A NEO population generation and observation simulation software tool

NASA Astrophysics Data System (ADS)

Müller, Sven; Gelhaus, Johannes; Hahn, Gerhard; Franco, Raffaella

One of the main targets of ESA's Space Situational Awareness (SSA) program is to build a wide knowledge base about objects that can potentially harm Earth (Near-Earth Objects, NEOs). An important part of this effort is to create the Small Bodies Data Centre (SBDC) which is going to aggregate measurement data from a fully-integrated NEO observation sensor network. Until this network is developed, artificial NEO measurement data is needed in order to validate SBDC algorithms. Moreover, to establish a functioning NEO observation sensor network, it has to be determined where to place sensors, what technical requirements have to be met in order to be able to detect NEOs and which observation strategies work the best. Because of this, a sensor simulation software was needed. This paper presents a software tool which allows users to create and analyse NEO populations and to simulate and analyse population observations. It is a console program written in Fortran and comes with a Graphical User Interface (GUI) written in Java and C. The tool can be distinguished into the components ``Population Generator'' and ``Observation Simulator''. The Population Generator component is responsible for generating and analysing a NEO population. Users can choose between creating fictitious (random) and synthetic populations. The latter are based on one of two models describing the orbital and size distribution of observed NEOs: The existing socalled ``Bottke Model'' (Bottke et al. 2000, 2002) and the new ``Granvik Model'' (Granvik et al. 2014, in preparation) which has been developed in parallel to the tool. Generated populations can be analysed by defining 2D, 3D and scatter plots using various NEO attributes. As a result, the tool creates the appropiate files for the plotting tool ``gnuplot''. The tool's Observation Simulator component yields the Observation Simulation and Observation Analysis functions. Users can define sensor systems using ground- or space-based locations as well as optical or radar sensors and simulate observation campaigns. The tool outputs field-of-view crossings and actual detections of the selected NEO population objects. Using the Observation Analysis users are able to process and plot the results of the Observation Simulation. In order to enable end-users to handle the tool in a user-intuitive and comfortable way, a GUI has been created based on the modular Eclipse Rich Client Platform (RCP) technology. Through the GUI users can easily enter input data for the tool, execute it and view its output data in a clear way. Additionally, the GUI runs gnuplot to create plot pictures and presents them to the user. Furthermore, users can create projects to organise executions of the tool.

An empirical model for estimating annual consumption by freshwater fish populations

USGS Publications Warehouse

Liao, H.; Pierce, C.L.; Larscheid, J.G.

2005-01-01

Population consumption is an important process linking predator populations to their prey resources. Simple tools are needed to enable fisheries managers to estimate population consumption. We assembled 74 individual estimates of annual consumption by freshwater fish populations and their mean annual population size, 41 of which also included estimates of mean annual biomass. The data set included 14 freshwater fish species from 10 different bodies of water. From this data set we developed two simple linear regression models predicting annual population consumption. Log-transformed population size explained 94% of the variation in log-transformed annual population consumption. Log-transformed biomass explained 98% of the variation in log-transformed annual population consumption. We quantified the accuracy of our regressions and three alternative consumption models as the mean percent difference from observed (bioenergetics-derived) estimates in a test data set. Predictions from our population-size regression matched observed consumption estimates poorly (mean percent difference = 222%). Predictions from our biomass regression matched observed consumption reasonably well (mean percent difference = 24%). The biomass regression was superior to an alternative model, similar in complexity, and comparable to two alternative models that were more complex and difficult to apply. Our biomass regression model, log10(consumption) = 0.5442 + 0.9962??log10(biomass), will be a useful tool for fishery managers, enabling them to make reasonably accurate annual population consumption predictions from mean annual biomass estimates. ?? Copyright by the American Fisheries Society 2005.

Human-like, population-level specialization in the manufacture of pandanus tools by New Caledonian crows Corvus moneduloides.

PubMed Central

Hunt, G R

2000-01-01

The main way of gaining insight into the behaviour and neurological faculties of our early ancestors is to study artefactual evidence for the making and use of tools, but this places severe constraints on what knowledge can be obtained. New Caledonian crows, however, offer a potential analogous model system for learning about these difficult-to-establish aspects of prehistoric humans. I found new evidence of human-like specialization in crows' manufacture of hook tools from pandanus leaves: functional lateralization or 'handedness' and the shaping of these tools to a rule system. These population-level features are unprecedented in the tool behaviour of free-living non-humans and provide the first demonstration that a population bias for handedness in tool-making and the shaping of tools to rule systems are not concomitant with symbolic thought and language. It is unknown how crows obtain their tool behaviour. Nevertheless, at the least they can be studied in order to learn about the neuropsychology associated with early specialized and/or advanced population features in tool-making such as hook use, handedness and the shaping of tools to rule systems. PMID:10722223

Dynamics of buckbrush populations under simulated forest restoration alternatives

Treesearch

David W. Huffman; Margaret M. Moore

2008-01-01

Plant population models are valuable tools for assessing ecological tradeoffs between forest management approaches. In addition, these models can provide insight on plant life history patterns and processes important for persistence and recovery of populations in changing environments. In this study, we evaluated a set of ecological restoration alternatives for their...

Dynamics of buckbrush populations under simulated forest restoration alternatives (P-53)

Treesearch

David W. Huffman; Margaret M. Moore

2008-01-01

Plant population models are valuable tools for assessing ecological tradeoffs between forest management approaches. In addition, these models can provide insight on plant life history patterns and processes important for persistence and recovery of populations in changing environments. In this study, we evaluated a set of ecological restoration alternatives for their...

FRED (a Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations.

PubMed

Grefenstette, John J; Brown, Shawn T; Rosenfeld, Roni; DePasse, Jay; Stone, Nathan T B; Cooley, Phillip C; Wheaton, William D; Fyshe, Alona; Galloway, David D; Sriram, Anuroop; Guclu, Hasan; Abraham, Thomas; Burke, Donald S

2013-10-08

Mathematical and computational models provide valuable tools that help public health planners to evaluate competing health interventions, especially for novel circumstances that cannot be examined through observational or controlled studies, such as pandemic influenza. The spread of diseases like influenza depends on the mixing patterns within the population, and these mixing patterns depend in part on local factors including the spatial distribution and age structure of the population, the distribution of size and composition of households, employment status and commuting patterns of adults, and the size and age structure of schools. Finally, public health planners must take into account the health behavior patterns of the population, patterns that often vary according to socioeconomic factors such as race, household income, and education levels. FRED (a Framework for Reconstructing Epidemic Dynamics) is a freely available open-source agent-based modeling system based closely on models used in previously published studies of pandemic influenza. This version of FRED uses open-access census-based synthetic populations that capture the demographic and geographic heterogeneities of the population, including realistic household, school, and workplace social networks. FRED epidemic models are currently available for every state and county in the United States, and for selected international locations. State and county public health planners can use FRED to explore the effects of possible influenza epidemics in specific geographic regions of interest and to help evaluate the effect of interventions such as vaccination programs and school closure policies. FRED is available under a free open source license in order to contribute to the development of better modeling tools and to encourage open discussion of modeling tools being used to evaluate public health policies. We also welcome participation by other researchers in the further development of FRED.

Master Middle Ware: A Tool to Integrate Water Resources and Fish Population Dynamics Models

NASA Astrophysics Data System (ADS)

Yi, S.; Sandoval Solis, S.; Thompson, L. C.; Kilduff, D. P.

2017-12-01

Linking models that investigate separate components of ecosystem processes has the potential to unify messages regarding management decisions by evaluating potential trade-offs in a cohesive framework. This project aimed to improve the ability of riparian resource managers to forecast future water availability conditions and resultant fish habitat suitability, in order to better inform their management decisions. To accomplish this goal, we developed a middleware tool that is capable of linking and overseeing the operations of two existing models, a water resource planning tool Water Evaluation and Planning (WEAP) model and a habitat-based fish population dynamics model (WEAPhish). First, we designed the Master Middle Ware (MMW) software in Visual Basic for Application® in one Excel® file that provided a familiar framework for both data input and output Second, MMW was used to link and jointly operate WEAP and WEAPhish, using Visual Basic Application (VBA) macros to implement system level calls to run the models. To demonstrate the utility of this approach, hydrological, biological, and middleware model components were developed for the Butte Creek basin. This tributary of the Sacramento River, California is managed for both hydropower and the persistence of a threatened population of spring-run Chinook salmon (Oncorhynchus tschawytscha). While we have demonstrated the use of MMW for a particular watershed and fish population, MMW can be customized for use with different rivers and fish populations, assuming basic data requirements are met. This model integration improves on ad hoc linkages for managing data transfer between software programs by providing a consistent, user-friendly, and familiar interface across different model implementations. Furthermore, the data-viewing capabilities of MMW facilitate the rapid interpretation of model results by hydrologists, fisheries biologists, and resource managers, in order to accelerate learning and management decision making.

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.

A review of statistical updating methods for clinical prediction models.

PubMed

Su, Ting-Li; Jaki, Thomas; Hickey, Graeme L; Buchan, Iain; Sperrin, Matthew

2018-01-01

A clinical prediction model is a tool for predicting healthcare outcomes, usually within a specific population and context. A common approach is to develop a new clinical prediction model for each population and context; however, this wastes potentially useful historical information. A better approach is to update or incorporate the existing clinical prediction models already developed for use in similar contexts or populations. In addition, clinical prediction models commonly become miscalibrated over time, and need replacing or updating. In this article, we review a range of approaches for re-using and updating clinical prediction models; these fall in into three main categories: simple coefficient updating, combining multiple previous clinical prediction models in a meta-model and dynamic updating of models. We evaluated the performance (discrimination and calibration) of the different strategies using data on mortality following cardiac surgery in the United Kingdom: We found that no single strategy performed sufficiently well to be used to the exclusion of the others. In conclusion, useful tools exist for updating existing clinical prediction models to a new population or context, and these should be implemented rather than developing a new clinical prediction model from scratch, using a breadth of complementary statistical methods.

Matrix population models as a tool in development of habitat models

Treesearch

Gregory D. Hayward; David B. McDonald

1997-01-01

Building sophisticated habitat models for conservation of owls must stem from an understanding of the relative quality of habitats at a variety of geographic and temporal scales. Developing these models requires knowing the relationship between habitat conditions and owl performance. What measure should be used to compare the quality of habitats? Matrix population...

FURTHER REFINEMENTS AND TESTING OF APEX3.0: EPA'S POPULATION EXPOSURE MODEL FOR CRITERIA AND AIR TOXIC INHALATION

EPA Science Inventory

The Air Pollutants Exposure Model (APEX(3.0)) is a PC-based model that was derived from the probabilistic NAAQS Exposure Model for carbon monoxide (pNEM/CO). APEX will be one of the tools used to estimate human population exposure for criteria and air toxic pollutants as part ...

Introduction to Population Modeling.

ERIC Educational Resources Information Center

Frauenthal, James C.

The focus is on the formulation and solution of mathematical models with the idea of a population employed mainly as a pedogogical tool. If the biological setting is stripped away, the material can be interpreted as topics or the qualitative behavior of differential and difference equations. The first group of models investigate the dynamics of a…

ICLUS Tools and Datasets (Version 1.2) and User's Manual: Arcgis Tools and Datasets for Modeling US Housing Density (External Review Draft)

EPA Science Inventory

This draft Geographic Information System (GIS) tool can be used to generate scenarios of housing-density changes and calculate impervious surface cover for the conterminous United States. A draft User’s Guide accompanies the tool. This product distributes the population project...

DYNAMO-HIA--a Dynamic Modeling tool for generic Health Impact Assessments.

PubMed

Lhachimi, Stefan K; Nusselder, Wilma J; Smit, Henriette A; van Baal, Pieter; Baili, Paolo; Bennett, Kathleen; Fernández, Esteve; Kulik, Margarete C; Lobstein, Tim; Pomerleau, Joceline; Mackenbach, Johan P; Boshuizen, Hendriek C

2012-01-01

Currently, no standard tool is publicly available that allows researchers or policy-makers to quantify the impact of policies using epidemiological evidence within the causal framework of Health Impact Assessment (HIA). A standard tool should comply with three technical criteria (real-life population, dynamic projection, explicit risk-factor states) and three usability criteria (modest data requirements, rich model output, generally accessible) to be useful in the applied setting of HIA. With DYNAMO-HIA (Dynamic Modeling for Health Impact Assessment), we introduce such a generic software tool specifically designed to facilitate quantification in the assessment of the health impacts of policies. DYNAMO-HIA quantifies the impact of user-specified risk-factor changes on multiple diseases and in turn on overall population health, comparing one reference scenario with one or more intervention scenarios. The Markov-based modeling approach allows for explicit risk-factor states and simulation of a real-life population. A built-in parameter estimation module ensures that only standard population-level epidemiological evidence is required, i.e. data on incidence, prevalence, relative risks, and mortality. DYNAMO-HIA provides a rich output of summary measures--e.g. life expectancy and disease-free life expectancy--and detailed data--e.g. prevalences and mortality/survival rates--by age, sex, and risk-factor status over time. DYNAMO-HIA is controlled via a graphical user interface and is publicly available from the internet, ensuring general accessibility. We illustrate the use of DYNAMO-HIA with two example applications: a policy causing an overall increase in alcohol consumption and quantifying the disease-burden of smoking. By combining modest data needs with general accessibility and user friendliness within the causal framework of HIA, DYNAMO-HIA is a potential standard tool for health impact assessment based on epidemiologic evidence.

Understanding and managing fish populations: keeping the toolbox fit for purpose.

PubMed

Paris, J R; Sherman, K D; Bell, E; Boulenger, C; Delord, C; El-Mahdi, M B M; Fairfield, E A; Griffiths, A M; Gutmann Roberts, C; Hedger, R D; Holman, L E; Hooper, L H; Humphries, N E; Katsiadaki, I; King, R A; Lemopoulos, A; Payne, C J; Peirson, G; Richter, K K; Taylor, M I; Trueman, C N; Hayden, B; Stevens, J R

2018-03-01

Wild fish populations are currently experiencing unprecedented pressures, which are projected to intensify in the coming decades. Developing a thorough understanding of the influences of both biotic and abiotic factors on fish populations is a salient issue in contemporary fish conservation and management. During the 50th Anniversary Symposium of The Fisheries Society of the British Isles at the University of Exeter, UK, in July 2017, scientists from diverse research backgrounds gathered to discuss key topics under the broad umbrella of 'Understanding Fish Populations'. Below, the output of one such discussion group is detailed, focusing on tools used to investigate natural fish populations. Five main groups of approaches were identified: tagging and telemetry; molecular tools; survey tools; statistical and modelling tools; tissue analyses. The appraisal covered current challenges and potential solutions for each of these topics. In addition, three key themes were identified as applicable across all tool-based applications. These included data management, public engagement, and fisheries policy and governance. The continued innovation of tools and capacity to integrate interdisciplinary approaches into the future assessment and management of fish populations is highlighted as an important focus for the next 50 years of fisheries research. © 2018 The Fisheries Society of the British Isles.

Population and Activity of On-road Vehicles in MOVES2014

EPA Science Inventory

This report describes the sources and derivation for on-road vehicle population and activity information and associated adjustments as stored in the MOVES2014 default databases. Motor Vehicle Emission Simulator, the MOVES2014 model, is a set of modeling tools for estimating emiss...

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...

Heterogeneous Structure of Stem Cells Dynamics: Statistical Models and Quantitative Predictions

PubMed Central

Bogdan, Paul; Deasy, Bridget M.; Gharaibeh, Burhan; Roehrs, Timo; Marculescu, Radu

2014-01-01

Understanding stem cell (SC) population dynamics is essential for developing models that can be used in basic science and medicine, to aid in predicting cells fate. These models can be used as tools e.g. in studying patho-physiological events at the cellular and tissue level, predicting (mal)functions along the developmental course, and personalized regenerative medicine. Using time-lapsed imaging and statistical tools, we show that the dynamics of SC populations involve a heterogeneous structure consisting of multiple sub-population behaviors. Using non-Gaussian statistical approaches, we identify the co-existence of fast and slow dividing subpopulations, and quiescent cells, in stem cells from three species. The mathematical analysis also shows that, instead of developing independently, SCs exhibit a time-dependent fractal behavior as they interact with each other through molecular and tactile signals. These findings suggest that more sophisticated models of SC dynamics should view SC populations as a collective and avoid the simplifying homogeneity assumption by accounting for the presence of more than one dividing sub-population, and their multi-fractal characteristics. PMID:24769917

A Rainfall- and Temperature-Driven Abundance Model for Aedes albopictus Populations

PubMed Central

Tran, Annelise; L’Ambert, Grégory; Lacour, Guillaume; Benoît, Romain; Demarchi, Marie; Cros, Myriam; Cailly, Priscilla; Aubry-Kientz, Mélaine; Balenghien, Thomas; Ezanno, Pauline

2013-01-01

The mosquito Aedes (Stegomyia) albopictus (Skuse) (Diptera: Culicidae) is an invasive species which has colonized Southern Europe in the last two decades. As it is a competent vector for several arboviruses, its spread is of increasing public health concern, and there is a need for appropriate monitoring tools. In this paper, we have developed a modelling approach to predict mosquito abundance over time, and identify the main determinants of mosquito population dynamics. The model is temperature- and rainfall-driven, takes into account egg diapause during unfavourable periods, and was used to model the population dynamics of Ae. albopictus in the French Riviera since 2008. Entomological collections of egg stage from six locations in Nice conurbation were used for model validation. We performed a sensitivity analysis to identify the key parameters of the mosquito population dynamics. Results showed that the model correctly predicted entomological field data (Pearson r correlation coefficient values range from 0.73 to 0.93). The model’s main control points were related to adult’s mortality rates, the carrying capacity in pupae of the environment, and the beginning of the unfavourable period. The proposed model can be efficiently used as a tool to predict Ae. albopictus population dynamics, and to assess the efficiency of different control strategies. PMID:23624579

Global population genomics and comparisons of selective signatures from two invasions of melon fly, Zeugodacus cucurbitae (Diptera: Tephritidae)

USDA-ARS?s Scientific Manuscript database

Population genetics is a powerful tool for invasion biology and pest management, from tracing invasion pathways to informing management decisions with inference of population demographics. Genomics greatly increases the resolution of population-scale analyses, yet outside of model species with exten...

Population pharmacokinetics of busulfan in pediatric and young adult patients undergoing hematopoietic cell transplant: a model-based dosing algorithm for personalized therapy and implementation into routine clinical use.

PubMed

Long-Boyle, Janel R; Savic, Rada; Yan, Shirley; Bartelink, Imke; Musick, Lisa; French, Deborah; Law, Jason; Horn, Biljana; Cowan, Morton J; Dvorak, Christopher C

2015-04-01

Population pharmacokinetic (PK) studies of busulfan in children have shown that individualized model-based algorithms provide improved targeted busulfan therapy when compared with conventional dose guidelines. The adoption of population PK models into routine clinical practice has been hampered by the tendency of pharmacologists to develop complex models too impractical for clinicians to use. The authors aimed to develop a population PK model for busulfan in children that can reliably achieve therapeutic exposure (concentration at steady state) and implement a simple model-based tool for the initial dosing of busulfan in children undergoing hematopoietic cell transplantation. Model development was conducted using retrospective data available in 90 pediatric and young adult patients who had undergone hematopoietic cell transplantation with busulfan conditioning. Busulfan drug levels and potential covariates influencing drug exposure were analyzed using the nonlinear mixed effects modeling software, NONMEM. The final population PK model was implemented into a clinician-friendly Microsoft Excel-based tool and used to recommend initial doses of busulfan in a group of 21 pediatric patients prospectively dosed based on the population PK model. Modeling of busulfan time-concentration data indicates that busulfan clearance displays nonlinearity in children, decreasing up to approximately 20% between the concentrations of 250-2000 ng/mL. Important patient-specific covariates found to significantly impact busulfan clearance were actual body weight and age. The percentage of individuals achieving a therapeutic concentration at steady state was significantly higher in subjects receiving initial doses based on the population PK model (81%) than in historical controls dosed on conventional guidelines (52%) (P = 0.02). When compared with the conventional dosing guidelines, the model-based algorithm demonstrates significant improvement for providing targeted busulfan therapy in children and young adults.

Proposals for enhanced health risk assessment and stratification in an integrated care scenario

PubMed Central

Dueñas-Espín, Ivan; Vela, Emili; Pauws, Steffen; Bescos, Cristina; Cano, Isaac; Cleries, Montserrat; Contel, Joan Carles; de Manuel Keenoy, Esteban; Garcia-Aymerich, Judith; Gomez-Cabrero, David; Kaye, Rachelle; Lahr, Maarten M H; Lluch-Ariet, Magí; Moharra, Montserrat; Monterde, David; Mora, Joana; Nalin, Marco; Pavlickova, Andrea; Piera, Jordi; Ponce, Sara; Santaeugenia, Sebastià; Schonenberg, Helen; Störk, Stefan; Tegner, Jesper; Velickovski, Filip; Westerteicher, Christoph; Roca, Josep

2016-01-01

Objectives Population-based health risk assessment and stratification are considered highly relevant for large-scale implementation of integrated care by facilitating services design and case identification. The principal objective of the study was to analyse five health-risk assessment strategies and health indicators used in the five regions participating in the Advancing Care Coordination and Telehealth Deployment (ACT) programme (http://www.act-programme.eu). The second purpose was to elaborate on strategies toward enhanced health risk predictive modelling in the clinical scenario. Settings The five ACT regions: Scotland (UK), Basque Country (ES), Catalonia (ES), Lombardy (I) and Groningen (NL). Participants Responsible teams for regional data management in the five ACT regions. Primary and secondary outcome measures We characterised and compared risk assessment strategies among ACT regions by analysing operational health risk predictive modelling tools for population-based stratification, as well as available health indicators at regional level. The analysis of the risk assessment tool deployed in Catalonia in 2015 (GMAs, Adjusted Morbidity Groups) was used as a basis to propose how population-based analytics could contribute to clinical risk prediction. Results There was consensus on the need for a population health approach to generate health risk predictive modelling. However, this strategy was fully in place only in two ACT regions: Basque Country and Catalonia. We found marked differences among regions in health risk predictive modelling tools and health indicators, and identified key factors constraining their comparability. The research proposes means to overcome current limitations and the use of population-based health risk prediction for enhanced clinical risk assessment. Conclusions The results indicate the need for further efforts to improve both comparability and flexibility of current population-based health risk predictive modelling approaches. Applicability and impact of the proposals for enhanced clinical risk assessment require prospective evaluation. PMID:27084274

Population Models for Stream Fish Response to Habitat and Hydrologic Alteration: the CVI Watershed Tool. EPA/600/R-04/190

EPA Pesticide Factsheets

Models that predict the responses of fish populations and communities to key habitat characteristics are necessary for CVIs watershed management goals, for determining where to restore and how, as well as evaluating the most probable outcome.

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...

Refining prognosis in lung cancer: A report on the quality and relevance of clinical prognostic tools

PubMed Central

Mahar, Alyson L.; Compton, Carolyn; McShane, Lisa M.; Halabi, Susan; Asamura, Hisao; Rami-Porta, Ramon; Groome, Patti A.

2015-01-01

Introduction Accurate, individualized prognostication for lung cancer patients requires the integration of standard patient and pathologic factors, biologic, genetic, and other molecular characteristics of the tumor. Clinical prognostic tools aim to aggregate information on an individual patient to predict disease outcomes such as overall survival, but little is known about their clinical utility and accuracy in lung cancer. Methods A systematic search of the scientific literature for clinical prognostic tools in lung cancer published Jan 1, 1996-Jan 27, 2015 was performed. In addition, web-based resources were searched. A priori criteria determined by the Molecular Modellers Working Group of the American Joint Committee on Cancer were used to investigate the quality and usefulness of tools. Criteria included clinical presentation, model development approaches, validation strategies, and performance metrics. Results Thirty-two prognostic tools were identified. Patients with metastases were the most frequently considered population in non-small cell lung cancer. All tools for small cell lung cancer covered that entire patient population. Included prognostic factors varied considerably across tools. Internal validity was not formally evaluated for most tools and only eleven were evaluated for external validity. Two key considerations were highlighted for tool development: identification of an explicit purpose related to a relevant clinical population and clear decision-points, and prioritized inclusion of established prognostic factors over emerging factors. Conclusions Prognostic tools will contribute more meaningfully to the practice of personalized medicine if better study design and analysis approaches are used in their development and validation. PMID:26313682

A stochastic population model for Lepidium papilliferum (Brassicaceae), a rare desert ephemeral with a persistent seed bank

Treesearch

Susan E. Meyer; Dana Quinney; Jay Weaver

2006-01-01

Population viability analysis (PVA) is a valuable tool for rare plant conservation, but PVA for plants with persistent seed banks is difficult without reliable information on seed bank processes. We modeled the population dynamics of the Snake River Plains ephemeral Lepidium papilliferum using data from an 11-yr artificial seed bank experiment to estimate age-specific...

Predicting Operator Execution Times Using CogTool

NASA Technical Reports Server (NTRS)

Santiago-Espada, Yamira; Latorella, Kara A.

2013-01-01

Researchers and developers of NextGen systems can use predictive human performance modeling tools as an initial approach to obtain skilled user performance times analytically, before system testing with users. This paper describes the CogTool models for a two pilot crew executing two different types of a datalink clearance acceptance tasks, and on two different simulation platforms. The CogTool time estimates for accepting and executing Required Time of Arrival and Interval Management clearances were compared to empirical data observed in video tapes and registered in simulation files. Results indicate no statistically significant difference between empirical data and the CogTool predictions. A population comparison test found no significant differences between the CogTool estimates and the empirical execution times for any of the four test conditions. We discuss modeling caveats and considerations for applying CogTool to crew performance modeling in advanced cockpit environments.

Early visual analysis tool using magnetoencephalography for treatment and recovery of neuronal dysfunction.

PubMed

Rasheed, Waqas; Neoh, Yee Yik; Bin Hamid, Nor Hisham; Reza, Faruque; Idris, Zamzuri; Tang, Tong Boon

2017-10-01

Functional neuroimaging modalities play an important role in deciding the diagnosis and course of treatment of neuronal dysfunction and degeneration. This article presents an analytical tool with visualization by exploiting the strengths of the MEG (magnetoencephalographic) neuroimaging technique. The tool automates MEG data import (in tSSS format), channel information extraction, time/frequency decomposition, and circular graph visualization (connectogram) for simple result inspection. For advanced users, the tool also provides magnitude squared coherence (MSC) values allowing personalized threshold levels, and the computation of default model from MEG data of control population. Default model obtained from healthy population data serves as a useful benchmark to diagnose and monitor neuronal recovery during treatment. The proposed tool further provides optional labels with international 10-10 system nomenclature in order to facilitate comparison studies with EEG (electroencephalography) sensor space. Potential applications in epilepsy and traumatic brain injury studies are also discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of a new generation of high-resolution anatomical models for medical device evaluation: the Virtual Population 3.0

NASA Astrophysics Data System (ADS)

Gosselin, Marie-Christine; Neufeld, Esra; Moser, Heidi; Huber, Eveline; Farcito, Silvia; Gerber, Livia; Jedensjö, Maria; Hilber, Isabel; Di Gennaro, Fabienne; Lloyd, Bryn; Cherubini, Emilio; Szczerba, Dominik; Kainz, Wolfgang; Kuster, Niels

2014-09-01

The Virtual Family computational whole-body anatomical human models were originally developed for electromagnetic (EM) exposure evaluations, in particular to study how absorption of radiofrequency radiation from external sources depends on anatomy. However, the models immediately garnered much broader interest and are now applied by over 300 research groups, many from medical applications research fields. In a first step, the Virtual Family was expanded to the Virtual Population to provide considerably broader population coverage with the inclusion of models of both sexes ranging in age from 5 to 84 years old. Although these models have proven to be invaluable for EM dosimetry, it became evident that significantly enhanced models are needed for reliable effectiveness and safety evaluations of diagnostic and therapeutic applications, including medical implants safety. This paper describes the research and development performed to obtain anatomical models that meet the requirements necessary for medical implant safety assessment applications. These include implementation of quality control procedures, re-segmentation at higher resolution, more-consistent tissue assignments, enhanced surface processing and numerous anatomical refinements. Several tools were developed to enhance the functionality of the models, including discretization tools, posing tools to expand the posture space covered, and multiple morphing tools, e.g., to develop pathological models or variations of existing ones. A comprehensive tissue properties database was compiled to complement the library of models. The results are a set of anatomically independent, accurate, and detailed models with smooth, yet feature-rich and topologically conforming surfaces. The models are therefore suited for the creation of unstructured meshes, and the possible applications of the models are extended to a wider range of solvers and physics. The impact of these improvements is shown for the MRI exposure of an adult woman with an orthopedic spinal implant. Future developments include the functionalization of the models for specific physical and physiological modeling tasks.

The Relational-Behavior Model: A Pilot Assessment Study for At-Risk College Populations

ERIC Educational Resources Information Center

Chandler, Donald S., Jr.; Perkins, Michele D.

2007-01-01

This pilot study examined the relational-behavior model (RBM) as an HIV/AIDS assessment tool for at-risk college populations. Based on this theory, a survey was constructed to assess the six areas associated with HIV/AIDS prevention: personal awareness, knowledge deficiency, relational skills, HIV/STD stigmatization, community awareness, and…

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.

Applications of bioenergetics models to fish ecology and management: where do we go from here?

USGS Publications Warehouse

Hansen, Michael J.; Boisclair, Daniel; Brandt, Stephen B.; Hewett, Steven W.; Kitchell, James F.; Lucas, Martyn C.; Ney, John J.

1993-01-01

Papers and panel discussions given during a 1992 symposium on bioenergetics models are summarized. Bioenergetics models have been applied to a variety of research and management questions related to fish stocks, populations, food webs, and ecosystems. Applications include estimates of the intensity and dynamics of predator-prey interactions, nutrient cycling within aquatic food webs of varying trophic structure, and food requirements of single animals, whole populations, and communities of fishes. As tools in food web and ecosystem applications, bioenergetics models have been used to compare forage consumption by salmonid predators across the Laurentian Great Lakes for single populations and whole communities, and to estimate the growth potential of pelagic predators in Chesapeake Bay and Lake Ontario. Some critics say that bioenergetics models lack sufficient detail to produce reliable results in such field applications, whereas others say that the models are too complex to be useful tools for fishery managers. Nevertheless, bioenergetics models have achieved notable predictive successes. Improved estimates are needed for model parameters such as metabolic costs of activity, and more complete studies are needed of the bioenergetics of larval and juvenile fishes. Future research on bioenergetics should include laboratory and field measurements of key model parameters such as weight-dependent maximum consumption, respiration and activity, and thermal habitats actually occupied by fish. Future applications of bioenergetics models to fish populations also depend on accurate estimates of population sizes and survival rates.

Using exposure prediction tools to link exposure and dosimetry for risk based decisions: a case study with phthalates

EPA Science Inventory

The Population Life-course Exposure to Health Effects Modeling (PLETHEM) platform being developed provides a tool that links results from emerging toxicity testing tools to exposure estimates for humans as defined by the USEPA. A reverse dosimetry case study using phthalates was ...

Final Report: Demographic Tools for Climate Change and Environmental Assessments

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

O'Neill, Brian

2017-01-24

This report summarizes work over the course of a three-year project (2012-2015, with one year no-cost extension to 2016). The full proposal detailed six tasks: Task 1: Population projection model Task 2: Household model Task 3: Spatial population model Task 4: Integrated model development Task 5: Population projections for Shared Socio-economic Pathways (SSPs) Task 6: Population exposure to climate extremes We report on all six tasks, provide details on papers that have appeared or been submitted as a result of this project, and list selected key presentations that have been made within the university community and at professional meetings.

EFFECTS OF HABITAT LOSS ON POPULATIONS OF WHITE-FOOTED MICE: MATRIX MODEL PREDICTIONS WITH LANDSCAPE-SCALE PERTURBATION EXPERIMENTS

EPA Science Inventory

Habitat loss is the leading cause of decline in wildlife diversity and abundance throughout the world, and understanding its impacts on animal populations is a critical challenge facing conservation biologists. Population viability analysis (PVA) is a commonly used tool for pred...

Identifying critical life stage transitions for biological control of long-lived perennial Vincetoxicum species

USDA-ARS?s Scientific Manuscript database

Demographic matrix modeling of invasive plant populations can be a powerful tool to identify key life stage transitions for targeted disruption in order to cause population decline. This approach can provide quantitative estimates of reductions in select vital rates needed to reduce population growt...

DYNAMO-HIA–A Dynamic Modeling Tool for Generic Health Impact Assessments

PubMed Central

Lhachimi, Stefan K.; Nusselder, Wilma J.; Smit, Henriette A.; van Baal, Pieter; Baili, Paolo; Bennett, Kathleen; Fernández, Esteve; Kulik, Margarete C.; Lobstein, Tim; Pomerleau, Joceline; Mackenbach, Johan P.; Boshuizen, Hendriek C.

2012-01-01

Background Currently, no standard tool is publicly available that allows researchers or policy-makers to quantify the impact of policies using epidemiological evidence within the causal framework of Health Impact Assessment (HIA). A standard tool should comply with three technical criteria (real-life population, dynamic projection, explicit risk-factor states) and three usability criteria (modest data requirements, rich model output, generally accessible) to be useful in the applied setting of HIA. With DYNAMO-HIA (Dynamic Modeling for Health Impact Assessment), we introduce such a generic software tool specifically designed to facilitate quantification in the assessment of the health impacts of policies. Methods and Results DYNAMO-HIA quantifies the impact of user-specified risk-factor changes on multiple diseases and in turn on overall population health, comparing one reference scenario with one or more intervention scenarios. The Markov-based modeling approach allows for explicit risk-factor states and simulation of a real-life population. A built-in parameter estimation module ensures that only standard population-level epidemiological evidence is required, i.e. data on incidence, prevalence, relative risks, and mortality. DYNAMO-HIA provides a rich output of summary measures – e.g. life expectancy and disease-free life expectancy – and detailed data – e.g. prevalences and mortality/survival rates – by age, sex, and risk-factor status over time. DYNAMO-HIA is controlled via a graphical user interface and is publicly available from the internet, ensuring general accessibility. We illustrate the use of DYNAMO-HIA with two example applications: a policy causing an overall increase in alcohol consumption and quantifying the disease-burden of smoking. Conclusion By combining modest data needs with general accessibility and user friendliness within the causal framework of HIA, DYNAMO-HIA is a potential standard tool for health impact assessment based on epidemiologic evidence. PMID:22590491

Mathematical Modelling as a Tool to Understand Cell Self-renewal and Differentiation.

PubMed

Getto, Philipp; Marciniak-Czochra, Anna

2015-01-01

Mathematical modeling is a powerful technique to address key questions and paradigms in a variety of complex biological systems and can provide quantitative insights into cell kinetics, fate determination and development of cell populations. The chapter is devoted to a review of modeling of the dynamics of stem cell-initiated systems using mathematical methods of ordinary differential equations. Some basic concepts and tools for cell population dynamics are summarized and presented as a gentle introduction to non-mathematicians. The models take into account different plausible mechanisms regulating homeostasis. Two mathematical frameworks are proposed reflecting, respectively, a discrete (punctuated by division events) and a continuous character of transitions between differentiation stages. Advantages and constraints of the mathematical approaches are presented on examples of models of blood systems and compared to patients data on healthy hematopoiesis.

A multi-scale assessment of population connectivity in African lions (Panthera leo) in response to landscape change

Treesearch

Samuel A. Cushman; Nicholas B. Elliot; David W. Macdonald; Andrew J. Loveridge

2015-01-01

Habitat loss and fragmentation are among the major drivers of population declines and extinction, particularly in large carnivores. Connectivity models provide practical tools for assessing fragmentation effects and developing mitigation or conservation responses. To be useful to conservation practitioners, connectivity models need to incorporate multiple scales and...

Predictive models to assess risk of type 2 diabetes, hypertension and comorbidity: machine-learning algorithms and validation using national health data from Kuwait--a cohort study.

PubMed

Farran, Bassam; Channanath, Arshad Mohamed; Behbehani, Kazem; Thanaraj, Thangavel Alphonse

2013-05-14

We build classification models and risk assessment tools for diabetes, hypertension and comorbidity using machine-learning algorithms on data from Kuwait. We model the increased proneness in diabetic patients to develop hypertension and vice versa. We ascertain the importance of ethnicity (and natives vs expatriate migrants) and of using regional data in risk assessment. Retrospective cohort study. Four machine-learning techniques were used: logistic regression, k-nearest neighbours (k-NN), multifactor dimensionality reduction and support vector machines. The study uses fivefold cross validation to obtain generalisation accuracies and errors. Kuwait Health Network (KHN) that integrates data from primary health centres and hospitals in Kuwait. 270 172 hospital visitors (of which, 89 858 are diabetic, 58 745 hypertensive and 30 522 comorbid) comprising Kuwaiti natives, Asian and Arab expatriates. Incident type 2 diabetes, hypertension and comorbidity. Classification accuracies of >85% (for diabetes) and >90% (for hypertension) are achieved using only simple non-laboratory-based parameters. Risk assessment tools based on k-NN classification models are able to assign 'high' risk to 75% of diabetic patients and to 94% of hypertensive patients. Only 5% of diabetic patients are seen assigned 'low' risk. Asian-specific models and assessments perform even better. Pathological conditions of diabetes in the general population or in hypertensive population and those of hypertension are modelled. Two-stage aggregate classification models and risk assessment tools, built combining both the component models on diabetes (or on hypertension), perform better than individual models. Data on diabetes, hypertension and comorbidity from the cosmopolitan State of Kuwait are available for the first time. This enabled us to apply four different case-control models to assess risks. These tools aid in the preliminary non-intrusive assessment of the population. Ethnicity is seen significant to the predictive models. Risk assessments need to be developed using regional data as we demonstrate the applicability of the American Diabetes Association online calculator on data from Kuwait.

Using Collaborative Simulation Modeling to Develop a Web-Based Tool to Support Policy-Level Decision Making About Breast Cancer Screening Initiation Age

PubMed Central

Burnside, Elizabeth S.; Lee, Sandra J.; Bennette, Carrie; Near, Aimee M.; Alagoz, Oguzhan; Huang, Hui; van den Broek, Jeroen J.; Kim, Joo Yeon; Ergun, Mehmet A.; van Ravesteyn, Nicolien T.; Stout, Natasha K.; de Koning, Harry J.; Mandelblatt, Jeanne S.

2017-01-01

Background There are no publicly available tools designed specifically to assist policy makers to make informed decisions about the optimal ages of breast cancer screening initiation for different populations of US women. Objective To use three established simulation models to develop a web-based tool called Mammo OUTPuT. Methods The simulation models use the 1970 US birth cohort and common parameters for incidence, digital screening performance, and treatment effects. Outcomes include breast cancers diagnosed, breast cancer deaths averted, breast cancer mortality reduction, false-positive mammograms, benign biopsies, and overdiagnosis. The Mammo OUTPuT tool displays these outcomes for combinations of age at screening initiation (every year from 40 to 49), annual versus biennial interval, lifetime versus 10-year horizon, and breast density, compared to waiting to start biennial screening at age 50 and continuing to 74. The tool was piloted by decision makers (n = 16) who completed surveys. Results The tool demonstrates that benefits in the 40s increase linearly with earlier initiation age, without a specific threshold age. Likewise, the harms of screening increase monotonically with earlier ages of initiation in the 40s. The tool also shows users how the balance of benefits and harms varies with breast density. Surveys revealed that 100% of users (16/16) liked the appearance of the site; 94% (15/16) found the tool helpful; and 94% (15/16) would recommend the tool to a colleague. Conclusions This tool synthesizes a representative subset of the most current CISNET (Cancer Intervention and Surveillance Modeling Network) simulation model outcomes to provide policy makers with quantitative data on the benefits and harms of screening women in the 40s. Ultimate decisions will depend on program goals, the population served, and informed judgments about the weight of benefits and harms. PMID:29376135

DATA FOR ENVIRONMENTAL MODELING: AN OVERVIEW

EPA Science Inventory

The objective of the project described here, entitled Data for Environmental Modeling (D4EM), is the development of a comprehensive set of software tools that allow an environmental model developer to automatically populate model input files with environmental data available from...

Pedestrian Evacuation Analysis for Tsunami Hazards

NASA Astrophysics Data System (ADS)

Jones, J. M.; Ng, P.; Wood, N. J.

