; Noor, Abdisalan M

2017-09-18

Precise quantification of health service utilisation is important for the estimation of disease burden and allocation of health resources. Current approaches to mapping health facility utilisation rely on spatial accessibility alone as the predictor. However, other spatially varying social, demographic and economic factors may affect the use of health services. The exclusion of these factors can lead to the inaccurate estimation of health facility utilisation. Here, we compare the accuracy of a univariate spatial model, developed only from estimated travel time, to a multivariate model that also includes relevant social, demographic and economic factors. A theoretical surface of travel time to the nearest public health facility was developed. These were assigned to each child reported to have had fever in the Kenya demographic and health survey of 2014 (KDHS 2014). The relationship of child treatment seeking for fever with travel time, household and individual factors from the KDHS2014 were determined using multilevel mixed modelling. Bayesian information criterion (BIC) and likelihood ratio test (LRT) tests were carried out to measure how selected factors improve parsimony and goodness of fit of the time model. Using the mixed model, a univariate spatial model of health facility utilisation was fitted using travel time as the predictor. The mixed model was also used to compute a multivariate spatial model of utilisation, using travel time and modelled surfaces of selected household and individual factors as predictors. The univariate and multivariate spatial models were then compared using the receiver operating area under the curve (AUC) and a percent correct prediction (PCP) test. The best fitting multivariate model had travel time, household wealth index and number of children in household as the predictors. These factors reduced BIC of the time model from 4008 to 2959, a change which was confirmed by the LRT test. Although there was a high correlation of the two modelled probability surfaces (Adj R 2  = 88%), the multivariate model had better AUC compared to the univariate model; 0.83 versus 0.73 and PCP 0.61 versus 0.45 values. Our study shows that a model that uses travel time, as well as household and individual-level socio-demographic factors, results in a more accurate estimation of use of health facilities for the treatment of childhood fever, compared to one that relies on only travel time.

Genomic evidence of demographic fluctuations and lack of genetic structure across flyways in a long distance migrant, the European turtle dove.

PubMed

Calderón, Luciano; Campagna, Leonardo; Wilke, Thomas; Lormee, Hervé; Eraud, Cyril; Dunn, Jenny C; Rocha, Gregorio; Zehtindjiev, Pavel; Bakaloudis, Dimitrios E; Metzger, Benjamin; Cecere, Jacopo G; Marx, Melanie; Quillfeldt, Petra

2016-11-07

Understanding how past climatic oscillations have affected organismic evolution will help predict the impact that current climate change has on living organisms. The European turtle dove, Streptopelia turtur, is a warm-temperature adapted species and a long distance migrant that uses multiple flyways to move between Europe and Africa. Despite being abundant, it is categorized as vulnerable because of a long-term demographic decline. We studied the demographic history and population genetic structure of the European turtle dove using genomic data and mitochondrial DNA sequences from individuals sampled across Europe, and performing paleoclimatic niche modelling simulations. Overall our data suggest that this species is panmictic across Europe, and is not genetically structured across flyways. We found the genetic signatures of demographic fluctuations, inferring an effective population size (Ne) expansion that occurred between the late Pleistocene and early Holocene, followed by a decrease in the Ne that started between the mid Holocene and the present. Our niche modelling analyses suggest that the variations in the Ne are coincident with recent changes in the availability of suitable habitat. We argue that the European turtle dove is prone to undergo demographic fluctuations, a trait that makes it sensitive to anthropogenic impacts, especially when its numbers are decreasing. Also, considering the lack of genetic structure, we suggest all populations across Europe are equally relevant for conservation.

Why abundant tropical tree species are phylogenetically old.

PubMed

Wang, Shaopeng; Chen, Anping; Fang, Jingyun; Pacala, Stephen W

2013-10-01

Neutral models of species diversity predict patterns of abundance for communities in which all individuals are ecologically equivalent. These models were originally developed for Panamanian trees and successfully reproduce observed distributions of abundance. Neutral models also make macroevolutionary predictions that have rarely been evaluated or tested. Here we show that neutral models predict a humped or flat relationship between species age and population size. In contrast, ages and abundances of tree species in the Panamanian Canal watershed are found to be positively correlated, which falsifies the models. Speciation rates vary among phylogenetic lineages and are partially heritable from mother to daughter species. Variable speciation rates in an otherwise neutral model lead to a demographic advantage for species with low speciation rate. This demographic advantage results in a positive correlation between species age and abundance, as found in the Panamanian tropical forest community.

Demographic Divergence History of Pied Flycatcher and Collared Flycatcher Inferred from Whole-Genome Re-sequencing Data

PubMed Central

Nadachowska-Brzyska, Krystyna; Burri, Reto; Olason, Pall I.; Kawakami, Takeshi; Smeds, Linnéa; Ellegren, Hans

2013-01-01

Profound knowledge of demographic history is a prerequisite for the understanding and inference of processes involved in the evolution of population differentiation and speciation. Together with new coalescent-based methods, the recent availability of genome-wide data enables investigation of differentiation and divergence processes at unprecedented depth. We combined two powerful approaches, full Approximate Bayesian Computation analysis (ABC) and pairwise sequentially Markovian coalescent modeling (PSMC), to reconstruct the demographic history of the split between two avian speciation model species, the pied flycatcher and collared flycatcher. Using whole-genome re-sequencing data from 20 individuals, we investigated 15 demographic models including different levels and patterns of gene flow, and changes in effective population size over time. ABC provided high support for recent (mode 0.3 my, range <0.7 my) species divergence, declines in effective population size of both species since their initial divergence, and unidirectional recent gene flow from pied flycatcher into collared flycatcher. The estimated divergence time and population size changes, supported by PSMC results, suggest that the ancestral species persisted through one of the glacial periods of middle Pleistocene and then split into two large populations that first increased in size before going through severe bottlenecks and expanding into their current ranges. Secondary contact appears to have been established after the last glacial maximum. The severity of the bottlenecks at the last glacial maximum is indicated by the discrepancy between current effective population sizes (20,000–80,000) and census sizes (5–50 million birds) of the two species. The recent divergence time challenges the supposition that avian speciation is a relatively slow process with extended times for intrinsic postzygotic reproductive barriers to evolve. Our study emphasizes the importance of using genome-wide data to unravel tangled demographic histories. Moreover, it constitutes one of the first examples of the inference of divergence history from genome-wide data in non-model species. PMID:24244198

Demographic divergence history of pied flycatcher and collared flycatcher inferred from whole-genome re-sequencing data.