2014-12-01

Recent catastrophic tsunamis in the last decade, as well as the 50th anniversary of the 1964 Alaskan event, have heightened awareness of the threats these natural hazards present to large and increasing coastal populations. For communities located close to the earthquake epicenter that generated the tsunami, strong shaking may also cause significant infrastructure damage, impacting the road network and hampering evacuation. There may also be insufficient time between the earthquake and first wave arrival to rely on a coordinated evacuation, leaving at-risk populations to self-evacuate on foot and across the landscape. Emergency managers evaluating these coastal risks need tools to assess the evacuation potential of low-lying areas in order to discuss mitigation options, which may include vertical evacuation structures to provide local safe havens in vulnerable communities. The U.S. Geological Survey has developed the Pedestrian Evacuation Analyst software tool for use by researchers and emergency managers to assist in the assessment of a community's evacuation potential by modeling travel times across the landscape and producing both maps of travel times and charts of population counts with corresponding times. The tool uses an anisotropic (directionally dependent) least cost distance model to estimate evacuation potential and allows for the variation of travel speed to measure its effect on travel time. The effectiveness of vertical evacuation structures on evacuation time can also be evaluated and compared with metrics such as travel time maps showing each structure in place and graphs displaying the percentage change in population exposure for each structure against the baseline. Using the tool, travel time maps and at-risk population counts have been generated for some coastal communities of the U.S. Pacific Northwest and Alaska. The tool can also be used to provide valuable decision support for tsunami vertical evacuation siting.

Population Pharmacokinetics of Busulfan in Pediatric and Young Adult Patients Undergoing Hematopoietic Cell Transplant: A Model-Based Dosing Algorithm for Personalized Therapy and Implementation into Routine Clinical Use

PubMed Central

Long-Boyle, Janel; Savic, Rada; Yan, Shirley; Bartelink, Imke; Musick, Lisa; French, Deborah; Law, Jason; Horn, Biljana; Cowan, Morton J.; Dvorak, Christopher C.

2014-01-01

Background Population pharmacokinetic (PK) studies of busulfan in children have shown that individualized model-based algorithms provide improved targeted busulfan therapy when compared to conventional dosing. The adoption of population PK models into routine clinical practice has been hampered by the tendency of pharmacologists to develop complex models too impractical for clinicians to use. The authors aimed to develop a population PK model for busulfan in children that can reliably achieve therapeutic exposure (concentration-at-steady-state, Css) and implement a simple, model-based tool for the initial dosing of busulfan in children undergoing HCT. Patients and Methods Model development was conducted using retrospective data available in 90 pediatric and young adult patients who had undergone HCT with busulfan conditioning. Busulfan drug levels and potential covariates influencing drug exposure were analyzed using the non-linear mixed effects modeling software, NONMEM. The final population PK model was implemented into a clinician-friendly, Microsoft Excel-based tool and used to recommend initial doses of busulfan in a group of 21 pediatric patients prospectively dosed based on the population PK model. Results Modeling of busulfan time-concentration data indicates busulfan CL displays non-linearity in children, decreasing up to approximately 20% between the concentrations of 250–2000 ng/mL. Important patient-specific covariates found to significantly impact busulfan CL were actual body weight and age. The percentage of individuals achieving a therapeutic Css was significantly higher in subjects receiving initial doses based on the population PK model (81%) versus historical controls dosed on conventional guidelines (52%) (p = 0.02). Conclusion When compared to the conventional dosing guidelines, the model-based algorithm demonstrates significant improvement for providing targeted busulfan therapy in children and young adults. PMID:25162216

EmpiriciSN: Re-sampling Observed Supernova/Host Galaxy Populations Using an XD Gaussian Mixture Model

NASA Astrophysics Data System (ADS)

Holoien, Thomas W.-S.; Marshall, Philip J.; Wechsler, Risa H.

2017-06-01

We describe two new open-source tools written in Python for performing extreme deconvolution Gaussian mixture modeling (XDGMM) and using a conditioned model to re-sample observed supernova and host galaxy populations. XDGMM is new program that uses Gaussian mixtures to perform density estimation of noisy data using extreme deconvolution (XD) algorithms. Additionally, it has functionality not available in other XD tools. It allows the user to select between the AstroML and Bovy et al. fitting methods and is compatible with scikit-learn machine learning algorithms. Most crucially, it allows the user to condition a model based on the known values of a subset of parameters. This gives the user the ability to produce a tool that can predict unknown parameters based on a model that is conditioned on known values of other parameters. EmpiriciSN is an exemplary application of this functionality, which can be used to fit an XDGMM model to observed supernova/host data sets and predict likely supernova parameters using a model conditioned on observed host properties. It is primarily intended to simulate realistic supernovae for LSST data simulations based on empirical galaxy properties.

EmpiriciSN: Re-sampling Observed Supernova/Host Galaxy Populations Using an XD Gaussian Mixture Model

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

Holoien, Thomas W. -S.; Marshall, Philip J.; Wechsler, Risa H.

We describe two new open-source tools written in Python for performing extreme deconvolution Gaussian mixture modeling (XDGMM) and using a conditioned model to re-sample observed supernova and host galaxy populations. XDGMM is new program that uses Gaussian mixtures to perform density estimation of noisy data using extreme deconvolution (XD) algorithms. Additionally, it has functionality not available in other XD tools. It allows the user to select between the AstroML and Bovy et al. fitting methods and is compatible with scikit-learn machine learning algorithms. Most crucially, it allows the user to condition a model based on the known values of amore » subset of parameters. This gives the user the ability to produce a tool that can predict unknown parameters based on a model that is conditioned on known values of other parameters. EmpiriciSN is an exemplary application of this functionality, which can be used to fit an XDGMM model to observed supernova/host data sets and predict likely supernova parameters using a model conditioned on observed host properties. It is primarily intended to simulate realistic supernovae for LSST data simulations based on empirical galaxy properties.« less

Comparison of Data Development Tools for Populating Cognitive Models in Social Simulation

DTIC Science & Technology

2011-09-01

world surveys. STANLEY was evaluated by scoring sentiment in a document corpus and attempting to correlate those scores to a real world issue ...corpus and attempting to correlate those scores to a real world issue . Results of the study indicate that the survey data tool generated case files of...15 1. Issues with the Initial Version of the Tool .......................................21 2. The Tool Used in the Research

Proposals for enhanced health risk assessment and stratification in an integrated care scenario.

PubMed

Dueñas-Espín, Ivan; Vela, Emili; Pauws, Steffen; Bescos, Cristina; Cano, Isaac; Cleries, Montserrat; Contel, Joan Carles; de Manuel Keenoy, Esteban; Garcia-Aymerich, Judith; Gomez-Cabrero, David; Kaye, Rachelle; Lahr, Maarten M H; Lluch-Ariet, Magí; Moharra, Montserrat; Monterde, David; Mora, Joana; Nalin, Marco; Pavlickova, Andrea; Piera, Jordi; Ponce, Sara; Santaeugenia, Sebastià; Schonenberg, Helen; Störk, Stefan; Tegner, Jesper; Velickovski, Filip; Westerteicher, Christoph; Roca, Josep

2016-04-15

Population-based health risk assessment and stratification are considered highly relevant for large-scale implementation of integrated care by facilitating services design and case identification. The principal objective of the study was to analyse five health-risk assessment strategies and health indicators used in the five regions participating in the Advancing Care Coordination and Telehealth Deployment (ACT) programme (http://www.act-programme.eu). The second purpose was to elaborate on strategies toward enhanced health risk predictive modelling in the clinical scenario. The five ACT regions: Scotland (UK), Basque Country (ES), Catalonia (ES), Lombardy (I) and Groningen (NL). Responsible teams for regional data management in the five ACT regions. We characterised and compared risk assessment strategies among ACT regions by analysing operational health risk predictive modelling tools for population-based stratification, as well as available health indicators at regional level. The analysis of the risk assessment tool deployed in Catalonia in 2015 (GMAs, Adjusted Morbidity Groups) was used as a basis to propose how population-based analytics could contribute to clinical risk prediction. There was consensus on the need for a population health approach to generate health risk predictive modelling. However, this strategy was fully in place only in two ACT regions: Basque Country and Catalonia. We found marked differences among regions in health risk predictive modelling tools and health indicators, and identified key factors constraining their comparability. The research proposes means to overcome current limitations and the use of population-based health risk prediction for enhanced clinical risk assessment. The results indicate the need for further efforts to improve both comparability and flexibility of current population-based health risk predictive modelling approaches. Applicability and impact of the proposals for enhanced clinical risk assessment require prospective evaluation. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

A stochastic population model to evaluate Moapa dace (Moapa coriacea) population growth under alternative management scenarios

USGS Publications Warehouse

Perry, Russell W.; Jones, Edward; Scoppettone, G. Gary

2015-07-14

Increasing or decreasing the total carrying capacity of all stream segments resulted in changes in equilibrium population size that were directly proportional to the change in capacity. However, changes in carrying capacity to some stream segments but not others could result in disproportionate changes in equilibrium population sizes by altering density-dependent movement and survival in the stream network. These simulations show how our IBM can provide a useful management tool for understanding the effect of restoration actions or reintroductions on carrying capacity, and, in turn, how these changes affect Moapa dace abundance. Such tools are critical for devising management strategies to achieve recovery goals.

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.

Exploiting the Brachypodium Tool Box in cereal and grass research

USDA-ARS?s Scientific Manuscript database

It is now a decade since Brachypodium distachyon was suggested as a model species for temperate grasses and cereals. Since then transformation protocols, large expressed sequence tag (EST) populations, tools for forward and reverse genetic screens, highly refined cytogenetic probes, germplasm coll...

An Upper Bound for Population Exposure Variability (SOT)

EPA Science Inventory

Tools for the rapid assessment of exposure potential are needed in order to put the results of rapidly-applied tools for assessing biological activity, such as ToxCast® and other high throughput methodologies, into a quantitative exposure context. The ExpoCast models (Wambaugh et...

Agile Model Driven Development of Electronic Health Record-Based Specialty Population Registries.

PubMed

Kannan, Vaishnavi; Fish, Jason C; Willett, DuWayne L

2016-02-01

The transformation of the American healthcare payment system from fee-for-service to value-based care increasingly makes it valuable to develop patient registries for specialized populations, to better assess healthcare quality and costs. Recent widespread adoption of Electronic Health Records (EHRs) in the U.S. now makes possible construction of EHR-based specialty registry data collection tools and reports, previously unfeasible using manual chart abstraction. But the complexities of specialty registry EHR tools and measures, along with the variety of stakeholders involved, can result in misunderstood requirements and frequent product change requests, as users first experience the tools in their actual clinical workflows. Such requirements churn could easily stall progress in specialty registry rollout. Modeling a system's requirements and solution design can be a powerful way to remove ambiguities, facilitate shared understanding, and help evolve a design to meet newly-discovered needs. "Agile Modeling" retains these values while avoiding excessive unused up-front modeling in favor of iterative incremental modeling. Using Agile Modeling principles and practices, in calendar year 2015 one institution developed 58 EHR-based specialty registries, with 111 new data collection tools, supporting 134 clinical process and outcome measures, and enrolling over 16,000 patients. The subset of UML and non-UML models found most consistently useful in designing, building, and iteratively evolving EHR-based specialty registries included User Stories, Domain Models, Use Case Diagrams, Decision Trees, Graphical User Interface Storyboards, Use Case text descriptions, and Solution Class Diagrams.

Tailored tools to improve pharmacotherapy in infants.

PubMed

Allegaert, Karel

2014-08-01

Extensive within-population variability is the essence of neonatal pharmacology. Despite this, infants remain one of the last therapeutic orphans. Together with additional legal initiatives, tailoring of already available tools (modeling, covariates, pharmacovigilance) may significantly improve pharmacotherapy in infants. Modeling approaches that hold the promise to improve pharmacotherapy in infants are between-compound extrapolation for compounds that undergo the same route of elimination and integration of time-varying physiology to adapt for the fast maturational changes. Besides these maturational covariates (size, age), newly emerging covariates relate to novel treatment modalities (extracorporeal circulation, hypothermia), environmental issues (microbiome, critical illness) or pharmacogenetics. All these covariates interact with the maturational variation. Finally, pharmacovigilance also needs to be tailored to the characteristics of this population. This relates to preventive strategies, signal detection and assessment of causality. Knowledge on pharmacotherapy in infants is lagging. Tailoring available tools to the specific characteristics (maturation) and clinical needs (newly emerging covariates) of infants is feasible but needs creativity and a multidisciplinary collaboration between modelers, academia, clinical researchers and, obviously, the public, including parents.

The Pathologist Workforce in the United States: II. An Interactive Modeling Tool for Analyzing Future Qualitative and Quantitative Staffing Demands for Services.

PubMed

Robboy, Stanley J; Gupta, Saurabh; Crawford, James M; Cohen, Michael B; Karcher, Donald S; Leonard, Debra G B; Magnani, Barbarajean; Novis, David A; Prystowsky, Michael B; Powell, Suzanne Z; Gross, David J; Black-Schaffer, W Stephen

2015-11-01

Pathologists are physicians who make diagnoses based on interpretation of tissue and cellular specimens (surgical/cytopathology, molecular/genomic pathology, autopsy), provide medical leadership and consultation for laboratory medicine, and are integral members of their institutions' interdisciplinary patient care teams. To develop a dynamic modeling tool to examine how individual factors and practice variables can forecast demand for pathologist services. Build and test a computer-based software model populated with data from surveys and best estimates about current and new pathologist efforts. Most pathologists' efforts focus on anatomic (52%), laboratory (14%), and other direct services (8%) for individual patients. Population-focused services (12%) (eg, laboratory medical direction) and other professional responsibilities (14%) (eg, teaching, research, and hospital committees) consume the rest of their time. Modeling scenarios were used to assess the need to increase or decrease efforts related globally to the Affordable Care Act, and specifically, to genomic medicine, laboratory consolidation, laboratory medical direction, and new areas where pathologists' expertise can add value. Our modeling tool allows pathologists, educators, and policy experts to assess how various factors may affect demand for pathologists' services. These factors include an aging population, advances in biomedical technology, and changing roles in capitated, value-based, and team-based medical care systems. In the future, pathologists will likely have to assume new roles, develop new expertise, and become more efficient in practicing medicine to accommodate new value-based delivery models.

Statistical Tools for Fitting Models of the Population Consequences of Acoustic Disturbance to Data from Marine Mammal Populations (PCAD Tools 2)

DTIC Science & Technology

2013-09-30

proceedings of a recent conference on The Effects of Noise on Aquatic Life (Schick et al. 2014). In addition to this work, Schick has been working...Lisbon, Portugal (April), the UK National Centre for Statistical Ecology annual workshop (June), and the Effects of Aquatic Noise conference (August). We...A. N. Popper and A. Hawkins, editors. Effects of Noise on Aquatic Life II. Springer. [in press] Fleishman, E., M. Burgman, M. C. Runge, R. S

Integrating the simulation of domestic water demand behaviour to an urban water model using agent based modelling

NASA Astrophysics Data System (ADS)

Koutiva, Ifigeneia; Makropoulos, Christos

2015-04-01

The urban water system's sustainable evolution requires tools that can analyse and simulate the complete cycle including both physical and cultural environments. One of the main challenges, in this regard, is the design and development of tools that are able to simulate the society's water demand behaviour and the way policy measures affect it. The effects of these policy measures are a function of personal opinions that subsequently lead to the formation of people's attitudes. These attitudes will eventually form behaviours. This work presents the design of an ABM tool for addressing the social dimension of the urban water system. The created tool, called Urban Water Agents' Behaviour (UWAB) model, was implemented, using the NetLogo agent programming language. The main aim of the UWAB model is to capture the effects of policies and environmental pressures to water conservation behaviour of urban households. The model consists of agents representing urban households that are linked to each other creating a social network that influences the water conservation behaviour of its members. Household agents are influenced as well by policies and environmental pressures, such as drought. The UWAB model simulates behaviour resulting in the evolution of water conservation within an urban population. The final outcome of the model is the evolution of the distribution of different conservation levels (no, low, high) to the selected urban population. In addition, UWAB is implemented in combination with an existing urban water management simulation tool, the Urban Water Optioneering Tool (UWOT) in order to create a modelling platform aiming to facilitate an adaptive approach of water resources management. For the purposes of this proposed modelling platform, UWOT is used in a twofold manner: (1) to simulate domestic water demand evolution and (2) to simulate the response of the water system to the domestic water demand evolution. The main advantage of the UWAB - UWOT model integration is that it allows the investigation of the effects of different water demand management strategies to an urban population's water demand behaviour and ultimately the effects of these policies to the volume of domestic water demand and the water resources system. The proposed modelling platform is optimised to simulate the effects of water policies during the Athens drought period of 1988-1994. The calibrated modelling platform is then applied to evaluate scenarios of water supply, water demand and water demand management strategies.

USING ECO-EVOLUTIONARY INDIVIDUAL-BASED MODELS TO INVESTIGATE SPATIALLY-DEPENDENT PROCESSES IN CONSERVATION GENETICS

EPA Science Inventory

Eco-evolutionary population simulation models are powerful new forecasting tools for exploring management strategies for climate change and other dynamic disturbance regimes. Additionally, eco-evo individual-based models (IBMs) are useful for investigating theoretical feedbacks ...

Population and Activity of On-road Vehicles in MOVES2014 ...

EPA Pesticide Factsheets

This report describes the sources and derivation for on-road vehicle population and activity information and associated adjustments as stored in the MOVES2014 default databases. Motor Vehicle Emission Simulator, the MOVES2014 model, is a set of modeling tools for estimating emissions produced by on-road (cars, trucks, motorcycles, etc.) and nonroad (backhoes, lawnmowers, etc.) mobile sources. The national default activity information in MOVES2014 provides a reasonable basis for estimating national emissions. However, the uncertainties and variability in the default data contribute to the uncertainty in the resulting emission estimates. Properly characterizing emissions from the on-road vehicle subset requires a detailed understanding of the cars and trucks that make up the vehicle fleet and their patterns of operation. The MOVES model calculates emission inventories by multiplying emission rates by the appropriate emission-related activity, applying correction (adjustment) factors as needed to simulate specific situations, and then adding up the emissions from all sources (populations) and regions. This report describes the sources and derivation for on-road vehicle population and activity information and associated adjustments as stored in the MOVES2014 default databases. Motor Vehicle Emission Simulator, the MOVES2014 model, is a set of modeling tools for estimating emissions produced by on-road (cars, trucks, motorcycles, etc.) and nonroad (backhoes, law

Modeling the role of environmental variables on the population dynamics of the malaria vector Anopheles gambiae sensu stricto

PubMed Central

2012-01-01

Background The impact of weather and climate on malaria transmission has attracted considerable attention in recent years, yet uncertainties around future disease trends under climate change remain. Mathematical models provide powerful tools for addressing such questions and understanding the implications for interventions and eradication strategies, but these require realistic modeling of the vector population dynamics and its response to environmental variables. Methods Published and unpublished field and experimental data are used to develop new formulations for modeling the relationships between key aspects of vector ecology and environmental variables. These relationships are integrated within a validated deterministic model of Anopheles gambiae s.s. population dynamics to provide a valuable tool for understanding vector response to biotic and abiotic variables. Results A novel, parsimonious framework for assessing the effects of rainfall, cloudiness, wind speed, desiccation, temperature, relative humidity and density-dependence on vector abundance is developed, allowing ease of construction, analysis, and integration into malaria transmission models. Model validation shows good agreement with longitudinal vector abundance data from Tanzania, suggesting that recent malaria reductions in certain areas of Africa could be due to changing environmental conditions affecting vector populations. Conclusions Mathematical models provide a powerful, explanatory means of understanding the role of environmental variables on mosquito populations and hence for predicting future malaria transmission under global change. The framework developed provides a valuable advance in this respect, but also highlights key research gaps that need to be resolved if we are to better understand future malaria risk in vulnerable communities. PMID:22877154

Tools for quantifying isotopic niche space and dietary variation at the individual and population level.

USGS Publications Warehouse

Newsome, Seth D.; Yeakel, Justin D.; Wheatley, Patrick V.; Tinker, M. Tim

2012-01-01

Ecologists are increasingly using stable isotope analysis to inform questions about variation in resource and habitat use from the individual to community level. In this study we investigate data sets from 2 California sea otter (Enhydra lutris nereis) populations to illustrate the advantages and potential pitfalls of applying various statistical and quantitative approaches to isotopic data. We have subdivided these tools, or metrics, into 3 categories: IsoSpace metrics, stable isotope mixing models, and DietSpace metrics. IsoSpace metrics are used to quantify the spatial attributes of isotopic data that are typically presented in bivariate (e.g., δ13C versus δ15N) 2-dimensional space. We review IsoSpace metrics currently in use and present a technique by which uncertainty can be included to calculate the convex hull area of consumers or prey, or both. We then apply a Bayesian-based mixing model to quantify the proportion of potential dietary sources to the diet of each sea otter population and compare this to observational foraging data. Finally, we assess individual dietary specialization by comparing a previously published technique, variance components analysis, to 2 novel DietSpace metrics that are based on mixing model output. As the use of stable isotope analysis in ecology continues to grow, the field will need a set of quantitative tools for assessing isotopic variance at the individual to community level. Along with recent advances in Bayesian-based mixing models, we hope that the IsoSpace and DietSpace metrics described here will provide another set of interpretive tools for ecologists.

Development and Implementation of Team-Based Panel Management Tools: Filling the Gap between Patient and Population Information Systems.

PubMed

Watts, Brook; Lawrence, Renée H; Drawz, Paul; Carter, Cameron; Shumaker, Amy Hirsch; Kern, Elizabeth F

2016-08-01

Effective team-based models of care, such as the Patient-Centered Medical Home, require electronic tools to support proactive population management strategies that emphasize care coordination and quality improvement. Despite the spread of electronic health records (EHRs) and vendors marketing population health tools, clinical practices still may lack the ability to have: (1) local control over types of data collected/reports generated, (2) timely data (eg, up-to-date data, not several months old), and accordingly (3) the ability to efficiently monitor and improve patient outcomes. This article describes a quality improvement project at the hospital system level to develop and implement a flexible panel management (PM) tool to improve care of subpopulations of patients (eg, panels of patients with diabetes) by clinical teams. An in-depth case analysis approach is used to explore barriers and facilitators in building a PM registry tool for team-based management needs using standard data elements (eg, laboratory values, pharmacy records) found in EHRs. Also described are factors that may contribute to sustainability; to date the tool has been adapted to 6 disease-focused subpopulations encompassing more than 200,000 patients. Two key lessons emerged from this initiative: (1) though challenging, team-based clinical end users and information technology needed to work together consistently to refine the product, and (2) locally developed population management tools can provide efficient data tracking for frontline clinical teams and leadership. The preliminary work identified critical gaps that were successfully addressed by building local PM registry tools from EHR-derived data and offers lessons learned for others engaged in similar work. (Population Health Management 2016;19:232-239).

A case study comparison of landfire fuel loading and emissions generation on a mixed conifer forest in northern Idaho, USA

Treesearch

Josh Hyde; Eva K. Strand; Andrew T. Hudak; Dale Hamilton

2015-01-01

The use of fire as a land management tool is well recognized for its ecological benefits in many natural systems. To continue to use fire while complying with air quality regulations, land managers are often tasked with modeling emissions from fire during the planning process. To populate such models, the Landscape Fire and Resource Management Planning Tools (...

Agile Model Driven Development of Electronic Health Record-Based Specialty Population Registries

PubMed Central

Kannan, Vaishnavi; Fish, Jason C.; Willett, DuWayne L.

2018-01-01

The transformation of the American healthcare payment system from fee-for-service to value-based care increasingly makes it valuable to develop patient registries for specialized populations, to better assess healthcare quality and costs. Recent widespread adoption of Electronic Health Records (EHRs) in the U.S. now makes possible construction of EHR-based specialty registry data collection tools and reports, previously unfeasible using manual chart abstraction. But the complexities of specialty registry EHR tools and measures, along with the variety of stakeholders involved, can result in misunderstood requirements and frequent product change requests, as users first experience the tools in their actual clinical workflows. Such requirements churn could easily stall progress in specialty registry rollout. Modeling a system’s requirements and solution design can be a powerful way to remove ambiguities, facilitate shared understanding, and help evolve a design to meet newly-discovered needs. “Agile Modeling” retains these values while avoiding excessive unused up-front modeling in favor of iterative incremental modeling. Using Agile Modeling principles and practices, in calendar year 2015 one institution developed 58 EHR-based specialty registries, with 111 new data collection tools, supporting 134 clinical process and outcome measures, and enrolling over 16,000 patients. The subset of UML and non-UML models found most consistently useful in designing, building, and iteratively evolving EHR-based specialty registries included User Stories, Domain Models, Use Case Diagrams, Decision Trees, Graphical User Interface Storyboards, Use Case text descriptions, and Solution Class Diagrams. PMID:29750222

Conceptual FOM design tool

NASA Astrophysics Data System (ADS)

Krause, Lee S.; Burns, Carla L.

2000-06-01

This paper discusses the research currently in progress to develop the Conceptual Federation Object Model Design Tool. The objective of the Conceptual FOM (C-FOM) Design Tool effort is to provide domain and subject matter experts, such as scenario developers, with automated support for understanding and utilizing available HLA simulation and other simulation assets during HLA Federation development. The C-FOM Design Tool will import Simulation Object Models from HLA reuse repositories, such as the MSSR, to populate the domain space that will contain all the objects and their supported interactions. In addition, the C-FOM tool will support the conversion of non-HLA legacy models into HLA- compliant models by applying proven abstraction techniques against the legacy models. Domain experts will be able to build scenarios based on the domain objects and interactions in both a text and graphical form and export a minimal FOM. The ability for domain and subject matter experts to effectively access HLA and non-HLA assets is critical to the long-term acceptance of the HLA initiative.

Predicting High Health Care Resource Utilization in a Single-payer Public Health Care System: Development and Validation of the High Resource User Population Risk Tool (HRUPoRT).

PubMed

Rosella, Laura C; Kornas, Kathy; Yao, Zhan; Manuel, Douglas G; Bornbaum, Catherine; Fransoo, Randall; Stukel, Therese

2017-11-17

A large proportion of health care spending is incurred by a small proportion of the population. Population-based health planning tools that consider both the clinical and upstream determinants of high resource users (HRU) of the health system are lacking. To develop and validate the High Resource User Population Risk Tool (HRUPoRT), a predictive model of adults that will become the top 5% of health care users over a 5-year period, based on self-reported clinical, sociodemographic, and health behavioral predictors in population survey data. The HRUPoRT model was developed in a prospective cohort design using the combined 2005 and 2007/2008 Canadian Community Health Surveys (CCHS) (N=58,617), and validated using the external 2009/2010 CCHS cohort (N=28,721). Health care utilization for each of the 5 years following CCHS interview date were determined by applying a person-centered costing algorithm to the linked health administrative databases. Discrimination and calibration of the model were assessed using c-statistic and Hosmer-Lemeshow (HL) χ statistic. The best prediction model for 5-year transition to HRU status included 12 predictors and had good discrimination (c-statistic=0.8213) and calibration (HL χ=18.71) in the development cohort. The model performed similarly in the validation cohort (c-statistic=0.8171; HL χ=19.95). The strongest predictors in the HRUPoRT model were age, perceived general health, and body mass index. HRUPoRT can accurately project the proportion of individuals in the population that will become a HRU over 5 years. HRUPoRT can be applied to inform health resource planning and prevention strategies at the community level.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0/.

Identifying currents in the gene pool for bacterial populations using an integrative approach.

PubMed

Tang, Jing; Hanage, William P; Fraser, Christophe; Corander, Jukka

2009-08-01

The evolution of bacterial populations has recently become considerably better understood due to large-scale sequencing of population samples. It has become clear that DNA sequences from a multitude of genes, as well as a broad sample coverage of a target population, are needed to obtain a relatively unbiased view of its genetic structure and the patterns of ancestry connected to the strains. However, the traditional statistical methods for evolutionary inference, such as phylogenetic analysis, are associated with several difficulties under such an extensive sampling scenario, in particular when a considerable amount of recombination is anticipated to have taken place. To meet the needs of large-scale analyses of population structure for bacteria, we introduce here several statistical tools for the detection and representation of recombination between populations. Also, we introduce a model-based description of the shape of a population in sequence space, in terms of its molecular variability and affinity towards other populations. Extensive real data from the genus Neisseria are utilized to demonstrate the potential of an approach where these population genetic tools are combined with an phylogenetic analysis. The statistical tools introduced here are freely available in BAPS 5.2 software, which can be downloaded from http://web.abo.fi/fak/mnf/mate/jc/software/baps.html.

A DYNAMIC MODEL OF AN ESTUARINE INVASION BY A NON-NATIVE SEAGRASS

EPA Science Inventory

Mathematical and simulation models provide an excellent tool for examining and predicting biological invasions in time and space; however, traditional models do not incorporate dynamic rates of population growth, which limits their realism. We developed a spatially explicit simul...

Employing the clinical service unit model.

PubMed

Harger, J; Gualtieri-Reed, T; Burton, W

2001-01-01

Duke University Hospital has instituted a decision tool that enables administrators and medical directors to manage from both the operational (departmental) perspective as well as from the patient population perspective. The tool automates routine reporting, aligns business information with a new, cross-functional management structure, and provides a focus for improvement opportunities.

Model-based reasoning for system and software engineering: The Knowledge From Pictures (KFP) environment

NASA Technical Reports Server (NTRS)

Bailin, Sydney; Paterra, Frank; Henderson, Scott; Truszkowski, Walt

1993-01-01

This paper presents a discussion of current work in the area of graphical modeling and model-based reasoning being undertaken by the Automation Technology Section, Code 522.3, at Goddard. The work was initially motivated by the growing realization that the knowledge acquisition process was a major bottleneck in the generation of fault detection, isolation, and repair (FDIR) systems for application in automated Mission Operations. As with most research activities this work started out with a simple objective: to develop a proof-of-concept system demonstrating that a draft rule-base for a FDIR system could be automatically realized by reasoning from a graphical representation of the system to be monitored. This work was called Knowledge From Pictures (KFP) (Truszkowski et. al. 1992). As the work has successfully progressed the KFP tool has become an environment populated by a set of tools that support a more comprehensive approach to model-based reasoning. This paper continues by giving an overview of the graphical modeling objectives of the work, describing the three tools that now populate the KFP environment, briefly presenting a discussion of related work in the field, and by indicating future directions for the KFP environment.

Programming strategy for efficient modeling of dynamics in a population of heterogeneous cells.

PubMed

Hald, Bjørn Olav; Garkier Hendriksen, Morten; Sørensen, Preben Graae

2013-05-15

Heterogeneity is a ubiquitous property of biological systems. Even in a genetically identical population of a single cell type, cell-to-cell differences are observed. Although the functional behavior of a given population is generally robust, the consequences of heterogeneity are fairly unpredictable. In heterogeneous populations, synchronization of events becomes a cardinal problem-particularly for phase coherence in oscillating systems. The present article presents a novel strategy for construction of large-scale simulation programs of heterogeneous biological entities. The strategy is designed to be tractable, to handle heterogeneity and to handle computational cost issues simultaneously, primarily by writing a generator of the 'model to be simulated'. We apply the strategy to model glycolytic oscillations among thousands of yeast cells coupled through the extracellular medium. The usefulness is illustrated through (i) benchmarking, showing an almost linear relationship between model size and run time, and (ii) analysis of the resulting simulations, showing that contrary to the experimental situation, synchronous oscillations are surprisingly hard to achieve, underpinning the need for tools to study heterogeneity. Thus, we present an efficient strategy to model the biological heterogeneity, neglected by ordinary mean-field models. This tool is well posed to facilitate the elucidation of the physiologically vital problem of synchronization. The complete python code is available as Supplementary Information. bjornhald@gmail.com or pgs@kiku.dk Supplementary data are available at Bioinformatics online.

Incorporating evolutionary processes into population viability models.

PubMed

Pierson, Jennifer C; Beissinger, Steven R; Bragg, Jason G; Coates, David J; Oostermeijer, J Gerard B; Sunnucks, Paul; Schumaker, Nathan H; Trotter, Meredith V; Young, Andrew G

2015-06-01

We examined how ecological and evolutionary (eco-evo) processes in population dynamics could be better integrated into population viability analysis (PVA). Complementary advances in computation and population genomics can be combined into an eco-evo PVA to offer powerful new approaches to understand the influence of evolutionary processes on population persistence. We developed the mechanistic basis of an eco-evo PVA using individual-based models with individual-level genotype tracking and dynamic genotype-phenotype mapping to model emergent population-level effects, such as local adaptation and genetic rescue. We then outline how genomics can allow or improve parameter estimation for PVA models by providing genotypic information at large numbers of loci for neutral and functional genome regions. As climate change and other threatening processes increase in rate and scale, eco-evo PVAs will become essential research tools to evaluate the effects of adaptive potential, evolutionary rescue, and locally adapted traits on persistence. © 2014 Society for Conservation Biology.

Mouse Models for Drug Discovery. Can New Tools and Technology Improve Translational Power?

PubMed Central

Zuberi, Aamir; Lutz, Cathleen

2016-01-01

Abstract The use of mouse models in biomedical research and preclinical drug evaluation is on the rise. The advent of new molecular genome-altering technologies such as CRISPR/Cas9 allows for genetic mutations to be introduced into the germ line of a mouse faster and less expensively than previous methods. In addition, the rapid progress in the development and use of somatic transgenesis using viral vectors, as well as manipulations of gene expression with siRNAs and antisense oligonucleotides, allow for even greater exploration into genomics and systems biology. These technological advances come at a time when cost reductions in genome sequencing have led to the identification of pathogenic mutations in patient populations, providing unprecedented opportunities in the use of mice to model human disease. The ease of genetic engineering in mice also offers a potential paradigm shift in resource sharing and the speed by which models are made available in the public domain. Predictively, the knowledge alone that a model can be quickly remade will provide relief to resources encumbered by licensing and Material Transfer Agreements. For decades, mouse strains have provided an exquisite experimental tool to study the pathophysiology of the disease and assess therapeutic options in a genetically defined system. However, a major limitation of the mouse has been the limited genetic diversity associated with common laboratory mice. This has been overcome with the recent development of the Collaborative Cross and Diversity Outbred mice. These strains provide new tools capable of replicating genetic diversity to that approaching the diversity found in human populations. The Collaborative Cross and Diversity Outbred strains thus provide a means to observe and characterize toxicity or efficacy of new therapeutic drugs for a given population. The combination of traditional and contemporary mouse genome editing tools, along with the addition of genetic diversity in new modeling systems, are synergistic and serve to make the mouse a better model for biomedical research, enhancing the potential for preclinical drug discovery and personalized medicine. PMID:28053071

Assessing Breast Cancer Risk Estimates Based on the Gail Model and Its Predictors in Qatari Women.

PubMed

Bener, Abdulbari; Çatan, Funda; El Ayoubi, Hanadi R; Acar, Ahmet; Ibrahim, Wanis H

2017-07-01

The Gail model is the most widely used breast cancer risk assessment tool. An accurate assessment of individual's breast cancer risk is very important for prevention of the disease and for the health care providers to make decision on taking chemoprevention for high-risk women in clinical practice in Qatar. To assess the breast cancer risk among Arab women population in Qatar using the Gail model and provide a global comparison of risk assessment. In this cross-sectional study of 1488 women (aged 35 years and older), we used the Gail Risk Assessment Tool to assess the risk of developing breast cancer. Sociodemographic features such as age, lifestyle habits, body mass index, breast-feeding duration, consanguinity among parents, and family history of breast cancer were considered as possible risks. The mean age of the study population was 47.8 ± 10.8 years. Qatari women and Arab women constituted 64.7% and 35.3% of the study population, respectively. The mean 5-year and lifetime breast cancer risks were 1.12 ± 0.52 and 10.57 ± 3.1, respectively. Consanguineous marriage among parents was seen in 30.6% of participants. We found a relationship between the 5-year and lifetime risks of breast cancer and variables such as age, age at menarche, gravidity, parity, body mass index, family history of cancer, menopause age, occupation, and level of education. The linear regression analysis identified the predictors for breast cancer in women such as age, age at menarche, age of first birth, family history and age of menopausal were considered the strong predictors and significant contributing risk factors for breast cancer after adjusting for ethnicity, parity and other variables. The current study is the first to evaluate the performance of the Gail model for Arab women population in the Gulf Cooperation Council. Gail model is an appropriate breast cancer risk assessment tool for female population in Qatar.

eBird—Using citizen-science data to help solve real-world conservation challenges (Invited)

NASA Astrophysics Data System (ADS)

Sullivan, B. L.; Iliff, M. J.; Wood, C. L.; Fink, D.; Kelling, S.

2010-12-01

eBird (www.ebird.org) is an Internet-based citizen-science project that collects bird observations worldwide. eBird is foremost a tool for birders, providing users with a resource for bird information and a way to keep track of their personal bird lists, thus establishing a model for sustained participation and new project growth. Importantly, eBird data are shared with scientists and conservationists working to save birds and their habitats. Here we highlight two different ways these data are used: as a real-time data gathering and visualization tool; and as the primary resource for developing large-scale bird distribution models that explore species-habitat associations and climate change scenarios. eBird provides data across broad temporal and spatial scales, and is a valuable tool for documenting and monitoring bird populations facing a multitude of anthropogenic and environmental impacts. For example, a focused effort to monitor birds on Gulf Coast beaches using eBird is providing essential baseline data and enabling long-term monitoring of bird populations throughout the region. Additionally, new data visualization tools that incorporate data from eBird, NOAA, and Google, are specifically designed to highlight the potential impacts of the Gulf oil spill on bird populations. Through a collaboration of partners in the DataONE network, such as the Oak Ridge National Laboratory, we will use supercomputing time from the National Science Foundation’s TeraGrid to allow Lab scientists to model bird migration phenology at the population level based on eBird data. The process involves combining bird observations with remotely sensed variables such as landcover and greening index to predict bird movements. Preliminary results of these models allow us to animate bird movements across large spatial scales, and to explore how migration timing might be affected under different climate change scenarios.

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.

Predictive models to assess risk of type 2 diabetes, hypertension and comorbidity: machine-learning algorithms and validation using national health data from Kuwait—a cohort study

PubMed Central

Farran, Bassam; Channanath, Arshad Mohamed; Behbehani, Kazem; Thanaraj, Thangavel Alphonse

2013-01-01

Objective We build classification models and risk assessment tools for diabetes, hypertension and comorbidity using machine-learning algorithms on data from Kuwait. We model the increased proneness in diabetic patients to develop hypertension and vice versa. We ascertain the importance of ethnicity (and natives vs expatriate migrants) and of using regional data in risk assessment. Design Retrospective cohort study. Four machine-learning techniques were used: logistic regression, k-nearest neighbours (k-NN), multifactor dimensionality reduction and support vector machines. The study uses fivefold cross validation to obtain generalisation accuracies and errors. Setting Kuwait Health Network (KHN) that integrates data from primary health centres and hospitals in Kuwait. Participants 270 172 hospital visitors (of which, 89 858 are diabetic, 58 745 hypertensive and 30 522 comorbid) comprising Kuwaiti natives, Asian and Arab expatriates. Outcome measures Incident type 2 diabetes, hypertension and comorbidity. Results Classification accuracies of >85% (for diabetes) and >90% (for hypertension) are achieved using only simple non-laboratory-based parameters. Risk assessment tools based on k-NN classification models are able to assign ‘high’ risk to 75% of diabetic patients and to 94% of hypertensive patients. Only 5% of diabetic patients are seen assigned ‘low’ risk. Asian-specific models and assessments perform even better. Pathological conditions of diabetes in the general population or in hypertensive population and those of hypertension are modelled. Two-stage aggregate classification models and risk assessment tools, built combining both the component models on diabetes (or on hypertension), perform better than individual models. Conclusions Data on diabetes, hypertension and comorbidity from the cosmopolitan State of Kuwait are available for the first time. This enabled us to apply four different case–control models to assess risks. These tools aid in the preliminary non-intrusive assessment of the population. Ethnicity is seen significant to the predictive models. Risk assessments need to be developed using regional data as we demonstrate the applicability of the American Diabetes Association online calculator on data from Kuwait. PMID:23676796

Assessment of dysglycemia risk in the Kitikmeot region of Nunavut: using the CANRISK tool

PubMed Central

Ying, Jiang; Susan, Rogers Van Katwyk; Yang, Mao; Heather, Orpana; Gina, Agarwal; Margaret, de Groh; Monique, Skinner; Robyn, Clarke

2017-01-01

Abstract Introduction: The Public Health Agency of Canada adapted a Finnish diabetes screening tool (FINDRISC) to create a tool (CANRISK) tailored to Canada’s multi-ethnic population. CANRISK was developed using data collected in seven Canadian provinces. In an effort to extend the applicability of CANRISK to northern territorial populations, we completed a study with the mainly Inuit population in the Kitikmeot region of Nunavut. Methods: We obtained CANRISK questionnaires, physical measures and blood samples from participants in five Nunavut communities in Kitikmeot. We used logistic regression to test model fit using the original CANRISK risk factors for dysglycemia (prediabetes and diabetes). Dysglycemia was assessed using fasting plasma glucose (FPG) alone and/or oral glucose tolerance test. We generated participants’ CANRISK scores to test the functioning of this tool in the Inuit population. Results: A total of 303 individuals participated in the study. Half were aged less than 45 years, two-thirds were female and 84% were Inuit. A total of 18% had prediabetes, and an additional 4% had undiagnosed diabetes. The odds of having dysglycemia rose exponentially with age, while the relationship with BMI was U-shaped. Compared with lab test results, using a cut-off point of 32 the CANRISK tool achieved a sensitivity of 61%, a specificity of 66%, a positive predictive value of 34% and an accuracy rate of 65%. Conclusion: The CANRISK tool achieved a similar accuracy in detecting dysglycemia in this mainly Inuit population as it did in a multi-ethnic sample of Canadians. We found the CANRISK tool to be adaptable to the Kitikmeot region, and more generally to Nunavut. PMID:28402800

Emergencies planning and response: Coupling an exposure model with different atmospheric dispersion models

NASA Astrophysics Data System (ADS)

Sanchez, E. Y.; Colman Lerner, J. E.; Porta, A.; Jacovkis, P. M.

2013-11-01

Information on spatial and time dependent concentration patterns of hazardous substances, as well as on the potential effects on population, is necessary to assist in chemical emergency planning and response. To that end, some models predict transport and dispersion of hazardous substances, and others estimate potential effects upon exposed population. Taken together, both groups constitute a powerful tool to estimate vulnerable regions and to evaluate environmental impact upon affected populations. The development of methodologies and models with direct application to the context in which we live allows us to draft a more clear representation of the risk scenario and, hence, to obtain the adequate tools for an optimal response. By means of the recently developed DDC (Damage Differential Coupling) exposure model, it was possible to optimize, from both the qualitative and the quantitative points of view, the estimation of the population affected by a toxic cloud, because the DDC model has a very good capacity to couple with different atmospheric dispersion models able to provide data over time. In this way, DDC analyzes the different concentration profiles (output from the transport model) associating them with some reference concentration to identify risk zones. In this work we present a disaster scenario in Chicago (USA), by coupling DDC with two transport models of different complexity, showing the close relationship between a representative result and the run time of the models. In the same way, it becomes evident that knowing the time evolution of the toxic cloud and of the affected regions significantly improves the probability of taking the correct decisions on planning and response facing the emergency.

FITPOP, a heuristic simulation model of population dynamics and genetics with special reference to fisheries

USGS Publications Warehouse

McKenna, James E.

2000-01-01

Although, perceiving genetic differences and their effects on fish population dynamics is difficult, simulation models offer a means to explore and illustrate these effects. I partitioned the intrinsic rate of increase parameter of a simple logistic-competition model into three components, allowing specification of effects of relative differences in fitness and mortality, as well as finite rate of increase. This model was placed into an interactive, stochastic environment to allow easy manipulation of model parameters (FITPOP). Simulation results illustrated the effects of subtle differences in genetic and population parameters on total population size, overall fitness, and sensitivity of the system to variability. Several consequences of mixing genetically distinct populations were illustrated. For example, behaviors such as depression of population size after initial introgression and extirpation of native stocks due to continuous stocking of genetically inferior fish were reproduced. It also was shown that carrying capacity relative to the amount of stocking had an important influence on population dynamics. Uncertainty associated with parameter estimates reduced confidence in model projections. The FITPOP model provided a simple tool to explore population dynamics, which may assist in formulating management strategies and identifying research needs.

Combination of a higher-tier flow-through system and population modeling to assess the effects of time-variable exposure of isoproturon on the green algae Desmodesmus subspicatus and Pseudokirchneriella subcapitata.

PubMed

Weber, Denis; Schaefer, Dieter; Dorgerloh, Michael; Bruns, Eric; Goerlitz, Gerhard; Hammel, Klaus; Preuss, Thomas G; Ratte, Hans Toni

2012-04-01

A flow-through system was developed to investigate the effects of time-variable exposure of pesticides on algae. A recently developed algae population model was used for simulations supported and verified by laboratory experiments. Flow-through studies with Desmodesmus subspicatus and Pseudokirchneriella subcapitata under time-variable exposure to isoproturon were performed, in which the exposure patterns were based on the results of FOrum for Co-ordination of pesticide fate models and their USe (FOCUS) model calculations for typical exposure situations via runoff or drain flow. Different types of pulsed exposure events were realized, including a whole range of repeated pulsed and steep peaks as well as periods of constant exposure. Both species recovered quickly in terms of growth from short-term exposure and according to substance dissipation from the system. Even at a peak 10 times the maximum predicted environmental concentration of isoproturon, only transient effects occurred on algae populations. No modified sensitivity or reduced growth was observed after repeated exposure. Model predictions of algal growth in the flow-through tests agreed well with the experimental data. The experimental boundary conditions and the physiological properties of the algae were used as the only model input. No calibration or parameter fitting was necessary. The combination of the flow-through experiments with the algae population model was revealed to be a powerful tool for the assessment of pulsed exposure on algae. It allowed investigating the growth reduction and recovery potential of algae after complex exposure, which is not possible with standard laboratory experiments alone. The results of the combined approach confirm the beneficial use of population models as supporting tools in higher-tier risk assessments of pesticides. Copyright © 2012 SETAC.

Cell lineage tracing in the developing enteric nervous system: superstars revealed by experiment and simulation

PubMed Central

Cheeseman, Bevan L.; Zhang, Dongcheng; Binder, Benjamin J.; Newgreen, Donald F.; Landman, Kerry A.

2014-01-01

Cell lineage tracing is a powerful tool for understanding how proliferation and differentiation of individual cells contribute to population behaviour. In the developing enteric nervous system (ENS), enteric neural crest (ENC) cells move and undergo massive population expansion by cell division within self-growing mesenchymal tissue. We show that single ENC cells labelled to follow clonality in the intestine reveal extraordinary and unpredictable variation in number and position of descendant cells, even though ENS development is highly predictable at the population level. We use an agent-based model to simulate ENC colonization and obtain agent lineage tracing data, which we analyse using econometric data analysis tools. In all realizations, a small proportion of identical initial agents accounts for a substantial proportion of the total final agent population. We term these individuals superstars. Their existence is consistent across individual realizations and is robust to changes in model parameters. This inequality of outcome is amplified at elevated proliferation rate. The experiments and model suggest that stochastic competition for resources is an important concept when understanding biological processes which feature high levels of cell proliferation. The results have implications for cell-fate processes in the ENS. PMID:24501272

Modeling persistence of motion in a crowded environment: The diffusive limit of excluding velocity-jump processes

NASA Astrophysics Data System (ADS)

Gavagnin, Enrico; Yates, Christian A.

2018-03-01

Persistence of motion is the tendency of an object to maintain motion in a direction for short time scales without necessarily being biased in any direction in the long term. One of the most appropriate mathematical tools to study this behavior is an agent-based velocity-jump process. In the absence of agent-agent interaction, the mean-field continuum limit of the agent-based model (ABM) gives rise to the well known hyperbolic telegraph equation. When agent-agent interaction is included in the ABM, a strictly advective system of partial differential equations (PDEs) can be derived at the population level. However, no diffusive limit of the ABM has been obtained from such a model. Connecting the microscopic behavior of the ABM to a diffusive macroscopic description is desirable, since it allows the exploration of a wider range of scenarios and establishes a direct connection with commonly used statistical tools of movement analysis. In order to connect the ABM at the population level to a diffusive PDE at the population level, we consider a generalization of the agent-based velocity-jump process on a two-dimensional lattice with three forms of agent interaction. This generalization allows us to take a diffusive limit and obtain a faithful population-level description. We investigate the properties of the model at both the individual and population levels and we elucidate some of the models' key characteristic features. In particular, we show an intrinsic anisotropy inherent to the models and we find evidence of a spontaneous form of aggregation at both the micro- and macroscales.

Multi-locus mixed model analysis of stem rust resistance in a worldwide collection of winter wheat

USDA-ARS?s Scientific Manuscript database

Genome-wide association mapping is a powerful tool for dissecting the relationship between phenotypes and genetic variants in diverse populations. With improved cost efficiency of high-throughput genotyping platforms, association mapping is a desirable method to mine populations for favorable allele...

Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth.

PubMed

Poleszczuk, Jan; Macklin, Paul; Enderling, Heiko

2016-01-01

Computational modeling of tumor growth has become an invaluable tool to simulate complex cell-cell interactions and emerging population-level dynamics. Agent-based models are commonly used to describe the behavior and interaction of individual cells in different environments. Behavioral rules can be informed and calibrated by in vitro assays, and emerging population-level dynamics may be validated with both in vitro and in vivo experiments. Here, we describe the design and implementation of a lattice-based agent-based model of cancer stem cell driven tumor growth.

The Population Tracking Model: A Simple, Scalable Statistical Model for Neural Population Data

PubMed Central

O'Donnell, Cian; alves, J. Tiago Gonç; Whiteley, Nick; Portera-Cailliau, Carlos; Sejnowski, Terrence J.

2017-01-01

Our understanding of neural population coding has been limited by a lack of analysis methods to characterize spiking data from large populations. The biggest challenge comes from the fact that the number of possible network activity patterns scales exponentially with the number of neurons recorded (∼2Neurons). Here we introduce a new statistical method for characterizing neural population activity that requires semi-independent fitting of only as many parameters as the square of the number of neurons, requiring drastically smaller data sets and minimal computation time. The model works by matching the population rate (the number of neurons synchronously active) and the probability that each individual neuron fires given the population rate. We found that this model can accurately fit synthetic data from up to 1000 neurons. We also found that the model could rapidly decode visual stimuli from neural population data from macaque primary visual cortex about 65 ms after stimulus onset. Finally, we used the model to estimate the entropy of neural population activity in developing mouse somatosensory cortex and, surprisingly, found that it first increases, and then decreases during development. This statistical model opens new options for interrogating neural population data and can bolster the use of modern large-scale in vivo Ca2+ and voltage imaging tools. PMID:27870612

Data for Environmental Modeling (D4EM): Background and Applications of Data Automation

EPA Science Inventory

The Data for Environmental Modeling (D4EM) project demonstrates the development of a comprehensive set of open source software tools that overcome obstacles to accessing data needed by automating the process of populating model input data sets with environmental data available fr...

Comparing listeriosis risks in at-risk populations using a user-friendly quantitative microbial risk assessment tool and epidemiological data.

PubMed

Falk, L E; Fader, K A; Cui, D S; Totton, S C; Fazil, A M; Lammerding, A M; Smith, B A

2016-10-01

Although infection by the pathogenic bacterium Listeria monocytogenes is relatively rare, consequences can be severe, with a high case-fatality rate in vulnerable populations. A quantitative, probabilistic risk assessment tool was developed to compare estimates of the number of invasive listeriosis cases in vulnerable Canadian subpopulations given consumption of contaminated ready-to-eat delicatessen meats and hot dogs, under various user-defined scenarios. The model incorporates variability and uncertainty through Monte Carlo simulation. Processes considered within the model include cross-contamination, growth, risk factor prevalence, subpopulation susceptibilities, and thermal inactivation. Hypothetical contamination events were simulated. Results demonstrated varying risk depending on the consumer risk factors and implicated product (turkey delicatessen meat without growth inhibitors ranked highest for this scenario). The majority (80%) of listeriosis cases were predicted in at-risk subpopulations comprising only 20% of the total Canadian population, with the greatest number of predicted cases in the subpopulation with dialysis and/or liver disease. This tool can be used to simulate conditions and outcomes under different scenarios, such as a contamination event and/or outbreak, to inform public health interventions.

Simulating the Performance of Ground-Based Optical Asteroid Surveys

NASA Astrophysics Data System (ADS)

Christensen, Eric J.; Shelly, Frank C.; Gibbs, Alex R.; Grauer, Albert D.; Hill, Richard E.; Johnson, Jess A.; Kowalski, Richard A.; Larson, Stephen M.

2014-11-01

We are developing a set of asteroid survey simulation tools in order to estimate the capability of existing and planned ground-based optical surveys, and to test a variety of possible survey cadences and strategies. The survey simulator is composed of several layers, including a model population of solar system objects and an orbital integrator, a site-specific atmospheric model (including inputs for seeing, haze and seasonal cloud cover), a model telescope (with a complete optical path to estimate throughput), a model camera (including FOV, pixel scale, and focal plane fill factor) and model source extraction and moving object detection layers with tunable detection requirements. We have also developed a flexible survey cadence planning tool to automatically generate nightly survey plans. Inputs to the cadence planner include camera properties (FOV, readout time), telescope limits (horizon, declination, hour angle, lunar and zenithal avoidance), preferred and restricted survey regions in RA/Dec, ecliptic, and Galactic coordinate systems, and recent coverage by other asteroid surveys. Simulated surveys are created for a subset of current and previous NEO surveys (LINEAR, Pan-STARRS and the three Catalina Sky Survey telescopes), and compared against the actual performance of these surveys in order to validate the model’s performance. The simulator tracks objects within the FOV of any pointing that were not discovered (e.g. too few observations, too trailed, focal plane array gaps, too fast or slow), thus dividing the population into “discoverable” and “discovered” subsets, to inform possible survey design changes. Ongoing and future work includes generating a realistic “known” subset of the model NEO population, running multiple independent simulated surveys in coordinated and uncoordinated modes, and testing various cadences to find optimal strategies for detecting NEO sub-populations. These tools can also assist in quantifying the efficiency of novel yet unverified survey cadences (e.g. the baseline LSST cadence) that sparsely spread the observations required for detection over several days or weeks.

Health System Advance Care Planning Culture Change for High-Risk Patients: The Promise and Challenges of Engaging Providers, Patients, and Families in Systematic Advance Care Planning.

PubMed

Reidy, Jennifer; Halvorson, Jennifer; Makowski, Suzana; Katz, Delila; Weinstein, Barbara; McCluskey, Christine; Doering, Alex; DeCarli, Kathryn; Tjia, Jennifer

2017-04-01

The success of a facilitator-based model for advance care planning (ACP) in LaCrosse, Wisconsin, has inspired health systems to aim for widespread documentation of advance directives, but limited resources impair efforts to replicate this model. One promising strategy is the development of interactive, Internet-based tools that might increase access to individualized ACP at minimal cost. However, widespread adoption and implementation of Internet-based ACP efforts has yet to be described. We describe our early experiences in building a systematic, population-based ACP initiative focused on health system-wide deployment of an Internet-based tool as an adjunct to a facilitator-based model. With the sponsorship of our healthcare system's population health leadership, we engaged a diverse group of clinical stakeholders as champions to design an Internet-based ACP tool and facilitate local practice change. We describe how we simultaneously began to train clinicians in ACP conversations, engage patients and health system employees in thinking about ACP, redesign clinic workflows to accommodate ACP discussions, and integrate the Internet-based tool into the electronic medical record (EMR). Over 18 months, our project engaged two subspecialty clinics in a systematic ACP process and began work with a large primary care practice with a large Medicare Accountable Care Organization at-risk population. Overall, 807 people registered at the Internet site and 85% completed ACPs. We learned that changing culture and systems to promote ACP requires a comprehensive vision with simultaneous, interconnected strategies targeting patient education, clinician training, EMR documentation, and community awareness.

Augmenting Predictive Modeling Tools with Clinical Insights for Care Coordination Program Design and Implementation.

PubMed

Johnson, Tracy L; Brewer, Daniel; Estacio, Raymond; Vlasimsky, Tara; Durfee, Michael J; Thompson, Kathy R; Everhart, Rachel M; Rinehart, Deborath J; Batal, Holly

2015-01-01

The Center for Medicare and Medicaid Innovation (CMMI) awarded Denver Health's (DH) integrated, safety net health care system $19.8 million to implement a "population health" approach into the delivery of primary care. This major practice transformation builds on the Patient Centered Medical Home (PCMH) and Wagner's Chronic Care Model (CCM) to achieve the "Triple Aim": improved health for populations, care to individuals, and lower per capita costs. This paper presents a case study of how DH integrated published predictive models and front-line clinical judgment to implement a clinically actionable, risk stratification of patients. This population segmentation approach was used to deploy enhanced care team staff resources and to tailor care-management services to patient need, especially for patients at high risk of avoidable hospitalization. Developing, implementing, and gaining clinical acceptance of the Health Information Technology (HIT) solution for patient risk stratification was a major grant objective. In addition to describing the Information Technology (IT) solution itself, we focus on the leadership and organizational processes that facilitated its multidisciplinary development and ongoing iterative refinement, including the following: team composition, target population definition, algorithm rule development, performance assessment, and clinical-workflow optimization. We provide examples of how dynamic business intelligence tools facilitated clinical accessibility for program design decisions by enabling real-time data views from a population perspective down to patient-specific variables. We conclude that population segmentation approaches that integrate clinical perspectives with predictive modeling results can better identify high opportunity patients amenable to medical home-based, enhanced care team interventions.

Irena : tool suite for modeling and analysis of small-angle scattering.

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

Ilavsky, J.; Jemian, P.

2009-04-01

Irena, a tool suite for analysis of both X-ray and neutron small-angle scattering (SAS) data within the commercial Igor Pro application, brings together a comprehensive suite of tools useful for investigations in materials science, physics, chemistry, polymer science and other fields. In addition to Guinier and Porod fits, the suite combines a variety of advanced SAS data evaluation tools for the modeling of size distribution in the dilute limit using maximum entropy and other methods, dilute limit small-angle scattering from multiple non-interacting populations of scatterers, the pair-distance distribution function, a unified fit, the Debye-Bueche model, the reflectivity (X-ray and neutron)more » using Parratt's formalism, and small-angle diffraction. There are also a number of support tools, such as a data import/export tool supporting a broad sampling of common data formats, a data modification tool, a presentation-quality graphics tool optimized for small-angle scattering data, and a neutron and X-ray scattering contrast calculator. These tools are brought together into one suite with consistent interfaces and functionality. The suite allows robust automated note recording and saving of parameters during export.« less

Target prioritization and strategy selection for active case-finding of pulmonary tuberculosis: a tool to support country-level project planning.

PubMed

Nishikiori, Nobuyuki; Van Weezenbeek, Catharina

2013-02-02

Despite the progress made in the past decade, tuberculosis (TB) control still faces significant challenges. In many countries with declining TB incidence, the disease tends to concentrate in vulnerable populations that often have limited access to health care. In light of the limitations of the current case-finding approach and the global urgency to improve case detection, active case-finding (ACF) has been suggested as an important complementary strategy to accelerate tuberculosis control especially among high-risk populations. The present exercise aims to develop a model that can be used for county-level project planning. A simple deterministic model was developed to calculate the number of estimated TB cases diagnosed and the associated costs of diagnosis. The model was designed to compare cost-effectiveness parameters, such as the cost per case detected, for different diagnostic algorithms when they are applied to different risk populations. The model was transformed into a web-based tool that can support national TB programmes and civil society partners in designing ACF activities. According to the model output, tuberculosis active case-finding can be a costly endeavor, depending on the target population and the diagnostic strategy. The analysis suggests the following: (1) Active case-finding activities are cost-effective only if the tuberculosis prevalence among the target population is high. (2) Extensive diagnostic methods (e.g. X-ray screening for the entire group, use of sputum culture or molecular diagnostics) can be applied only to very high-risk groups such as TB contacts, prisoners or people living with human immunodeficiency virus (HIV) infection. (3) Basic diagnostic approaches such as TB symptom screening are always applicable although the diagnostic yield is very limited. The cost-effectiveness parameter was sensitive to local diagnostic costs and the tuberculosis prevalence of target populations. The prioritization of appropriate target populations and careful selection of cost-effective diagnostic strategies are critical prerequisites for rational active case-finding activities. A decision to conduct such activities should be based on the setting-specific cost-effectiveness analysis and programmatic assessment. A web-based tool was developed and is available to support national tuberculosis programmes and partners in the formulation of cost-effective active case-finding activities at the national and subnational levels.

The use of the Dutch Self-Sufficiency Matrix (SSM-D) to inform allocation decisions to public mental health care for homeless people.

PubMed

Lauriks, Steve; de Wit, Matty A S; Buster, Marcel C A; Fassaert, Thijs J L; van Wifferen, Ron; Klazinga, Niek S

2014-10-01

The current study set out to develop a decision support tool based on the Self-Sufficiency Matrix (Dutch version; SSM-D) for the clinical decision to allocate homeless people to the public mental health care system at the central access point of public mental health care in Amsterdam, The Netherlands. Logistic regression and receiver operating characteristic-curve analyses were used to model professional decisions and establish four decision categories based on SSM-D scores from half of the research population (Total n = 612). The model and decision categories were found to be accurate and reliable in predicting professional decisions in the second half of the population. Results indicate that the decision support tool based on the SSM-D is useful and feasible. The method to develop the SSM-D as a decision support tool could be applied to decision-making processes in other systems and services where the SSM-D has been implemented, to further increase the utility of the instrument.

A Gompertz population model with Allee effect and fuzzy initial values

NASA Astrophysics Data System (ADS)

Amarti, Zenia; Nurkholipah, Nenden Siti; Anggriani, Nursanti; Supriatna, Asep K.

2018-03-01

Growth and population dynamics models are important tools used in preparing a good management for society to predict the future of population or species. This has been done by various known methods, one among them is by developing a mathematical model that describes population growth. Models are usually formed into differential equations or systems of differential equations, depending on the complexity of the underlying properties of the population. One example of biological complexity is Allee effect. It is a phenomenon showing a high correlation between very small population size and the mean individual fitness of the population. In this paper the population growth model used is the Gompertz equation model by considering the Allee effect on the population. We explore the properties of the solution to the model numerically using the Runge-Kutta method. Further exploration is done via fuzzy theoretical approach to accommodate uncertainty of the initial values of the model. It is known that an initial value greater than the Allee threshold will cause the solution rises towards carrying capacity asymptotically. However, an initial value smaller than the Allee threshold will cause the solution decreases towards zero asymptotically, which means the population is eventually extinct. Numerical solutions show that modeling uncertain initial value of the critical point A (the Allee threshold) with a crisp initial value could cause the extinction of population of a certain possibilistic degree, depending on the predetermined membership function of the initial value.

Resource development in otolaryngology-head and neck surgery: an analysis on patient education resource development.

PubMed

Goldfarb, Jeremy; Gupta, Vishaal; Sampson, Heather; Chiodo, Albino

2014-01-01

There is a need for educational tools in the consenting process of otolaryngology-head and neck procedures. A development strategy for the creation of educational tools in otolaryngology-head and neck surgery, particularly pamphlets on the peri-operative period in an adenotonsillectomy, is described. A participatory design approach, which engages key stakeholders in the development of an educational tool, is used. Pamphlets were created through a review of traditional and grey literature and then reviewed by a community expert in the field. The pamphlets were then reviewed by an interdisciplinary team including educational experts, and finally by less vulnerable members of the target population. Questionnaires evaluating the pamphlets' content, layout, style, and general qualitative features were included. The pamphlets yielded high ratings across all domains regardless of patient population. General feedback was provided by a non-vulnerable patient population and final pamphlets were drafted. By using a participatory design model, the pamphlets are written at an appropriate educational level to incorporate a broad audience. Furthermore, this methodology can be used in future resource development of educational tools.

Resource development in otolaryngology-head and neck surgery: an analysis on patient education resource development

PubMed Central

2014-01-01

Background There is a need for educational tools in the consenting process of otolaryngology-head and neck procedures. A development strategy for the creation of educational tools in otolaryngology-head and neck surgery, particularly pamphlets on the peri-operative period in an adenotonsillectomy, is described. Methods A participatory design approach, which engages key stakeholders in the development of an educational tool, is used. Pamphlets were created through a review of traditional and grey literature and then reviewed by a community expert in the field. The pamphlets were then reviewed by an interdisciplinary team including educational experts, and finally by less vulnerable members of the target population. Questionnaires evaluating the pamphlets’ content, layout, style, and general qualitative features were included. Results The pamphlets yielded high ratings across all domains regardless of patient population. General feedback was provided by a non-vulnerable patient population and final pamphlets were drafted. Conclusions By using a participatory design model, the pamphlets are written at an appropriate educational level to incorporate a broad audience. Furthermore, this methodology can be used in future resource development of educational tools. PMID:25022351

Implementation of Structured Inquiry Based Model Learning toward Students' Understanding of Geometry

ERIC Educational Resources Information Center

Salim, Kalbin; Tiawa, Dayang Hjh

2015-01-01

The purpose of this study is implementation of a structured inquiry learning model in instruction of geometry. The model used is a model with a quasi-experimental study amounted to two classes of samples selected from the population of the ten classes with cluster random sampling technique. Data collection tool consists of a test item…

Numeric, Agent-based or System Dynamics Model? Which Modeling Approach is the Best for Vast Population Simulation?

PubMed

Cimler, Richard; Tomaskova, Hana; Kuhnova, Jitka; Dolezal, Ondrej; Pscheidl, Pavel; Kuca, Kamil

2018-01-01

Alzheimer's disease is one of the most common mental illnesses. It is posited that more than 25% of the population is affected by some mental disease during their lifetime. Treatment of each patient draws resources from the economy concerned. Therefore, it is important to quantify the potential economic impact. Agent-based, system dynamics and numerical approaches to dynamic modeling of the population of the European Union and its patients with Alzheimer's disease are presented in this article. Simulations, their characteristics, and the results from different modeling tools are compared. The results of these approaches are compared with EU population growth predictions from the statistical office of the EU by Eurostat. The methodology of a creation of the models is described and all three modeling approaches are compared. The suitability of each modeling approach for the population modeling is discussed. In this case study, all three approaches gave us the results corresponding with the EU population prediction. Moreover, we were able to predict the number of patients with AD and, based on the modeling method, we were also able to monitor different characteristics of the population. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks.

PubMed

Jenness, Samuel M; Goodreau, Steven M; Morris, Martina

2018-04-01

Package EpiModel provides tools for building, simulating, and analyzing mathematical models for the population dynamics of infectious disease transmission in R. Several classes of models are included, but the unique contribution of this software package is a general stochastic framework for modeling the spread of epidemics on networks. EpiModel integrates recent advances in statistical methods for network analysis (temporal exponential random graph models) that allow the epidemic modeling to be grounded in empirical data on contacts that can spread infection. This article provides an overview of both the modeling tools built into EpiModel , designed to facilitate learning for students new to modeling, and the application programming interface for extending package EpiModel , designed to facilitate the exploration of novel research questions for advanced modelers.

EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks

PubMed Central

Jenness, Samuel M.; Goodreau, Steven M.; Morris, Martina

2018-01-01

Package EpiModel provides tools for building, simulating, and analyzing mathematical models for the population dynamics of infectious disease transmission in R. Several classes of models are included, but the unique contribution of this software package is a general stochastic framework for modeling the spread of epidemics on networks. EpiModel integrates recent advances in statistical methods for network analysis (temporal exponential random graph models) that allow the epidemic modeling to be grounded in empirical data on contacts that can spread infection. This article provides an overview of both the modeling tools built into EpiModel, designed to facilitate learning for students new to modeling, and the application programming interface for extending package EpiModel, designed to facilitate the exploration of novel research questions for advanced modelers. PMID:29731699

Idea Bank.

ERIC Educational Resources Information Center

Bisbee, Gregory D.; Fritz, Jane K.; Zurenda, Deb

1997-01-01

Presents three science activities: (1) Pizza Quadrants, a tool for estimating population size; (2) Ion Models, to assist students in understanding how to balance equations; and (3) Endangered Species Project, an interdisciplinary unit. (DDR)

A Predictive Model for Readmissions Among Medicare Patients in a California Hospital.

PubMed

Duncan, Ian; Huynh, Nhan

2017-11-17

Predictive models for hospital readmission rates are in high demand because of the Centers for Medicare & Medicaid Services (CMS) Hospital Readmission Reduction Program (HRRP). The LACE index is one of the most popular predictive tools among hospitals in the United States. The LACE index is a simple tool with 4 parameters: Length of stay, Acuity of admission, Comorbidity, and Emergency visits in the previous 6 months. The authors applied logistic regression to develop a predictive model for a medium-sized not-for-profit community hospital in California using patient-level data with more specific patient information (including 13 explanatory variables). Specifically, the logistic regression is applied to 2 populations: a general population including all patients and the specific group of patients targeted by the CMS penalty (characterized as ages 65 or older with select conditions). The 2 resulting logistic regression models have a higher sensitivity rate compared to the sensitivity of the LACE index. The C statistic values of the model applied to both populations demonstrate moderate levels of predictive power. The authors also build an economic model to demonstrate the potential financial impact of the use of the model for targeting high-risk patients in a sample hospital and demonstrate that, on balance, whether the hospital gains or loses from reducing readmissions depends on its margin and the extent of its readmission penalties.

A malaria transmission-directed model of mosquito life cycle and ecology

PubMed Central

2011-01-01

Background Malaria is a major public health issue in much of the world, and the mosquito vectors which drive transmission are key targets for interventions. Mathematical models for planning malaria eradication benefit from detailed representations of local mosquito populations, their natural dynamics and their response to campaign pressures. Methods A new model is presented for mosquito population dynamics, effects of weather, and impacts of multiple simultaneous interventions. This model is then embedded in a large-scale individual-based simulation and results for local elimination of malaria are discussed. Mosquito population behaviours, such as anthropophily and indoor feeding, are included to study their effect upon the efficacy of vector control-based elimination campaigns. Results Results for vector control tools, such as bed nets, indoor spraying, larval control and space spraying, both alone and in combination, are displayed for a single-location simulation with vector species and seasonality characteristic of central Tanzania, varying baseline transmission intensity and vector bionomics. The sensitivities to habitat type, anthropophily, indoor feeding, and baseline transmission intensity are explored. Conclusions The ability to model a spectrum of local vector species with different ecologies and behaviours allows local customization of packages of interventions and exploration of the effect of proposed new tools. PMID:21999664

Modeling of Tool-Tissue Interactions for Computer-Based Surgical Simulation: A Literature Review

PubMed Central

Misra, Sarthak; Ramesh, K. T.; Okamura, Allison M.

2009-01-01

Surgical simulators present a safe and potentially effective method for surgical training, and can also be used in robot-assisted surgery for pre- and intra-operative planning. Accurate modeling of the interaction between surgical instruments and organs has been recognized as a key requirement in the development of high-fidelity surgical simulators. Researchers have attempted to model tool-tissue interactions in a wide variety of ways, which can be broadly classified as (1) linear elasticity-based, (2) nonlinear (hyperelastic) elasticity-based finite element (FE) methods, and (3) other techniques that not based on FE methods or continuum mechanics. Realistic modeling of organ deformation requires populating the model with real tissue data (which are difficult to acquire in vivo) and simulating organ response in real time (which is computationally expensive). Further, it is challenging to account for connective tissue supporting the organ, friction, and topological changes resulting from tool-tissue interactions during invasive surgical procedures. Overcoming such obstacles will not only help us to model tool-tissue interactions in real time, but also enable realistic force feedback to the user during surgical simulation. This review paper classifies the existing research on tool-tissue interactions for surgical simulators specifically based on the modeling techniques employed and the kind of surgical operation being simulated, in order to inform and motivate future research on improved tool-tissue interaction models. PMID:20119508

HYDROLOGIC MODELING OF AN EASTERN PENNSYLVANIA WATERSHED WITH NEXRAD AND RAIN GAUGE DATA

EPA Science Inventory

This paper applies the Soil Water Assessment Tool (SWAT) to model the hydrology in the Pocono Creek watershed located in Monroe County, Pa. The calibrated model will be used in a subsequent study to examine the impact of population growth and rapid urbanization in the watershed o...

Recent progress in the theoretical modelling of Cepheids and RR Lyrae stars

NASA Astrophysics Data System (ADS)

Marconi, Marcella

2017-09-01

Cepheids and RR Lyrae are among the most important primary distance indicators to calibrate the extragalactic distance ladder and excellent stellar population tracers, for Population I and Population II, respectively. In this paper I first mention some recent theoretical studies of Cepheids and RR Lyrae obtained with different theoretical tools. Then I focus the attention on new results based on nonlinear convective pulsation models in the context of some international projects, including VMC@VISTA and the Gaia collaboration. The open problems for both Cepheids and RR Lyrae are briefly discussed together with some challenging future application.

Implications of Nine Risk Prediction Models for Selecting Ever-Smokers for Computed Tomography Lung Cancer Screening.

PubMed

Katki, Hormuzd A; Kovalchik, Stephanie A; Petito, Lucia C; Cheung, Li C; Jacobs, Eric; Jemal, Ahmedin; Berg, Christine D; Chaturvedi, Anil K

2018-05-15

Lung cancer screening guidelines recommend using individualized risk models to refer ever-smokers for screening. However, different models select different screening populations. The performance of each model in selecting ever-smokers for screening is unknown. To compare the U.S. screening populations selected by 9 lung cancer risk models (the Bach model; the Spitz model; the Liverpool Lung Project [LLP] model; the LLP Incidence Risk Model [LLPi]; the Hoggart model; the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Model 2012 [PLCOM2012]; the Pittsburgh Predictor; the Lung Cancer Risk Assessment Tool [LCRAT]; and the Lung Cancer Death Risk Assessment Tool [LCDRAT]) and to examine their predictive performance in 2 cohorts. Population-based prospective studies. United States. Models selected U.S. screening populations by using data from the National Health Interview Survey from 2010 to 2012. Model performance was evaluated using data from 337 388 ever-smokers in the National Institutes of Health-AARP Diet and Health Study and 72 338 ever-smokers in the CPS-II (Cancer Prevention Study II) Nutrition Survey cohort. Model calibration (ratio of model-predicted to observed cases [expected-observed ratio]) and discrimination (area under the curve [AUC]). At a 5-year risk threshold of 2.0%, the models chose U.S. screening populations ranging from 7.6 million to 26 million ever-smokers. These disagreements occurred because, in both validation cohorts, 4 models (the Bach model, PLCOM2012, LCRAT, and LCDRAT) were well-calibrated (expected-observed ratio range, 0.92 to 1.12) and had higher AUCs (range, 0.75 to 0.79) than 5 models that generally overestimated risk (expected-observed ratio range, 0.83 to 3.69) and had lower AUCs (range, 0.62 to 0.75). The 4 best-performing models also had the highest sensitivity at a fixed specificity (and vice versa) and similar discrimination at a fixed risk threshold. These models showed better agreement on size of the screening population (7.6 million to 10.9 million) and achieved consensus on 73% of persons chosen. No consensus on risk thresholds for screening. The 9 lung cancer risk models chose widely differing U.S. screening populations. However, 4 models (the Bach model, PLCOM2012, LCRAT, and LCDRAT) most accurately predicted risk and performed best in selecting ever-smokers for screening. Intramural Research Program of the National Institutes of Health/National Cancer Institute.

Meteorological limits on the growth and development of screwworm populations

NASA Technical Reports Server (NTRS)

Phinney, D. E.; Arp, G. K.

1978-01-01

A program to evaluate the use of remotely sensed data as an additional tool in existing and projected efforts to eradicate the screwworm began in 1973. Estimating weather conditions by use of remotely sensed data was part of the study. Next, the effect of weather on screwworm populations was modeled. A significant portion of the variation in screwworm population growth and development has been traced to weather-related parameters. This report deals with the salient points of the weather and the screwworm population interaction.

Emergent properties of interacting populations of spiking neurons.

PubMed

Cardanobile, Stefano; Rotter, Stefan

2011-01-01

Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations.

Emergent Properties of Interacting Populations of Spiking Neurons

PubMed Central

Cardanobile, Stefano; Rotter, Stefan

2011-01-01

Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations. PMID:22207844

Multiscale musculoskeletal modelling, data–model fusion and electromyography-informed modelling

PubMed Central

Zhang, J.; Heidlauf, T.; Sartori, M.; Besier, T.; Röhrle, O.; Lloyd, D.

2016-01-01

This paper proposes methods and technologies that advance the state of the art for modelling the musculoskeletal system across the spatial and temporal scales; and storing these using efficient ontologies and tools. We present population-based modelling as an efficient method to rapidly generate individual morphology from only a few measurements and to learn from the ever-increasing supply of imaging data available. We present multiscale methods for continuum muscle and bone models; and efficient mechanostatistical methods, both continuum and particle-based, to bridge the scales. Finally, we examine both the importance that muscles play in bone remodelling stimuli and the latest muscle force prediction methods that use electromyography-assisted modelling techniques to compute musculoskeletal forces that best reflect the underlying neuromuscular activity. Our proposal is that, in order to have a clinically relevant virtual physiological human, (i) bone and muscle mechanics must be considered together; (ii) models should be trained on population data to permit rapid generation and use underlying principal modes that describe both muscle patterns and morphology; and (iii) these tools need to be available in an open-source repository so that the scientific community may use, personalize and contribute to the database of models. PMID:27051510

High-resolution simulation of link-level vehicle emissions and concentrations for air pollutants in a traffic-populated eastern Asian city

NASA Astrophysics Data System (ADS)

Zhang, Shaojun; Wu, Ye; Huang, Ruikun; Wang, Jiandong; Yan, Han; Zheng, Yali; Hao, Jiming

2016-08-01

Vehicle emissions containing air pollutants created substantial environmental impacts on air quality for many traffic-populated cities in eastern Asia. A high-resolution emission inventory is a useful tool compared with traditional tools (e.g. registration data-based approach) to accurately evaluate real-world traffic dynamics and their environmental burden. In this study, Macau, one of the most populated cities in the world, is selected to demonstrate a high-resolution simulation of vehicular emissions and their contribution to air pollutant concentrations by coupling multimodels. First, traffic volumes by vehicle category on 47 typical roads were investigated during weekdays in 2010 and further applied in a networking demand simulation with the TransCAD model to establish hourly profiles of link-level vehicle counts. Local vehicle driving speed and vehicle age distribution data were also collected in Macau. Second, based on a localized vehicle emission model (e.g. the emission factor model for the Beijing vehicle fleet - Macau, EMBEV-Macau), this study established a link-based vehicle emission inventory in Macau with high resolution meshed in a temporal and spatial framework. Furthermore, we employed the AERMOD (AMS/EPA Regulatory Model) model to map concentrations of CO and primary PM2.5 contributed by local vehicle emissions during weekdays in November 2010. This study has discerned the strong impact of traffic flow dynamics on the temporal and spatial patterns of vehicle emissions, such as a geographic discrepancy of spatial allocation up to 26 % between THC and PM2.5 emissions owing to spatially heterogeneous vehicle-use intensity between motorcycles and diesel fleets. We also identified that the estimated CO2 emissions from gasoline vehicles agreed well with the statistical fuel consumption in Macau. Therefore, this paper provides a case study and a solid framework for developing high-resolution environment assessment tools for other vehicle-populated cities in eastern Asia.

Mouse Models for Drug Discovery. Can New Tools and Technology Improve Translational Power?

PubMed

Zuberi, Aamir; Lutz, Cathleen

2016-12-01

The use of mouse models in biomedical research and preclinical drug evaluation is on the rise. The advent of new molecular genome-altering technologies such as CRISPR/Cas9 allows for genetic mutations to be introduced into the germ line of a mouse faster and less expensively than previous methods. In addition, the rapid progress in the development and use of somatic transgenesis using viral vectors, as well as manipulations of gene expression with siRNAs and antisense oligonucleotides, allow for even greater exploration into genomics and systems biology. These technological advances come at a time when cost reductions in genome sequencing have led to the identification of pathogenic mutations in patient populations, providing unprecedented opportunities in the use of mice to model human disease. The ease of genetic engineering in mice also offers a potential paradigm shift in resource sharing and the speed by which models are made available in the public domain. Predictively, the knowledge alone that a model can be quickly remade will provide relief to resources encumbered by licensing and Material Transfer Agreements. For decades, mouse strains have provided an exquisite experimental tool to study the pathophysiology of the disease and assess therapeutic options in a genetically defined system. However, a major limitation of the mouse has been the limited genetic diversity associated with common laboratory mice. This has been overcome with the recent development of the Collaborative Cross and Diversity Outbred mice. These strains provide new tools capable of replicating genetic diversity to that approaching the diversity found in human populations. The Collaborative Cross and Diversity Outbred strains thus provide a means to observe and characterize toxicity or efficacy of new therapeutic drugs for a given population. The combination of traditional and contemporary mouse genome editing tools, along with the addition of genetic diversity in new modeling systems, are synergistic and serve to make the mouse a better model for biomedical research, enhancing the potential for preclinical drug discovery and personalized medicine. © The Author 2016. Published by Oxford University Press.