PubMed

Nadachowska-Brzyska, Krystyna; Burri, Reto; Olason, Pall I; Kawakami, Takeshi; Smeds, Linnéa; Ellegren, Hans

2013-11-01

Profound knowledge of demographic history is a prerequisite for the understanding and inference of processes involved in the evolution of population differentiation and speciation. Together with new coalescent-based methods, the recent availability of genome-wide data enables investigation of differentiation and divergence processes at unprecedented depth. We combined two powerful approaches, full Approximate Bayesian Computation analysis (ABC) and pairwise sequentially Markovian coalescent modeling (PSMC), to reconstruct the demographic history of the split between two avian speciation model species, the pied flycatcher and collared flycatcher. Using whole-genome re-sequencing data from 20 individuals, we investigated 15 demographic models including different levels and patterns of gene flow, and changes in effective population size over time. ABC provided high support for recent (mode 0.3 my, range <0.7 my) species divergence, declines in effective population size of both species since their initial divergence, and unidirectional recent gene flow from pied flycatcher into collared flycatcher. The estimated divergence time and population size changes, supported by PSMC results, suggest that the ancestral species persisted through one of the glacial periods of middle Pleistocene and then split into two large populations that first increased in size before going through severe bottlenecks and expanding into their current ranges. Secondary contact appears to have been established after the last glacial maximum. The severity of the bottlenecks at the last glacial maximum is indicated by the discrepancy between current effective population sizes (20,000-80,000) and census sizes (5-50 million birds) of the two species. The recent divergence time challenges the supposition that avian speciation is a relatively slow process with extended times for intrinsic postzygotic reproductive barriers to evolve. Our study emphasizes the importance of using genome-wide data to unravel tangled demographic histories. Moreover, it constitutes one of the first examples of the inference of divergence history from genome-wide data in non-model species.

Population growth of Yellowstone grizzly bears: Uncertainty and future monitoring

USGS Publications Warehouse

Harris, R.B.; White, Gary C.; Schwartz, C.C.; Haroldson, M.A.

2007-01-01

Grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem of the US Rocky Mountains have recently increased in numbers, but remain vulnerable due to isolation from other populations and predicted reductions in favored food resources. Harris et al. (2006) projected how this population might fare in the future under alternative survival rates, and in doing so estimated the rate of population growth, 1983–2002. We address issues that remain from that earlier work: (1) the degree of uncertainty surrounding our estimates of the rate of population change (λ); (2) the effect of correlation among demographic parameters on these estimates; and (3) how a future monitoring system using counts of females accompanied by cubs might usefully differentiate between short-term, expected, and inconsequential fluctuations versus a true change in system state. We used Monte Carlo re-sampling of beta distributions derived from the demographic parameters used by Harris et al. (2006) to derive distributions of λ during 1983–2002 given our sampling uncertainty. Approximate 95% confidence intervals were 0.972–1.096 (assuming females with unresolved fates died) and 1.008–1.115 (with unresolved females censored at last contact). We used well-supported models of Haroldson et al. (2006) and Schwartz et al. (2006a,b,c) to assess the strength of correlations among demographic processes and the effect of omitting them in projection models. Incorporating correlations among demographic parameters yielded point estimates of λ that were nearly identical to those from the earlier model that omitted correlations, but yielded wider confidence intervals surrounding λ. Finally, we suggest that fitting linear and quadratic curves to the trend suggested by the estimated number of females with cubs in the ecosystem, and using AICc model weights to infer population sizes and λ provides an objective means to monitoring approximate population trajectories in addition to demographic analysis.

On the dynamics of the world demographic transition and financial-economic crises forecasts

NASA Astrophysics Data System (ADS)

Akaev, A.; Sadovnichy, V.; Korotayev, A.

2012-05-01

The article considers dynamic processes involving non-linear power-law behavior in such apparently diverse spheres, as demographic dynamics and dynamics of prices of highly liquid commodities such as oil and gold. All the respective variables exhibit features of explosive growth containing precursors indicating approaching phase transitions/catastrophes/crises. The first part of the article analyzes mathematical models of demographic dynamics that describe various scenarios of demographic development in the post-phase-transition period, including a model that takes the limitedness of the Earth carrying capacity into account. This model points to a critical point in the early 2050s, when the world population, after reaching its maximum value may decrease afterward stabilizing then at a certain stationary level. The article presents an analysis of the influence of the demographic transition (directly connected with the hyperexponential growth of the world population) on the global socioeconomic and geopolitical development. The second part deals with the phenomenon of explosive growth of prices of such highly liquid commodities as oil and gold. It is demonstrated that at present the respective processes could be regarded as precursors of waves of the global financial-economic crisis that will demand the change of the current global economic and political system. It is also shown that the moments of the start of the first and second waves of the current global crisis could have been forecasted with a model of accelerating log-periodic fluctuations superimposed over a power-law trend with a finite singularity developed by Didier Sornette and collaborators. With respect to the oil prices, it is shown that it was possible to forecast the 2008 crisis with a precision up to a month already in 2007. The gold price dynamics was used to calculate the possible time of the start of the second wave of the global crisis (July-August 2011); note that this forecast has turned out to be quite correct.