Novel 3D Approach to Flare Modeling via Interactive IDL Widget Tools

NASA Astrophysics Data System (ADS)

Nita, G. M.; Fleishman, G. D.; Gary, D. E.; Kuznetsov, A.; Kontar, E. P.

2011-12-01

Currently, and soon-to-be, available sophisticated 3D models of particle acceleration and transport in solar flares require a new level of user-friendly visualization and analysis tools allowing quick and easy adjustment of the model parameters and computation of realistic radiation patterns (images, spectra, polarization, etc). We report the current state of the art of these tools in development, already proved to be highly efficient for the direct flare modeling. We present an interactive IDL widget application intended to provide a flexible tool that allows the user to generate spatially resolved radio and X-ray spectra. The object-based architecture of this application provides full interaction with imported 3D magnetic field models (e.g., from an extrapolation) that may be embedded in a global coronal model. Various tools provided allow users to explore the magnetic connectivity of the model by generating magnetic field lines originating in user-specified volume positions. Such lines may serve as reference lines for creating magnetic flux tubes, which are further populated with user-defined analytical thermal/non thermal particle distribution models. By default, the application integrates IDL callable DLL and Shared libraries containing fast GS emission codes developed in FORTRAN and C++ and soft and hard X-ray codes developed in IDL. However, the interactive interface allows interchanging these default libraries with any user-defined IDL or external callable codes designed to solve the radiation transfer equation in the same or other wavelength ranges of interest. To illustrate the tool capacity and generality, we present a step-by-step real-time computation of microwave and X-ray images from realistic magnetic structures obtained from a magnetic field extrapolation preceding a real event, and compare them with the actual imaging data obtained by NORH and RHESSI instruments. We discuss further anticipated developments of the tools needed to accommodate temporal evolution of the magnetic field structure and/or fast electron population implied by the electron acceleration and transport. This work was supported in part by NSF grants AGS-0961867, AST-0908344, and NASA grants NNX10AF27G and NNX11AB49G to New Jersey Institute of Technology, by a UK STFC rolling grant, STFC/PPARC Advanced Fellowship, and the Leverhulme Trust, UK. Financial support by the European Commission through the SOLAIRE and HESPE Networks is gratefully acknowledged.

Modeling oscillations and spiral waves in Dictyostelium populations

NASA Astrophysics Data System (ADS)

Noorbakhsh, Javad; Schwab, David J.; Sgro, Allyson E.; Gregor, Thomas; Mehta, Pankaj

2015-06-01

Unicellular organisms exhibit elaborate collective behaviors in response to environmental cues. These behaviors are controlled by complex biochemical networks within individual cells and coordinated through cell-to-cell communication. Describing these behaviors requires new mathematical models that can bridge scales—from biochemical networks within individual cells to spatially structured cellular populations. Here we present a family of "multiscale" models for the emergence of spiral waves in the social amoeba Dictyostelium discoideum. Our models exploit new experimental advances that allow for the direct measurement and manipulation of the small signaling molecule cyclic adenosine monophosphate (cAMP) used by Dictyostelium cells to coordinate behavior in cellular populations. Inspired by recent experiments, we model the Dictyostelium signaling network as an excitable system coupled to various preprocessing modules. We use this family of models to study spatially unstructured populations of "fixed" cells by constructing phase diagrams that relate the properties of population-level oscillations to parameters in the underlying biochemical network. We then briefly discuss an extension of our model that includes spatial structure and show how this naturally gives rise to spiral waves. Our models exhibit a wide range of novel phenomena. including a density-dependent frequency change, bistability, and dynamic death due to slow cAMP dynamics. Our modeling approach provides a powerful tool for bridging scales in modeling of Dictyostelium populations.

Using partial least squares regression as a predictive tool in describing equine third metacarpal bone shape.

PubMed

Liley, Helen; Zhang, Ju; Firth, Elwyn; Fernandez, Justin; Besier, Thor

2017-11-01

Population variance in bone shape is an important consideration when applying the results of subject-specific computational models to a population. In this letter, we demonstrate the ability of partial least squares regression to provide an improved shape prediction of the equine third metacarpal epiphysis, using two easily obtained measurements.

Tools for assessing climate impacts on fish and wildlife

Treesearch

Chad B. Wilsey; Joshua J. Lawler; Edwin P. Maurer; Donald McKenzie; Patricia A. Townsend; Richard Gwozdz; James A. Freund; Keala Hagmann; Karen M. Hutten

2013-01-01

Climate change is already affecting many fish and wildlife populations. Managing these populations requires an understanding of the nature, magnitude, and distribution of current and future climate impacts. Scientists and managers have at their disposal a wide array of models for projecting climate impacts that can be used to build such an understanding. Here, we...

Operation Reliability Assessment for Cutting Tools by Applying a Proportional Covariate Model to Condition Monitoring Information

PubMed Central

Cai, Gaigai; Chen, Xuefeng; Li, Bing; Chen, Baojia; He, Zhengjia

2012-01-01

The reliability of cutting tools is critical to machining precision and production efficiency. The conventional statistic-based reliability assessment method aims at providing a general and overall estimation of reliability for a large population of identical units under given and fixed conditions. However, it has limited effectiveness in depicting the operational characteristics of a cutting tool. To overcome this limitation, this paper proposes an approach to assess the operation reliability of cutting tools. A proportional covariate model is introduced to construct the relationship between operation reliability and condition monitoring information. The wavelet packet transform and an improved distance evaluation technique are used to extract sensitive features from vibration signals, and a covariate function is constructed based on the proportional covariate model. Ultimately, the failure rate function of the cutting tool being assessed is calculated using the baseline covariate function obtained from a small sample of historical data. Experimental results and a comparative study show that the proposed method is effective for assessing the operation reliability of cutting tools. PMID:23201980

Implementing and Simulating Dynamic Traffic Assignment with Intelligent Transportation Systems in Cube Avenue

NASA Technical Reports Server (NTRS)

Foytik, Peter; Robinson, Mike

2010-01-01

As urban populations and traffic congestion levels increase, effective use of information and communication tools and intelligent transportation systems as becoming increasingly important in order to maximize the efficiency of transportation networks. The appropriate placement and employment of these tools within a network is critical to their effectiveness. This presentation proposes and demonstrates the use of a commercial transportation simulation tool to simulate dynamic traffic assignment and rerouting to model route modifications as a result of traffic information.

Population genetics and the evolution of geographic range limits in an annual plant.

PubMed

Moeller, David A; Geber, Monica A; Tiffin, Peter

2011-10-01

Abstract Theoretical models of species' geographic range limits have identified both demographic and evolutionary mechanisms that prevent range expansion. Stable range limits have been paradoxical for evolutionary biologists because they represent locations where populations chronically fail to respond to selection. Distinguishing among the proposed causes of species' range limits requires insight into both current and historical population dynamics. The tools of molecular population genetics provide a window into the stability of range limits, historical demography, and rates of gene flow. Here we evaluate alternative range limit models using a multilocus data set based on DNA sequences and microsatellites along with field demographic data from the annual plant Clarkia xantiana ssp. xantiana. Our data suggest that central and peripheral populations have very large historical and current effective population sizes and that there is little evidence for population size changes or bottlenecks associated with colonization in peripheral populations. Whereas range limit populations appear to have been stable, central populations exhibit a signature of population expansion and have contributed asymmetrically to the genetic diversity of peripheral populations via migration. Overall, our results discount strictly demographic models of range limits and more strongly support evolutionary genetic models of range limits, where adaptation is prevented by a lack of genetic variation or maladaptive gene flow.

Forecasting climate change impacts on plant populations over large spatial extents

DOE PAGES

Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; ...

2016-10-24

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less

Forecasting climate change impacts on plant populations over large spatial extents

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

Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less

Forecasting climate change impacts on plant populations over large spatial extents

USGS Publications Warehouse

Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; Homer, Collin G.; Kleinhesselink, Andrew R.; Adler, Peter B.

2016-01-01

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. We overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.

Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

PubMed

Heinonen, Johannes P M; Palmer, Stephen C F; Redpath, Steve M; Travis, Justin M J

2014-01-01

Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions.

Viability of piping plover Charadrius melodus metapopulations

USGS Publications Warehouse

Plissner, Jonathan H.; Haig, Susan M.

2000-01-01

The metapopulation viability analysis package, VORTEX, was used to examine viability and recovery objectives for piping plovers Charadrius melodus, an endangered shorebird that breeds in three distinct regions of North America. Baseline models indicate that while Atlantic Coast populations, under current management practices, are at little risk of near-term extinction, Great Plains and Great Lakes populations require 36% higher mean fecundity for a significant probability of persisting for the next 100 years. Metapopulation structure (i.e. the delineation of populations within the metapopulation) and interpopulation dispersal rates had varying effects on model results; however, spatially-structured metapopulations exhibited lower viability than that reported for single-population models. The models were most sensitive to variation in survivorship; hence, additional mortality data will improve their accuracy. With this information, such models become useful tools in identifying successful management objectives; and sensitivity analyses, even in the absence of some data, may indicate which options are likely to be most effective. Metapopulation viability models are best suited for developing conservation strategies for achieving recovery objectives based on maintaining an externally derived, target population size and structure.

Modelling Hen Harrier Dynamics to Inform Human-Wildlife Conflict Resolution: A Spatially-Realistic, Individual-Based Approach

PubMed Central

Heinonen, Johannes P. M.; Palmer, Stephen C. F.; Redpath, Steve M.; Travis, Justin M. J.

2014-01-01

Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions. PMID:25405860

Modeling Selection and Extinction Mechanisms of Biological Systems

NASA Astrophysics Data System (ADS)

Amirjanov, Adil

In this paper, the behavior of a genetic algorithm is modeled to enhance its applicability as a modeling tool of biological systems. A new description model for selection mechanism is introduced which operates on a portion of individuals of population. The extinction and recolonization mechanism is modeled, and solving the dynamics analytically shows that the genetic drift in the population with extinction/recolonization is doubled. The mathematical analysis of the interaction between selection and extinction/recolonization processes is carried out to assess the dynamics of motion of the macroscopic statistical properties of population. Computer simulations confirm that the theoretical predictions of described models are in good approximations. A mathematical model of GA dynamics was also examined, which describes the anti-predator vigilance in an animal group with respect to a known analytical solution of the problem, and showed a good agreement between them to find the evolutionarily stable strategies.

Enhancing population pharmacokinetic modeling efficiency and quality using an integrated workflow.

PubMed

Schmidt, Henning; Radivojevic, Andrijana

2014-08-01

Population pharmacokinetic (popPK) analyses are at the core of Pharmacometrics and need to be performed regularly. Although these analyses are relatively standard, a large variability can be observed in both the time (efficiency) and the way they are performed (quality). Main reasons for this variability include the level of experience of a modeler, personal preferences and tools. This paper aims to examine how the process of popPK model building can be supported in order to increase its efficiency and quality. The presented approach to the conduct of popPK analyses is centered around three key components: (1) identification of most common and important popPK model features, (2) required information content and formatting of the data for modeling, and (3) methodology, workflow and workflow supporting tools. This approach has been used in several popPK modeling projects and a documented example is provided in the supplementary material. Efficiency of model building is improved by avoiding repetitive coding and other labor-intensive tasks and by putting the emphasis on a fit-for-purpose model. Quality is improved by ensuring that the workflow and tools are in alignment with a popPK modeling guidance which is established within an organization. The main conclusion of this paper is that workflow based approaches to popPK modeling are feasible and have significant potential to ameliorate its various aspects. However, the implementation of such an approach in a pharmacometric organization requires openness towards innovation and change-the key ingredient for evolution of integrative and quantitative drug development in the pharmaceutical industry.

An Innovative Interactive Modeling Tool to Analyze Scenario-Based Physician Workforce Supply and Demand.

PubMed

Gupta, Saurabh; Black-Schaffer, W Stephen; Crawford, James M; Gross, David; Karcher, Donald S; Kaufman, Jill; Knapman, Doug; Prystowsky, Michael B; Wheeler, Thomas M; Bean, Sarah; Kumar, Paramhans; Sharma, Raghav; Chamoli, Vaibhav; Ghai, Vikrant; Gogia, Vineet; Weintraub, Sally; Cohen, Michael B; Robboy, Stanley J

2015-01-01

Effective physician workforce management requires that the various organizations comprising the House of Medicine be able to assess their current and future workforce supply. This information has direct relevance to funding of graduate medical education. We describe a dynamic modeling tool that examines how individual factors and practice variables can be used to measure and forecast the supply and demand for existing and new physician services. The system we describe, while built to analyze the pathologist workforce, is sufficiently broad and robust for use in any medical specialty. Our design provides a computer-based software model populated with data from surveys and best estimates by specialty experts about current and new activities in the scope of practice. The model describes the steps needed and data required for analysis of supply and demand. Our modeling tool allows educators and policy makers, in addition to physician specialty organizations, to assess how various factors may affect demand (and supply) of current and emerging services. Examples of factors evaluated include types of professional services (3 categories with 16 subcategories), service locations, elements related to the Patient Protection and Affordable Care Act, new technologies, aging population, and changing roles in capitated, value-based, and team-based systems of care. The model also helps identify where physicians in a given specialty will likely need to assume new roles, develop new expertise, and become more efficient in practice to accommodate new value-based payment models.

An Innovative Interactive Modeling Tool to Analyze Scenario-Based Physician Workforce Supply and Demand

PubMed Central

Gupta, Saurabh; Black-Schaffer, W. Stephen; Crawford, James M.; Gross, David; Karcher, Donald S.; Kaufman, Jill; Knapman, Doug; Prystowsky, Michael B.; Wheeler, Thomas M.; Bean, Sarah; Kumar, Paramhans; Sharma, Raghav; Chamoli, Vaibhav; Ghai, Vikrant; Gogia, Vineet; Weintraub, Sally; Cohen, Michael B.

2015-01-01

Effective physician workforce management requires that the various organizations comprising the House of Medicine be able to assess their current and future workforce supply. This information has direct relevance to funding of graduate medical education. We describe a dynamic modeling tool that examines how individual factors and practice variables can be used to measure and forecast the supply and demand for existing and new physician services. The system we describe, while built to analyze the pathologist workforce, is sufficiently broad and robust for use in any medical specialty. Our design provides a computer-based software model populated with data from surveys and best estimates by specialty experts about current and new activities in the scope of practice. The model describes the steps needed and data required for analysis of supply and demand. Our modeling tool allows educators and policy makers, in addition to physician specialty organizations, to assess how various factors may affect demand (and supply) of current and emerging services. Examples of factors evaluated include types of professional services (3 categories with 16 subcategories), service locations, elements related to the Patient Protection and Affordable Care Act, new technologies, aging population, and changing roles in capitated, value-based, and team-based systems of care. The model also helps identify where physicians in a given specialty will likely need to assume new roles, develop new expertise, and become more efficient in practice to accommodate new value-based payment models. PMID:28725751

A network-based approach for resistance transmission in bacterial populations.

PubMed

Gehring, Ronette; Schumm, Phillip; Youssef, Mina; Scoglio, Caterina

2010-01-07

Horizontal transfer of mobile genetic elements (conjugation) is an important mechanism whereby resistance is spread through bacterial populations. The aim of our work is to develop a mathematical model that quantitatively describes this process, and to use this model to optimize antimicrobial dosage regimens to minimize resistance development. The bacterial population is conceptualized as a compartmental mathematical model to describe changes in susceptible, resistant, and transconjugant bacteria over time. This model is combined with a compartmental pharmacokinetic model to explore the effect of different plasma drug concentration profiles. An agent-based simulation tool is used to account for resistance transfer occurring when two bacteria are adjacent or in close proximity. In addition, a non-linear programming optimal control problem is introduced to minimize bacterial populations as well as the drug dose. Simulation and optimization results suggest that the rapid death of susceptible individuals in the population is pivotal in minimizing the number of transconjugants in a population. This supports the use of potent antimicrobials that rapidly kill susceptible individuals and development of dosage regimens that maintain effective antimicrobial drug concentrations for as long as needed to kill off the susceptible population. Suggestions are made for experiments to test the hypotheses generated by these simulations.

Modeling evolution of spatially distributed bacterial communities: a simulation with the haploid evolutionary constructor

PubMed Central

2015-01-01

Background Multiscale approaches for integrating submodels of various levels of biological organization into a single model became the major tool of systems biology. In this paper, we have constructed and simulated a set of multiscale models of spatially distributed microbial communities and study an influence of unevenly distributed environmental factors on the genetic diversity and evolution of the community members. Results Haploid Evolutionary Constructor software http://evol-constructor.bionet.nsc.ru/ was expanded by adding the tool for the spatial modeling of a microbial community (1D, 2D and 3D versions). A set of the models of spatially distributed communities was built to demonstrate that the spatial distribution of cells affects both intensity of selection and evolution rate. Conclusion In spatially heterogeneous communities, the change in the direction of the environmental flow might be reflected in local irregular population dynamics, while the genetic structure of populations (frequencies of the alleles) remains stable. Furthermore, in spatially heterogeneous communities, the chemotaxis might dramatically affect the evolution of community members. PMID:25708911

Mobile Building Energy Audit and Modeling Tools: Cooperative Research and Development Final Report, CRADA Number CRD-11-00441

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

Brackney, L.

Broadly accessible, low cost, accurate, and easy-to-use energy auditing tools remain out of reach for managers of the aging U.S. building population (over 80% of U.S. commercial buildings are more than 10 years old*). concept3D and NREL's commercial buildings group will work to translate and extend NREL's existing spreadsheet-based energy auditing tool for a browser-friendly and mobile-computing platform. NREL will also work with concept3D to further develop a prototype geometry capture and materials inference tool operable on a smart phone/pad platform. These tools will be developed to interoperate with NREL's Building Component Library and OpenStudio energy modeling platforms, and willmore » be marketed by concept3D to commercial developers, academic institutions and governmental agencies. concept3D is NREL's lead developer and subcontractor of the Building Component Library.« less

Conference on Geospatial Approaches to Cancer Control and Population Sciences

Cancer.gov

The purpose of this conference is to bring together a community of researchers across the cancer control continuum using geospatial tools, models and approaches to address cancer prevention and control.

Population modeling for pesticide risk assessment of threatened species-A case study of a terrestrial plant, Boltonia decurrens.

PubMed

Schmolke, Amelie; Brain, Richard; Thorbek, Pernille; Perkins, Daniel; Forbes, Valery

2017-02-01

Although population models are recognized as necessary tools in the ecological risk assessment of pesticides, particularly for species listed under the Endangered Species Act, their application in this context is currently limited to very few cases. The authors developed a detailed, individual-based population model for a threatened plant species, the decurrent false aster (Boltonia decurrens), for application in pesticide risk assessment. Floods and competition with other plant species are known factors that drive the species' population dynamics and were included in the model approach. The authors use the model to compare the population-level effects of 5 toxicity surrogates applied to B. decurrens under varying environmental conditions. The model results suggest that the environmental conditions under which herbicide applications occur may have a higher impact on populations than organism-level sensitivities to an herbicide within a realistic range. Indirect effects may be as important as the direct effects of herbicide applications by shifting competition strength if competing species have different sensitivities to the herbicide. The model approach provides a case study for population-level risk assessments of listed species. Population-level effects of herbicides can be assessed in a realistic and species-specific context, and uncertainties can be addressed explicitly. The authors discuss how their approach can inform the future development and application of modeling for population-level risk assessments of listed species, and ecological risk assessment in general. Environ Toxicol Chem 2017;36:480-491. © 2016 SETAC. © 2016 SETAC.

Injury risk functions based on population-based finite element model responses: Application to femurs under dynamic three-point bending.

PubMed

Park, Gwansik; Forman, Jason; Kim, Taewung; Panzer, Matthew B; Crandall, Jeff R

2018-02-28

The goal of this study was to explore a framework for developing injury risk functions (IRFs) in a bottom-up approach based on responses of parametrically variable finite element (FE) models representing exemplar populations. First, a parametric femur modeling tool was developed and validated using a subject-specific (SS)-FE modeling approach. Second, principal component analysis and regression were used to identify parametric geometric descriptors of the human femur and the distribution of those factors for 3 target occupant sizes (5th, 50th, and 95th percentile males). Third, distributions of material parameters of cortical bone were obtained from the literature for 3 target occupant ages (25, 50, and 75 years) using regression analysis. A Monte Carlo method was then implemented to generate populations of FE models of the femur for target occupants, using a parametric femur modeling tool. Simulations were conducted with each of these models under 3-point dynamic bending. Finally, model-based IRFs were developed using logistic regression analysis, based on the moment at fracture observed in the FE simulation. In total, 100 femur FE models incorporating the variation in the population of interest were generated, and 500,000 moments at fracture were observed (applying 5,000 ultimate strains for each synthesized 100 femur FE models) for each target occupant characteristics. Using the proposed framework on this study, the model-based IRFs for 3 target male occupant sizes (5th, 50th, and 95th percentiles) and ages (25, 50, and 75 years) were developed. The model-based IRF was located in the 95% confidence interval of the test-based IRF for the range of 15 to 70% injury risks. The 95% confidence interval of the developed IRF was almost in line with the mean curve due to a large number of data points. The framework proposed in this study would be beneficial for developing the IRFs in a bottom-up manner, whose range of variabilities is informed by the population-based FE model responses. Specifically, this method mitigates the uncertainties in applying empirical scaling and may improve IRF fidelity when a limited number of experimental specimens are available.

Renewable Energy Data Explorer User Guide

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

Cox, Sarah L; Grue, Nicholas W; Tran, July

This publication provides a user guide for the Renewable Energy Data Explorer and technical potential tool within the Explorer. The Renewable Energy Data Explorer is a dynamic, web-based geospatial analysis tool that facilitates renewable energy decision-making, investment, and deployment. It brings together renewable energy resource data and other modeled or measured geographic information system (GIS) layers, including land use, weather, environmental, population density, administrative, and grid data.

Importance and pitfalls of molecular analysis to parasite epidemiology.

PubMed

Constantine, Clare C

2003-08-01

Molecular tools are increasingly being used to address questions about parasite epidemiology. Parasites represent a diverse group and they might not fit traditional population genetic models. Testing hypotheses depends equally on correct sampling, appropriate tool and/or marker choice, appropriate analysis and careful interpretation. All methods of analysis make assumptions which, if violated, make the results invalid. Some guidelines to avoid common pitfalls are offered here.

Quality improvement in neonatal digital radiography: implementing the basic quality improvement tools.

PubMed

Eslamy, Hedieh K; Newman, Beverley; Weinberger, Ed

2014-12-01

A quality improvement (QI) program may be implemented using the plan-do-study-act cycle (as a model for making improvements) and the basic QI tools (used to visually display and analyze variation in data). Managing radiation dose has come to the forefront as a safety goal for radiology departments. This is especially true in the pediatric population, which is more radiosensitive than the adult population. In this article, we use neonatal digital radiography to discuss developing a QI program with the principle goals of decreasing the radiation dose, decreasing variation in radiation dose, and optimizing image quality. Copyright © 2014 Elsevier Inc. All rights reserved.

A Mathematical Model of Economic Population Dynamics in a Country That Has Optimal Zakat Management

NASA Astrophysics Data System (ADS)

Subhan, M.

2018-04-01

Zakat is the main tools against two issues in Islamic economy: economic justice and helping the poor. However, no government of Islamic countries can solve the economic disparity today. A mathematical model could give some understanding about this phenomenon. The goal of this research is to obtain a mathematical model that can describe the dynamic of economic group population. The research is theoretical based on relevance references. From the analytical and numerical simulation, we conclude that well-manage zakat and full comitment of the wealthy can achieve wealth equilibrium that represents minimum poverty.

Scalable Entity-Based Modeling of Population-Based Systems, Final LDRD Report

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

Cleary, A J; Smith, S G; Vassilevska, T K

2005-01-27

The goal of this project has been to develop tools, capabilities and expertise in the modeling of complex population-based systems via scalable entity-based modeling (EBM). Our initial focal application domain has been the dynamics of large populations exposed to disease-causing agents, a topic of interest to the Department of Homeland Security in the context of bioterrorism. In the academic community, discrete simulation technology based on individual entities has shown initial success, but the technology has not been scaled to the problem sizes or computational resources of LLNL. Our developmental emphasis has been on the extension of this technology to parallelmore » computers and maturation of the technology from an academic to a lab setting.« less

A principled dimension-reduction method for the population density approach to modeling networks of neurons with synaptic dynamics.

PubMed

Ly, Cheng

2013-10-01

The population density approach to neural network modeling has been utilized in a variety of contexts. The idea is to group many similar noisy neurons into populations and track the probability density function for each population that encompasses the proportion of neurons with a particular state rather than simulating individual neurons (i.e., Monte Carlo). It is commonly used for both analytic insight and as a time-saving computational tool. The main shortcoming of this method is that when realistic attributes are incorporated in the underlying neuron model, the dimension of the probability density function increases, leading to intractable equations or, at best, computationally intensive simulations. Thus, developing principled dimension-reduction methods is essential for the robustness of these powerful methods. As a more pragmatic tool, it would be of great value for the larger theoretical neuroscience community. For exposition of this method, we consider a single uncoupled population of leaky integrate-and-fire neurons receiving external excitatory synaptic input only. We present a dimension-reduction method that reduces a two-dimensional partial differential-integral equation to a computationally efficient one-dimensional system and gives qualitatively accurate results in both the steady-state and nonequilibrium regimes. The method, termed modified mean-field method, is based entirely on the governing equations and not on any auxiliary variables or parameters, and it does not require fine-tuning. The principles of the modified mean-field method have potential applicability to more realistic (i.e., higher-dimensional) neural networks.

The Italian Hub of Population Biobanks as a Potential Tool for Improving Public Health Stewardship

PubMed Central

Napolitano, Mariarosaria; Santoro, Filippo; Belardelli, Filippo; Federici, Antonio

2013-01-01

In Italy, a country that is experiencing the decentralization of health services from central to regional level of government, the Minister of Health is proposing stewardship as a model of governance for the public health system. Stewardship favors efficiency in the policy decision-making process, based on reciprocal trust, and tends to be more ethical. The embryonic proposal to test stewardship in the field of population-based research was advanced during the launching conference Challenges and Opportunities of the Italian Hub of Population Biobanks (HIBP) held in 2012 in Rome. Resources collected by population biobanks (i.e., blood and its derivatives, and/or DNA isolated from any type of biological samples and relative associated data) have, in fact, a recognized scientific value for the investigation of links between genetics, health and life style, and epidemiological outcomes through population biobank-based studies, and are essential to planning effective and qualified interventions for public health. The current economic crisis requires a strong push to rationalize investment in health policies. In particular, population biobank-based studies require financial commitment, often of long duration, for the realization of their goals. Thus, innovative solutions to allow fast integration of scientific knowledge into political health strategy are required. During the conference in Rome, it was proposed to test the stewardship model by its application to the inter-relationship between population biobank-based studies and disease prevention. Stewardship minimizes barriers to innovation and uses information more effectively to better develop new strategies for prevention and/or treatment. In the months following the conference, the proposal was defined more clearly, and the HIBP network became a potential tool for testing and implementing this model in the Italian Public Health prevention system. PMID:23840926

Capture-recapture methodology

USGS Publications Warehouse

Gould, William R.; Kendall, William L.

2013-01-01

Capture-recapture methods were initially developed to estimate human population abundance, but since that time have seen widespread use for fish and wildlife populations to estimate and model various parameters of population, metapopulation, and disease dynamics. Repeated sampling of marked animals provides information for estimating abundance and tracking the fate of individuals in the face of imperfect detection. Mark types have evolved from clipping or tagging to use of noninvasive methods such as photography of natural markings and DNA collection from feces. Survival estimation has been emphasized more recently as have transition probabilities between life history states and/or geographical locations, even where some states are unobservable or uncertain. Sophisticated software has been developed to handle highly parameterized models, including environmental and individual covariates, to conduct model selection, and to employ various estimation approaches such as maximum likelihood and Bayesian approaches. With these user-friendly tools, complex statistical models for studying population dynamics have been made available to ecologists. The future will include a continuing trend toward integrating data types, both for tagged and untagged individuals, to produce more precise and robust population models.

Young macaques (Macaca fascicularis) preferentially bias attention towards closer, older, and better tool users.

PubMed

Tan, Amanda W Y; Hemelrijk, Charlotte K; Malaivijitnond, Suchinda; Gumert, Michael D

2018-05-12

Examining how animals direct social learning during skill acquisition under natural conditions, generates data for examining hypotheses regarding how transmission biases influence cultural change in animal populations. We studied a population of macaques on Koram Island, Thailand, and examined model-based biases during interactions by unskilled individuals with tool-using group members. We first compared the prevalence of interactions (watching, obtaining food, object exploration) and proximity to tool users during interactions, in developing individuals (infants, juveniles) versus mature non-learners (adolescents, adults), to provide evidence that developing individuals are actively seeking information about tool use from social partners. All infants and juveniles, but only 49% of mature individuals carried out interacted with tool users. Macaques predominantly obtained food by scrounging or stealing, suggesting maximizing scrounging opportunities motivates interactions with tool users. However, while interactions by adults was limited to obtaining food, young macaques and particularly infants also watched tool users and explored objects, indicating additional interest in tool use itself. We then ran matrix correlations to identify interaction biases, and what attributes of tool users influenced these. Biases correlated with social affiliation, but macaques also preferentially targeted tool users that potentially increase scrounging and learning opportunities. Results suggest that social structure may constrain social learning, but the motivation to bias interactions towards tool users to maximize feeding opportunities may also socially modulate learning by facilitating close proximity to better tool users, and further interest in tool-use actions and materials, especially during development.

Communication and flood risk awareness in the framework of DRIHM project

NASA Astrophysics Data System (ADS)

Llasat, Maria-Carmen; Llasat-Botija, Montserrat; Gilabert, Joan; Marcos, Raül; Parodi, Antonio; Rebora, Nicola; Garrote, Luís

2014-05-01

One of the main objectives of the Hyogo Framework for Action 2005-2015 of the United Nations is to increase public awareness so as to understand the risks, vulnerabilities and disaster reduction globally. In the case of floods they are a major hazard in Spain. In the last 30 years alone, more than 300 flood and flash-flood events have been recorded. Usually these events produce minor damages and, occasionally, some deaths, usually due to imprudent behavior. In this context, improvements in the forecast and warning systems, the communication process and for the population to have a better knowledge using new technologies are welcome. The starting point of this communication is the analysis of the treatment of flood events made by the press, the risk perception of the population, as well as the communication tools and protocols of Civil Protection and Water Catalan Agency (ACA) in Catalonia (NE of Iberian Peninsula). Afterwards, the analysis of the application of new tools developed by the University of Barcelona, with specific emphasis on the collaboration with the population, is shown. La Rambla is an informative portal of flood prevention, where share knowledge and experiences with the population. It is also a historical flood site where everyone can contribute and participate by sending experiences, data, records, pictures and much more. In La Rambla we can find information such as flood prevention plans, acts, scientific vocabulary ... There are also sections on historical floods, photo galleries, quizzes, flood news, and much more. The blog will be also used as a platform to distribute post-event questionnaires in order to analyze social impact as well as the population behavior when faced with a flood. Besides this, social networks are some of the most important channels where warnings and flood risk situations can be communicated. In the case of Facebook and Twitter, we use the platforms as a warning channel, to have a simple monitoring of the event and introducing some explanations to understand the situation, as well as to recommend scientific lectures or show new achievements. This work has been developed in the framework of the "FP7 DRIHM (Distributed Research Infrastructure for Hydro-Meteorology, www.drihm.eu) project that intends to develop a prototype e-Science environment to facilitate this collaboration and provide end-to-end hydrometeorological services (models, datasets and post-processing tools) at the European level, with the ability to expand to global scale. The objectives of DRIHM are to lead the definition of a common long-term strategy, to foster the development of new HMR models and observational archives for the study of severe hydrometeorological events, to promote the execution and analysis of high-end simulations, and to support the dissemination of predictive models as decision analysis tools. The project also aims to give students and professionals some tools to simulate flood events by combining different meteorological models with different hydrological models. Some of the cases of study are also used as an example for the communication tools, which includes, besides those previously showed, a newsletter and some videos.

Assessing three fish species ecological status in Colorado River, Grand Canyon based on physical habitat and population models.

PubMed

Yao, Weiwei; Chen, Yuansheng

2018-04-01

Colorado River is a unique ecosystem and provides important ecological services such as habitat for fish species as well as water power energy supplies. River management for this ecosystem requires assessment and decision support tools for fish which involves protecting, restoring as well as forecasting of future conditions. In this paper, a habitat and population model was developed and used to determine the levels of fish habitat suitability and population density in Colorado River between Lees Ferry and Lake Mead. The short term target fish populations are also predicted based on native fish recovery strategy. This model has been developed by combining hydrodynamics, heat transfer and sediment transport models with a habitat suitability index model and then coupling with habitat model into life stage population model. The fish were divided into four life stages according to the fish length. Three most abundant and typical native and non-native fish were selected as target species, which are rainbow trout (Oncorhynchus mykiss), brown trout (Salmo trutta) and flannelmouth sucker (Catostomus latipinnis). Flow velocity, water depth, water temperature and substrates were used as the suitability indicators in habitat model and overall suitability index (OSI) as well as weight usable area (WUA) was used as an indicator in population model. A comparison was made between simulated fish population alteration and surveyed fish number fluctuation during 2000 to 2009. The application of this habitat and population model indicates that this model can be accurate present habitat situation and targets fish population dynamics of in the study areas. The analysis also indicates the flannelmouth sucker population will steadily increase while the rainbow trout will decrease based on the native fish recovery scheme. Copyright © 2018. Published by Elsevier Inc.

A Dynamic Simulation Model of Land-Use, Population, and Rural Livelihoods in the Central Rift Valley of Ethiopia

NASA Astrophysics Data System (ADS)

Garedew, Efrem; Sandewall, Mats; Soderberg, Ulf

2012-01-01

The dynamic interactions between society and land resources have to be taken into account when planning and managing natural resources. A computer model, using STELLA software, was developed through active participation of purposively selected farm households from different wealth groups, age groups and gender within a rural community and some members of Kebelle council. The aim of the modeling was to study the perceived changes in land-use, population and livelihoods over the next 30 years and to improve our understanding of the interactions among them. The modeling output is characterized by rapid population growth, declining farm size and household incomes, deteriorating woody vegetation cover and worsening land degradation if current conditions remain. However, through integrated intervention strategies (including forest increase, micro-finance, family planning, health and education) the woody vegetation cover is likely to increase in the landscape, population growth is likely to slow down and households' income is likely to improve. A validation assessment of the simulation model based on historical data on land-use and population from 1973 to 2006 showed that the model is relatively robust. We conclude that as a supporting tool, the simulation model can contribute to the decision making process.

Genome-wide analysis of signatures of selection in populations of African honey bees (Apis mellifera) using new web-based tools.

PubMed

Fuller, Zachary L; Niño, Elina L; Patch, Harland M; Bedoya-Reina, Oscar C; Baumgarten, Tracey; Muli, Elliud; Mumoki, Fiona; Ratan, Aakrosh; McGraw, John; Frazier, Maryann; Masiga, Daniel; Schuster, Stephen; Grozinger, Christina M; Miller, Webb

2015-07-10

With the development of inexpensive, high-throughput sequencing technologies, it has become feasible to examine questions related to population genetics and molecular evolution of non-model species in their ecological contexts on a genome-wide scale. Here, we employed a newly developed suite of integrated, web-based programs to examine population dynamics and signatures of selection across the genome using several well-established tests, including F ST, pN/pS, and McDonald-Kreitman. We applied these techniques to study populations of honey bees (Apis mellifera) in East Africa. In Kenya, there are several described A. mellifera subspecies, which are thought to be localized to distinct ecological regions. We performed whole genome sequencing of 11 worker honey bees from apiaries distributed throughout Kenya and identified 3.6 million putative single-nucleotide polymorphisms. The dense coverage allowed us to apply several computational procedures to study population structure and the evolutionary relationships among the populations, and to detect signs of adaptive evolution across the genome. While there is considerable gene flow among the sampled populations, there are clear distinctions between populations from the northern desert region and those from the temperate, savannah region. We identified several genes showing population genetic patterns consistent with positive selection within African bee populations, and between these populations and European A. mellifera or Asian Apis florea. These results lay the groundwork for future studies of adaptive ecological evolution in honey bees, and demonstrate the use of new, freely available web-based tools and workflows ( http://usegalaxy.org/r/kenyanbee ) that can be applied to any model system with genomic information.

How Immunocontraception Can Contribute to Elephant Management in Small, Enclosed Reserves: Munyawana Population as a Case Study

PubMed Central

Druce, Heleen C.; Mackey, Robin L.; Slotow, Rob

2011-01-01

Immunocontraception has been widely used as a management tool to reduce population growth in captive as well as wild populations of various fauna. We model the use of an individual-based rotational immunocontraception plan on a wild elephant, Loxodonta africana, population and quantify the social and reproductive advantages of this method of implementation using adaptive management. The use of immunocontraception on an individual, rotational basis stretches the inter-calving interval for each individual female elephant to a management-determined interval, preventing exposing females to unlimited long-term immunocontraception use (which may have as yet undocumented negative effects). Such rotational immunocontraception can effectively lower population growth rates, age the population, and alter the age structure. Furthermore, such structured intervention can simulate natural process such as predation or episodic catastrophic events (e.g., drought), which regulates calf recruitment within an abnormally structured population. A rotational immunocontraception plan is a feasible and useful elephant population management tool, especially in a small, enclosed conservation area. Such approaches should be considered for other long-lived, social species in enclosed areas where the long-term consequences of consistent contraception may be unknown. PMID:22174758

Artificial neural network models for prediction of cardiovascular autonomic dysfunction in general Chinese population

PubMed Central

2013-01-01

Background The present study aimed to develop an artificial neural network (ANN) based prediction model for cardiovascular autonomic (CA) dysfunction in the general population. Methods We analyzed a previous dataset based on a population sample consisted of 2,092 individuals aged 30–80 years. The prediction models were derived from an exploratory set using ANN analysis. Performances of these prediction models were evaluated in the validation set. Results Univariate analysis indicated that 14 risk factors showed statistically significant association with CA dysfunction (P < 0.05). The mean area under the receiver-operating curve was 0.762 (95% CI 0.732–0.793) for prediction model developed using ANN analysis. The mean sensitivity, specificity, positive and negative predictive values were similar in the prediction models was 0.751, 0.665, 0.330 and 0.924, respectively. All HL statistics were less than 15.0. Conclusion ANN is an effective tool for developing prediction models with high value for predicting CA dysfunction among the general population. PMID:23902963

Stochastic population dynamics in spatially extended predator-prey systems

NASA Astrophysics Data System (ADS)

Dobramysl, Ulrich; Mobilia, Mauro; Pleimling, Michel; Täuber, Uwe C.

2018-02-01

Spatially extended population dynamics models that incorporate demographic noise serve as case studies for the crucial role of fluctuations and correlations in biological systems. Numerical and analytic tools from non-equilibrium statistical physics capture the stochastic kinetics of these complex interacting many-particle systems beyond rate equation approximations. Including spatial structure and stochastic noise in models for predator-prey competition invalidates the neutral Lotka-Volterra population cycles. Stochastic models yield long-lived erratic oscillations stemming from a resonant amplification mechanism. Spatially extended predator-prey systems display noise-stabilized activity fronts that generate persistent correlations. Fluctuation-induced renormalizations of the oscillation parameters can be analyzed perturbatively via a Doi-Peliti field theory mapping of the master equation; related tools allow detailed characterization of extinction pathways. The critical steady-state and non-equilibrium relaxation dynamics at the predator extinction threshold are governed by the directed percolation universality class. Spatial predation rate variability results in more localized clusters, enhancing both competing species’ population densities. Affixing variable interaction rates to individual particles and allowing for trait inheritance subject to mutations induces fast evolutionary dynamics for the rate distributions. Stochastic spatial variants of three-species competition with ‘rock-paper-scissors’ interactions metaphorically describe cyclic dominance. These models illustrate intimate connections between population dynamics and evolutionary game theory, underscore the role of fluctuations to drive populations toward extinction, and demonstrate how space can support species diversity. Two-dimensional cyclic three-species May-Leonard models are characterized by the emergence of spiraling patterns whose properties are elucidated by a mapping onto a complex Ginzburg-Landau equation. Multiple-species extensions to general ‘food networks’ can be classified on the mean-field level, providing both fundamental understanding of ensuing cooperativity and profound insight into the rich spatio-temporal features and coarsening kinetics in the corresponding spatially extended systems. Novel space-time patterns emerge as a result of the formation of competing alliances; e.g. coarsening domains that each incorporate rock-paper-scissors competition games.

Combining Computational Fluid Dynamics and Agent-Based Modeling: A New Approach to Evacuation Planning

PubMed Central

Epstein, Joshua M.; Pankajakshan, Ramesh; Hammond, Ross A.

2011-01-01

We introduce a novel hybrid of two fields—Computational Fluid Dynamics (CFD) and Agent-Based Modeling (ABM)—as a powerful new technique for urban evacuation planning. CFD is a predominant technique for modeling airborne transport of contaminants, while ABM is a powerful approach for modeling social dynamics in populations of adaptive individuals. The hybrid CFD-ABM method is capable of simulating how large, spatially-distributed populations might respond to a physically realistic contaminant plume. We demonstrate the overall feasibility of CFD-ABM evacuation design, using the case of a hypothetical aerosol release in Los Angeles to explore potential effectiveness of various policy regimes. We conclude by arguing that this new approach can be powerfully applied to arbitrary population centers, offering an unprecedented preparedness and catastrophic event response tool. PMID:21687788

Weak ergodicity of population evolution processes.

PubMed

Inaba, H

1989-10-01

The weak ergodic theorems of mathematical demography state that the age distribution of a closed population is asymptotically independent of the initial distribution. In this paper, we provide a new proof of the weak ergodic theorem of the multistate population model with continuous time. The main tool to attain this purpose is a theory of multiplicative processes, which was mainly developed by Garrett Birkhoff, who showed that ergodic properties generally hold for an appropriate class of multiplicative processes. First, we construct a general theory of multiplicative processes on a Banach lattice. Next, we formulate a dynamical model of a multistate population and show that its evolution operator forms a multiplicative process on the state space of the population. Subsequently, we investigate a sufficient condition that guarantees the weak ergodicity of the multiplicative process. Finally, we prove the weak and strong ergodic theorems for the multistate population and resolve the consistency problem.

Population size predicts technological complexity in Oceania

PubMed Central

Kline, Michelle A.; Boyd, Robert

2010-01-01

Much human adaptation depends on the gradual accumulation of culturally transmitted knowledge and technology. Recent models of this process predict that large, well-connected populations will have more diverse and complex tool kits than small, isolated populations. While several examples of the loss of technology in small populations are consistent with this prediction, it found no support in two systematic quantitative tests. Both studies were based on data from continental populations in which contact rates were not available, and therefore these studies do not provide a test of the models. Here, we show that in Oceania, around the time of early European contact, islands with small populations had less complicated marine foraging technology. This finding suggests that explanations of existing cultural variation based on optimality models alone are incomplete because demography plays an important role in generating cumulative cultural adaptation. It also indicates that hominin populations with similar cognitive abilities may leave very different archaeological records, a conclusion that has important implications for our understanding of the origin of anatomically modern humans and their evolved psychology. PMID:20392733

DNAPrint Genomics, Inc.: better drugs for segmented markets.

PubMed

Frudakis, Tony

2008-02-01

The postgenome era promises more efficient drug-development cycles and medications targeted to compatible populations, resulting in improved outcomes, fewer drug-company failures, less litigation, fewer recalls and a refurbished image of 'pharma' in the mind of the customer. DNAPrint was founded to help precipitate these changes. Since 1999, we have developed and optimized novel methods for assessing patient response proclivities as individuals but also as constituents of populations, and we have introduced a computational platform for modeling drug biology. We expect these tools will allow us to maximize the efficiency of our clinical trials and, more importantly, ensure better postmarket performance parameters. With these tools, we are now carefully engineering select drug-development projects in an attempt to illustrate the viability of a novel drug-development model - one based on the application of intelligence and new technologies for superior drug performance in segmented markets.

Confronting species distribution model predictions with species functional traits.

PubMed

Wittmann, Marion E; Barnes, Matthew A; Jerde, Christopher L; Jones, Lisa A; Lodge, David M

2016-02-01

Species distribution models are valuable tools in studies of biogeography, ecology, and climate change and have been used to inform conservation and ecosystem management. However, species distribution models typically incorporate only climatic variables and species presence data. Model development or validation rarely considers functional components of species traits or other types of biological data. We implemented a species distribution model (Maxent) to predict global climate habitat suitability for Grass Carp (Ctenopharyngodon idella). We then tested the relationship between the degree of climate habitat suitability predicted by Maxent and the individual growth rates of both wild (N = 17) and stocked (N = 51) Grass Carp populations using correlation analysis. The Grass Carp Maxent model accurately reflected the global occurrence data (AUC = 0.904). Observations of Grass Carp growth rate covered six continents and ranged from 0.19 to 20.1 g day(-1). Species distribution model predictions were correlated (r = 0.5, 95% CI (0.03, 0.79)) with observed growth rates for wild Grass Carp populations but were not correlated (r = -0.26, 95% CI (-0.5, 0.012)) with stocked populations. Further, a review of the literature indicates that the few studies for other species that have previously assessed the relationship between the degree of predicted climate habitat suitability and species functional traits have also discovered significant relationships. Thus, species distribution models may provide inferences beyond just where a species may occur, providing a useful tool to understand the linkage between species distributions and underlying biological mechanisms.

Incorporating parametric uncertainty into population viability analysis models

USGS Publications Warehouse

McGowan, Conor P.; Runge, Michael C.; Larson, Michael A.

2011-01-01

Uncertainty in parameter estimates from sampling variation or expert judgment can introduce substantial uncertainty into ecological predictions based on those estimates. However, in standard population viability analyses, one of the most widely used tools for managing plant, fish and wildlife populations, parametric uncertainty is often ignored in or discarded from model projections. We present a method for explicitly incorporating this source of uncertainty into population models to fully account for risk in management and decision contexts. Our method involves a two-step simulation process where parametric uncertainty is incorporated into the replication loop of the model and temporal variance is incorporated into the loop for time steps in the model. Using the piping plover, a federally threatened shorebird in the USA and Canada, as an example, we compare abundance projections and extinction probabilities from simulations that exclude and include parametric uncertainty. Although final abundance was very low for all sets of simulations, estimated extinction risk was much greater for the simulation that incorporated parametric uncertainty in the replication loop. Decisions about species conservation (e.g., listing, delisting, and jeopardy) might differ greatly depending on the treatment of parametric uncertainty in population models.

Ecological drivers of variation in tool-use frequency across sea otter populations

USGS Publications Warehouse

Fujii, Jessica; Ralls, Katherine; Tinker, M. Tim

2015-01-01

Sea otters are well-known tool users, employing objects such as rocks or shells to break open hard-shelled invertebrate prey. However, little is known about how the frequency of tool use varies among sea otter populations and the factors that drive these differences. We examined 17 years of observational data on prey capture and tool use from 8 sea otter populations ranging from southern California to the Aleutian Islands in Alaska. There were significant differences in the diets of these populations as well as variation in the frequency of tool use. Sea otters at Amchitka Island, Alaska, used tools on less than 1% of dives that resulted in the capture of prey compared with approximately 16% in Monterey, California. The percentage of individuals in the population that used tools ranged from 10% to 93%. In all populations, marine snails and thick-shelled bivalves were most likely to be associated with tool use, whereas soft-bodied prey items such as worms and sea stars were the least likely. The probability that a tool would be used on a given prey type varied across populations. The morphology of the prey item being handled and the prevalence of various types of prey in local diets were major ecological drivers of tool use: together they accounted for about 64% of the variation in tool-use frequency among populations. The remaining variation may be related to changes in the relative costs and benefits to an individual otter of learning to use tools effectively under differing ecological circumstances.

Population models for passerine birds: structure, parameterization, and analysis

USGS Publications Warehouse

Noon, B.R.; Sauer, J.R.; McCullough, D.R.; Barrett, R.H.

1992-01-01

Population models have great potential as management tools, as they use infonnation about the life history of a species to summarize estimates of fecundity and survival into a description of population change. Models provide a framework for projecting future populations, determining the effects of management decisions on future population dynamics, evaluating extinction probabilities, and addressing a variety of questions of ecological and evolutionary interest. Even when insufficient information exists to allow complete identification of the model, the modelling procedure is useful because it forces the investigator to consider the life history of the species when determining what parameters should be estimated from field studies and provides a context for evaluating the relative importance of demographic parameters. Models have been little used in the study of the population dynamics of passerine birds because of: (1) widespread misunderstandings of the model structures and parameterizations, (2) a lack of knowledge of life histories of many species, (3) difficulties in obtaining statistically reliable estimates of demographic parameters for most passerine species, and (4) confusion about functional relationships among demographic parameters. As a result, studies of passerine demography are often designed inappropriately and fail to provide essential data. We review appropriate models for passerine bird populations and illustrate their possible uses in evaluating the effects of management or other environmental influences on population dynamics. We identify environmental influences on population dynamics. We identify parameters that must be estimated from field data, briefly review existing statistical methods for obtaining valid estimates, and evaluate the present status of knowledge of these parameters.

Human population dynamics in Europe over the Last Glacial Maximum.

PubMed

Tallavaara, Miikka; Luoto, Miska; Korhonen, Natalia; Järvinen, Heikki; Seppä, Heikki

2015-07-07

The severe cooling and the expansion of the ice sheets during the Last Glacial Maximum (LGM), 27,000-19,000 y ago (27-19 ky ago) had a major impact on plant and animal populations, including humans. Changes in human population size and range have affected our genetic evolution, and recent modeling efforts have reaffirmed the importance of population dynamics in cultural and linguistic evolution, as well. However, in the absence of historical records, estimating past population levels has remained difficult. Here we show that it is possible to model spatially explicit human population dynamics from the pre-LGM at 30 ky ago through the LGM to the Late Glacial in Europe by using climate envelope modeling tools and modern ethnographic datasets to construct a population calibration model. The simulated range and size of the human population correspond significantly with spatiotemporal patterns in the archaeological data, suggesting that climate was a major driver of population dynamics 30-13 ky ago. The simulated population size declined from about 330,000 people at 30 ky ago to a minimum of 130,000 people at 23 ky ago. The Late Glacial population growth was fastest during Greenland interstadial 1, and by 13 ky ago, there were almost 410,000 people in Europe. Even during the coldest part of the LGM, the climatically suitable area for human habitation remained unfragmented and covered 36% of Europe.

Human population dynamics in Europe over the Last Glacial Maximum

PubMed Central

Tallavaara, Miikka; Luoto, Miska; Korhonen, Natalia; Järvinen, Heikki; Seppä, Heikki

2015-01-01

The severe cooling and the expansion of the ice sheets during the Last Glacial Maximum (LGM), 27,000–19,000 y ago (27–19 ky ago) had a major impact on plant and animal populations, including humans. Changes in human population size and range have affected our genetic evolution, and recent modeling efforts have reaffirmed the importance of population dynamics in cultural and linguistic evolution, as well. However, in the absence of historical records, estimating past population levels has remained difficult. Here we show that it is possible to model spatially explicit human population dynamics from the pre-LGM at 30 ky ago through the LGM to the Late Glacial in Europe by using climate envelope modeling tools and modern ethnographic datasets to construct a population calibration model. The simulated range and size of the human population correspond significantly with spatiotemporal patterns in the archaeological data, suggesting that climate was a major driver of population dynamics 30–13 ky ago. The simulated population size declined from about 330,000 people at 30 ky ago to a minimum of 130,000 people at 23 ky ago. The Late Glacial population growth was fastest during Greenland interstadial 1, and by 13 ky ago, there were almost 410,000 people in Europe. Even during the coldest part of the LGM, the climatically suitable area for human habitation remained unfragmented and covered 36% of Europe. PMID:26100880

The OncoSim model: development and use for better decision-making in Canadian cancer control.

PubMed

Gauvreau, C L; Fitzgerald, N R; Memon, S; Flanagan, W M; Nadeau, C; Asakawa, K; Garner, R; Miller, A B; Evans, W K; Popadiuk, C M; Wolfson, M; Coldman, A J

2017-12-01

The Canadian Partnership Against Cancer was created in 2007 by the federal government to accelerate cancer control across Canada. Its OncoSim microsimulation model platform, which consists of a suite of specific cancer models, was conceived as a tool to augment conventional resources for population-level policy- and decision-making. The Canadian Partnership Against Cancer manages the OncoSim program, with funding from Health Canada and model development by Statistics Canada. Microsimulation modelling allows for the detailed capture of population heterogeneity and health and demographic history over time. Extensive data from multiple Canadian sources were used as inputs or to validate the model. OncoSim has been validated through expert consultation; assessments of face validity, internal validity, and external validity; and model fit against observed data. The platform comprises three in-depth cancer models (lung, colorectal, cervical), with another in-depth model (breast) and a generalized model (25 cancers) being in development. Unique among models of its class, OncoSim is available online for public sector use free of charge. Users can customize input values and output display, and extensive user support is provided. OncoSim has been used to support decision-making at the national and jurisdictional levels. Although simulation studies are generally not included in hierarchies of evidence, they are integral to informing cancer control policy when clinical studies are not feasible. OncoSim can evaluate complex intervention scenarios for multiple cancers. Canadian decision-makers thus have a powerful tool to assess the costs, benefits, cost-effectiveness, and budgetary effects of cancer control interventions when faced with difficult choices for improvements in population health and resource allocation.

The genealogical decomposition of a matrix population model with applications to the aggregation of stages.

PubMed

Bienvenu, François; Akçay, Erol; Legendre, Stéphane; McCandlish, David M

2017-06-01

Matrix projection models are a central tool in many areas of population biology. In most applications, one starts from the projection matrix to quantify the asymptotic growth rate of the population (the dominant eigenvalue), the stable stage distribution, and the reproductive values (the dominant right and left eigenvectors, respectively). Any primitive projection matrix also has an associated ergodic Markov chain that contains information about the genealogy of the population. In this paper, we show that these facts can be used to specify any matrix population model as a triple consisting of the ergodic Markov matrix, the dominant eigenvalue and one of the corresponding eigenvectors. This decomposition of the projection matrix separates properties associated with lineages from those associated with individuals. It also clarifies the relationships between many quantities commonly used to describe such models, including the relationship between eigenvalue sensitivities and elasticities. We illustrate the utility of such a decomposition by introducing a new method for aggregating classes in a matrix population model to produce a simpler model with a smaller number of classes. Unlike the standard method, our method has the advantage of preserving reproductive values and elasticities. It also has conceptually satisfying properties such as commuting with changes of units. Copyright © 2017 Elsevier Inc. All rights reserved.

Automated finite element modeling of the lumbar spine: Using a statistical shape model to generate a virtual population of models.

PubMed

Campbell, J Q; Petrella, A J

2016-09-06

Population-based modeling of the lumbar spine has the potential to be a powerful clinical tool. However, developing a fully parameterized model of the lumbar spine with accurate geometry has remained a challenge. The current study used automated methods for landmark identification to create a statistical shape model of the lumbar spine. The shape model was evaluated using compactness, generalization ability, and specificity. The primary shape modes were analyzed visually, quantitatively, and biomechanically. The biomechanical analysis was performed by using the statistical shape model with an automated method for finite element model generation to create a fully parameterized finite element model of the lumbar spine. Functional finite element models of the mean shape and the extreme shapes (±3 standard deviations) of all 17 shape modes were created demonstrating the robust nature of the methods. This study represents an advancement in finite element modeling of the lumbar spine and will allow population-based modeling in the future. Copyright © 2016 Elsevier Ltd. All rights reserved.

Personalizing oncology treatments by predicting drug efficacy, side-effects, and improved therapy: mathematics, statistics, and their integration.

PubMed

Agur, Zvia; Elishmereni, Moran; Kheifetz, Yuri

2014-01-01

Despite its great promise, personalized oncology still faces many hurdles, and it is increasingly clear that targeted drugs and molecular biomarkers alone yield only modest clinical benefit. One reason is the complex relationships between biomarkers and the patient's response to drugs, obscuring the true weight of the biomarkers in the overall patient's response. This complexity can be disentangled by computational models that integrate the effects of personal biomarkers into a simulator of drug-patient dynamic interactions, for predicting the clinical outcomes. Several computational tools have been developed for personalized oncology, notably evidence-based tools for simulating pharmacokinetics, Bayesian-estimated tools for predicting survival, etc. We describe representative statistical and mathematical tools, and discuss their merits, shortcomings and preliminary clinical validation attesting to their potential. Yet, the individualization power of mathematical models alone, or statistical models alone, is limited. More accurate and versatile personalization tools can be constructed by a new application of the statistical/mathematical nonlinear mixed effects modeling (NLMEM) approach, which until recently has been used only in drug development. Using these advanced tools, clinical data from patient populations can be integrated with mechanistic models of disease and physiology, for generating personal mathematical models. Upon a more substantial validation in the clinic, this approach will hopefully be applied in personalized clinical trials, P-trials, hence aiding the establishment of personalized medicine within the main stream of clinical oncology. © 2014 Wiley Periodicals, Inc.

Gunnison sage-grouse lek site suitability modeling

USGS Publications Warehouse

Ouren, Douglas S.; Ignizio, Drew A.; Siders, Melissa; Childers, Theresa; Tucker, Karen; Seward, Nathan

2014-01-01

In order to better understand and protect species with minimal or decreasing populations, it is imperative to determine their actual existing population size. The focal species for this project is the Gunnison sage-grouse (GUSG), which became a proposed endangered species under the Endangered Species Act, thus confirming the need for better population estimates. Lek site counting during mating season has historically been the primary method for estimating population size since the grouse are very difficult to count at other times of the year. The objective of this project was to use historical data and available technology to identify additional potential lekking sites. This was done by determining areas throughout the study area that have the same landscape characteristics as those where known lekking activities occur. More accurate population counts could be the outcome of locating more lek sites. One of the remaining seven GUSG populations, the Crawford population (estimated at 128 individuals) exists in an area that includes the Gunnison Gorge National Conservation Area and the northern portion of the Black Canyon of the Gunnison National Park (our study area). While the Crawford population is small, it is still considered a self-sustaining population; the persistence and growth of this population directly contribute to genetic diversity conservation of this declining species. To date, only observational and anecdotal information about the Crawford population’s range, movements, and seasonal habitat use exist. From 1978 to the present, GUSG population monitoring has been accomplished through annual lek counts conducted each spring during GUSG mating season. Although this method has provided information on GUSG population trends, it is somewhat limited because counts are based only on known lekking sites and historically minimal efforts have been made to identify additional lek sites. To meet the objective of locating more potential lekking sites, we used a suite of spatial data, geographic information system tools, and maximum entropy species distribution tools. Based on expert knowledge and landscape variables, the modeling process evolved into a hybrid approach for delineating areas that would have a significant probability for supporting GUSG lekking activities. Based on model results, a sampling protocol was developed for model verification. The results of this project provide wildlife managers with a more sophisticated methodology to evaluate GUSG habitat for potential lekking sites.

Network Models: An Underutilized Tool in Wildlife Epidemiology?

PubMed Central

Craft, Meggan E.; Caillaud, Damien

2011-01-01

Although the approach of contact network epidemiology has been increasing in popularity for studying transmission of infectious diseases in human populations, it has generally been an underutilized approach for investigating disease outbreaks in wildlife populations. In this paper we explore the differences between the type of data that can be collected on human and wildlife populations, provide an update on recent advances that have been made in wildlife epidemiology by using a network approach, and discuss why networks might have been underutilized and why networks could and should be used more in the future. We conclude with ideas for future directions and a call for field biologists and network modelers to engage in more cross-disciplinary collaboration. PMID:21527981

Anthropometry and Biomechanics Facility Presentation to Open EVA Research Forum

NASA Technical Reports Server (NTRS)

Rajulu, Sudhakar

2017-01-01

NASA is required to accommodate individuals who fall within a 1st to 99th percentile range on a variety of critical dimensions. The hardware the crew interacts with must therefore be designed and verified to allow these selected individuals to complete critical mission tasks safely and at an optimal performance level. Until now, designers have been provided simpler univariate critical dimensional analyses. The multivariate characteristics of intra-individual and inter-individual size variation must be accounted for, since an individual who is 1st percentile in one body dimension will not be 1st percentile in all other dimensions. A more simplistic approach, assuming every measurement of an individual will fall within the same percentile range, can lead to a model that does not represent realistic members of the population. In other words, there is no '1st percentile female' or '99th percentile male', and designing for these unrealistic body types can lead to hardware issues down the road. Furthermore, due to budget considerations, designers are normally limited to providing only 1 size of a prototype suit, thus requiring other possible means to ensure that a given suit architecture would yield the necessary suit sizes to accommodate the entire user population. Fortunately, modeling tools can be used to more accurately model the types of human body sizes and shapes that will be encountered in a population. Anthropometry toolkits have been designed with a variety of capabilities, including grouping the population into clusters based on critical dimensions, providing percentile information given test subject measurements, and listing measurement ranges for critical dimensions in the 1st-99th percentile range. These toolkits can be combined with full body laser scans to allow designers to build human models that better represent the astronaut population. More recently, some rescaling and reposing capabilities have been developed, to allow reshaping of these static laser scans in more representative postures, such as an abducted shoulder. All of the hardware designed for use with the crew must be sized to accommodate the user population, but the interaction between subject size and hardware fit is complicated with multi-component, complex systems like a space suit. Again, prototype suits are normally only provided in a limited size range, and suited testing is an expensive endeavor; both of these factors limit the number and size of people who can be used to benchmark a spacesuit. However, modeling tools for assessing suit-human interaction can allow potential issues to be modeled and visualized. These types of modeling tools can be used for analysis of a larger combination of anthropometries and hardware types than could feasibly be done with actual human subjects and physical mockups.

Critically evaluating best management practices for preventing freshwater turtle extinctions.

PubMed

Spencer, R-J; Van Dyke, J U; Thompson, Michael B

2017-12-01

Ex situ conservation tools, such as captive breeding for reintroduction, are considered a last resort to recover threatened or endangered species, but they may also help reduce anthropogenic threats where it is difficult or impossible to address them directly. Headstarting, or captive rearing of eggs or neonate animals for subsequent release into the wild, is controversial because it treats only a symptom of a larger conservation problem; however, it may provide a mechanism to address multiple threats, particularly near population centers. We conducted a population viability analysis of Australia's most widespread freshwater turtle, Chelodina longicollis, to determine the effect of adult roadkill (death by collision with motor vehicles), which is increasing, and reduced recruitment through nest predation from introduced European red foxes (Vulpes vulpes). We also modeled management scenarios to test the effectiveness of headstarting, fox management, and measures to reduce mortality on roads. Only scenarios with headstarting from source populations eliminated all risks of extinction and allowed population growth. Small increases in adult mortality (2%) had the greatest effect on population growth and extinction risk. Where threats simultaneously affected other life-history stages (e.g., recruitment), eliminating harvest pressures on adult females alone did not eliminate the risk of population extinction. In our models, one source population could supply enough hatchlings annually to supplement 25 other similar-sized populations such that extinction was avoided. Based on our results, we believe headstarting should be a primary tool for managing freshwater turtles for which threats affect multiple life-history stages. We advocate the creation of source populations for managing freshwater turtles that are greatly threatened at multiple life-history stages, such as depredation of eggs by invasive species and adult mortality via roadkill. © 2017 Society for Conservation Biology.

Public Library Site Evaluation and Location: Past and Present Market-Based Modelling Tools for the Future.

ERIC Educational Resources Information Center

Koontz, Christine M.

1992-01-01

Presents a methodology for construction of location modeling for public library facilities in diverse urban environments. Historical and current research in library location is reviewed; and data collected from a survey of six library systems are analyzed according to population, spatial, library use, and library attractiveness variables. (48…

Gastro-esophageal reflux disease symptoms and demographic factors as a pre-screening tool for Barrett's esophagus.

PubMed

Liu, Xinxue; Wong, Angela; Kadri, Sudarshan R; Corovic, Andrej; O'Donovan, Maria; Lao-Sirieix, Pierre; Lovat, Laurence B; Burnham, Rodney W; Fitzgerald, Rebecca C

2014-01-01

Barrett's esophagus (BE) occurs as consequence of reflux and is a risk factor for esophageal adenocarcinoma. The current "gold-standard" for diagnosing BE is endoscopy which remains prohibitively expensive and impractical as a population screening tool. We aimed to develop a pre-screening tool to aid decision making for diagnostic referrals. A prospective (training) cohort of 1603 patients attending for endoscopy was used for identification of risk factors to develop a risk prediction model. Factors associated with BE in the univariate analysis were selected to develop prediction models that were validated in an independent, external cohort of 477 non-BE patients referred for endoscopy with symptoms of reflux or dyspepsia. Two prediction models were developed separately for columnar lined epithelium (CLE) of any length and using a stricter definition of intestinal metaplasia (IM) with segments ≥ 2 cm with areas under the ROC curves (AUC) of 0.72 (95%CI: 0.67-0.77) and 0.81 (95%CI: 0.76-0.86), respectively. The two prediction models included demographics (age, sex), symptoms (heartburn, acid reflux, chest pain, abdominal pain) and medication for "stomach" symptoms. These two models were validated in the independent cohort with AUCs of 0.61 (95%CI: 0.54-0.68) and 0.64 (95%CI: 0.52-0.77) for CLE and IM ≥ 2 cm, respectively. We have identified and validated two prediction models for CLE and IM ≥ 2 cm. Both models have fair prediction accuracies and can select out around 20% of individuals unlikely to benefit from investigation for Barrett's esophagus. Such prediction models have the potential to generate useful cost-savings for BE screening among the symptomatic population.

Cost-effective management alternatives for Snake River Chinook salmon: a biological-economic synthesis.

PubMed

Halsing, David L; Moore, Michael R

2008-04-01

The mandate to increase endangered salmon populations in the Columbia River Basin of North America has created a complex, controversial resource-management issue. We constructed an integrated assessment model as a tool for analyzing biological-economic trade-offs in recovery of Snake River spring- and summer-run chinook salmon (Oncorhynchus tshawytscha). We merged 3 frameworks: a salmon-passage model to predict migration and survival of smolts; an age-structured matrix model to predict long-term population growth rates of salmon stocks; and a cost-effectiveness analysis to determine a set of least-cost management alternatives for achieving particular population growth rates. We assessed 6 individual salmon-management measures and 76 management alternatives composed of one or more measures. To reflect uncertainty, results were derived for different assumptions of effectiveness of smolt transport around dams. Removal of an estuarine predator, the Caspian Tern (Sterna caspia), was cost-effective and generally increased long-term population growth rates regardless of transport effectiveness. Elimination of adult salmon harvest had a similar effect over a range of its cost estimates. The specific management alternatives in the cost-effective set depended on assumptions about transport effectiveness. On the basis of recent estimates of smolt transport effectiveness, alternatives that discontinued transportation or breached dams were prevalent in the cost-effective set, whereas alternatives that maximized transportation dominated if transport effectiveness was relatively high. More generally, the analysis eliminated 80-90% of management alternatives from the cost-effective set. Application of our results to salmon management is limited by data availability and model assumptions, but these limitations can help guide research that addresses critical uncertainties and information. Our results thus demonstrate that linking biology and economics through integrated models can provide valuable tools for science-based policy and management.

Cost-effective management alternatives for Snake river chinook salmon: A biological-economic synthesis

USGS Publications Warehouse

Halsing, D.L.; Moore, M.R.

2008-01-01

The mandate to increase endangered salmon populations in the Columbia River Basin of North America has created a complex, controversial resource-management issue. We constructed an integrated assessment model as a tool for analyzing biological-economic trade-offs in recovery of Snake River spring- and summer-run chinook salmon (Oncorhynchus tshawytscha). We merged 3 frameworks: a salmon-passage model to predict migration and survival of smolts; an age-structured matrix model to predict long-term population growth rates of salmon stocks; and a cost-effectiveness analysis to determine a set of least-cost management alternatives for achieving particular population growth rates. We assessed 6 individual salmon-management measures and 76 management alternatives composed of one or more measures. To reflect uncertainty, results were derived for different assumptions of effectiveness of smolt transport around dams. Removal of an estuarine predator, the Caspian Tern (Sterna caspia), was cost-effective and generally increased long-term population growth rates regardless of transport effectiveness. Elimination of adult salmon harvest had a similar effect over a range of its cost estimates. The specific management alternatives in the cost-effective set depended on assumptions about transport effectiveness. On the basis of recent estimates of smolt transport effectiveness, alternatives that discontinued transportation or breached dams were prevalent in the cost-effective set, whereas alternatives that maximized transportation dominated if transport effectiveness was relatively high. More generally, the analysis eliminated 80-90% of management alternatives from the cost-effective set. Application of our results to salmon management is limited by data availability and model assumptions, but these limitations can help guide research that addresses critical uncertainties and information. Our results thus demonstrate that linking biology and economics through integrated models can provide valuable tools for science-based policy and management.

Forecasting municipal solid waste generation using prognostic tools and regression analysis.

PubMed

Ghinea, Cristina; Drăgoi, Elena Niculina; Comăniţă, Elena-Diana; Gavrilescu, Marius; Câmpean, Teofil; Curteanu, Silvia; Gavrilescu, Maria

2016-11-01

For an adequate planning of waste management systems the accurate forecast of waste generation is an essential step, since various factors can affect waste trends. The application of predictive and prognosis models are useful tools, as reliable support for decision making processes. In this paper some indicators such as: number of residents, population age, urban life expectancy, total municipal solid waste were used as input variables in prognostic models in order to predict the amount of solid waste fractions. We applied Waste Prognostic Tool, regression analysis and time series analysis to forecast municipal solid waste generation and composition by considering the Iasi Romania case study. Regression equations were determined for six solid waste fractions (paper, plastic, metal, glass, biodegradable and other waste). Accuracy Measures were calculated and the results showed that S-curve trend model is the most suitable for municipal solid waste (MSW) prediction. Copyright © 2016 Elsevier Ltd. All rights reserved.

Forecasting the incidence of tuberculosis in China using the seasonal auto-regressive integrated moving average (SARIMA) model.

PubMed

Mao, Qiang; Zhang, Kai; Yan, Wu; Cheng, Chaonan

2018-05-02

The aims of this study were to develop a forecasting model for the incidence of tuberculosis (TB) and analyze the seasonality of infections in China; and to provide a useful tool for formulating intervention programs and allocating medical resources. Data for the monthly incidence of TB from January 2004 to December 2015 were obtained from the National Scientific Data Sharing Platform for Population and Health (China). The Box-Jenkins method was applied to fit a seasonal auto-regressive integrated moving average (SARIMA) model to forecast the incidence of TB over the subsequent six months. During the study period of 144 months, 12,321,559 TB cases were reported in China, with an average monthly incidence of 6.4426 per 100,000 of the population. The monthly incidence of TB showed a clear 12-month cycle, and a seasonality with two peaks occurring in January and March and a trough in December. The best-fit model was SARIMA (1,0,0)(0,1,1) 12 , which demonstrated adequate information extraction (white noise test, p>0.05). Based on the analysis, the incidence of TB from January to June 2016 were 6.6335, 4.7208, 5.8193, 5.5474, 5.2202 and 4.9156 per 100,000 of the population, respectively. According to the seasonal pattern of TB incidence in China, the SARIMA model was proposed as a useful tool for monitoring epidemics. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

A dynamic simulation model of land-use, population, and rural livelihoods in the Central Rift Valley of Ethiopia.

PubMed

Garedew, Efrem; Sandewall, Mats; Soderberg, Ulf

2012-01-01

The dynamic interactions between society and land resources have to be taken into account when planning and managing natural resources. A computer model, using STELLA software, was developed through active participation of purposively selected farm households from different wealth groups, age groups and gender within a rural community and some members of Kebelle council. The aim of the modeling was to study the perceived changes in land-use, population and livelihoods over the next 30 years and to improve our understanding of the interactions among them. The modeling output is characterized by rapid population growth, declining farm size and household incomes, deteriorating woody vegetation cover and worsening land degradation if current conditions remain. However, through integrated intervention strategies (including forest increase, micro-finance, family planning, health and education) the woody vegetation cover is likely to increase in the landscape, population growth is likely to slow down and households' income is likely to improve. A validation assessment of the simulation model based on historical data on land-use and population from 1973 to 2006 showed that the model is relatively robust. We conclude that as a supporting tool, the simulation model can contribute to the decision making process.

Estimating risks of heat strain by age and sex: a population-level simulation model.

PubMed

Glass, Kathryn; Tait, Peter W; Hanna, Elizabeth G; Dear, Keith

2015-05-18

Individuals living in hot climates face health risks from hyperthermia due to excessive heat. Heat strain is influenced by weather exposure and by individual characteristics such as age, sex, body size, and occupation. To explore the population-level drivers of heat strain, we developed a simulation model that scales up individual risks of heat storage (estimated using Myrup and Morgan's man model "MANMO") to a large population. Using Australian weather data, we identify high-risk weather conditions together with individual characteristics that increase the risk of heat stress under these conditions. The model identifies elevated risks in children and the elderly, with females aged 75 and older those most likely to experience heat strain. Risk of heat strain in males does not increase as rapidly with age, but is greatest on hot days with high solar radiation. Although cloudy days are less dangerous for the wider population, older women still have an elevated risk of heat strain on hot cloudy days or when indoors during high temperatures. Simulation models provide a valuable method for exploring population level risks of heat strain, and a tool for evaluating public health and other government policy interventions.

Measuring health literacy in populations: illuminating the design and development process of the European Health Literacy Survey Questionnaire (HLS-EU-Q)

PubMed Central

2013-01-01

Background Several measurement tools have been developed to measure health literacy. The tools vary in their approach and design, but few have focused on comprehensive health literacy in populations. This paper describes the design and development of the European Health Literacy Survey Questionnaire (HLS-EU-Q), an innovative, comprehensive tool to measure health literacy in populations. Methods Based on a conceptual model and definition, the process involved item development, pre-testing, field-testing, external consultation, plain language check, and translation from English to Bulgarian, Dutch, German, Greek, Polish, and Spanish. Results The development process resulted in the HLS-EU-Q, which entailed two sections, a core health literacy section and a section on determinants and outcomes associated to health literacy. The health literacy section included 47 items addressing self-reported difficulties in accessing, understanding, appraising and applying information in tasks concerning decisions making in healthcare, disease prevention, and health promotion. The second section included items related to, health behaviour, health status, health service use, community participation, socio-demographic and socio-economic factors. Conclusions By illuminating the detailed steps in the design and development process of the HLS-EU-Q, it is the aim to provide a deeper understanding of its purpose, its capability and its limitations for others using the tool. By stimulating a wide application it is the vision that HLS-EU-Q will be validated in more countries to enhance the understanding of health literacy in different populations. PMID:24112855

Geophysical Tools, Challenges and Perspectives Related to Natural Hazards, Climate Change and Food Security

NASA Astrophysics Data System (ADS)

Fucugauchi, J. U.

2013-05-01

In the coming decades a changing climate and natural hazards will likely increase the vulnerability of agricultural and other food production infrastructures, posing increasing treats to industrialized and developing economies. While food security concerns affect us globally, the huge differences among countries in stocks, population size, poverty levels, economy, technologic development, transportation, health care systems and basic infrastructure will pose a much larger burden on populations in the developing and less developed world. In these economies, increase in the magnitude, duration and frequency of droughts, floods, hurricanes, rising sea levels, heat waves, thunderstorms, freezing events and other phenomena will pose severe costs on the population. For this presentation, we concentrate on a geophysical perspective of the problems, tools available, challenges and short and long-term perspectives. In many instances, a range of natural hazards are considered as unforeseen catastrophes, which suddenly affect without warning, resulting in major losses. Although the forecasting capacity in the different situations arising from climate change and natural hazards is still limited, there are a range of tools available to assess scenarios and forecast models for developing and implementing better mitigation strategies and prevention programs. Earth observation systems, geophysical instrumental networks, satellite observatories, improved understanding of phenomena, expanded global and regional databases, geographic information systems, higher capacity for computer modeling, numerical simulations, etc provide a scientific-technical framework for developing strategies. Hazard prevention and mitigation programs will result in high costs globally, however major costs and challenges concentrate on the less developed economies already affected by poverty, famines, health problems, social inequalities, poor infrastructure, low life expectancy, high population growth, inadequate education systems, immigration, economic crises, conflicts and other issues. Case history analyses and proposals for collaboration programs, know-how transfer and better use of geophysical tools, data, observatories and monitoring networks will be discussed.

Model reduction for agent-based social simulation: coarse-graining a civil violence model.

PubMed

Zou, Yu; Fonoberov, Vladimir A; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G

2012-06-01

Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

Model reduction for agent-based social simulation: Coarse-graining a civil violence model

NASA Astrophysics Data System (ADS)

Zou, Yu; Fonoberov, Vladimir A.; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G.

2012-06-01

Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

Computer simulation models as tools for identifying research needs: A black duck population model

USGS Publications Warehouse

Ringelman, J.K.; Longcore, J.R.

1980-01-01

Existing data on the mortality and production rates of the black duck (Anas rubripes) were used to construct a WATFIV computer simulation model. The yearly cycle was divided into 8 phases: hunting, wintering, reproductive, molt, post-molt, and juvenile dispersal mortality, and production from original and renesting attempts. The program computes population changes for sex and age classes during each phase. After completion of a standard simulation run with all variable default values in effect, a sensitivity analysis was conducted by changing each of 50 input variables, 1 at a time, to assess the responsiveness of the model to changes in each variable. Thirteen variables resulted in a substantial change in population level. Adult mortality factors were important during hunting and wintering phases. All production and mortality associated with original nesting attempts were sensitive, as was juvenile dispersal mortality. By identifying those factors which invoke the greatest population change, and providing an indication of the accuracy required in estimating these factors, the model helps to identify those variables which would be most profitable topics for future research.

Modeling the Population Dynamics of Antibiotic-Resistant Bacteria:. AN Agent-Based Approach

NASA Astrophysics Data System (ADS)

Murphy, James T.; Walshe, Ray; Devocelle, Marc

The response of bacterial populations to antibiotic treatment is often a function of a diverse range of interacting factors. In order to develop strategies to minimize the spread of antibiotic resistance in pathogenic bacteria, a sound theoretical understanding of the systems of interactions taking place within a colony must be developed. The agent-based approach to modeling bacterial populations is a useful tool for relating data obtained at the molecular and cellular level with the overall population dynamics. Here we demonstrate an agent-based model, called Micro-Gen, which has been developed to simulate the growth and development of bacterial colonies in culture. The model also incorporates biochemical rules and parameters describing the kinetic interactions of bacterial cells with antibiotic molecules. Simulations were carried out to replicate the development of methicillin-resistant S. aureus (MRSA) colonies growing in the presence of antibiotics. The model was explored to see how the properties of the system emerge from the interactions of the individual bacterial agents in order to achieve a better mechanistic understanding of the population dynamics taking place. Micro-Gen provides a good theoretical framework for investigating the effects of local environmental conditions and cellular properties on the response of bacterial populations to antibiotic exposure in the context of a simulated environment.

What predictors matter: Risk factors for late adolescent outcomes.

PubMed

Wall-Wieler, Elizabeth; Roos, Leslie L; Chateau, Dan G; Rosella, Laura C

2016-06-27

A life course approach and linked Manitoba data from birth to age 18 were used to facilitate comparisons of two important outcomes: high school graduation and Attention-Deficit/Hyperactivity Disorder (ADHD). With a common set of variables, we sought to answer the following questions: Do the measures predicting high school graduation differ from those that predict ADHD? Which factors are most important? How well do the models fit each outcome? Administrative data from the Population Health Research Data Repository at the Manitoba Centre for Health Policy were used to conduct one of the strongest observational designs: multilevel modelling of large population (n = 62,739) and sibling (n = 29,444) samples. Variables included are neighbourhood characteristics, measures of family stability, and mental and physical health conditions in childhood and adolescence. The adverse childhood experiences important for each outcome differ. While family instability and economic adversity more strongly affect failing to graduate from high school, adverse health events in childhood and early adolescence have a greater effect on late adolescent ADHD. The variables included in the model provided excellent accuracy and discrimination. These results offer insights on the role of several family and social variables and can serve as the basis for reliable, valid prediction tools that can identify high-risk individuals. Applying such a tool at the population level would provide insight into the future burden of these outcomes in an entire region or nation and further quantify the burden of risk in the population.