Demographic and Indication-Specific Characteristics Have Limited Association With Social Network Engagement: Evidence From 24,954 Members of Four Health Care Support Groups

PubMed Central

2017-01-01

Background Digital health social networks (DHSNs) are widespread, and the consensus is that they contribute to wellness by offering social support and knowledge sharing. The success of a DHSN is based on the number of participants and their consistent creation of externalities through the generation of new content. To promote network growth, it would be helpful to identify characteristics of superusers or actors who create value by generating positive network externalities. Objective The aim of the study was to investigate the feasibility of developing predictive models that identify potential superusers in real time. This study examined associations between posting behavior, 4 demographic variables, and 20 indication-specific variables. Methods Data were extracted from the custom structured query language (SQL) databases of 4 digital health behavior change interventions with DHSNs. Of these, 2 were designed to assist in the treatment of addictions (problem drinking and smoking cessation), and 2 for mental health (depressive disorder, panic disorder). To analyze posting behavior, 10 models were developed, and negative binomial regressions were conducted to examine associations between number of posts, and demographic and indication-specific variables. Results The DHSNs varied in number of days active (3658-5210), number of registrants (5049-52,396), number of actors (1085-8452), and number of posts (16,231-521,997). In the sample, all 10 models had low R2 values (.013-.086) with limited statistically significant demographic and indication-specific variables. Conclusions Very few variables were associated with social network engagement. Although some variables were statistically significant, they did not appear to be practically significant. Based on the large number of study participants, variation in DHSN theme, and extensive time-period, we did not find strong evidence that demographic characteristics or indication severity sufficiently explain the variability in number of posts per actor. Researchers should investigate alternative models that identify superusers or other individuals who create social network externalities. PMID:28213340

Disentangling the effects of climate and people on Sahel vegetation dynamics

NASA Astrophysics Data System (ADS)

Seaquist, J. W.; Hickler, T.; Eklundh, L.; Ardö, J.; Heumann, B. W.

2009-03-01

The Sahel belt of Africa has been the focus of intensive scientific research since the 1960s, spurred on by the chronic vulnerability of its population to recurring drought and the threat of long-term land degradation. But satellite sensors have recently shown that much of the region has experienced significant increases in photosynthetic activity since the early 1980s, thus re-energizing long-standing debates about the role that people play in shaping land surface status, and thus climate at regional scales. In this paper, we test the hypothesis that people have had a measurable impact on vegetation dynamics in the Sahel for the period 1982-2002. We compare potential natural vegetation dynamics predicted by a process-based ecosystem model with satellite-derived greenness observations, and map the agreement between the two across a geographic grid at a spatial resolution of 0.5°. As aggregated data-model agreement is very good, any local differences between the two could be due to human impact. We then relate this agreement metric to state-of-the-art data sets on demographics, pasture, and cropping. Our findings suggest that demographic and agricultural pressures in the Sahel are unable to account for differences between simulated and observed vegetation dynamics, even for the most densely populated areas. But we do identify a weak, positive correlation between data-model agreement and pasture intensity at the Sahel-wide level. This indicates that herding or grazing does not appreciably affect vegetation dynamics in the region. Either people have not had a significant impact on vegetation dynamics in the Sahel or the identification of a human "footprint" is precluded by inconsistent or subtle vegetation response to complex socio-environmental interactions, and/or limitations in the data used for this study. We do not exclude the possibility of a greater human influence on vegetation dynamics over the coming decades with changing land use.

The earliest settlers' antiquity and evolutionary history of Indian populations: evidence from M2 mtDNA lineage

PubMed Central

2008-01-01

Background The "out of Africa" model postulating single "southern route" dispersal posits arrival of "Anatomically Modern Human" to Indian subcontinent around 66–70 thousand years before present (kyBP). However the contributions and legacy of these earliest settlers in contemporary Indian populations, owing to the complex past population dynamics and later migrations has been an issue of controversy. The high frequency of mitochondrial lineage "M2" consistent with its greater age and distribution suggests that it may represent the phylogenetic signature of earliest settlers. Accordingly, we attempted to re-evaluate the impact and contribution of earliest settlers in shaping the genetic diversity and structure of contemporary Indian populations; using our newly sequenced 72 and 4 published complete mitochondrial genomes of this lineage. Results The M2 lineage, harbouring two deep rooting subclades M2a and M2b encompasses approximately one tenth of the mtDNA pool of studied tribes. The phylogeographic spread and diversity indices of M2 and its subclades among the tribes of different geographic regions and linguistic phyla were investigated in detail. Further the reconstructed demographic history of M2 lineage as a surrogate of earliest settlers' component revealed that the demographic events with pronounced regional variations had played pivotal role in shaping the complex net of populations phylogenetic relationship in Indian subcontinent. Conclusion Our results suggest that tribes of southern and eastern region along with Dravidian and Austro-Asiatic speakers of central India are the modern representatives of earliest settlers of subcontinent. The Last Glacial Maximum aridity and post LGM population growth mechanised some sort of homogeneity and redistribution of earliest settlers' component in India. The demic diffusion of agriculture and associated technologies around 3 kyBP, which might have marginalized hunter-gatherer, is coincidental with the decline of earliest settlers' population during this period. PMID:18691441

Contrasting effects of climate change on rabbit populations through reproduction.

PubMed

Tablado, Zulima; Revilla, Eloy

2012-01-01

Climate change is affecting many physical and biological processes worldwide. Anticipating its effects at the level of populations and species is imperative, especially for organisms of conservation or management concern. Previous studies have focused on estimating future species distributions and extinction probabilities directly from current climatic conditions within their geographical ranges. However, relationships between climate and population parameters may be so complex that to make these high-level predictions we need first to understand the underlying biological processes driving population size, as well as their individual response to climatic alterations. Therefore, the objective of this study is to investigate the influence that climate change may have on species population dynamics through altering breeding season. We used a mechanistic model based on drivers of rabbit reproductive physiology together with demographic simulations to show how future climate-driven changes in breeding season result in contrasting rabbit population trends across Europe. In the Iberian Peninsula, where rabbits are a native species of high ecological and economic value, breeding seasons will shorten and become more variable leading to population declines, higher extinction risk, and lower resilience to perturbations. Whereas towards north-eastern countries, rabbit numbers are expected to increase through longer and more stable reproductive periods, which augment the probability of new rabbit invasions in those areas. Our study reveals the type of mechanisms through which climate will cause alterations at the species level and emphasizes the need to focus on them in order to better foresee large-scale complex population trends. This is especially important in species like the European rabbit whose future responses may aggravate even further its dual keystone/pest problematic. Moreover, this approach allows us to predict not only distribution shifts but also future population status and growth, and to identify the demographic parameters on which to focus to mitigate global change effects.

Contrasting Effects of Climate Change on Rabbit Populations through Reproduction

PubMed Central

Tablado, Zulima; Revilla, Eloy

2012-01-01

Background Climate change is affecting many physical and biological processes worldwide. Anticipating its effects at the level of populations and species is imperative, especially for organisms of conservation or management concern. Previous studies have focused on estimating future species distributions and extinction probabilities directly from current climatic conditions within their geographical ranges. However, relationships between climate and population parameters may be so complex that to make these high-level predictions we need first to understand the underlying biological processes driving population size, as well as their individual response to climatic alterations. Therefore, the objective of this study is to investigate the influence that climate change may have on species population dynamics through altering breeding season. Methodology/Principal Findings We used a mechanistic model based on drivers of rabbit reproductive physiology together with demographic simulations to show how future climate-driven changes in breeding season result in contrasting rabbit population trends across Europe. In the Iberian Peninsula, where rabbits are a native species of high ecological and economic value, breeding seasons will shorten and become more variable leading to population declines, higher extinction risk, and lower resilience to perturbations. Whereas towards north-eastern countries, rabbit numbers are expected to increase through longer and more stable reproductive periods, which augment the probability of new rabbit invasions in those areas. Conclusions/Significance Our study reveals the type of mechanisms through which climate will cause alterations at the species level and emphasizes the need to focus on them in order to better foresee large-scale complex population trends. This is especially important in species like the European rabbit whose future responses may aggravate even further its dual keystone/pest problematic. Moreover, this approach allows us to predict not only distribution shifts but also future population status and growth, and to identify the demographic parameters on which to focus to mitigate global change effects. PMID:23152836

Molecular epidemiology of Campylobacter jejuni infection in Israel-a nationwide study.

PubMed

Weinberger, M; Moran-Gilad, J; Rokney, A; Davidov, Y; Agmon, V; Peretz, C; Valinsky, L

2016-12-01

The incidence of Campylobacter infection in Israel, particularly among children <2 years of age, has risen over the last decade and became one of the highest among industrialized countries. This study explored the molecular epidemiology of Campylobacter jejuni in Israel over a decade (2003-2012) using multilocus sequence typing (MLST) combined with demographic metadata. Representative clinical isolates (438) from a large national repository together with selected veterinary isolates (74) were subject to MLST. The distribution of age groups, ethnicity and clinical source across various genotypes was evaluated using Poisson modelling. The 512 studied isolates were assigned 126 distinct sequence types (STs) (18.8% novel STs) grouped into 21 clonal complexes (CCs). Most human, poultry and bovine STs clustered together in the leading CCs. Three dominant STs (ST21, ST6608, ST4766) were detected only since 2006. Patients infected with the leading CCs were similarly distributed along densely populated areas. The frequency of blood isolates was higher in patients infected with CC353 (relative rate (RR)=2.0, 95% CI 1.03-3.9, adjusted p value (adj.p) 0.047) and CC42 (RR=4.4, 95% CI 1.7-11.6, adj.p 0.018) and lower with CC257 (RR=0.3, 95% CI 0.1-0.9, adj. p 0.047). The distribution of age groups and ethnicity also varied across the leading CCs. In conclusion, C. jejuni isolates in a national sample appeared highly diverse with a high proportion of new STs. Phylogenic analysis was compatible with poultry and cattle as possible food sources of clinical infection. Demographic characteristics of the infected patients coupled with strain invasiveness across different genotypes revealed a complex epidemiology of C. jejuni transmission in Israel. Copyright © 2016 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Socio-demographics, spirituality, and quality of life among community-dwelling and institutionalized older adults: A structural equation model.

PubMed

Soriano, Christian Albert F; Sarmiento, Winona D; Songco, Francis Justin G; Macindo, John Rey B; Conde, Alita R

2016-01-01

The increasing life expectancy of the population prompts an array of health conditions that impair an older adults' quality of life (QoL). Although demographics and spirituality have been associated with QoL, limited literature elucidated the exact mechanisms of their interactions, especially in a culturally-diverse country like Philippines. Hence, this study determined the relationship among socio-demographics, spirituality, and QoL of Filipino older adults in a community and institutional setting. A predictive-correlational study among 200 randomly-selected community-dwelling and institutionalized older adults was conducted, with a 99% power and a medium effect size. Data were collected using a three-part questionnaire from September to November 2015. The questionnaire was composed of the robotfoto, Spirituality Assessment Scale, and modified Older People's Quality of Life which assessed socio-demographics, spirituality, and QoL. Analysis showed that institutionalization in a nursing home positively and negatively affected spirituality and QoL, generating an acceptable model (χ(2)/df=2.12, RMSEA=0.08, and CFI=0.95). The negative direct effect of institutionalization on social relationship, leisure, & social activities QoL (β=-0.42, p<0.01) also initiates a cascade of indirect negative effects on both spirituality and QoL dimensions. The development of a structural model illustrating the interrelationship of socio-demographics, spirituality, and QoL helps healthcare professionals in predicting facets of spirituality and QoL that can be compromised by living in a nursing home. This understanding provides impetus in evaluating and refining geriatric healthcare programs, policies, and protocols to render individualized, holistic care in a socially-cohesive environment among older adults. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Population structure and demographic history of a tropical lowland rainforest tree species Shorea parvifolia (Dipterocarpaceae) from Southeastern Asia.