A ‘tool box’ for deciphering neuronal circuits in the developing chick spinal cord

PubMed Central

Hadas, Yoav; Etlin, Alex; Falk, Haya; Avraham, Oshri; Kobiler, Oren; Panet, Amos; Lev-Tov, Aharon; Klar, Avihu

2014-01-01

The genetic dissection of spinal circuits is an essential new means for understanding the neural basis of mammalian behavior. Molecular targeting of specific neuronal populations, a key instrument in the genetic dissection of neuronal circuits in the mouse model, is a complex and time-demanding process. Here we present a circuit-deciphering ‘tool box’ for fast, reliable and cheap genetic targeting of neuronal circuits in the developing spinal cord of the chick. We demonstrate targeting of motoneurons and spinal interneurons, mapping of axonal trajectories and synaptic targeting in both single and populations of spinal interneurons, and viral vector-mediated labeling of pre-motoneurons. We also demonstrate fluorescent imaging of the activity pattern of defined spinal neurons during rhythmic motor behavior, and assess the role of channel rhodopsin-targeted population of interneurons in rhythmic behavior using specific photoactivation. PMID:25147209

A pandemic influenza modeling and visualization tool

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

Maciejewski, Ross; Livengood, Philip; Rudolph, Stephen

2011-08-01

The National Strategy for Pandemic Influenza outlines a plan for community response to a potential pandemic. In this outline, state and local communities are charged with enhancing their preparedness. In order to help public health officials better understand these charges, we have developed a modeling and visualization toolkit (PanViz) for analyzing the effect of decision measures implemented during a simulated pandemic influenza scenario. Spread vectors based on the point of origin and distance traveled over time are calculated and the factors of age distribution and population density are taken into effect. Healthcare officials are able to explore the effects ofmore » the pandemic on the population through a spatiotemporal view, moving forward and backward through time and inserting decision points at various days to determine the impact. Linked statistical displays are also shown, providing county level summaries of data in terms of the number of sick, hospitalized and dead as a result of the outbreak. Currently, this tool has been deployed in Indiana State Department of Health planning and preparedness exercises, and as an educational tool for demonstrating the impact of social distancing strategies during the recent H1N1 (swine flu) outbreak.« less

TARDEC FIXED HEEL POINT (FHP): DRIVER CAD ACCOMMODATION MODEL VERIFICATION REPORT

DTIC Science & Technology

2017-11-09

SUPPLEMENTARY NOTES N/A 14. ABSTRACT Easy-to-use Computer-Aided Design (CAD) tools, known as accommodation models, are needed by the ground vehicle... designers when developing the interior workspace for the occupant. The TARDEC Fixed Heel Point (FHP): Driver CAD Accommodation Model described in this...is intended to provide the composite boundaries representing the body of the defined target design population, including posture prediction

Clinical implementation of a knowledge based planning tool for prostate VMAT.

PubMed

Powis, Richard; Bird, Andrew; Brennan, Matthew; Hinks, Susan; Newman, Hannah; Reed, Katie; Sage, John; Webster, Gareth

2017-05-08

A knowledge based planning tool has been developed and implemented for prostate VMAT radiotherapy plans providing a target average rectum dose value based on previously achievable values for similar rectum/PTV overlap. The purpose of this planning tool is to highlight sub-optimal clinical plans and to improve plan quality and consistency. A historical cohort of 97 VMAT prostate plans was interrogated using a RayStation script and used to develop a local model for predicting optimum average rectum dose based on individual anatomy. A preliminary validation study was performed whereby historical plans identified as "optimal" and "sub-optimal" by the local model were replanned in a blinded study by four experienced planners and compared to the original clinical plan to assess whether any improvement in rectum dose was observed. The predictive model was then incorporated into a RayStation script and used as part of the clinical planning process. Planners were asked to use the script during planning to provide a patient specific prediction for optimum average rectum dose and to optimise the plan accordingly. Plans identified as "sub-optimal" in the validation study observed a statistically significant improvement in average rectum dose compared to the clinical plan when replanned whereas plans that were identified as "optimal" observed no improvement when replanned. This provided confidence that the local model can identify plans that were suboptimal in terms of rectal sparing. Clinical implementation of the knowledge based planning tool reduced the population-averaged mean rectum dose by 5.6Gy. There was a small but statistically significant increase in total MU and femoral head dose and a reduction in conformity index. These did not affect the clinical acceptability of the plans and no significant changes to other plan quality metrics were observed. The knowledge-based planning tool has enabled substantial reductions in population-averaged mean rectum dose for prostate VMAT patients. This suggests plans are improved when planners receive quantitative feedback on plan quality against historical data.

The Pelagics Habitat Analysis Module (PHAM): Decision Support Tools for Pelagic Fisheries

NASA Astrophysics Data System (ADS)

Armstrong, E. M.; Harrison, D. P.; Kiefer, D.; O'Brien, F.; Hinton, M.; Kohin, S.; Snyder, S.

2009-12-01

PHAM is a project funded by NASA to integrate satellite imagery and circulation models into the management of commercial and threatened pelagic species. Specifically, the project merges data from fishery surveys, and fisheries catch and effort data with satellite imagery and circulation models to define the habitat of each species. This new information on habitat will then be used to inform population distribution and models of population dynamics that are used for management. During the first year of the project, we created two prototype modules. One module, which was developed for the Inter-American Tropical Tuna Commission, is designed to help improve information available to manage the tuna fisheries of the eastern Pacific Ocean. The other module, which was developed for the Coastal Pelagics Division of the Southwest Fishery Science Center, assists management of by-catch of mako, blue, and thresher sharks along the Californian coast. Both modules were built with the EASy marine geographic information system, which provides a 4 dimensional (latitude, longitude, depth, and time) home for integration of the data. The projects currently provide tools for automated downloading and geo-referencing of satellite imagery of sea surface temperature, height, and chlorophyll concentrations; output from JPL’s ECCO2 global circulation model and its ROM California current model; and gridded data from fisheries and fishery surveys. It also provides statistical tools for defining species habitat from these and other types of environmental data. These tools include unbalanced ANOVA, EOF analysis of satellite imagery, and multivariate search routines for fitting fishery data to transforms of the environmental data. Output from the projects consists of dynamic maps of the distribution of the species that are driven by the time series of satellite imagery and output from the circulation models. It also includes relationships between environmental variables and recruitment. During the talk, we will briefly demonstrate features of the software and present the results of our analyses of habitats.

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

A closure test for time-specific capture-recapture data

USGS Publications Warehouse

Stanley, T.R.; Burnham, K.P.

1999-01-01

The assumption of demographic closure in the analysis of capture-recapture data under closed-population models is of fundamental importance. Yet, little progress has been made in the development of omnibus tests of the closure assumption. We present a closure test for time-specific data that, in principle, tests the null hypothesis of closed-population model M(t) against the open-population Jolly-Seber model as a specific alternative. This test is chi-square, and can be decomposed into informative components that can be interpreted to determine the nature of closure violations. The test is most sensitive to permanent emigration and least sensitive to temporary emigration, and is of intermediate sensitivity to permanent or temporary immigration. This test is a versatile tool for testing the assumption of demographic closure in the analysis of capture-recapture data.

Host culling as an adaptive management tool for chronic wasting disease in white-tailed deer: a modelling study.

PubMed

Wasserberg, Gideon; Osnas, Erik E; Rolley, Robert E; Samuel, Michael D

2009-04-01

Emerging wildlife diseases pose a significant threat to natural and human systems. Because of real or perceived risks of delayed actions, disease management strategies such as culling are often implemented before thorough scientific knowledge of disease dynamics is available. Adaptive management is a valuable approach in addressing the uncertainty and complexity associated with wildlife disease problems and can be facilitated by using a formal model.We developed a multi-state computer simulation model using age, sex, infection-stage, and seasonality as a tool for scientific learning and managing chronic wasting disease (CWD) in white-tailed deer Odocoileus virginianus. Our matrix model used disease transmission parameters based on data collected through disease management activities. We used this model to evaluate management issues on density- (DD) and frequency-dependent (FD) transmission, time since disease introduction, and deer culling on the demographics, epizootiology, and management of CWD.Both DD and FD models fit the Wisconsin data for a harvested white-tailed deer population, but FD was slightly better. Time since disease introduction was estimated as 36 (95% CI, 24-50) and 188 (41->200) years for DD and FD transmission, respectively. Deer harvest using intermediate to high non-selective rates can be used to reduce uncertainty between DD and FD transmission and improve our prediction of long-term epidemic patterns and host population impacts. A higher harvest rate allows earlier detection of these differences, but substantially reduces deer abundance.Results showed that CWD has spread slowly within Wisconsin deer populations, and therefore, epidemics and disease management are expected to last for decades. Non-hunted deer populations can develop and sustain a high level of infection, generating a substantial risk of disease spread. In contrast, CWD prevalence remains lower in hunted deer populations, but at a higher prevalence the disease competes with recreational hunting to reduce deer abundance.Synthesis and applications. Uncertainty about density- or frequency-dependent transmission hinders predictions about the long-term impacts of chronic wasting disease on cervid populations and the development of appropriate management strategies. An adaptive management strategy using computer modelling coupled with experimental management and monitoring can be used to test model predictions, identify the likely mode of disease transmission, and evaluate the risks of alternative management responses.

Cosmic Strings Stabilized by Quantum Fluctuations

NASA Astrophysics Data System (ADS)

Weigel, H.

2017-03-01

Fermion quantum corrections to the energy of cosmic strings are computed. A number of rather technical tools are needed to formulate this correction, and isospin and gauge invariance are employed to verify consistency of these tools. These corrections must also be included when computing the energy of strings that are charged by populating fermion bound states in its background. It is found that charged strings are dynamically stabilized in theories similar to the standard model of particle physics.

Army Sustainability Modelling Analysis and Reporting Tool Phase 1: User Manual and Results Interpretation Guide

DTIC Science & Technology

2009-11-01

force structure liability analysis tool, designed to forecast the dynamics of personnel and equipment populations over time for a particular scenario...it is intended that it will support analysis of the sustainability of planned Army force structures against a range of possible scenarios, as well as...the force options testing process. A-SMART Phase 1 has been limited to the development of personnel, major equipment and supplies/strategic lift

Health Impacts of Increased Physical Activity from Changes in Transportation Infrastructure: Quantitative Estimates for Three Communities

PubMed Central

2015-01-01

Recently, two quantitative tools have emerged for predicting the health impacts of projects that change population physical activity: the Health Economic Assessment Tool (HEAT) and Dynamic Modeling for Health Impact Assessment (DYNAMO-HIA). HEAT has been used to support health impact assessments of transportation infrastructure projects, but DYNAMO-HIA has not been previously employed for this purpose nor have the two tools been compared. To demonstrate the use of DYNAMO-HIA for supporting health impact assessments of transportation infrastructure projects, we employed the model in three communities (urban, suburban, and rural) in North Carolina. We also compared DYNAMO-HIA and HEAT predictions in the urban community. Using DYNAMO-HIA, we estimated benefit-cost ratios of 20.2 (95% C.I.: 8.7–30.6), 0.6 (0.3–0.9), and 4.7 (2.1–7.1) for the urban, suburban, and rural projects, respectively. For a 40-year time period, the HEAT predictions of deaths avoided by the urban infrastructure project were three times as high as DYNAMO-HIA's predictions due to HEAT's inability to account for changing population health characteristics over time. Quantitative health impact assessment coupled with economic valuation is a powerful tool for integrating health considerations into transportation decision-making. However, to avoid overestimating benefits, such quantitative HIAs should use dynamic, rather than static, approaches. PMID:26504832

Health Impacts of Increased Physical Activity from Changes in Transportation Infrastructure: Quantitative Estimates for Three Communities.

PubMed

Mansfield, Theodore J; MacDonald Gibson, Jacqueline

2015-01-01

Recently, two quantitative tools have emerged for predicting the health impacts of projects that change population physical activity: the Health Economic Assessment Tool (HEAT) and Dynamic Modeling for Health Impact Assessment (DYNAMO-HIA). HEAT has been used to support health impact assessments of transportation infrastructure projects, but DYNAMO-HIA has not been previously employed for this purpose nor have the two tools been compared. To demonstrate the use of DYNAMO-HIA for supporting health impact assessments of transportation infrastructure projects, we employed the model in three communities (urban, suburban, and rural) in North Carolina. We also compared DYNAMO-HIA and HEAT predictions in the urban community. Using DYNAMO-HIA, we estimated benefit-cost ratios of 20.2 (95% C.I.: 8.7-30.6), 0.6 (0.3-0.9), and 4.7 (2.1-7.1) for the urban, suburban, and rural projects, respectively. For a 40-year time period, the HEAT predictions of deaths avoided by the urban infrastructure project were three times as high as DYNAMO-HIA's predictions due to HEAT's inability to account for changing population health characteristics over time. Quantitative health impact assessment coupled with economic valuation is a powerful tool for integrating health considerations into transportation decision-making. However, to avoid overestimating benefits, such quantitative HIAs should use dynamic, rather than static, approaches.

Inferring Population Exposure from Biomonitoring Data on Urinary Concentrations (SOT)

EPA Science Inventory

Biomonitoring studies such as the National Health and Nutrition Examination Survey (NHANES) are valuable to exposure assessment both as sources of data to evaluate exposure models and as training sets to develop heuristics for rapid-exposure-assessment tools. However, linking in...

IPMP 2013 - A comprehensive data analysis tool for predictive microbiology

USDA-ARS?s Scientific Manuscript database

Predictive microbiology is an area of applied research in food science that uses mathematical models to predict the changes in the population of pathogenic or spoilage microorganisms in foods undergoing complex environmental changes during processing, transportation, distribution, and storage. It f...

A computational model that predicts behavioral sensitivity to intracortical microstimulation

PubMed Central

Kim, Sungshin; Callier, Thierri; Bensmaia, Sliman J.

2016-01-01

Objective Intracortical microstimulation (ICMS) is a powerful tool to investigate the neural mechanisms of perception and can be used to restore sensation for patients who have lost it. While sensitivity to ICMS has previously been characterized, no systematic framework has been developed to summarize the detectability of individual ICMS pulse trains or the discriminability of pairs of pulse trains. Approach We develop a simple simulation that describes the responses of a population of neurons to a train of electrical pulses delivered through a microelectrode. We then perform an ideal observer analysis on the simulated population responses to predict the behavioral performance of non-human primates in ICMS detection and discrimination tasks. Main results Our computational model can predict behavioral performance across a wide range of stimulation conditions with high accuracy (R2 = 0.97) and generalizes to novel ICMS pulse trains that were not used to fit its parameters. Furthermore, the model provides a theoretical basis for the finding that amplitude discrimination based on ICMS violates Weber's law. Significance The model can be used to characterize the sensitivity to ICMS across the range of perceptible and safe stimulation regimes. As such, it will be a useful tool for both neuroscience and neuroprosthetics. PMID:27977419

A computational model that predicts behavioral sensitivity to intracortical microstimulation.

PubMed

Kim, Sungshin; Callier, Thierri; Bensmaia, Sliman J

2017-02-01

Intracortical microstimulation (ICMS) is a powerful tool to investigate the neural mechanisms of perception and can be used to restore sensation for patients who have lost it. While sensitivity to ICMS has previously been characterized, no systematic framework has been developed to summarize the detectability of individual ICMS pulse trains or the discriminability of pairs of pulse trains. We develop a simple simulation that describes the responses of a population of neurons to a train of electrical pulses delivered through a microelectrode. We then perform an ideal observer analysis on the simulated population responses to predict the behavioral performance of non-human primates in ICMS detection and discrimination tasks. Our computational model can predict behavioral performance across a wide range of stimulation conditions with high accuracy (R 2  = 0.97) and generalizes to novel ICMS pulse trains that were not used to fit its parameters. Furthermore, the model provides a theoretical basis for the finding that amplitude discrimination based on ICMS violates Weber's law. The model can be used to characterize the sensitivity to ICMS across the range of perceptible and safe stimulation regimes. As such, it will be a useful tool for both neuroscience and neuroprosthetics.

Preliminary stochastic model for managing Vibrio parahaemolyticus and total viable bacterial counts in a Pacific oyster (Crassostrea gigas) supply chain.

PubMed

Fernandez-Piquer, Judith; Bowman, John P; Ross, Tom; Estrada-Flores, Silvia; Tamplin, Mark L

2013-07-01

Vibrio parahaemolyticus can accumulate and grow in oysters stored without refrigeration, representing a potential food safety risk. High temperatures during oyster storage can lead to an increase in total viable bacteria counts, decreasing product shelf life. Therefore, a predictive tool that allows the estimation of both V. parahaemolyticus populations and total viable bacteria counts in parallel is needed. A stochastic model was developed to quantitatively assess the populations of V. parahaemolyticus and total viable bacteria in Pacific oysters for six different supply chain scenarios. The stochastic model encompassed operations from oyster farms through consumers and was built using risk analysis software. Probabilistic distributions and predictions for the percentage of Pacific oysters containing V. parahaemolyticus and high levels of viable bacteria at the point of consumption were generated for each simulated scenario. This tool can provide valuable information about V. parahaemolyticus exposure and potential control measures and can help oyster companies and regulatory agencies evaluate the impact of product quality and safety during cold chain management. If coupled with suitable monitoring systems, such models could enable preemptive action to be taken to counteract unfavorable supply chain conditions.

A computational model that predicts behavioral sensitivity to intracortical microstimulation

NASA Astrophysics Data System (ADS)

Kim, Sungshin; Callier, Thierri; Bensmaia, Sliman J.

2017-02-01

Objective. Intracortical microstimulation (ICMS) is a powerful tool to investigate the neural mechanisms of perception and can be used to restore sensation for patients who have lost it. While sensitivity to ICMS has previously been characterized, no systematic framework has been developed to summarize the detectability of individual ICMS pulse trains or the discriminability of pairs of pulse trains. Approach. We develop a simple simulation that describes the responses of a population of neurons to a train of electrical pulses delivered through a microelectrode. We then perform an ideal observer analysis on the simulated population responses to predict the behavioral performance of non-human primates in ICMS detection and discrimination tasks. Main results. Our computational model can predict behavioral performance across a wide range of stimulation conditions with high accuracy (R 2 = 0.97) and generalizes to novel ICMS pulse trains that were not used to fit its parameters. Furthermore, the model provides a theoretical basis for the finding that amplitude discrimination based on ICMS violates Weber’s law. Significance. The model can be used to characterize the sensitivity to ICMS across the range of perceptible and safe stimulation regimes. As such, it will be a useful tool for both neuroscience and neuroprosthetics.

New Rodent Population Models May Inform Human Health Risk Assessment and Identification of Genetic Susceptibility to Environmental Exposures.

PubMed

Harrill, Alison H; McAllister, Kimberly A

2017-08-15

This paper provides an introduction for environmental health scientists to emerging population-based rodent resources. Mouse reference populations provide an opportunity to model environmental exposures and gene-environment interactions in human disease and to inform human health risk assessment. This review will describe several mouse populations for toxicity assessment, including older models such as the Mouse Diversity Panel (MDP), and newer models that include the Collaborative Cross (CC) and Diversity Outbred (DO) models. This review will outline the features of the MDP, CC, and DO mouse models and will discuss published case studies investigating the use of these mouse population resources in each step of the risk assessment paradigm. These unique resources have the potential to be powerful tools for generating hypotheses related to gene-environment interplay in human disease, performing controlled exposure studies to understand the differential responses in humans for susceptibility or resistance to environmental exposures, and identifying gene variants that influence sensitivity to toxicity and disease states. These new resources offer substantial advances to classical toxicity testing paradigms by including genetically sensitive individuals that may inform toxicity risks for sensitive subpopulations. Both in vivo and complementary in vitro resources provide platforms with which to reduce uncertainty by providing population-level data around biological variability. https://doi.org/10.1289/EHP1274.

New Rodent Population Models May Inform Human Health Risk Assessment and Identification of Genetic Susceptibility to Environmental Exposures

PubMed Central

Harrill, Alison H.

2017-01-01

Background: This paper provides an introduction for environmental health scientists to emerging population-based rodent resources. Mouse reference populations provide an opportunity to model environmental exposures and gene–environment interactions in human disease and to inform human health risk assessment. Objectives: This review will describe several mouse populations for toxicity assessment, including older models such as the Mouse Diversity Panel (MDP), and newer models that include the Collaborative Cross (CC) and Diversity Outbred (DO) models. Methods: This review will outline the features of the MDP, CC, and DO mouse models and will discuss published case studies investigating the use of these mouse population resources in each step of the risk assessment paradigm. Discussion: These unique resources have the potential to be powerful tools for generating hypotheses related to gene–environment interplay in human disease, performing controlled exposure studies to understand the differential responses in humans for susceptibility or resistance to environmental exposures, and identifying gene variants that influence sensitivity to toxicity and disease states. Conclusions: These new resources offer substantial advances to classical toxicity testing paradigms by including genetically sensitive individuals that may inform toxicity risks for sensitive subpopulations. Both in vivo and complementary in vitro resources provide platforms with which to reduce uncertainty by providing population-level data around biological variability. https://doi.org/10.1289/EHP1274 PMID:28886592

Modeling social norms and social influence in obesity

PubMed Central

Shoham, David A.; Hammond, Ross; Rahmandad, Hazhir; Wang, Youfa; Hovmand, Peter

2015-01-01

The worldwide increase in obesity has led to changes in what is considered “normal” or desirable weight, especially among populations at higher risk. We show that social norms are key to understanding the obesity epidemic, and that social influence mechanisms provide a necessary linkage between individual obesity-related behaviors and population-level characteristics. Because influence mechanisms cannot be directly observed, we show how three complex systems tools may be used to gain insights into observed epidemiologic patterns: social network analysis, agent-based modeling, and systems dynamics modeling. However, simulation and mathematical modeling approaches raise questions regarding acceptance of findings, especially among policy makers. Nevertheless, we point to modeling successes in obesity and other fields, including the NIH-funded National Collaborative on Childhood Obesity Research (NCCOR) Envison project. PMID:26576335

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.

DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation

PubMed Central

Sherfey, Jason S.; Soplata, Austin E.; Ardid, Salva; Roberts, Erik A.; Stanley, David A.; Pittman-Polletta, Benjamin R.; Kopell, Nancy J.

2018-01-01

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community. PMID:29599715

DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation.

PubMed

Sherfey, Jason S; Soplata, Austin E; Ardid, Salva; Roberts, Erik A; Stanley, David A; Pittman-Polletta, Benjamin R; Kopell, Nancy J

2018-01-01

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community.

Probabilistic Fracture Mechanics of Reactor Pressure Vessels with Populations of Flaws

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

Spencer, Benjamin; Backman, Marie; Williams, Paul

This report documents recent progress in developing a tool that uses the Grizzly and RAVEN codes to perform probabilistic fracture mechanics analyses of reactor pressure vessels in light water reactor nuclear power plants. The Grizzly code is being developed with the goal of creating a general tool that can be applied to study a variety of degradation mechanisms in nuclear power plant components. Because of the central role of the reactor pressure vessel (RPV) in a nuclear power plant, particular emphasis is being placed on developing capabilities to model fracture in embrittled RPVs to aid in the process surrounding decisionmore » making relating to life extension of existing plants. A typical RPV contains a large population of pre-existing flaws introduced during the manufacturing process. The use of probabilistic techniques is necessary to assess the likelihood of crack initiation at one or more of these flaws during a transient event. This report documents development and initial testing of a capability to perform probabilistic fracture mechanics of large populations of flaws in RPVs using reduced order models to compute fracture parameters. The work documented here builds on prior efforts to perform probabilistic analyses of a single flaw with uncertain parameters, as well as earlier work to develop deterministic capabilities to model the thermo-mechanical response of the RPV under transient events, and compute fracture mechanics parameters at locations of pre-defined flaws. The capabilities developed as part of this work provide a foundation for future work, which will develop a platform that provides the flexibility needed to consider scenarios that cannot be addressed with the tools used in current practice.« less

Infectious disease transmission and contact networks in wildlife and livestock.

PubMed

Craft, Meggan E

2015-05-26

The use of social and contact networks to answer basic and applied questions about infectious disease transmission in wildlife and livestock is receiving increased attention. Through social network analysis, we understand that wild animal and livestock populations, including farmed fish and poultry, often have a heterogeneous contact structure owing to social structure or trade networks. Network modelling is a flexible tool used to capture the heterogeneous contacts of a population in order to test hypotheses about the mechanisms of disease transmission, simulate and predict disease spread, and test disease control strategies. This review highlights how to use animal contact data, including social networks, for network modelling, and emphasizes that researchers should have a pathogen of interest in mind before collecting or using contact data. This paper describes the rising popularity of network approaches for understanding transmission dynamics in wild animal and livestock populations; discusses the common mismatch between contact networks as measured in animal behaviour and relevant parasites to match those networks; and highlights knowledge gaps in how to collect and analyse contact data. Opportunities for the future include increased attention to experiments, pathogen genetic markers and novel computational tools. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Infectious disease transmission and contact networks in wildlife and livestock

PubMed Central

Craft, Meggan E.

2015-01-01

The use of social and contact networks to answer basic and applied questions about infectious disease transmission in wildlife and livestock is receiving increased attention. Through social network analysis, we understand that wild animal and livestock populations, including farmed fish and poultry, often have a heterogeneous contact structure owing to social structure or trade networks. Network modelling is a flexible tool used to capture the heterogeneous contacts of a population in order to test hypotheses about the mechanisms of disease transmission, simulate and predict disease spread, and test disease control strategies. This review highlights how to use animal contact data, including social networks, for network modelling, and emphasizes that researchers should have a pathogen of interest in mind before collecting or using contact data. This paper describes the rising popularity of network approaches for understanding transmission dynamics in wild animal and livestock populations; discusses the common mismatch between contact networks as measured in animal behaviour and relevant parasites to match those networks; and highlights knowledge gaps in how to collect and analyse contact data. Opportunities for the future include increased attention to experiments, pathogen genetic markers and novel computational tools. PMID:25870393

Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD): Data and Tools for Dynamic Management and Decision Support

NASA Technical Reports Server (NTRS)

Humphries, G. R. W.; Naveen, R.; Schwaller, M.; Che-Castaldo, C.; McDowall, P.; Schrimpf, M.; Schrimpf, Michael; Lynch, H. J.

2017-01-01

The Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD) is a web-based, open access, decision-support tool designed to assist scientists, non-governmental organizations and policy-makers working to meet the management objectives as set forth by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) and other components of the Antarctic Treaty System (ATS) (that is, Consultative Meetings and the ATS Committee on Environmental Protection). MAPPPD was designed specifically to complement existing efforts such as the CCAMLR Ecosystem Monitoring Program (CEMP) and the ATS site guidelines for visitors. The database underlying MAPPPD includes all publicly available (published and unpublished) count data on emperor, gentoo, Adelie) and chinstrap penguins in Antarctica. Penguin population models are used to assimilate available data into estimates of abundance for each site and year.Results are easily aggregated across multiple sites to obtain abundance estimates over any user-defined area of interest. A front end web interface located at www.penguinmap.com provides free and ready access to the most recent count and modelled data, and can act as a facilitator for data transfer between scientists and Antarctic stakeholders to help inform management decisions for the continent.

A decision-support tool to inform Australian strategies for preventing suicide and suicidal behaviour.

PubMed

Page, Andrew; Atkinson, Jo-An; Heffernan, Mark; McDonnell, Geoff; Hickie, Ian

2017-04-27

Dynamic simulation modelling is increasingly being recognised as a valuable decision-support tool to help guide investments and actions to address complex public health issues such as suicide. In particular, participatory system dynamics (SD) modelling provides a useful tool for asking high-level 'what if' questions, and testing the likely impacts of different combinations of policies and interventions at an aggregate level before they are implemented in the real world. We developed an SD model for suicide prevention in Australia, and investigated the hypothesised impacts over the next 10 years (2015-2025) of a combination of current intervention strategies proposed for population interventions in Australia: 1) general practitioner (GP) training, 2) coordinated aftercare in those who have attempted suicide, 3) school-based mental health literacy programs, 4) brief-contact interventions in hospital settings, and 5) psychosocial treatment approaches. Findings suggest that the largest reductions in suicide were associated with GP training (6%) and coordinated aftercare approaches (4%), with total reductions of 12% for all interventions combined. This paper highlights the value of dynamic modelling methods for managing complexity and uncertainty, and demonstrates their potential use as a decision-support tool for policy makers and program planners for community suicide prevention actions.

Developing population models with data from marked individuals

USGS Publications Warehouse

Hae Yeong Ryu,; Kevin T. Shoemaker,; Eva Kneip,; Anna Pidgeon,; Patricia Heglund,; Brooke Bateman,; Thogmartin, Wayne E.; Reşit Akçakaya,

2016-01-01

Population viability analysis (PVA) is a powerful tool for biodiversity assessments, but its use has been limited because of the requirements for fully specified population models such as demographic structure, density-dependence, environmental stochasticity, and specification of uncertainties. Developing a fully specified population model from commonly available data sources – notably, mark–recapture studies – remains complicated due to lack of practical methods for estimating fecundity, true survival (as opposed to apparent survival), natural temporal variability in both survival and fecundity, density-dependence in the demographic parameters, and uncertainty in model parameters. We present a general method that estimates all the key parameters required to specify a stochastic, matrix-based population model, constructed using a long-term mark–recapture dataset. Unlike standard mark–recapture analyses, our approach provides estimates of true survival rates and fecundities, their respective natural temporal variabilities, and density-dependence functions, making it possible to construct a population model for long-term projection of population dynamics. Furthermore, our method includes a formal quantification of parameter uncertainty for global (multivariate) sensitivity analysis. We apply this approach to 9 bird species and demonstrate the feasibility of using data from the Monitoring Avian Productivity and Survivorship (MAPS) program. Bias-correction factors for raw estimates of survival and fecundity derived from mark–recapture data (apparent survival and juvenile:adult ratio, respectively) were non-negligible, and corrected parameters were generally more biologically reasonable than their uncorrected counterparts. Our method allows the development of fully specified stochastic population models using a single, widely available data source, substantially reducing the barriers that have until now limited the widespread application of PVA. This method is expected to greatly enhance our understanding of the processes underlying population dynamics and our ability to analyze viability and project trends for species of conservation concern.

Service quality assessment of workers compensation health care delivery programs in New York using SERVQUAL.

PubMed

Arunasalam, Mark; Paulson, Albert; Wallace, William

2003-01-01

Preferred provider organizations (PPOs) provide healthcare services to an expanding proportion of the U.S. population. This paper presents a programmatic assessment of service quality in the workers' compensation environment using two different models: the PPO program model and the fee-for-service (FFS) payor model. The methodology used here will augment currently available research in workers' compensation, which has been lacking in measuring service quality determinants and assessing programmatic success/failure of managed care type programs. Results indicated that the SERVQUAL tool provided a reliable and valid clinical quality assessment tool that ascertained that PPO marketers should focus on promoting physician outreach (to show empathy) and accessibility (to show reliability) for injured workers.

Stability and bifurcation analysis of three-species predator-prey model with non-monotonic delayed predator response

NASA Astrophysics Data System (ADS)

Balilo, Aldrin T.; Collera, Juancho A.

2018-03-01

In this paper, we consider delayed three-species predator-prey model with non-monotonic functional response where two predator populations feed on a single prey population. Response function in both predator populations includes a time delay which represents the gestation period of the predator populations. We call a positive equlibrium solution of the form E*S=(x*,y*,y*) as a symmetric equilibrium. The goal of this paper is to determine the effect of the difference in gestation periods of predator populations to the local dynamics of symmetric equilibria. Our results include conditions on the existence of equilibrium solutions, and stability and bifurcations of symmetric equilibria as the gestation periods of predator populations are varied. A numerical bifurcation analysis tool is also used to illustrate our results. Stability switch occurs at a Hopf bifurcation. Moreover, a branch of stable periodic solutions, obtained using numerical continuation, emerges from the Hopf bifurcation. This shows that the predator population with longer gestation period oscillates higher than the predator population with shorter gestation period.

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.

A case study of bats and white-nose syndrome demonstrating how to model population viability with evolutionary effects.

PubMed

Maslo, Brooke; Fefferman, Nina H

2015-08-01

Ecological factors generally affect population viability on rapid time scales. Traditional population viability analyses (PVA) therefore focus on alleviating ecological pressures, discounting potential evolutionary impacts on individual phenotypes. Recent studies of evolutionary rescue (ER) focus on cases in which severe, environmentally induced population bottlenecks trigger a rapid evolutionary response that can potentially reverse demographic threats. ER models have focused on shifting genetics and resulting population recovery, but no one has explored how to incorporate those findings into PVA. We integrated ER into PVA to identify the critical decision interval for evolutionary rescue (DIER) under which targeted conservation action should be applied to buffer populations undergoing ER against extinction from stochastic events and to determine the most appropriate vital rate to target to promote population recovery. We applied this model to little brown bats (Myotis lucifugus) affected by white-nose syndrome (WNS), a fungal disease causing massive declines in several North American bat populations. Under the ER scenario, the model predicted that the DIER period for little brown bats was within 11 years of initial WNS emergence, after which they stabilized at a positive growth rate (λ = 1.05). By comparing our model results with population trajectories of multiple infected hibernacula across the WNS range, we concluded that ER is a potential explanation of observed little brown bat population trajectories across multiple hibernacula within the affected range. Our approach provides a tool that can be used by all managers to provide testable hypotheses regarding the occurrence of ER in declining populations, suggest empirical studies to better parameterize the population genetics and conservation-relevant vital rates, and identify the DIER period during which management strategies will be most effective for species conservation. © 2015 Society for Conservation Biology.

Assessing the risks of pesticides to threatened and endangered species using population modeling: A critical review and recommendations for future work.

PubMed

Forbes, Valery E; Galic, Nika; Schmolke, Amelie; Vavra, Janna; Pastorok, Rob; Thorbek, Pernille

2016-08-01

United States legislation requires the US Environmental Protection Agency to ensure that pesticide use does not cause unreasonable adverse effects on the environment, including species listed under the Endangered Species Act (ESA; hereafter referred to as listed species). Despite a long history of population models used in conservation biology and resource management and a 2013 report from the US National Research Council recommending their use, application of population models for pesticide risk assessments under the ESA has been minimal. The pertinent literature published from 2004 to 2014 was reviewed to explore the availability of population models and their frequency of use in listed species risk assessments. The models were categorized in terms of structure, taxonomic coverage, purpose, inputs and outputs, and whether the models included density dependence, stochasticity, or risk estimates, or were spatially explicit. Despite the widespread availability of models and an extensive literature documenting their use in other management contexts, only 2 of the approximately 400 studies reviewed used population models to assess the risks of pesticides to listed species. This result suggests that there is an untapped potential to adapt existing models for pesticide risk assessments under the ESA, but also that there are some challenges to do so for listed species. Key conclusions from the analysis are summarized, and priorities are recommended for future work to increase the usefulness of population models as tools for pesticide risk assessments. Environ Toxicol Chem 2016;35:1904-1913. © 2016 SETAC. © 2016 SETAC.

A literature review of the cardiovascular risk-assessment tools: applicability among Asian population.

PubMed

Liau, Siow Yen; Mohamed Izham, M I; Hassali, M A; Shafie, A A

2010-01-01

Cardiovascular diseases, the main causes of hospitalisations and death globally, have put an enormous economic burden on the healthcare system. Several risk factors are associated with the occurrence of cardiovascular events. At the heart of efficient prevention of cardiovascular disease is the concept of risk assessment. This paper aims to review the available cardiovascular risk-assessment tools and its applicability in predicting cardiovascular risk among Asian populations. A systematic search was performed using keywords as MeSH and Boolean terms. A total of 25 risk-assessment tools were identified. Of these, only two risk-assessment tools (8%) were derived from an Asian population. These risk-assessment tools differ in various ways, including characteristics of the derivation sample, type of study, time frame of follow-up, end points, statistical analysis and risk factors included. Very few cardiovascular risk-assessment tools were developed in Asian populations. In order to accurately predict the cardiovascular risk of our population, there is a need to develop a risk-assessment tool based on local epidemiological data.

A Comparison of Career-Related Assessment Tools/Models. Final [Report].

ERIC Educational Resources Information Center

WestEd, San Francisco, CA.

This document contains charts that evaluate career related assessment items. Chart categories include: Purpose/Current Uses/Format; Intended Population; Oregon Career Related Learning Standards Addressed; Relationship to the Standards; Relationship to Endorsement Area Frameworks; Evidence of Validity; Evidence of Reliability; Evidence of Fairness…

RECONSTRUCTING POPULATION EXPOSURES FROM DOSE BIOMARKERS: INHALATION OF TRICHLOROETHYLENE (TCE) AS A CASE STUDY

EPA Science Inventory

Physiologically based pharmacokinetic (PBPK) modeling is a well-established toxicological tool designed to relate exposure to a target tissue dose. The emergence of federal and state programs for environmental health tracking and the availability of exposure monitoring through bi...

Modelling the effect of severe storms in coastal pollution

NASA Astrophysics Data System (ADS)

Grau, A.; Bolea, Y.; Guerra, E.

2009-09-01

Modelling and simulation of real events can be very useful to prevent environmental disasters, but these disasters can affect the health and life of human beings; then such tools become definitively necessary for governmental authorities to avoid population risk. In this wok we present a mathematical model that combines the effect of Mediterranean storms together with the effect of wastewater emissary dissolutions at the sea. The emissary model corresponds to a Catalan wastewater plant, the Besos plant in Barcelona. This plant throws the wastewater to the Mediterranean Sea with a 3-km pipe emissary, after a bacteriologically polluted secondary treatment. This polluted water is dissoluted in the salty water, provoking the death of all bacteria agents before they reach the coast. But in difficult conditions under violent storms, with strong East winds, the bacteriological polluted dissolution reaches the shore before the bacteria die and, therefore, a severe coastal pollution is produced. Its consequence can incur in a public health problem and the different governmental agencies activate great alarms to avoid population hazard. Storms modelling permits to evaluate the risk of coastal pollution predicting the wastewater dissolution path and velocity. Several simulations are presented under different storm conditions, making this tool very useful for the environmental protection agencies in the Catalan government.

Wildlife as valuable natural resources vs. intolerable pests: A suburban wildlife management model

USGS Publications Warehouse

DeStefano, S.; Deblinger, R.D.

2005-01-01

Management of wildlife in suburban environments involves a complex set of interactions between both human and wildlife populations. Managers need additional tools, such as models, that can help them assess the status of wildlife populations, devise and apply management programs, and convey this information to other professionals and the public. We present a model that conceptualizes how some wildlife populations can fluctuate between extremely low (rare, threatened, or endangered status) and extremely high (overabundant) numbers over time. Changes in wildlife abundance can induce changes in human perceptions, which continually redefine species as a valuable resource to be protected versus a pest to be controlled. Management programs thatincorporate a number of approaches and promote more stable populations of wildlife avoid the problems of the resource versus pest transformation, are less costly to society, and encourage more positive and less negative interactions between humans and wildlife. We presenta case example of the beaver Castor canadensis in Massachusetts to illustrate how this model functions and can be applied. ?? 2005 Springer Science + Business Media, Inc.

On the relationship between cell cycle analysis with ergodic principles and age-structured cell population models.

PubMed

Kuritz, K; Stöhr, D; Pollak, N; Allgöwer, F

2017-02-07

Cyclic processes, in particular the cell cycle, are of great importance in cell biology. Continued improvement in cell population analysis methods like fluorescence microscopy, flow cytometry, CyTOF or single-cell omics made mathematical methods based on ergodic principles a powerful tool in studying these processes. In this paper, we establish the relationship between cell cycle analysis with ergodic principles and age structured population models. To this end, we describe the progression of a single cell through the cell cycle by a stochastic differential equation on a one dimensional manifold in the high dimensional dataspace of cell cycle markers. Given the assumption that the cell population is in a steady state, we derive transformation rules which transform the number density on the manifold to the steady state number density of age structured population models. Our theory facilitates the study of cell cycle dependent processes including local molecular events, cell death and cell division from high dimensional "snapshot" data. Ergodic analysis can in general be applied to every process that exhibits a steady state distribution. By combining ergodic analysis with age structured population models we furthermore provide the theoretic basis for extensions of ergodic principles to distribution that deviate from their steady state. Copyright © 2016 Elsevier Ltd. All rights reserved.

Attacking the mosquito on multiple fronts: Insights from the Vector Control Optimization Model (VCOM) for malaria elimination.

PubMed

Kiware, Samson S; Chitnis, Nakul; Tatarsky, Allison; Wu, Sean; Castellanos, Héctor Manuel Sánchez; Gosling, Roly; Smith, David; Marshall, John M

2017-01-01

Despite great achievements by insecticide-treated nets (ITNs) and indoor residual spraying (IRS) in reducing malaria transmission, it is unlikely these tools will be sufficient to eliminate malaria transmission on their own in many settings today. Fortunately, field experiments indicate that there are many promising vector control interventions that can be used to complement ITNs and/or IRS by targeting a wide range of biological and environmental mosquito resources. The majority of these experiments were performed to test a single vector control intervention in isolation; however, there is growing evidence and consensus that effective vector control with the goal of malaria elimination will require a combination of interventions. We have developed a model of mosquito population dynamic to describe the mosquito life and feeding cycles and to optimize the impact of vector control intervention combinations at suppressing mosquito populations. The model simulations were performed for the main three malaria vectors in sub-Saharan Africa, Anopheles gambiae s.s, An. arabiensis and An. funestus. We considered areas having low, moderate and high malaria transmission, corresponding to entomological inoculation rates of 10, 50 and 100 infective bites per person per year, respectively. In all settings, we considered baseline ITN coverage of 50% or 80% in addition to a range of other vector control tools to interrupt malaria transmission. The model was used to sweep through parameters space to select the best optimal intervention packages. Sample model simulations indicate that, starting with ITNs at a coverage of 50% (An. gambiae s.s. and An. funestus) or 80% (An. arabiensis) and adding interventions that do not require human participation (e.g. larviciding at 80% coverage, endectocide treated cattle at 50% coverage and attractive toxic sugar baits at 50% coverage) may be sufficient to suppress all the three species to an extent required to achieve local malaria elimination. The Vector Control Optimization Model (VCOM) is a computational tool to predict the impact of combined vector control interventions at the mosquito population level in a range of eco-epidemiological settings. The model predicts specific combinations of vector control tools to achieve local malaria elimination in a range of eco-epidemiological settings and can assist researchers and program decision-makers on the design of experimental or operational research to test vector control interventions. A corresponding graphical user interface is available for national malaria control programs and other end users.

New tools for integrative thermochronology, and their application to the Colombian Eastern Cordillera

NASA Astrophysics Data System (ADS)

Ketcham, R. A.; Mora, A.; Almendral, A.; Parra-Amezquita, M.; Casallas, W.; Robles, W.

2013-12-01

We present two new tools for interpreting thermochronometric data that facilitate the joint use of multiple samples to better constrain thermal history, and demonstrate their utilization in the Colombian Eastern Cordillera. The first, Fetkin, is a finite element solver that takes as input a series of detailed balanced cross sections created using dedicated software such as (2D)Move, and solves the heat flow equation in 2D along with predicted thermochronometric ages which can be compared against measured data. It also performs an independent analysis of the cross sections and flags aspects that are structurally out of balance. It is distinguished from similar tools in 2D and 3D principally by providing a level of detail that allows for investigation of samples in very specific and complex structural contexts, and a workflow that allows the interpreter to engage in successive refinements of the structural model using the inferences provided by thermochronometric data. The second tool is a new set of functionality in HeFTy for inverse modeling of thermochronometric data that allows for simultaneous modeling of samples down a well or borehole. This extension forces attention on issues that have previously been relatively neglected in such modeling, in particular that of multiple provenance. It is axiomatic that mineral grains in different strata may have come from different regions and have different inherited thermal histories. Interpreting such data in a realistic geological context thus requires allowing for different inherited populations within and between samples. The rewards in doing so include more robust modeling and interpretation and, in some cases, insights concerning the unroofing histories of the source rocks that contributed to a given sedimentary unit. Similarly, the mutual constraints imposed by modeling multiple samples with known or constrained depositional and structural context considerably amplifies the resolving power of thermochronometric data. The usefulness of these tools is demonstrated in our studies of the development and unroofing history of the Colombian Eastern Cordillera. Example insights gained using Fetkin include the degree of acceleration of thrust-induced unroofing along the eastern range-bounding faults, and the times at which potential petroleum source rocks were in the oil generation window. Multi-sample modeling in HeFTy results in considerably refined thermal reconstructions, and a possible division between quickly-unroofed and slowly-unroofed apatite populations contributing to different stratigraphic horizons.

Earliest evidence for the structure of Homo sapiens populations in Africa

NASA Astrophysics Data System (ADS)

Scerri, Eleanor M. L.; Drake, Nick A.; Jennings, Richard; Groucutt, Huw S.

2014-10-01

Understanding the structure and variation of Homo sapiens populations in Africa is critical for interpreting multiproxy evidence of their subsequent dispersals into Eurasia. However, there is no consensus on early H. sapiens demographic structure, or its effects on intra-African dispersals. Here, we show how a patchwork of ecological corridors and bottlenecks triggered a successive budding of populations across the Sahara. Using a temporally and spatially explicit palaeoenvironmental model, we found that the Sahara was not uniformly ameliorated between ∼130 and 75 thousand years ago (ka), as has been stated. Model integration with multivariate analyses of corresponding stone tools then revealed several spatially defined technological clusters which correlated with distinct palaeobiomes. Similarities between technological clusters were such that they decreased with distance except where connected by palaeohydrological networks. These results indicate that populations at the Eurasian gateway were strongly structured, which has implications for refining the demographic parameters of dispersals out of Africa.

Population Structure With Localized Haplotype Clusters

PubMed Central

Browning, Sharon R.; Weir, Bruce S.

2010-01-01

We propose a multilocus version of FST and a measure of haplotype diversity using localized haplotype clusters. Specifically, we use haplotype clusters identified with BEAGLE, which is a program implementing a hidden Markov model for localized haplotype clustering and performing several functions including inference of haplotype phase. We apply this methodology to HapMap phase 3 data. With this haplotype-cluster approach, African populations have highest diversity and lowest divergence from the ancestral population, East Asian populations have lowest diversity and highest divergence, and other populations (European, Indian, and Mexican) have intermediate levels of diversity and divergence. These relationships accord with expectation based on other studies and accepted models of human history. In contrast, the population-specific FST estimates obtained directly from single-nucleotide polymorphisms (SNPs) do not reflect such expected relationships. We show that ascertainment bias of SNPs has less impact on the proposed haplotype-cluster-based FST than on the SNP-based version, which provides a potential explanation for these results. Thus, these new measures of FST and haplotype-cluster diversity provide an important new tool for population genetic analysis of high-density SNP data. PMID:20457877

Mapping and Eradication Prioritization Modeling of Red Sesbania ( Sesbania punicea) Populations

NASA Astrophysics Data System (ADS)

Robison, Ramona; Barve, Nita; Owens, Christina; Skurka Darin, Gina; DiTomaso, Joseph M.

2013-07-01

Red sesbania is an invasive South American shrub that has rapidly expanded its range along California waterways, emphasizing the need to prioritize eradication sites at a regional scale. To accomplish this, we updated baseline location data in summer 2010 using field surveys throughout the state. We collected relevant GPS attribute data for GIS analysis and eradication prioritization modeling. The regional survey identified upstream and downstream extents for each watershed, as well as outliers in urban areas. We employed the Weed Heuristics: Invasive Population Prioritization for Eradication Tool (WHIPPET) to prioritize red sesbania sites for eradication, and revised the WHIPPET model to consider directional propagule flow of a riparian species. WHIPPET prioritized small populations isolated from larger infestations, as well as outliers in residential areas. When we compared five experts' assessments of a stratified sample of the red sesbania populations to WHIPPET's prioritization results, there was a positive, but nonsignificant, correlation. The combination of WHIPPET and independent expert opinion suggests that small, isolated populations and upstream source populations should be the primary targets for eradication. Particular attention should be paid to these small populations in watersheds where red sesbania is a new introduction. The use of this model in conjunction with evaluation by the land manager may help prevent the establishment of new seed sources and protect uninfested riparian corridors and their adjacent watersheds.

Mapping and eradication prioritization modeling of red sesbania (Sesbania punicea) populations.

PubMed

Robison, Ramona; Barve, Nita; Owens, Christina; Skurka Darin, Gina; DiTomaso, Joseph M

2013-07-01

Red sesbania is an invasive South American shrub that has rapidly expanded its range along California waterways, emphasizing the need to prioritize eradication sites at a regional scale. To accomplish this, we updated baseline location data in summer 2010 using field surveys throughout the state. We collected relevant GPS attribute data for GIS analysis and eradication prioritization modeling. The regional survey identified upstream and downstream extents for each watershed, as well as outliers in urban areas. We employed the Weed Heuristics: Invasive Population Prioritization for Eradication Tool (WHIPPET) to prioritize red sesbania sites for eradication, and revised the WHIPPET model to consider directional propagule flow of a riparian species. WHIPPET prioritized small populations isolated from larger infestations, as well as outliers in residential areas. When we compared five experts' assessments of a stratified sample of the red sesbania populations to WHIPPET's prioritization results, there was a positive, but nonsignificant, correlation. The combination of WHIPPET and independent expert opinion suggests that small, isolated populations and upstream source populations should be the primary targets for eradication. Particular attention should be paid to these small populations in watersheds where red sesbania is a new introduction. The use of this model in conjunction with evaluation by the land manager may help prevent the establishment of new seed sources and protect uninfested riparian corridors and their adjacent watersheds.

Health economics, equity, and efficiency: are we almost there?

PubMed

Ferraz, Marcos Bosi

2015-01-01

Health care is a highly complex, dynamic, and creative sector of the economy. While health economics has to continue its efforts to improve its methods and tools to better inform decisions, the application needs to be aligned with the insights and models of other social sciences disciplines. Decisions may be guided by four concept models based on ethical and distributive justice: libertarian, communitarian, egalitarian, and utilitarian. The societal agreement on one model or a defined mix of models is critical to avoid inequity and unfair decisions in a public and/or private insurance-based health care system. The excess use of methods and tools without fully defining the basic goals and philosophical principles of the health care system and without evaluating the fitness of these measures to reaching these goals may not contribute to an efficient improvement of population health.

Health economics, equity, and efficiency: are we almost there?

PubMed Central

Ferraz, Marcos Bosi

2015-01-01

Health care is a highly complex, dynamic, and creative sector of the economy. While health economics has to continue its efforts to improve its methods and tools to better inform decisions, the application needs to be aligned with the insights and models of other social sciences disciplines. Decisions may be guided by four concept models based on ethical and distributive justice: libertarian, communitarian, egalitarian, and utilitarian. The societal agreement on one model or a defined mix of models is critical to avoid inequity and unfair decisions in a public and/or private insurance-based health care system. The excess use of methods and tools without fully defining the basic goals and philosophical principles of the health care system and without evaluating the fitness of these measures to reaching these goals may not contribute to an efficient improvement of population health. PMID:25709481

Applicability of western chemical dietary exposure models to the Chinese population.

PubMed

Zhao, Shizhen; Price, Oliver; Liu, Zhengtao; Jones, Kevin C; Sweetman, Andrew J

2015-07-01

A range of exposure models, which have been developed in Europe and North America, are playing an increasingly important role in priority setting and the risk assessment of chemicals. However, the applicability of these tools, which are based on Western dietary exposure pathways, to estimate chemical exposure to the Chinese population to support the development of a risk-based environment and exposure assessment, is unclear. Three frequently used modelling tools, EUSES, RAIDAR and ACC-HUMANsteady, have been evaluated in terms of human dietary exposure estimation by application to a range of chemicals with different physicochemical properties under both model default and Chinese dietary scenarios. Hence, the modelling approaches were assessed by considering dietary pattern differences only. The predicted dietary exposure pathways were compared under both scenarios using a range of hypothetical and current emerging contaminants. Although the differences across models are greater than those between dietary scenarios, model predictions indicated that dietary preference can have a significant impact on human exposure, with the relatively high consumption of vegetables and cereals resulting in higher exposure via plants-based foodstuffs under Chinese consumption patterns compared to Western diets. The selected models demonstrated a good ability to identify key dietary exposure pathways which can be used for screening purposes and an evaluative risk assessment. However, some model adaptations will be required to cover a number of important Chinese exposure pathways, such as freshwater farmed-fish, grains and pork. Copyright © 2015 Elsevier Inc. All rights reserved.

Fracture prediction and calibration of a Canadian FRAX® tool: a population-based report from CaMos

PubMed Central

Fraser, L.-A.; Langsetmo, L.; Berger, C.; Ioannidis, G.; Goltzman, D.; Adachi, J. D.; Papaioannou, A.; Josse, R.; Kovacs, C. S.; Olszynski, W. P.; Towheed, T.; Hanley, D. A.; Kaiser, S. M.; Prior, J.; Jamal, S.; Kreiger, N.; Brown, J. P.; Johansson, H.; Oden, A.; McCloskey, E.; Kanis, J. A.

2016-01-01

Summary A new Canadian WHO fracture risk assessment (FRAX®) tool to predict 10-year fracture probability was compared with observed 10-year fracture outcomes in a large Canadian population-based study (CaMos). The Canadian FRAX tool showed good calibration and discrimination for both hip and major osteoporotic fractures. Introduction The purpose of this study was to validate a new Canadian WHO fracture risk assessment (FRAX®) tool in a prospective, population-based cohort, the Canadian Multi-centre Osteoporosis Study (CaMos). Methods A FRAX tool calibrated to the Canadian population was developed by the WHO Collaborating Centre for Metabolic Bone Diseases using national hip fracture and mortality data. Ten-year FRAX probabilities with and without bone mineral density (BMD) were derived for CaMos women (N=4,778) and men (N=1,919) and compared with observed fracture outcomes to 10 years (Kaplan–Meier method). Cox proportional hazard models were used to investigate the contribution of individual FRAX variables. Results Mean overall 10-year FRAX probability with BMD for major osteoporotic fractures was not significantly different from the observed value in men [predicted 5.4% vs. observed 6.4% (95%CI 5.2–7.5%)] and only slightly lower in women [predicted 10.8% vs. observed 12.0% (95%CI 11.0–12.9%)]. FRAX was well calibrated for hip fracture assessment in women [predicted 2.7% vs. observed 2.7% (95%CI 2.2–3.2%)] but underestimated risk in men [predicted 1.3% vs. observed 2.4% (95%CI 1.7–3.1%)]. FRAX with BMD showed better fracture discrimination than FRAX without BMD or BMD alone. Age, body mass index, prior fragility fracture and femoral neck BMD were significant independent predictors of major osteoporotic fractures; sex, age, prior fragility fracture and femoral neck BMD were significant independent predictors of hip fractures. Conclusion The Canadian FRAX tool provides predictions consistent with observed fracture rates in Canadian women and men, thereby providing a valuable tool for Canadian clinicians assessing patients at risk of fracture. PMID:21161508

A Framework for Daylighting Optimization in Whole Buildings with OpenStudio

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

None

2016-08-12

We present a toolkit and workflow for leveraging the OpenStudio (Guglielmetti et al. 2010) platform to perform daylighting analysis and optimization in a whole building energy modeling (BEM) context. We have re-implemented OpenStudio's integrated Radiance and EnergyPlus functionality as an OpenStudio Measure. The OpenStudio Radiance Measure works within the OpenStudio Application and Parametric Analysis Tool, as well as the OpenStudio Server large scale analysis framework, allowing a rigorous daylighting simulation to be performed on a single building model or potentially an entire population of programmatically generated models. The Radiance simulation results can automatically inform the broader building energy model, andmore » provide dynamic daylight metrics as a basis for decision. Through introduction and example, this paper illustrates the utility of the OpenStudio building energy modeling platform to leverage existing simulation tools for integrated building energy performance simulation, daylighting analysis, and reportage.« less

Population variability in animal health: Influence on dose-exposure-response relationships: Part II: Modelling and simulation.

PubMed

Martinez, Marilyn N; Gehring, Ronette; Mochel, Jonathan P; Pade, Devendra; Pelligand, Ludovic

2018-05-28

During the 2017 Biennial meeting, the American Academy of Veterinary Pharmacology and Therapeutics hosted a 1-day session on the influence of population variability on dose-exposure-response relationships. In Part I, we highlighted some of the sources of population variability. Part II provides a summary of discussions on modelling and simulation tools that utilize existing pharmacokinetic data, can integrate drug physicochemical characteristics with species physiological characteristics and dosing information or that combine observed with predicted and in vitro information to explore and describe sources of variability that may influence the safe and effective use of veterinary pharmaceuticals. © 2018 John Wiley & Sons Ltd. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

The functional consequences of non-genetic diversity in cellular navigation

NASA Astrophysics Data System (ADS)

Emonet, Thierry; Waite, Adam J.; Frankel, Nicholas W.; Dufour, Yann; Johnston, Jessica F.

Substantial non-genetic diversity in complex behaviors, such as chemotaxis in E. coli, has been observed for decades, but the relevance of this diversity for the population is not well understood. Here, we use microfluidics to show that non-genetic diversity leads to significant structuring of the population in space and time, which confirms predictions made by our detailed mathematical model of chemotaxis. We then use genetic tools to show that altering the expression level of a single chemotaxis protein is sufficient to alter the distribution of swimming behaviors, which directly determines the performance of a population in a gradient of attractant, a result also predicted by our model. Supported by NIH 1R01GM106189, the James S McDonnell Foundation, and the Paul Allen foundation.

The Role of Dog Population Management in Rabies Elimination—A Review of Current Approaches and Future Opportunities

PubMed Central

Taylor, Louise H.; Wallace, Ryan M.; Balaram, Deepashree; Lindenmayer, Joann M.; Eckery, Douglas C.; Mutonono-Watkiss, Beryl; Parravani, Ellie; Nel, Louis H.

2017-01-01

Free-roaming dogs and rabies transmission are integrally linked across many low-income countries, and large unmanaged dog populations can be daunting to rabies control program planners. Dog population management (DPM) is a multifaceted concept that aims to improve the health and well-being of free-roaming dogs, reduce problems they may cause, and may also aim to reduce dog population size. In theory, DPM can facilitate more effective rabies control. Community engagement focused on promoting responsible dog ownership and better veterinary care could improve the health of individual animals and dog vaccination coverage, thus reducing rabies transmission. Humane DPM tools, such as sterilization, could theoretically reduce dog population turnover and size, allowing rabies vaccination coverage to be maintained more easily. However, it is important to understand local dog populations and community attitudes toward them in order to determine whether and how DPM might contribute to rabies control and which DPM tools would be most successful. In practice, there is very limited evidence of DPM tools achieving reductions in the size or turnover of dog populations in canine rabies-endemic areas. Different DPM tools are frequently used together and combined with rabies vaccinations, but full impact assessments of DPM programs are not usually available, and therefore, evaluation of tools is difficult. Surgical sterilization is the most frequently documented tool and has successfully reduced dog population size and turnover in a few low-income settings. However, DPM programs are mostly conducted in urban settings and are usually not government funded, raising concerns about their applicability in rural settings and sustainability over time. Technical demands, costs, and the time necessary to achieve population-level impacts are major barriers. Given their potential value, we urgently need more evidence of the effectiveness of DPM tools in the context of canine rabies control. Cheaper, less labor-intensive tools for dog sterilization will be extremely valuable in realizing the potential benefits of reduced population turnover and size. No one DPM tool will fit all situations, but if DPM objectives are achieved dog populations may be stabilized or even reduced, facilitating higher dog vaccination coverages that will benefit rabies elimination efforts. PMID:28740850

The κ-generalized distribution: A new descriptive model for the size distribution of incomes

NASA Astrophysics Data System (ADS)

Clementi, F.; Di Matteo, T.; Gallegati, M.; Kaniadakis, G.

2008-05-01

This paper proposes the κ-generalized distribution as a model for describing the distribution and dispersion of income within a population. Formulas for the shape, moments and standard tools for inequality measurement-such as the Lorenz curve and the Gini coefficient-are given. A method for parameter estimation is also discussed. The model is shown to fit extremely well the data on personal income distribution in Australia and in the United States.

A Compartmental Model for Zika Virus with Dynamic Human and Vector Populations

PubMed Central

Lee, Eva K; Liu, Yifan; Pietz, Ferdinand H

2016-01-01

The Zika virus (ZIKV) outbreak in South American countries and its potential association with microcephaly in newborns and Guillain-Barré Syndrome led the World Health Organization to declare a Public Health Emergency of International Concern. To understand the ZIKV disease dynamics and evaluate the effectiveness of different containment strategies, we propose a compartmental model with a vector-host structure for ZIKV. The model utilizes logistic growth in human population and dynamic growth in vector population. Using this model, we derive the basic reproduction number to gain insight on containment strategies. We contrast the impact and influence of different parameters on the virus trend and outbreak spread. We also evaluate different containment strategies and their combination effects to achieve early containment by minimizing total infections. This result can help decision makers select and invest in the strategies most effective to combat the infection spread. The decision-support tool demonstrates the importance of “digital disease surveillance” in response to waves of epidemics including ZIKV, Dengue, Ebola and cholera. PMID:28269870

Using a new high resolution regional model for malaria that accounts for population density and surface hydrology to determine sensitivity of malaria risk to climate drivers

NASA Astrophysics Data System (ADS)

Tompkins, Adrian; Ermert, Volker; Di Giuseppe, Francesca

2013-04-01

In order to better address the role of population dynamics and surface hydrology in the assessment of malaria risk, a new dynamical disease model been developed at ICTP, known as VECTRI: VECtor borne disease community model of ICTP, TRIeste (VECTRI). The model accounts for the temperature impact on the larvae, parasite and adult vector populations. Local host population density affects the transmission intensity, and the model thus reproduces the differences between peri-urban and rural transmission noted in Africa. A new simple pond model framework represents surface hydrology. The model can be used on with spatial resolutions finer than 10km to resolve individual health districts and thus can be used as a planning tool. Results of the models representation of interannual variability and longer term projections of malaria transmission will be shown for Africa. These will show that the model represents the seasonality and spatial variations of malaria transmission well matching a wide range of survey data of parasite rate and entomological inoculation rate (EIR) from across West and East Africa taken in the period prior to large-scale interventions. The model is used to determine the sensitivity of malaria risk to climate variations, both in rainfall and temperature, and then its use in a prototype forecasting system coupled with ECMWF forecasts will be demonstrated.

Sociality influences cultural complexity.

PubMed

Muthukrishna, Michael; Shulman, Ben W; Vasilescu, Vlad; Henrich, Joseph

2014-01-07

Archaeological and ethnohistorical evidence suggests a link between a population's size and structure, and the diversity or sophistication of its toolkits or technologies. Addressing these patterns, several evolutionary models predict that both the size and social interconnectedness of populations can contribute to the complexity of its cultural repertoire. Some models also predict that a sudden loss of sociality or of population will result in subsequent losses of useful skills/technologies. Here, we test these predictions with two experiments that permit learners to access either one or five models (teachers). Experiment 1 demonstrates that naive participants who could observe five models, integrate this information and generate increasingly effective skills (using an image editing tool) over 10 laboratory generations, whereas those with access to only one model show no improvement. Experiment 2, which began with a generation of trained experts, shows how learners with access to only one model lose skills (in knot-tying) more rapidly than those with access to five models. In the final generation of both experiments, all participants with access to five models demonstrate superior skills to those with access to only one model. These results support theoretical predictions linking sociality to cumulative cultural evolution.

Sociality influences cultural complexity

PubMed Central

Muthukrishna, Michael; Shulman, Ben W.; Vasilescu, Vlad; Henrich, Joseph

2014-01-01

Archaeological and ethnohistorical evidence suggests a link between a population's size and structure, and the diversity or sophistication of its toolkits or technologies. Addressing these patterns, several evolutionary models predict that both the size and social interconnectedness of populations can contribute to the complexity of its cultural repertoire. Some models also predict that a sudden loss of sociality or of population will result in subsequent losses of useful skills/technologies. Here, we test these predictions with two experiments that permit learners to access either one or five models (teachers). Experiment 1 demonstrates that naive participants who could observe five models, integrate this information and generate increasingly effective skills (using an image editing tool) over 10 laboratory generations, whereas those with access to only one model show no improvement. Experiment 2, which began with a generation of trained experts, shows how learners with access to only one model lose skills (in knot-tying) more rapidly than those with access to five models. In the final generation of both experiments, all participants with access to five models demonstrate superior skills to those with access to only one model. These results support theoretical predictions linking sociality to cumulative cultural evolution. PMID:24225461

Identifying and prioritizing the tools/techniques of knowledge management based on the Asian Productivity Organization Model (APO) to use in hospitals.

PubMed

Khajouei, Hamid; Khajouei, Reza

2017-12-01

Appropriate knowledge, correct information, and relevant data are vital in medical diagnosis and treatment systems. Knowledge Management (KM) through its tools/techniques provides a pertinent framework for decision-making in healthcare systems. The objective of this study was to identify and prioritize the KM tools/techniques that apply to hospital setting. This is a descriptive-survey study. Data were collected using a -researcher-made questionnaire that was developed based on experts' opinions to select the appropriate tools/techniques from 26 tools/techniques of the Asian Productivity Organization (APO) model. Questions were categorized into five steps of KM (identifying, creating, storing, sharing, and applying the knowledge) according to this model. The study population consisted of middle and senior managers of hospitals and managing directors of Vice-Chancellor for Curative Affairs in Kerman University of Medical Sciences in Kerman, Iran. The data were analyzed in SPSS v.19 using one-sample t-test. Twelve out of 26 tools/techniques of the APO model were identified as the tools applicable in hospitals. "Knowledge café" and "APO knowledge management assessment tool" with respective means of 4.23 and 3.7 were the most and the least applicable tools in the knowledge identification step. "Mentor-mentee scheme", as well as "voice and Voice over Internet Protocol (VOIP)" with respective means of 4.20 and 3.52 were the most and the least applicable tools/techniques in the knowledge creation step. "Knowledge café" and "voice and VOIP" with respective means of 3.85 and 3.42 were the most and the least applicable tools/techniques in the knowledge storage step. "Peer assist and 'voice and VOIP' with respective means of 4.14 and 3.38 were the most and the least applicable tools/techniques in the knowledge sharing step. Finally, "knowledge worker competency plan" and "knowledge portal" with respective means of 4.38 and 3.85 were the most and the least applicable tools/techniques in the knowledge application step. The results showed that 12 out of 26 tools in the APO model are appropriate for hospitals of which 11 are significantly applicable, and "storytelling" is marginally applicable. In this study, the preferred tools/techniques for implementation of each of the five KM steps in hospitals are introduced. Copyright © 2017 Elsevier B.V. All rights reserved.

AccessMod 3.0: computing geographic coverage and accessibility to health care services using anisotropic movement of patients

PubMed Central

Ray, Nicolas; Ebener, Steeve

2008-01-01

Background Access to health care can be described along four dimensions: geographic accessibility, availability, financial accessibility and acceptability. Geographic accessibility measures how physically accessible resources are for the population, while availability reflects what resources are available and in what amount. Combining these two types of measure into a single index provides a measure of geographic (or spatial) coverage, which is an important measure for assessing the degree of accessibility of a health care network. Results This paper describes the latest version of AccessMod, an extension to the Geographical Information System ArcView 3.×, and provides an example of application of this tool. AccessMod 3 allows one to compute geographic coverage to health care using terrain information and population distribution. Four major types of analysis are available in AccessMod: (1) modeling the coverage of catchment areas linked to an existing health facility network based on travel time, to provide a measure of physical accessibility to health care; (2) modeling geographic coverage according to the availability of services; (3) projecting the coverage of a scaling-up of an existing network; (4) providing information for cost effectiveness analysis when little information about the existing network is available. In addition to integrating travelling time, population distribution and the population coverage capacity specific to each health facility in the network, AccessMod can incorporate the influence of landscape components (e.g. topography, river and road networks, vegetation) that impact travelling time to and from facilities. Topographical constraints can be taken into account through an anisotropic analysis that considers the direction of movement. We provide an example of the application of AccessMod in the southern part of Malawi that shows the influences of the landscape constraints and of the modes of transportation on geographic coverage. Conclusion By incorporating the demand (population) and the supply (capacities of heath care centers), AccessMod provides a unifying tool to efficiently assess the geographic coverage of a network of health care facilities. This tool should be of particular interest to developing countries that have a relatively good geographic information on population distribution, terrain, and health facility locations. PMID:19087277

Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement

USDA-ARS?s Scientific Manuscript database

To address the multiple challenges to food security posed by global climate change, population growth and rising incomes, plant breeders are developing new crop varieties that can enhance both agricultural productivity and environmental sustainability. Current breeding practices, however, are unable...

POPULATION MODELS FOR STREAM FISH RESPONSE TO HABITAT AND HYDROLOGIC ALTERATION: THE CVI WATERSHED TOOL

EPA Science Inventory

The Canaan Valley Institute (CVI) is dedicated to addressing the environmental problems in the Mid-Atlantic Highlands (MAH). Their goal is to develop and implement solutions to restore damaged areas and protect aquatic systems. In most wadeable streams of the Mid-Atlantic Highlan...

A new tool that links landscale connectivity and source-sink dynamics to population viability

EPA Science Inventory

The importance of connectivity and source-sink dynamics to conservation planning is widely appreciated. But the use of these concepts in practical applications such as the identification of critical habitat has been slowed because few models are designed to identify demographic s...

SDMProjectBuilder: SWAT Setup for Nutrient Fate and Transport

EPA Science Inventory

This tutorial reviews some of the screens, icons, and basic functions of the SDMProjectBuilder (SDMPB) and explains how one uses SDMPB output to populate the Soil and Water Assessment Tool (SWAT) input files for nutrient fate and transport modeling in the Salt River Basin. It dem...

Burden Calculator: a simple and open analytical tool for estimating the population burden of injuries.

PubMed

Bhalla, Kavi; Harrison, James E

2016-04-01

Burden of disease and injury methods can be used to summarise and compare the effects of conditions in terms of disability-adjusted life years (DALYs). Burden estimation methods are not inherently complex. However, as commonly implemented, the methods include complex modelling and estimation. To provide a simple and open-source software tool that allows estimation of incidence-DALYs due to injury, given data on incidence of deaths and non-fatal injuries. The tool includes a default set of estimation parameters, which can be replaced by users. The tool was written in Microsoft Excel. All calculations and values can be seen and altered by users. The parameter sets currently used in the tool are based on published sources. The tool is available without charge online at http://calculator.globalburdenofinjuries.org. To use the tool with the supplied parameter sets, users need to only paste a table of population and injury case data organised by age, sex and external cause of injury into a specified location in the tool. Estimated DALYs can be read or copied from tables and figures in another part of the tool. In some contexts, a simple and user-modifiable burden calculator may be preferable to undertaking a more complex study to estimate the burden of disease. The tool and the parameter sets required for its use can be improved by user innovation, by studies comparing DALYs estimates calculated in this way and in other ways, and by shared experience of its use. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

DIDEM - An integrated model for comparative health damage costs calculation of air pollution

NASA Astrophysics Data System (ADS)

Ravina, Marco; Panepinto, Deborah; Zanetti, Maria Chiara

2018-01-01

Air pollution represents a continuous hazard to human health. Administration, companies and population need efficient indicators of the possible effects given by a change in decision, strategy or habit. The monetary quantification of health effects of air pollution through the definition of external costs is increasingly recognized as a useful indicator to support decision and information at all levels. The development of modelling tools for the calculation of external costs can provide support to analysts in the development of consistent and comparable assessments. In this paper, the DIATI Dispersion and Externalities Model (DIDEM) is presented. The DIDEM model calculates the delta-external costs of air pollution comparing two alternative emission scenarios. This tool integrates CALPUFF's advanced dispersion modelling with the latest WHO recommendations on concentration-response functions. The model is based on the impact pathway method. It was designed to work with a fine spatial resolution and a local or national geographic scope. The modular structure allows users to input their own data sets. The DIDEM model was tested on a real case study, represented by a comparative analysis of the district heating system in Turin, Italy. Additional advantages and drawbacks of the tool are discussed in the paper. A comparison with other existing models worldwide is reported.

Concepts and tools for predictive modeling of microbial dynamics.

PubMed

Bernaerts, Kristel; Dens, Els; Vereecken, Karen; Geeraerd, Annemie H; Standaert, Arnout R; Devlieghere, Frank; Debevere, Johan; Van Impe, Jan F

2004-09-01

Description of microbial cell (population) behavior as influenced by dynamically changing environmental conditions intrinsically needs dynamic mathematical models. In the past, major effort has been put into the modeling of microbial growth and inactivation within a constant environment (static models). In the early 1990s, differential equation models (dynamic models) were introduced in the field of predictive microbiology. Here, we present a general dynamic model-building concept describing microbial evolution under dynamic conditions. Starting from an elementary model building block, the model structure can be gradually complexified to incorporate increasing numbers of influencing factors. Based on two case studies, the fundamentals of both macroscopic (population) and microscopic (individual) modeling approaches are revisited. These illustrations deal with the modeling of (i) microbial lag under variable temperature conditions and (ii) interspecies microbial interactions mediated by lactic acid production (product inhibition). Current and future research trends should address the need for (i) more specific measurements at the cell and/or population level, (ii) measurements under dynamic conditions, and (iii) more comprehensive (mechanistically inspired) model structures. In the context of quantitative microbial risk assessment, complexity of the mathematical model must be kept under control. An important challenge for the future is determination of a satisfactory trade-off between predictive power and manageability of predictive microbiology models.

Risk Reduction of an Invasive Insect by Targeting Surveillance Efforts with the Assistance of a Phenology Model and International Maritime Shipping Routes and Schedules.

PubMed

Gray, David R

2016-05-01

Reducing the risk of introduction to North America of the invasive Asian gypsy moth (Lymantria dispar asiatica Vnukovskij and L. d. japonica [Motschulsky]) on international maritime vessels involves two tactics: (1) vessels that wish to arrive in Canada or the United States and have visited any Asian port that is subject to regulation during designated times must obtain a predeparture inspection certificate from an approved entity; and (2) vessels with a certificate may be subjected to an additional inspection upon arrival. A decision support tool is described here with which the allocation of inspection resources at North American ports can be partitioned among multiple vessels according to estimates of the potential onboard Asian gypsy moth population and estimates of the onboard larval emergence pattern. The decision support tool assumes that port inspection is uniformly imperfect at the Asian ports and that each visit to a regulated port has potential for the vessel to be contaminated with gypsy moth egg masses. The decision support tool uses a multigenerational phenology model to estimate the potential onboard population of egg masses by calculating the temporal intersection between the dates of port visits to regulated ports and the simulated oviposition pattern in each port. The phenological development of the onboard population is simulated each day of the vessel log until the vessel arrives at the port being protected from introduction. Multiple independent simulations are used to create a probability distribution of the size and timing of larval emergence. © 2015 Society for Risk Analysis.

A system dynamics simulation model for sustainable water resources management and agricultural development in the Volta River Basin, Ghana.

PubMed

Kotir, Julius H; Smith, Carl; Brown, Greg; Marshall, Nadine; Johnstone, Ron

2016-12-15

In a rapidly changing water resources system, dynamic models based on the notion of systems thinking can serve as useful analytical tools for scientists and policy-makers to study changes in key system variables over time. In this paper, an integrated system dynamics simulation model was developed using a system dynamics modelling approach to examine the feedback processes and interaction between the population, the water resource, and the agricultural production sub-sectors of the Volta River Basin in West Africa. The objective of the model is to provide a learning tool for policy-makers to improve their understanding of the long-term dynamic behaviour of the basin, and as a decision support tool for exploring plausible policy scenarios necessary for sustainable water resource management and agricultural development. Structural and behavioural pattern tests, and statistical test were used to evaluate and validate the performance of the model. The results showed that the simulated outputs agreed well with the observed reality of the system. A sensitivity analysis also indicated that the model is reliable and robust to uncertainties in the major parameters. Results of the business as usual scenario showed that total population, agricultural, domestic, and industrial water demands will continue to increase over the simulated period. Besides business as usual, three additional policy scenarios were simulated to assess their impact on water demands, crop yield, and net-farm income. These were the development of the water infrastructure (scenario 1), cropland expansion (scenario 2) and dry conditions (scenario 3). The results showed that scenario 1 would provide the maximum benefit to people living in the basin. Overall, the model results could help inform planning and investment decisions within the basin to enhance food security, livelihoods development, socio-economic growth, and sustainable management of natural resources. Copyright © 2016 Elsevier B.V. All rights reserved.

Approach to functional magnetic resonance imaging of language based on models of language organization.

PubMed

McGraw, P; Mathews, V P; Wang, Y; Phillips, M D

2001-05-01

Functional MR imaging (fMRI) has been a useful tool in the evaluation of language both in normal individuals and patient populations. The purpose of this article is to use various models of language as a framework to review fMRI studies. Specifically, fMRI language studies are subdivided into the following categories: word generation or fluency, passive listening, orthography, phonology, semantics, and syntax.

Systems engineering medicine: engineering the inflammation response to infectious and traumatic challenges

PubMed Central

Parker, Robert S.; Clermont, Gilles

2010-01-01

The complexity of the systemic inflammatory response and the lack of a treatment breakthrough in the treatment of pathogenic infection demand that advanced tools be brought to bear in the treatment of severe sepsis and trauma. Systems medicine, the translational science counterpart to basic science's systems biology, is the interface at which these tools may be constructed. Rapid initial strides in improving sepsis treatment are possible through the use of phenomenological modelling and optimization tools for process understanding and device design. Higher impact, and more generalizable, treatment designs are based on mechanistic understanding developed through the use of physiologically based models, characterization of population variability, and the use of control-theoretic systems engineering concepts. In this review we introduce acute inflammation and sepsis as an example of just one area that is currently underserved by the systems medicine community, and, therefore, an area in which contributions of all types can be made. PMID:20147315

Systems engineering medicine: engineering the inflammation response to infectious and traumatic challenges.

PubMed

Parker, Robert S; Clermont, Gilles

2010-07-06

The complexity of the systemic inflammatory response and the lack of a treatment breakthrough in the treatment of pathogenic infection demand that advanced tools be brought to bear in the treatment of severe sepsis and trauma. Systems medicine, the translational science counterpart to basic science's systems biology, is the interface at which these tools may be constructed. Rapid initial strides in improving sepsis treatment are possible through the use of phenomenological modelling and optimization tools for process understanding and device design. Higher impact, and more generalizable, treatment designs are based on mechanistic understanding developed through the use of physiologically based models, characterization of population variability, and the use of control-theoretic systems engineering concepts. In this review we introduce acute inflammation and sepsis as an example of just one area that is currently underserved by the systems medicine community, and, therefore, an area in which contributions of all types can be made.

Modelling the effect of urbanization on the transmission of an infectious disease.

PubMed

Zhang, Ping; Atkinson, Peter M

2008-01-01

This paper models the impact of urbanization on infectious disease transmission by integrating a CA land use development model, population projection matrix model and CA epidemic model in S-Plus. The innovative feature of this model lies in both its explicit treatment of spatial land use development, demographic changes, infectious disease transmission and their combination in a dynamic, stochastic model. Heuristically-defined transition rules in cellular automata (CA) were used to capture the processes of both land use development with urban sprawl and infectious disease transmission. A population surface model and dwelling distribution surface were used to bridge the gap between urbanization and infectious disease transmission. A case study is presented involving modelling influenza transmission in Southampton, a dynamically evolving city in the UK. The simulation results for Southampton over a 30-year period show that the pattern of the average number of infection cases per day can depend on land use and demographic changes. The modelling framework presents a useful tool that may be of use in planning applications.

Dynamic occupancy models for explicit colonization processes

USGS Publications Warehouse

Broms, Kristin M.; Hooten, Mevin B.; Johnson, Devin S.; Altwegg, Res; Conquest, Loveday

2016-01-01

The dynamic, multi-season occupancy model framework has become a popular tool for modeling open populations with occupancies that change over time through local colonizations and extinctions. However, few versions of the model relate these probabilities to the occupancies of neighboring sites or patches. We present a modeling framework that incorporates this information and is capable of describing a wide variety of spatiotemporal colonization and extinction processes. A key feature of the model is that it is based on a simple set of small-scale rules describing how the process evolves. The result is a dynamic process that can account for complicated large-scale features. In our model, a site is more likely to be colonized if more of its neighbors were previously occupied and if it provides more appealing environmental characteristics than its neighboring sites. Additionally, a site without occupied neighbors may also become colonized through the inclusion of a long-distance dispersal process. Although similar model specifications have been developed for epidemiological applications, ours formally accounts for detectability using the well-known occupancy modeling framework. After demonstrating the viability and potential of this new form of dynamic occupancy model in a simulation study, we use it to obtain inference for the ongoing Common Myna (Acridotheres tristis) invasion in South Africa. Our results suggest that the Common Myna continues to enlarge its distribution and its spread via short distance movement, rather than long-distance dispersal. Overall, this new modeling framework provides a powerful tool for managers examining the drivers of colonization including short- vs. long-distance dispersal, habitat quality, and distance from source populations.

Parameter-expanded data augmentation for Bayesian analysis of capture-recapture models

USGS Publications Warehouse

Royle, J. Andrew; Dorazio, Robert M.