PubMed

Iwanaga, Hiroko; Teshima, Kosuke M; Khatab, Ismael A; Inomata, Nobuyuki; Finkeldey, Reiner; Siregar, Iskandar Z; Siregar, Ulfah J; Szmidt, Alfred E

2012-07-01

Distribution of tropical rainforests in Southeastern Asia has changed over geo-logical time scale, due to movement of tectonic plates and/or global climatic changes. Shorea parvifolia is one of the most common tropical lowland rainforest tree species in Southeastern Asia. To infer population structure and demographic history of S. parvifolia, as indicators of temporal changes in the distribution and extent of tropical rainforest in this region, we studied levels and patterns of nucleotide polymorphism in the following five nuclear gene regions: GapC, GBSSI, PgiC, SBE2, and SODH. Seven populations from peninsular Malaysia, Sumatra, and eastern Borneo were included in the analyses. STRUCTURE analysis revealed that the investigated populations are divided into two groups: Sumatra-Malay and Borneo. Furthermore, each group contained one admixed population. Under isolation with migration model, divergence of the two groups was estimated to occur between late Pliocene (2.6 MYA) and middle Pleistocene (0.7 MYA). The log-likelihood ratio tests of several demographic models strongly supported model with population expansion and low level of migration after divergence of the Sumatra-Malay and Borneo groups. The inferred demographic history of S. parvifolia suggested the presence of a scarcely forested land bridge on the Sunda Shelf during glacial periods in the Pleistocene and predominance of tropical lowland rainforest at least in Sumatra and eastern Borneo.

DESCARTES' RULE OF SIGNS AND THE IDENTIFIABILITY OF POPULATION DEMOGRAPHIC MODELS FROM GENOMIC VARIATION DATA.

PubMed

Bhaskar, Anand; Song, Yun S

2014-01-01

The sample frequency spectrum (SFS) is a widely-used summary statistic of genomic variation in a sample of homologous DNA sequences. It provides a highly efficient dimensional reduction of large-scale population genomic data and its mathematical dependence on the underlying population demography is well understood, thus enabling the development of efficient inference algorithms. However, it has been recently shown that very different population demographies can actually generate the same SFS for arbitrarily large sample sizes. Although in principle this nonidentifiability issue poses a thorny challenge to statistical inference, the population size functions involved in the counterexamples are arguably not so biologically realistic. Here, we revisit this problem and examine the identifiability of demographic models under the restriction that the population sizes are piecewise-defined where each piece belongs to some family of biologically-motivated functions. Under this assumption, we prove that the expected SFS of a sample uniquely determines the underlying demographic model, provided that the sample is sufficiently large. We obtain a general bound on the sample size sufficient for identifiability; the bound depends on the number of pieces in the demographic model and also on the type of population size function in each piece. In the cases of piecewise-constant, piecewise-exponential and piecewise-generalized-exponential models, which are often assumed in population genomic inferences, we provide explicit formulas for the bounds as simple functions of the number of pieces. Lastly, we obtain analogous results for the "folded" SFS, which is often used when there is ambiguity as to which allelic type is ancestral. Our results are proved using a generalization of Descartes' rule of signs for polynomials to the Laplace transform of piecewise continuous functions.

DESCARTES’ RULE OF SIGNS AND THE IDENTIFIABILITY OF POPULATION DEMOGRAPHIC MODELS FROM GENOMIC VARIATION DATA1

PubMed Central

Bhaskar, Anand; Song, Yun S.

2016-01-01

The sample frequency spectrum (SFS) is a widely-used summary statistic of genomic variation in a sample of homologous DNA sequences. It provides a highly efficient dimensional reduction of large-scale population genomic data and its mathematical dependence on the underlying population demography is well understood, thus enabling the development of efficient inference algorithms. However, it has been recently shown that very different population demographies can actually generate the same SFS for arbitrarily large sample sizes. Although in principle this nonidentifiability issue poses a thorny challenge to statistical inference, the population size functions involved in the counterexamples are arguably not so biologically realistic. Here, we revisit this problem and examine the identifiability of demographic models under the restriction that the population sizes are piecewise-defined where each piece belongs to some family of biologically-motivated functions. Under this assumption, we prove that the expected SFS of a sample uniquely determines the underlying demographic model, provided that the sample is sufficiently large. We obtain a general bound on the sample size sufficient for identifiability; the bound depends on the number of pieces in the demographic model and also on the type of population size function in each piece. In the cases of piecewise-constant, piecewise-exponential and piecewise-generalized-exponential models, which are often assumed in population genomic inferences, we provide explicit formulas for the bounds as simple functions of the number of pieces. Lastly, we obtain analogous results for the “folded” SFS, which is often used when there is ambiguity as to which allelic type is ancestral. Our results are proved using a generalization of Descartes’ rule of signs for polynomials to the Laplace transform of piecewise continuous functions. PMID:28018011

Modeling Contagion Through Social Networks to Explain and Predict Gunshot Violence in Chicago, 2006 to 2014.

PubMed

Green, Ben; Horel, Thibaut; Papachristos, Andrew V

2017-03-01

Every day in the United States, more than 200 people are murdered or assaulted with a firearm. Little research has considered the role of interpersonal ties in the pathways through which gun violence spreads. To evaluate the extent to which the people who will become subjects of gun violence can be predicted by modeling gun violence as an epidemic that is transmitted between individuals through social interactions. This study was an epidemiological analysis of a social network of individuals who were arrested during an 8-year period in Chicago, Illinois, with connections between people who were arrested together for the same offense. Modeling of the spread of gunshot violence over the network was assessed using a probabilistic contagion model that assumed individuals were subject to risks associated with being arrested together, in addition to demographic factors, such as age, sex, and neighborhood residence. Participants represented a network of 138 163 individuals who were arrested between January 1, 2006, and March 31, 2014 (29.9% of all individuals arrested in Chicago during this period), 9773 of whom were subjects of gun violence. Individuals were on average 27 years old at the midpoint of the study, predominantly male (82.0%) and black (75.6%), and often members of a gang (26.2%). Explanation and prediction of becoming a subject of gun violence (fatal or nonfatal) using epidemic models based on person-to-person transmission through a social network. Social contagion accounted for 63.1% of the 11 123 gunshot violence episodes; subjects of gun violence were shot on average 125 days after their infector (the person most responsible for exposing the subject to gunshot violence). Some subjects of gun violence were shot more than once. Models based on both social contagion and demographics performed best; when determining the 1.0% of people (n = 1382) considered at highest risk to be shot each day, the combined model identified 728 subjects of gun violence (6.5%) compared with 475 subjects of gun violence (4.3%) for the demographics model (53.3% increase) and 589 subjects of gun violence (5.3%) for the social contagion model (23.6% increase). Gunshot violence follows an epidemic-like process of social contagion that is transmitted through networks of people by social interactions. Violence prevention efforts that account for social contagion, in addition to demographics, have the potential to prevent more shootings than efforts that focus on only demographics.

Prospective Impact of Illness Uncertainty on Outcomes in Chronic Lung Disease

PubMed Central

Hoth, Karin F.; Wamboldt, Frederick S.; Strand, Matthew; Ford, Dee W.; Sandhaus, Robert A.; Strange, Charlie; Bekelman, David; Holm, Kristen E.

2014-01-01

Objective To determine which aspect of illness uncertainty (i.e., ambiguity or complexity) has a stronger association with psychological and clinical outcomes over a two year period among individuals with a genetic subtype of chronic obstructive pulmonary disease (COPD). Ambiguity reflects uncertainty about physical cues and symptoms, and complexity reflects uncertainty about treatment and the medical system. Methods 407 individuals with alpha-1 antitrypsin deficiency-associated COPD completed questionnaires at baseline, 1- and 2-year follow-up. Uncertainty was measured using the Mishel Uncertainty in Illness Scale. Outcomes were measured using the Hospital Anxiety and Depression Scale, St. George's Respiratory Questionnaire, and MMRC Dyspnea Scale. Ambiguity and complexity were examined as predictors of depressive symptoms, anxiety, quality of life, and breathlessness using linear mixed models adjusting for demographic and health characteristics. Results Ambiguity was associated with more depressive symptoms (b = 0.09, SE = 0.02, p < 0.001) and anxiety (b = 0.13, SE = 0.02, p < 0.001), worse quality of life (b = 0.57, SE = 0.10, p < 0.001), and more breathlessness (b = 0.02, SE = 0.006, p < 0.001). Complexity did not have an independent effect on any outcome. Interactions between ambiguity and time since diagnosis were not statistically significant. Conclusions Ambiguity was prospectively associated with worse mood, quality of life, and breathlessness. Thus, ambiguity should be targeted in psychosocial interventions. Time since diagnosis did not affect the association between ambiguity and outcomes, suggesting that the impact of ambiguity is equally strong throughout the course of COPD. PMID:23772888

An Agent-Based Model of Private Woodland Owner Management Behavior Using Social Interactions, Information Flow, and Peer-To-Peer Networks

PubMed Central

Huff, Emily Silver; Leahy, Jessica E.; Hiebeler, David; Weiskittel, Aaron R.; Noblet, Caroline L.

2015-01-01

Privately owned woodlands are an important source of timber and ecosystem services in North America and worldwide. Impacts of management on these ecosystems and timber supply from these woodlands are difficult to estimate because complex behavioral theory informs the owner’s management decisions. The decision-making environment consists of exogenous market factors, internal cognitive processes, and social interactions with fellow landowners, foresters, and other rural community members. This study seeks to understand how social interactions, information flow, and peer-to-peer networks influence timber harvesting behavior using an agent-based model. This theoretical model includes forested polygons in various states of ‘harvest readiness’ and three types of agents: forest landowners, foresters, and peer leaders (individuals trained in conservation who use peer-to-peer networking). Agent rules, interactions, and characteristics were parameterized with values from existing literature and an empirical survey of forest landowner attitudes, intentions, and demographics. The model demonstrates that as trust in foresters and peer leaders increases, the percentage of the forest that is harvested sustainably increases. Furthermore, peer leaders can serve to increase landowner trust in foresters. Model output and equations will inform forest policy and extension/outreach efforts. The model also serves as an important testing ground for new theories of landowner decision making and behavior. PMID:26562429

Model-based and Model-free Machine Learning Techniques for Diagnostic Prediction and Classification of Clinical Outcomes in Parkinson's Disease.

PubMed

Gao, Chao; Sun, Hanbo; Wang, Tuo; Tang, Ming; Bohnen, Nicolaas I; Müller, Martijn L T M; Herman, Talia; Giladi, Nir; Kalinin, Alexandr; Spino, Cathie; Dauer, William; Hausdorff, Jeffrey M; Dinov, Ivo D

2018-05-08

In this study, we apply a multidisciplinary approach to investigate falls in PD patients using clinical, demographic and neuroimaging data from two independent initiatives (University of Michigan and Tel Aviv Sourasky Medical Center). Using machine learning techniques, we construct predictive models to discriminate fallers and non-fallers. Through controlled feature selection, we identified the most salient predictors of patient falls including gait speed, Hoehn and Yahr stage, postural instability and gait difficulty-related measurements. The model-based and model-free analytical methods we employed included logistic regression, random forests, support vector machines, and XGboost. The reliability of the forecasts was assessed by internal statistical (5-fold) cross validation as well as by external out-of-bag validation. Four specific challenges were addressed in the study: Challenge 1, develop a protocol for harmonizing and aggregating complex, multisource, and multi-site Parkinson's disease data; Challenge 2, identify salient predictive features associated with specific clinical traits, e.g., patient falls; Challenge 3, forecast patient falls and evaluate the classification performance; and Challenge 4, predict tremor dominance (TD) vs. posture instability and gait difficulty (PIGD). Our findings suggest that, compared to other approaches, model-free machine learning based techniques provide a more reliable clinical outcome forecasting of falls in Parkinson's patients, for example, with a classification accuracy of about 70-80%.

Demand-supply dynamics in tourism systems: A spatio-temporal GIS analysis. The Alberta ski industry case study

NASA Astrophysics Data System (ADS)

Bertazzon, Stefania

The present research focuses on the interaction of supply and demand of down-hill ski tourism in the province of Alberta. The main hypothesis is that the demand for skiing depends on the socio-economic and demographic characteristics of the population living in the province and outside it. A second, consequent hypothesis is that the development of ski resorts (supply) is a response to the demand for skiing. From the latter derives the hypothesis of a dynamic interaction between supply (ski resorts) and demand (skiers). Such interaction occurs in space, within a range determined by physical distance and the means available to overcome it. The above hypotheses implicitly define interactions that take place in space and evolve over time. The hypotheses are tested by temporal, spatial, and spatio-temporal regression models, using the best available data and the latest commercially available software. The main purpose of this research is to explore analytical techniques to model spatial, temporal, and spatio-temporal dynamics in the context of regional science. The completion of the present research has produced more significant contributions than was originally expected. Many of the unexpected contributions resulted from theoretical and applied needs arising from the application of spatial regression models. Spatial regression models are a new and largely under-applied technique. The models are fairly complex and a considerable amount of preparatory work is needed, prior to their specification and estimation. Most of this work is specific to the field of application. The originality of the solutions devised is increased by the lack of applications in the field of tourism. The scarcity of applications in other fields adds to their value for other applications. The estimation of spatio-temporal models has been only partially attained in the present research. This apparent limitation is due to the novelty and complexity of the analytical methods applied. This opens new directions for further work in the field of spatial analysis, in conjunction with the development of specific software.

Reconstructing shifts in vital rates driven by long-term environmental change: a new demographic method based on readily available data.

PubMed

González, Edgar J; Martorell, Carlos

2013-07-01

Frequently, vital rates are driven by directional, long-term environmental changes. Many of these are of great importance, such as land degradation, climate change, and succession. Traditional demographic methods assume a constant or stationary environment, and thus are inappropriate to analyze populations subject to these changes. They also require repeat surveys of the individuals as change unfolds. Methods for reconstructing such lengthy processes are needed. We present a model that, based on a time series of population size structures and densities, reconstructs the impact of directional environmental changes on vital rates. The model uses integral projection models and maximum likelihood to identify the rates that best reconstructs the time series. The procedure was validated with artificial and real data. The former involved simulated species with widely different demographic behaviors. The latter used a chronosequence of populations of an endangered cactus subject to increasing anthropogenic disturbance. In our simulations, the vital rates and their change were always reconstructed accurately. Nevertheless, the model frequently produced alternative results. The use of coarse knowledge of the species' biology (whether vital rates increase or decrease with size or their plausible values) allowed the correct rates to be identified with a 90% success rate. With real data, the model correctly reconstructed the effects of disturbance on vital rates. These effects were previously known from two populations for which demographic data were available. Our procedure seems robust, as the data violated several of the model's assumptions. Thus, time series of size structures and densities contain the necessary information to reconstruct changing vital rates. However, additional biological knowledge may be required to provide reliable results. Because time series of size structures and densities are available for many species or can be rapidly generated, our model can contribute to understand populations that face highly pressing environmental problems.

Reconstructing shifts in vital rates driven by long-term environmental change: a new demographic method based on readily available data

PubMed Central

González, Edgar J; Martorell, Carlos

2013-01-01

Frequently, vital rates are driven by directional, long-term environmental changes. Many of these are of great importance, such as land degradation, climate change, and succession. Traditional demographic methods assume a constant or stationary environment, and thus are inappropriate to analyze populations subject to these changes. They also require repeat surveys of the individuals as change unfolds. Methods for reconstructing such lengthy processes are needed. We present a model that, based on a time series of population size structures and densities, reconstructs the impact of directional environmental changes on vital rates. The model uses integral projection models and maximum likelihood to identify the rates that best reconstructs the time series. The procedure was validated with artificial and real data. The former involved simulated species with widely different demographic behaviors. The latter used a chronosequence of populations of an endangered cactus subject to increasing anthropogenic disturbance. In our simulations, the vital rates and their change were always reconstructed accurately. Nevertheless, the model frequently produced alternative results. The use of coarse knowledge of the species' biology (whether vital rates increase or decrease with size or their plausible values) allowed the correct rates to be identified with a 90% success rate. With real data, the model correctly reconstructed the effects of disturbance on vital rates. These effects were previously known from two populations for which demographic data were available. Our procedure seems robust, as the data violated several of the model's assumptions. Thus, time series of size structures and densities contain the necessary information to reconstruct changing vital rates. However, additional biological knowledge may be required to provide reliable results. Because time series of size structures and densities are available for many species or can be rapidly generated, our model can contribute to understand populations that face highly pressing environmental problems. PMID:23919169

The relative importance of intrinsic and extrinsic drivers to population growth vary among local populations of Greater Sage-Grouse: An integrated population modeling approach

USGS Publications Warehouse

Coates, Peter S.; Prochazka, Brian G.; Ricca, Mark A.; Halstead, Brian J.; Casazza, Michael L.; Blomberg, Erik J.; Brussee, Brianne E.; Wiechman, Lief; Tebbenkamp, Joel; Gardner, Scott C.; Reese, Kerry P.

2018-01-01

Consideration of ecological scale is fundamental to understanding and managing avian population growth and decline. Empirically driven models for population dynamics and demographic processes across multiple spatial scales can be powerful tools to help guide conservation actions. Integrated population models (IPMs) provide a framework for better parameter estimation by unifying multiple sources of data (e.g., count and demographic data). Hierarchical structure within such models that include random effects allow for varying degrees of data sharing across different spatiotemporal scales. We developed an IPM to investigate Greater Sage-Grouse (Centrocercus urophasianus) on the border of California and Nevada, known as the Bi-State Distinct Population Segment. Our analysis integrated 13 years of lek count data (n > 2,000) and intensive telemetry (VHF and GPS; n > 350 individuals) data across 6 subpopulations. Specifically, we identified the most parsimonious models among varying random effects and density-dependent terms for each population vital rate (e.g., nest survival). Using a joint likelihood process, we integrated the lek count data with the demographic models to estimate apparent abundance and refine vital rate parameter estimates. To investigate effects of climatic conditions, we extended the model to fit a precipitation covariate for instantaneous rate of change (r). At a metapopulation extent (i.e. Bi-State), annual population rate of change λ (er) did not favor an overall increasing or decreasing trend through the time series. However, annual changes in λ were driven by changes in precipitation (one-year lag effect). At subpopulation extents, we identified substantial variation in λ and demographic rates. One subpopulation clearly decoupled from the trend at the metapopulation extent and exhibited relatively high risk of extinction as a result of low egg fertility. These findings can inform localized, targeted management actions for specific areas, and status of the species for the larger Bi-State.

Assessing psychological well-being: a holistic investigation of NHS employees.

PubMed

Loretto, W; Popham, F; Platt, S; Pavis, S; Hardy, G; MacLeod, L; Gibbs, J

2005-10-01

A substantial body of research has investigated the effects of work on the psychological well-being of employees. However, there has been little assessment of the ways in which workplace factors (such as job demands, working conditions, inter-personal relations and workplace change) interact with personal factors (such as work-life balance, family circumstances, key personality traits or demographic characteristics) to affect psychological health. This article reports findings from a study which aimed to construct and test a comprehensive model of the influences on employee well-being within the UK National Health Service (NHS). The results show that psychological well-being is influenced by a complex array of personal, environmental and work factors. A key finding is that there are clear associations between workplace change and well-being and between work-life (im)balance and well-being. These effects appear to be independent of one another and therefore require separate attention from managers and employers.

Teacher Efficacy, Work Engagement, and Social Support Among Chinese Special Education School Teachers

PubMed Central

Minghui, Lu; Lei, Hao; Xiaomeng, Chen; Potměšilc, Miloň

2018-01-01

This paper investigates the relationship between teacher efficacy and socio-demographic factors, work engagement, and social support among Chinese special education school teachers. The sample comprised 1,027 special education school teachers in mainland China. The Teachers’ Sense of Efficacy Scale, the Multi-Dimensional Scale of Perceived Social Support, and the Utrecht Work Engagement Scale were used for data collection. Correlation analysis revealed that social support, work engagement, and teacher efficacy were significantly correlated with each other. Additionally, gender, years of experience, and monthly salary were significant predictors of teacher efficacy. Furthermore, structural equation modeling analysis showed that social support exerted its indirect effect on teacher efficacy through the mediation of work engagement. The findings of this study provide a new perspective on the complex association between social support and teacher efficacy. The explanations and limitations of these findings are discussed. PMID:29867634

The impact of climate change on smallholder and subsistence agriculture.

PubMed

Morton, John F

2007-12-11

Some of the most important impacts of global climate change will be felt among the populations, predominantly in developing countries, referred to as "subsistence" or "smallholder" farmers. Their vulnerability to climate change comes both from being predominantly located in the tropics, and from various socioeconomic, demographic, and policy trends limiting their capacity to adapt to change. However, these impacts will be difficult to model or predict because of (i) the lack of standardised definitions of these sorts of farming system, and therefore of standard data above the national level, (ii) intrinsic characteristics of these systems, particularly their complexity, their location-specificity, and their integration of agricultural and nonagricultural livelihood strategies, and (iii) their vulnerability to a range of climate-related and other stressors. Some recent work relevant to these farming systems is reviewed, a conceptual framework for understanding the diverse forms of impacts in an integrated manner is proposed, and future research needs are identified.

Profiles and portfolios of adolescent school-based extracurricular activity participation.

PubMed

Feldman, A F; Matjasko, J L

2007-04-01

The current study presented a new description of adolescent school-based activity participation, in the form of mutually exclusive activity portfolios, and described the kinds of youth that participate in each portfolio. These portfolios included (1) Sports Only, (2) Academics Only, (3) School Only, (4) Performance Only, (5) Multiple Activities, and (6) Non-Participation. Findings indicated that youth demographic characteristics and school size differentiated between different kinds of activity participation as well as nonparticipation. More detailed activity portfolios were also identified that were complex and demonstrate the difficulty of examining participation beyond larger, more inclusive groupings. The Multiple Activity portfolio emerged as a unique group worthy of further examination. Characteristics of non-participators included: lower socioeconomic status, lower grades, and attended larger schools. Hispanic adolescents were also less likely to participate in school-based extracurricular activities. Findings from this study inform ecological models of adolescent development as well as school and social policy.

Development of a Suite of Analytical Tools for Energy and Water Infrastructure Knowledge Discovery

NASA Astrophysics Data System (ADS)

Morton, A.; Piburn, J.; Stewart, R.; Chandola, V.

2017-12-01

Energy and water generation and delivery systems are inherently interconnected. With demand for energy growing, the energy sector is experiencing increasing competition for water. With increasing population and changing environmental, socioeconomic, and demographic scenarios, new technology and investment decisions must be made for optimized and sustainable energy-water resource management. This also requires novel scientific insights into the complex interdependencies of energy-water infrastructures across multiple space and time scales. To address this need, we've developed a suite of analytical tools to support an integrated data driven modeling, analysis, and visualization capability for understanding, designing, and developing efficient local and regional practices related to the energy-water nexus. This work reviews the analytical capabilities available along with a series of case studies designed to demonstrate the potential of these tools for illuminating energy-water nexus solutions and supporting strategic (federal) policy decisions.

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