2012-01-01

Data augmentation (DA) is a flexible tool for analyzing closed and open population models of capture-recapture data, especially models which include sources of hetereogeneity among individuals. The essential concept underlying DA, as we use the term, is based on adding "observations" to create a dataset composed of a known number of individuals. This new (augmented) dataset, which includes the unknown number of individuals N in the population, is then analyzed using a new model that includes a reformulation of the parameter N in the conventional model of the observed (unaugmented) data. In the context of capture-recapture models, we add a set of "all zero" encounter histories which are not, in practice, observable. The model of the augmented dataset is a zero-inflated version of either a binomial or a multinomial base model. Thus, our use of DA provides a general approach for analyzing both closed and open population models of all types. In doing so, this approach provides a unified framework for the analysis of a huge range of models that are treated as unrelated "black boxes" and named procedures in the classical literature. As a practical matter, analysis of the augmented dataset by MCMC is greatly simplified compared to other methods that require specialized algorithms. For example, complex capture-recapture models of an augmented dataset can be fitted with popular MCMC software packages (WinBUGS or JAGS) by providing a concise statement of the model's assumptions that usually involves only a few lines of pseudocode. In this paper, we review the basic technical concepts of data augmentation, and we provide examples of analyses of closed-population models (M 0, M h , distance sampling, and spatial capture-recapture models) and open-population models (Jolly-Seber) with individual effects.

Application of digital human modeling and simulation for vision analysis of pilots in a jet aircraft: a case study.

PubMed

Karmakar, Sougata; Pal, Madhu Sudan; Majumdar, Deepti; Majumdar, Dhurjati

2012-01-01

Ergonomic evaluation of visual demands becomes crucial for the operators/users when rapid decision making is needed under extreme time constraint like navigation task of jet aircraft. Research reported here comprises ergonomic evaluation of pilot's vision in a jet aircraft in virtual environment to demonstrate how vision analysis tools of digital human modeling software can be used effectively for such study. Three (03) dynamic digital pilot models, representative of smallest, average and largest Indian pilot population were generated from anthropometric database and interfaced with digital prototype of the cockpit in Jack software for analysis of vision within and outside the cockpit. Vision analysis tools like view cones, eye view windows, blind spot area, obscuration zone, reflection zone etc. were employed during evaluation of visual fields. Vision analysis tool was also used for studying kinematic changes of pilot's body joints during simulated gazing activity. From present study, it can be concluded that vision analysis tool of digital human modeling software was found very effective in evaluation of position and alignment of different displays and controls in the workstation based upon their priorities within the visual fields and anthropometry of the targeted users, long before the development of its physical prototype.

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

EUCLID: an outcome analysis tool for high-dimensional clinical studies

NASA Astrophysics Data System (ADS)

Gayou, Olivier; Parda, David S.; Miften, Moyed

2007-03-01

Treatment management decisions in three-dimensional conformal radiation therapy (3DCRT) and intensity-modulated radiation therapy (IMRT) are usually made based on the dose distributions in the target and surrounding normal tissue. These decisions may include, for example, the choice of one treatment over another and the level of tumour dose escalation. Furthermore, biological predictors such as tumour control probability (TCP) and normal tissue complication probability (NTCP), whose parameters available in the literature are only population-based estimates, are often used to assess and compare plans. However, a number of other clinical, biological and physiological factors also affect the outcome of radiotherapy treatment and are often not considered in the treatment planning and evaluation process. A statistical outcome analysis tool, EUCLID, for direct use by radiation oncologists and medical physicists was developed. The tool builds a mathematical model to predict an outcome probability based on a large number of clinical, biological, physiological and dosimetric factors. EUCLID can first analyse a large set of patients, such as from a clinical trial, to derive regression correlation coefficients between these factors and a given outcome. It can then apply such a model to an individual patient at the time of treatment to derive the probability of that outcome, allowing the physician to individualize the treatment based on medical evidence that encompasses a wide range of factors. The software's flexibility allows the clinicians to explore several avenues to select the best predictors of a given outcome. Its link to record-and-verify systems and data spreadsheets allows for a rapid and practical data collection and manipulation. A wide range of statistical information about the study population, including demographics and correlations between different factors, is available. A large number of one- and two-dimensional plots, histograms and survival curves allow for an easy visual analysis of the population. Several visual and analytical methods are available to quantify the predictive power of the multivariate regression model. The EUCLID tool can be readily integrated with treatment planning and record-and-verify systems.

EUCLID: an outcome analysis tool for high-dimensional clinical studies.

PubMed

Gayou, Olivier; Parda, David S; Miften, Moyed

2007-03-21

Treatment management decisions in three-dimensional conformal radiation therapy (3DCRT) and intensity-modulated radiation therapy (IMRT) are usually made based on the dose distributions in the target and surrounding normal tissue. These decisions may include, for example, the choice of one treatment over another and the level of tumour dose escalation. Furthermore, biological predictors such as tumour control probability (TCP) and normal tissue complication probability (NTCP), whose parameters available in the literature are only population-based estimates, are often used to assess and compare plans. However, a number of other clinical, biological and physiological factors also affect the outcome of radiotherapy treatment and are often not considered in the treatment planning and evaluation process. A statistical outcome analysis tool, EUCLID, for direct use by radiation oncologists and medical physicists was developed. The tool builds a mathematical model to predict an outcome probability based on a large number of clinical, biological, physiological and dosimetric factors. EUCLID can first analyse a large set of patients, such as from a clinical trial, to derive regression correlation coefficients between these factors and a given outcome. It can then apply such a model to an individual patient at the time of treatment to derive the probability of that outcome, allowing the physician to individualize the treatment based on medical evidence that encompasses a wide range of factors. The software's flexibility allows the clinicians to explore several avenues to select the best predictors of a given outcome. Its link to record-and-verify systems and data spreadsheets allows for a rapid and practical data collection and manipulation. A wide range of statistical information about the study population, including demographics and correlations between different factors, is available. A large number of one- and two-dimensional plots, histograms and survival curves allow for an easy visual analysis of the population. Several visual and analytical methods are available to quantify the predictive power of the multivariate regression model. The EUCLID tool can be readily integrated with treatment planning and record-and-verify systems.

Stochastic empirical loading and dilution model for analysis of flows, concentrations, and loads of highway runoff constituents

USGS Publications Warehouse

Granato, Gregory E.; Jones, Susan C.

2014-01-01

In cooperation with FHWA, the U.S. Geological Survey developed the stochastic empirical loading and dilution model (SELDM) to supersede the 1990 FHWA runoff quality model. The SELDM tool is designed to transform disparate and complex scientific data into meaningful information about the adverse risks of runoff on receiving waters, the potential need for mitigation measures, and the potential effectiveness of such measures for reducing such risks. The SELDM tool is easy to use because much of the information and data needed to run it are embedded in the model and obtained by defining the site location and five simple basin properties. Information and data from thousands of sites across the country were compiled to facilitate the use of the SELDM tool. A case study illustrates how to use the SELDM tool for conducting the types of sensitivity analyses needed to properly assess water quality risks. For example, the use of deterministic values to model upstream stormflows instead of representative variations in prestorm flow and runoff may substantially overestimate the proportion of highway runoff in downstream flows. Also, the risks for total phosphorus excursions are substantially affected by the selected criteria and the modeling methods used. For example, if a single deterministic concentration is used rather than a stochastic population of values to model upstream concentrations, then the percentage of water quality excursions in the downstream receiving waters may depend entirely on the selected upstream concentration.

Population viability analysis: using a modeling tool to assess the viability of tapir populations in fragmented landscapes.

PubMed

Medici, Emília Patrícia; Desbiez, Arnaud Leonard Jean

2012-12-01

A population viability analysis (PVA) was conducted of the lowland tapir populations in the Atlantic Forest of the Pontal do Paranapanema region, Brazil, including Morro do Diabo State Park (MDSP) and surrounding forest fragments. Results from the model projected that the population of 126 tapirs in MDSP is likely to persist over the next 100 years; however, 200 tapirs would be required to maintain a viable population. Sensitivity analysis showed that sub-adult mortality and adult mortality have the strongest influence on the dynamics of lowland tapir populations. High road-kill has a major impact on the MDSP tapir population and can lead to population extinction. Metapopulation modeling showed that dispersal of tapirs from MDSP to the surrounding fragments can be detrimental to the overall metapopulation, as fragments act as sinks. Nevertheless, the model showed that under certain conditions the maintenance of the metapopulation dynamics might be determinant for the persistence of tapirs in the region, particularly in the smaller fragments. The establishment of corridors connecting MDSP to the forest fragments models resulted in an increase in the stochastic growth rate, making tapirs more resilient to threats and catastrophes, but only if rates of mortality were not increased when using corridors. The PVA showed that the conservation of tapirs in the Pontal region depends on: the effective protection of MDSP; maintenance and, whenever possible, enhancement of the functional connectivity of the landscape, reducing mortality during dispersal and threats in the unprotected forest fragments; and neutralization of all threats affecting tapirs in the smaller forest fragments. © 2012 Wiley Publishing Asia Pty Ltd, ISZS and IOZ/CAS.

Quality Dashboards: Technical and Architectural Considerations of an Actionable Reporting Tool for Population Management

PubMed Central

Olsha-Yehiav, Maya; Einbinder, Jonathan S.; Jung, Eunice; Linder, Jeffrey A.; Greim, Julie; Li, Qi; Schnipper, Jeffrey L.; Middleton, Blackford

2006-01-01

Quality Dashboards (QD) is a condition-specific, actionable web-based application for quality reporting and population management that is integrated into the Electronic Health Record (EHR). Using server-based graphic web controls in a .Net environment to construct Quality Dashboards allows customization of the reporting tool without the need to rely on commercial business intelligence tool. Quality Dashboards will improve patient care and quality outcomes as clinicians utilize the reporting tool for population management. PMID:17238671

Stellar Populations. A User Guide from Low to High Redshift

NASA Astrophysics Data System (ADS)

Greggio, Laura; Renzini, Alvio

2011-09-01

This textbook is meant to illustrate the specific role played by stellar population diagnostics in our attempt to understand galaxy formation and evolution. The book starts with a rather unconventional summary of the results of stellar evolution theory (Chapter 1), as they provide the basis for the construction of synthetic stellar populations. Current limitations of stellar models are highlighted, which arise from the necessity to parametrize all those physical processes that involve bulk mass motions, such as convection, mixing, mass loss, etc. Chapter 2 deals with the foundations of the theory of synthetic stellar populations, and illustrates their energetics and metabolic functions, providing basic tools that will be used in subsequent chapters. Chapters 3 and 4 deal with resolved stellar populations, first addressing some general problems encountered in photometric studies of stellar fields. Then some highlights are presented illustrating our current capacity of measuring stellar ages in Galactic globular clusters, in the Galactic bulge and in nearby galaxies. Chapter 5 is dedicated to the exemplification of synthetic spectra of simple as well as composite stellar populations, drawing attention to those spectral features that may depend on less secure results of stellar evolution models. Chapter 6 illustrates how synthetic stellar populations are used to derive basic galaxy properties, such as star formation rates, stellar masses, ages and metallicities, and does so for galaxies at low as well as at high redshifts. Chapter 7 is dedicated to supernovae, distinguishing them in core collapse and thermonuclear cases, describing the evolution of their rates for various star formation histories, and estimating the supernova productivity of stellar populations and their chemical yields. In Chapter 8 the stellar initial mass function (IMF) is discussed, first showing how even apparently small IMF variations may have large effects on the demo! graphy of stellar populations, and then using galaxies at low ! and high redshifts and clusters of galaxies to set tight constraints on possible IMF variations in space or time. In Chapter 9 a phenomenological model of galaxy evolution is presented which illustrates a concrete application of the stellar population tools described in the previous chapters. Finally, Chapter 10 is dedicated to the chemical evolution on the scale of galaxies, clusters of galaxies and the whole Universe.

New parsimonious simulation methods and tools to assess future food and environmental security of farm populations

PubMed Central

Antle, John M.; Stoorvogel, Jetse J.; Valdivia, Roberto O.

2014-01-01

This article presents conceptual and empirical foundations for new parsimonious simulation models that are being used to assess future food and environmental security of farm populations. The conceptual framework integrates key features of the biophysical and economic processes on which the farming systems are based. The approach represents a methodological advance by coupling important behavioural processes, for example, self-selection in adaptive responses to technological and environmental change, with aggregate processes, such as changes in market supply and demand conditions or environmental conditions as climate. Suitable biophysical and economic data are a critical limiting factor in modelling these complex systems, particularly for the characterization of out-of-sample counterfactuals in ex ante analyses. Parsimonious, population-based simulation methods are described that exploit available observational, experimental, modelled and expert data. The analysis makes use of a new scenario design concept called representative agricultural pathways. A case study illustrates how these methods can be used to assess food and environmental security. The concluding section addresses generalizations of parametric forms and linkages of regional models to global models. PMID:24535388

New parsimonious simulation methods and tools to assess future food and environmental security of farm populations.

PubMed

Antle, John M; Stoorvogel, Jetse J; Valdivia, Roberto O

2014-04-05

This article presents conceptual and empirical foundations for new parsimonious simulation models that are being used to assess future food and environmental security of farm populations. The conceptual framework integrates key features of the biophysical and economic processes on which the farming systems are based. The approach represents a methodological advance by coupling important behavioural processes, for example, self-selection in adaptive responses to technological and environmental change, with aggregate processes, such as changes in market supply and demand conditions or environmental conditions as climate. Suitable biophysical and economic data are a critical limiting factor in modelling these complex systems, particularly for the characterization of out-of-sample counterfactuals in ex ante analyses. Parsimonious, population-based simulation methods are described that exploit available observational, experimental, modelled and expert data. The analysis makes use of a new scenario design concept called representative agricultural pathways. A case study illustrates how these methods can be used to assess food and environmental security. The concluding section addresses generalizations of parametric forms and linkages of regional models to global models.

From data to function: functional modeling of poultry genomics data.

PubMed

McCarthy, F M; Lyons, E

2013-09-01

One of the challenges of functional genomics is to create a better understanding of the biological system being studied so that the data produced are leveraged to provide gains for agriculture, human health, and the environment. Functional modeling enables researchers to make sense of these data as it reframes a long list of genes or gene products (mRNA, ncRNA, and proteins) by grouping based upon function, be it individual molecular functions or interactions between these molecules or broader biological processes, including metabolic and signaling pathways. However, poultry researchers have been hampered by a lack of functional annotation data, tools, and training to use these data and tools. Moreover, this lack is becoming more critical as new sequencing technologies enable us to generate data not only for an increasingly diverse range of species but also individual genomes and populations of individuals. We discuss the impact of these new sequencing technologies on poultry research, with a specific focus on what functional modeling resources are available for poultry researchers. We also describe key strategies for researchers who wish to functionally model their own data, providing background information about functional modeling approaches, the data and tools to support these approaches, and the strengths and limitations of each. Specifically, we describe methods for functional analysis using Gene Ontology (GO) functional summaries, functional enrichment analysis, and pathways and network modeling. As annotation efforts begin to provide the fundamental data that underpin poultry functional modeling (such as improved gene identification, standardized gene nomenclature, temporal and spatial expression data and gene product function), tool developers are incorporating these data into new and existing tools that are used for functional modeling, and cyberinfrastructure is being developed to provide the necessary extendibility and scalability for storing and analyzing these data. This process will support the efforts of poultry researchers to make sense of their functional genomics data sets, and we provide here a starting point for researchers who wish to take advantage of these tools.

TMAP: Tübingen NLTE Model-Atmosphere Package

NASA Astrophysics Data System (ADS)

Werner, Klaus; Dreizler, Stefan; Rauch, Thomas

2012-12-01

The Tübingen NLTE Model-Atmosphere Package (TMAP) is a tool to calculate stellar atmospheres in spherical or plane-parallel geometry in hydrostatic and radiative equilibrium allowing departures from local thermodynamic equilibrium (LTE) for the population of atomic levels. It is based on the Accelerated Lambda Iteration (ALI) method and is able to account for line blanketing by metals. All elements from hydrogen to nickel may be included in the calculation with model atoms which are tailored for the aims of the user.

Disease management with ARIMA model in time series.

PubMed

Sato, Renato Cesar

2013-01-01

The evaluation of infectious and noninfectious disease management can be done through the use of a time series analysis. In this study, we expect to measure the results and prevent intervention effects on the disease. Clinical studies have benefited from the use of these techniques, particularly for the wide applicability of the ARIMA model. This study briefly presents the process of using the ARIMA model. This analytical tool offers a great contribution for researchers and healthcare managers in the evaluation of healthcare interventions in specific populations.

Collective learning modeling based on the kinetic theory of active particles

NASA Astrophysics Data System (ADS)

Burini, D.; De Lillo, S.; Gibelli, L.

2016-03-01

This paper proposes a systems approach to the theory of perception and learning in populations composed of many living entities. Starting from a phenomenological description of these processes, a mathematical structure is derived which is deemed to incorporate their complexity features. The modeling is based on a generalization of kinetic theory methods where interactions are described by theoretical tools of game theory. As an application, the proposed approach is used to model the learning processes that take place in a classroom.

Stochastic differential equations in NONMEM: implementation, application, and comparison with ordinary differential equations.

PubMed

Tornøe, Christoffer W; Overgaard, Rune V; Agersø, Henrik; Nielsen, Henrik A; Madsen, Henrik; Jonsson, E Niclas

2005-08-01

The objective of the present analysis was to explore the use of stochastic differential equations (SDEs) in population pharmacokinetic/pharmacodynamic (PK/PD) modeling. The intra-individual variability in nonlinear mixed-effects models based on SDEs is decomposed into two types of noise: a measurement and a system noise term. The measurement noise represents uncorrelated error due to, for example, assay error while the system noise accounts for structural misspecifications, approximations of the dynamical model, and true random physiological fluctuations. Since the system noise accounts for model misspecifications, the SDEs provide a diagnostic tool for model appropriateness. The focus of the article is on the implementation of the Extended Kalman Filter (EKF) in NONMEM for parameter estimation in SDE models. Various applications of SDEs in population PK/PD modeling are illustrated through a systematic model development example using clinical PK data of the gonadotropin releasing hormone (GnRH) antagonist degarelix. The dynamic noise estimates were used to track variations in model parameters and systematically build an absorption model for subcutaneously administered degarelix. The EKF-based algorithm was successfully implemented in NONMEM for parameter estimation in population PK/PD models described by systems of SDEs. The example indicated that it was possible to pinpoint structural model deficiencies, and that valuable information may be obtained by tracking unexplained variations in parameters.

Combining multistate capture-recapture data with tag recoveries to estimate demographic parameters

USGS Publications Warehouse

Kendall, W.L.; Conn, P.B.; Hines, J.E.

2006-01-01

Matrix population models that allow an animal to occupy more than one state over time are important tools for population and evolutionary ecologists. Definition of state can vary, including location for metapopulation models and breeding state for life history models. For populations whose members can be marked and subsequently re-encountered, multistate mark-recapture models are available to estimate the survival and transition probabilities needed to construct population models. Multistate models have proved extremely useful in this context, but they often require a substantial amount of data and restrict estimation of transition probabilities to those areas or states subjected to formal sampling effort. At the same time, for many species, there are considerable tag recovery data provided by the public that could be modeled in order to increase precision and to extend inference to a greater number of areas or states. Here we present a statistical model for combining multistate capture-recapture data (e.g., from a breeding ground study) with multistate tag recovery data (e.g., from wintering grounds). We use this method to analyze data from a study of Canada Geese (Branta canadensis) in the Atlantic Flyway of North America. Our analysis produced marginal improvement in precision, due to relatively few recoveries, but we demonstrate how precision could be further improved with increases in the probability that a retrieved tag is reported.

Parameterization and Sensitivity Analysis of a Complex Simulation Model for Mosquito Population Dynamics, Dengue Transmission, and Their Control

PubMed Central

Ellis, Alicia M.; Garcia, Andres J.; Focks, Dana A.; Morrison, Amy C.; Scott, Thomas W.

2011-01-01

Models can be useful tools for understanding the dynamics and control of mosquito-borne disease. More detailed models may be more realistic and better suited for understanding local disease dynamics; however, evaluating model suitability, accuracy, and performance becomes increasingly difficult with greater model complexity. Sensitivity analysis is a technique that permits exploration of complex models by evaluating the sensitivity of the model to changes in parameters. Here, we present results of sensitivity analyses of two interrelated complex simulation models of mosquito population dynamics and dengue transmission. We found that dengue transmission may be influenced most by survival in each life stage of the mosquito, mosquito biting behavior, and duration of the infectious period in humans. The importance of these biological processes for vector-borne disease models and the overwhelming lack of knowledge about them make acquisition of relevant field data on these biological processes a top research priority. PMID:21813844

Examples of Mathematical Modeling

PubMed Central

Johnston, Matthew D.; Edwards, Carina M.; Bodmer, Walter F.; Maini, Philip K.; Chapman, S. Jonathan

2008-01-01

Mathematical modeling is being increasingly recognized within the biomedical sciences as an important tool that can aid the understanding of biological systems. The heavily regulated cell renewal cycle in the colonic crypt provides a good example of how modeling can be used to find out key features of the system kinetics, and help to explain both the breakdown of homeostasis and the initiation of tumorigenesis. We use the cell population model by Johnston et al.5 to illustrate the power of mathematical modeling by considering two key questions about the cell population dynamics in the colonic crypt. We ask: how can a model describe both homeostasis and unregulated growth in tumorigenesis; and to which parameters in the system is the model most sensitive? In order to address these questions, we discuss what type of modeling approach is most appropriate in the crypt. We use the model to argue why tumorigenesis is observed to occur in stages with long lag phases between periods of rapid growth, and we identify the key parameters. PMID:17873520

Using latent class analysis to model prescription medications in the measurement of falling among a community elderly population

PubMed Central

2013-01-01

Background Falls among the elderly are a major public health concern. Therefore, the possibility of a modeling technique which could better estimate fall probability is both timely and needed. Using biomedical, pharmacological and demographic variables as predictors, latent class analysis (LCA) is demonstrated as a tool for the prediction of falls among community dwelling elderly. Methods Using a retrospective data-set a two-step LCA modeling approach was employed. First, we looked for the optimal number of latent classes for the seven medical indicators, along with the patients’ prescription medication and three covariates (age, gender, and number of medications). Second, the appropriate latent class structure, with the covariates, were modeled on the distal outcome (fall/no fall). The default estimator was maximum likelihood with robust standard errors. The Pearson chi-square, likelihood ratio chi-square, BIC, Lo-Mendell-Rubin Adjusted Likelihood Ratio test and the bootstrap likelihood ratio test were used for model comparisons. Results A review of the model fit indices with covariates shows that a six-class solution was preferred. The predictive probability for latent classes ranged from 84% to 97%. Entropy, a measure of classification accuracy, was good at 90%. Specific prescription medications were found to strongly influence group membership. Conclusions In conclusion the LCA method was effective at finding relevant subgroups within a heterogenous at-risk population for falling. This study demonstrated that LCA offers researchers a valuable tool to model medical data. PMID:23705639

Outside the Continental United States International Travel and Contagion Impact Quick Look Tool

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

Corley, Courtney D.; Lancaster, Mary J.; Brigantic, Robert T.

2012-11-09

ABSTRACT This paper describes a tool that will allow public health analysts to estimate infectious disease risk at the country level as a function of different international transportation modes. The prototype focuses on a cholera epidemic originating within Latin America or the Caribbean, but it can be expanded to consider other pathogens as well. This effort leverages previous work in collaboration with the Centers for Disease Control and Prevention to develop the International Travel to Community Impact (IT-CI) model, which analyzes and assesses potential international disease outbreaks then estimates the associated impacts to U.S. communities and the nation as amore » whole and orient it for use Outside the Continental United States (OCONUS). For brevity, we refer to this refined model as OIT-CI. First, we developed an operationalized meta-population spatial cholera model for Latin America and the Caribbean at the secondary administrative-level boundary. Secondly, we developed a robust function of human airline critical to approximating mixing patterns in the meta- population model. In the prototype version currently presented here, OIT-CI models a cholera epidemic originating in a Latin American or Caribbean country and spreading via airline transportation routes. Disease spread is modeled at the country level using a patch model with a connectivity function based on demographic, geospatial, and human transportation data. We have also identified data to estimate the water and health-related infrastructure capabilities of each country to include this potential impact on disease transmission.« less

A Biomathematical Model of Lymphopoiesis and Its Application to Acute and Chronic Irradiation Assessment

NASA Technical Reports Server (NTRS)

Hu, Shaowen; Cucinotta, Francis A.

2010-01-01

After the events of September 11, 2001, there is an increasing concern of the occurrence of radiological terrorism that may result in significant casualties in densely populated areas. Much effort has been made to establish various biomarkers to rapidly assess radiation dose in mass-casualty and population-monitoring scenarios, which are demanded for effective medical management and treatment of the exposed victims. Among these the count of lymphocytes in peripheral blood and their depletion kinetics are the most important early indicators of the severity of the radiation injury. In this study, we examine a biomathematical model of lymphopoiesis which has been successfully utilized to simulate and interpret experimental data of acute and chronic irradiations on rodents [1]. With revised parameters for humans, we find this model can reproduce several sets of clinical lymphocyte data of accident victims over a wide range of absorbed doses. In addition, the absolute lymphocyte counts and the depletion rate constants calculated by this model also show good correlation with the Guskova formula and the Goans model, the two empirical tools which have been widely recognized for early estimation of the exposed dose after radiation accidents [2]. We also use the model to analyze the hematological data of the Techa River residents which were exposed to chronic low-dose irradiation during 1950-1956 [3]. This model can serve as a computational tool in radiation accident management, military operations involving nuclear warfare, radiation therapy, and space radiation risk assessment.

Incorporating diverse data and realistic complexity into demographic estimation procedures for sea otters

USGS Publications Warehouse

Tinker, M. Timothy; Doak, Daniel F.; Estes, James A.; Hatfield, Brian B.; Staedler, Michelle M.; Gross, Arthur

2006-01-01

Reliable information on historical and current population dynamics is central to understanding patterns of growth and decline in animal populations. We developed a maximum likelihood-based analysis to estimate spatial and temporal trends in age/sex-specific survival rates for the threatened southern sea otter (Enhydra lutris nereis), using annual population censuses and the age structure of salvaged carcass collections. We evaluated a wide range of possible spatial and temporal effects and used model averaging to incorporate model uncertainty into the resulting estimates of key vital rates and their variances. We compared these results to current demographic parameters estimated in a telemetry-based study conducted between 2001 and 2004. These results show that survival has decreased substantially from the early 1990s to the present and is generally lowest in the north-central portion of the population's range. The greatest temporal decrease in survival was for adult females, and variation in the survival of this age/sex class is primarily responsible for regulating population growth and driving population trends. Our results can be used to focus future research on southern sea otters by highlighting the life history stages and mortality factors most relevant to conservation. More broadly, we have illustrated how the powerful and relatively straightforward tools of information-theoretic-based model fitting can be used to sort through and parameterize quite complex demographic modeling frameworks. ?? 2006 by the Ecological Society of America.

Restricted gene flow and fine-scale population structuring in tool using New Caledonian crows

NASA Astrophysics Data System (ADS)

Rutz, C.; Ryder, T. B.; Fleischer, R. C.

2012-04-01

New Caledonian crows Corvus moneduloides are the most prolific avian tool users. It has been suggested that some aspects of their complex tool use behaviour are under the influence of cultural processes, involving the social transmission—and perhaps even progressive refinement—of tool designs. Using microsatellite and mt-haplotype profiling of crows from three distinct habitats (dry forest, farmland and beachside habitat), we show that New Caledonian crow populations can exhibit significant fine-scale genetic structuring. Our finding that some sites of <10 km apart were highly differentiated demonstrates considerable potential for genetic and/or cultural isolation of crow groups. Restricted movement of birds between local populations at such small spatial scales, especially across habitat boundaries, illustrates how specific tool designs could be preserved over time, and how tool technologies of different crow groups could diverge due to drift and local selection pressures. Young New Caledonian crows have an unusually long juvenile dependency period, during which they acquire complex tool-related foraging skills. We suggest that the resulting delayed natal dispersal drives population-divergence patterns in this species. Our work provides essential context for future studies that examine the genetic makeup of crow populations across larger geographic areas, including localities with suspected cultural differences in crow tool technologies.

A Population Synthesis Study of Terrestrial Gamma-ray Flashes

NASA Astrophysics Data System (ADS)

Cramer, E. S.; Briggs, M. S.; Stanbro, M.; Dwyer, J. R.; Mailyan, B. G.; Roberts, O.

2017-12-01

In astrophysics, population synthesis models are tools used to determine what mix of stars could be consistent with the observations, e.g. how the intrinsic mass-to-light ratio changes by the measurement process. A similar technique could be used to understand the production of TGFs. The models used for this type of population study probe the conditions of electron acceleration inside the high electric field regions of thunderstorms, i.e. acceleration length, electric field strength, and beaming angles. In this work, we use a Monte Carlo code to generate bremsstrahlung photons from relativistic electrons that are accelerated by a large-scale RREA thunderstorm electric field. The code simulates the propagation of photons through the atmosphere at various source altitudes, where they interact with air via Compton scattering, pair production, and photoelectric absorption. We then show the differences in the hardness ratio at spacecraft altitude between these different simulations and compare them with TGF data from Fermi-GBM. Such comparisons can lead to constraints that can be applied to popular TGF beaming models, and help determine whether the population presented in this study is consistent or not with reality.

A stochastic simulator of birth-death master equations with application to phylodynamics.

PubMed

Vaughan, Timothy G; Drummond, Alexei J

2013-06-01

In this article, we present a versatile new software tool for the simulation and analysis of stochastic models of population phylodynamics and chemical kinetics. Models are specified via an expressive and human-readable XML format and can be used as the basis for generating either single population histories or large ensembles of such histories. Importantly, phylogenetic trees or networks can be generated alongside the histories they correspond to, enabling investigations into the interplay between genealogies and population dynamics. Summary statistics such as means and variances can be recorded in place of the full ensemble, allowing for a reduction in the amount of memory used--an important consideration for models including large numbers of individual subpopulations or demes. In the case of population size histories, the resulting simulation output is written to disk in the flexible JSON format, which is easily read into numerical analysis environments such as R for visualization or further processing. Simulated phylogenetic trees can be recorded using the standard Newick or NEXUS formats, with extensions to these formats used for non-tree-like inheritance relationships.

A Stochastic Simulator of Birth–Death Master Equations with Application to Phylodynamics

PubMed Central

Vaughan, Timothy G.; Drummond, Alexei J.

2013-01-01

In this article, we present a versatile new software tool for the simulation and analysis of stochastic models of population phylodynamics and chemical kinetics. Models are specified via an expressive and human-readable XML format and can be used as the basis for generating either single population histories or large ensembles of such histories. Importantly, phylogenetic trees or networks can be generated alongside the histories they correspond to, enabling investigations into the interplay between genealogies and population dynamics. Summary statistics such as means and variances can be recorded in place of the full ensemble, allowing for a reduction in the amount of memory used—an important consideration for models including large numbers of individual subpopulations or demes. In the case of population size histories, the resulting simulation output is written to disk in the flexible JSON format, which is easily read into numerical analysis environments such as R for visualization or further processing. Simulated phylogenetic trees can be recorded using the standard Newick or NEXUS formats, with extensions to these formats used for non-tree-like inheritance relationships. PMID:23505043

Statistical tools for analysis and modeling of cosmic populations and astronomical time series: CUDAHM and TSE

NASA Astrophysics Data System (ADS)

Loredo, Thomas; Budavari, Tamas; Scargle, Jeffrey D.

2018-01-01

This presentation provides an overview of open-source software packages addressing two challenging classes of astrostatistics problems. (1) CUDAHM is a C++ framework for hierarchical Bayesian modeling of cosmic populations, leveraging graphics processing units (GPUs) to enable applying this computationally challenging paradigm to large datasets. CUDAHM is motivated by measurement error problems in astronomy, where density estimation and linear and nonlinear regression must be addressed for populations of thousands to millions of objects whose features are measured with possibly complex uncertainties, potentially including selection effects. An example calculation demonstrates accurate GPU-accelerated luminosity function estimation for simulated populations of $10^6$ objects in about two hours using a single NVIDIA Tesla K40c GPU. (2) Time Series Explorer (TSE) is a collection of software in Python and MATLAB for exploratory analysis and statistical modeling of astronomical time series. It comprises a library of stand-alone functions and classes, as well as an application environment for interactive exploration of times series data. The presentation will summarize key capabilities of this emerging project, including new algorithms for analysis of irregularly-sampled time series.

Modeling Terrorism Risk to the Air Transportation System: An Independent Assessment of TSA’s Risk Management Analysis Tool and Associated Methods

DTIC Science & Technology

2012-01-01

our own work for this discussion. DoD Instruction 5000.61 defines model validation as “the pro - cess of determining the degree to which a model and its... determined that RMAT is highly con - crete code, potentially leading to redundancies in the code itself and making RMAT more difficult to maintain...system con - ceptual models valid, and are the data used to support them adequate? (Chapters Two and Three) 2. Are the sources and methods for populating

Building the bridge between animal movement and population dynamics.

PubMed

Morales, Juan M; Moorcroft, Paul R; Matthiopoulos, Jason; Frair, Jacqueline L; Kie, John G; Powell, Roger A; Merrill, Evelyn H; Haydon, Daniel T

2010-07-27

While the mechanistic links between animal movement and population dynamics are ecologically obvious, it is much less clear when knowledge of animal movement is a prerequisite for understanding and predicting population dynamics. GPS and other technologies enable detailed tracking of animal location concurrently with acquisition of landscape data and information on individual physiology. These tools can be used to refine our understanding of the mechanistic links between behaviour and individual condition through 'spatially informed' movement models where time allocation to different behaviours affects individual survival and reproduction. For some species, socially informed models that address the movements and average fitness of differently sized groups and how they are affected by fission-fusion processes at relevant temporal scales are required. Furthermore, as most animals revisit some places and avoid others based on their previous experiences, we foresee the incorporation of long-term memory and intention in movement models. The way animals move has important consequences for the degree of mixing that we expect to find both within a population and between individuals of different species. The mixing rate dictates the level of detail required by models to capture the influence of heterogeneity and the dynamics of intra- and interspecific interaction.

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.

A comparative phylogenetic study of genetics and folk music.

PubMed

Pamjav, Horolma; Juhász, Zoltán; Zalán, Andrea; Németh, Endre; Damdin, Bayarlkhagva

2012-04-01

Computer-aided comparison of folk music from different nations is one of the newest research areas. We were intrigued to have identified some important similarities between phylogenetic studies and modern folk music. First of all, both of them use similar concepts and representation tools such as multidimensional scaling for modelling relationship between populations. This gave us the idea to investigate whether these connections are merely accidental or if they mirror population migrations from the past. We raised the question; does the complex structure of musical connections display a clear picture and can this system be interpreted by the genetic analysis? This study is the first to systematically investigate the incidental genetic background of the folk music context between different populations. Paternal (42 populations) and maternal lineages (56 populations) were compared based on Fst genetic distances of the Y chromosomal and mtDNA haplogroup frequencies. To test this hypothesis, the corresponding musical cultures were also compared using an automatic overlap analysis of parallel melody styles for 31 Eurasian nations. We found that close musical relations of populations indicate close genetic distances (<0.05) with a probability of 82%. It was observed that there is a significant correlation between population genetics and folk music; maternal lineages have a more important role in folk music traditions than paternal lineages. Furthermore, the combination of these disciplines establishing a new interdisciplinary research field of "music-genetics" can be an efficient tool to get a more comprehensive picture on the complex behaviour of populations in prehistoric time.

From Experiment to Theory: What Can We Learn from Growth Curves?

PubMed

Kareva, Irina; Karev, Georgy

2018-01-01

Finding an appropriate functional form to describe population growth based on key properties of a described system allows making justified predictions about future population development. This information can be of vital importance in all areas of research, ranging from cell growth to global demography. Here, we use this connection between theory and observation to pose the following question: what can we infer about intrinsic properties of a population (i.e., degree of heterogeneity, or dependence on external resources) based on which growth function best fits its growth dynamics? We investigate several nonstandard classes of multi-phase growth curves that capture different stages of population growth; these models include hyperbolic-exponential, exponential-linear, exponential-linear-saturation growth patterns. The constructed models account explicitly for the process of natural selection within inhomogeneous populations. Based on the underlying hypotheses for each of the models, we identify whether the population that it best fits by a particular curve is more likely to be homogeneous or heterogeneous, grow in a density-dependent or frequency-dependent manner, and whether it depends on external resources during any or all stages of its development. We apply these predictions to cancer cell growth and demographic data obtained from the literature. Our theory, if confirmed, can provide an additional biomarker and a predictive tool to complement experimental research.

Forecasting extinction risk with nonstationary matrix models.

PubMed

Gotelli, Nicholas J; Ellison, Aaron M

2006-02-01

Matrix population growth models are standard tools for forecasting population change and for managing rare species, but they are less useful for predicting extinction risk in the face of changing environmental conditions. Deterministic models provide point estimates of lambda, the finite rate of increase, as well as measures of matrix sensitivity and elasticity. Stationary matrix models can be used to estimate extinction risk in a variable environment, but they assume that the matrix elements are randomly sampled from a stationary (i.e., non-changing) distribution. Here we outline a method for using nonstationary matrix models to construct realistic forecasts of population fluctuation in changing environments. Our method requires three pieces of data: (1) field estimates of transition matrix elements, (2) experimental data on the demographic responses of populations to altered environmental conditions, and (3) forecasting data on environmental drivers. These three pieces of data are combined to generate a series of sequential transition matrices that emulate a pattern of long-term change in environmental drivers. Realistic estimates of population persistence and extinction risk can be derived from stochastic permutations of such a model. We illustrate the steps of this analysis with data from two populations of Sarracenia purpurea growing in northern New England. Sarracenia purpurea is a perennial carnivorous plant that is potentially at risk of local extinction because of increased nitrogen deposition. Long-term monitoring records or models of environmental change can be used to generate time series of driver variables under different scenarios of changing environments. Both manipulative and natural experiments can be used to construct a linking function that describes how matrix parameters change as a function of the environmental driver. This synthetic modeling approach provides quantitative estimates of extinction probability that have an explicit mechanistic basis.

Acquisition of a socially learned tool use sequence in chimpanzees: Implications for cumulative culture

PubMed Central

Vale, Gillian L.; Davis, Sarah J.; Lambeth, Susan P.; Schapiro, Steven J.; Whiten, Andrew

2017-01-01

Cumulative culture underpins humanity’s enormous success as a species. Claims that other animals are incapable of cultural ratcheting are prevalent, but are founded on just a handful of empirical studies. Whether cumulative culture is unique to humans thus remains a controversial and understudied question that has far-reaching implications for our understanding of the evolution of this phenomenon. We investigated whether one of human’s two closest living primate relatives, chimpanzees, are capable of a degree of cultural ratcheting by exposing captive populations to a novel juice extraction task. We found that groups (N = 3) seeded with a model trained to perform a tool modification that built upon simpler, unmodified tool use developed the seeded tool method that allowed greater juice returns than achieved by groups not exposed to a trained model (non-seeded controls; N = 3). One non-seeded group also discovered the behavioral sequence, either by coupling asocial and social learning or by repeated invention. This behavioral sequence was found to be beyond what an additional control sample of chimpanzees (N = 1 group) could discover for themselves without a competent model and lacking experience with simpler, unmodified tool behaviors. Five chimpanzees tested individually with no social information, but with experience of simple unmodified tool use, invented part, but not all, of the behavioral sequence. Our findings indicate that (i) social learning facilitated the propagation of the model-demonstrated tool modification technique, (ii) experience with simple tool behaviors may facilitate individual discovery of more complex tool manipulations, and (iii) a subset of individuals were capable of learning relatively complex behaviors either by learning asocially and socially or by repeated invention over time. That chimpanzees learn increasingly complex behaviors through social and asocial learning suggests that humans’ extraordinary ability to do so was built on such prior foundations. PMID:29333058

Controlling Release Kinetics of PLG Microspheres Using a Manufacturing Technique

NASA Astrophysics Data System (ADS)

Berchane, Nader

2005-11-01

Controlled drug delivery offers numerous advantages compared with conventional free dosage forms, in particular: improved efficacy and patient compliance. Emulsification is a widely used technique to entrap drugs in biodegradable microspheres for controlled drug delivery. The size of the formed microspheres has a significant influence on drug release kinetics. Despite the advantages of controlled drug delivery, previous attempts to achieve predetermined release rates have seen limited success. This study develops a tool to tailor desired release kinetics by combining microsphere batches of specified mean diameter and size distribution. A fluid mechanics based correlation that predicts the average size of Poly(Lactide-co-Glycolide) [PLG] microspheres from the manufacturing technique, is constructed and validated by comparison with experimental results. The microspheres produced are accurately represented by the Rosin-Rammler mathematical distribution function. A mathematical model is formulated that incorporates the microsphere distribution function to predict the release kinetics from mono-dispersed and poly-dispersed populations. Through this mathematical model, different release kinetics can be achieved by combining different sized populations in different ratios. The resulting design tool should prove useful for the pharmaceutical industry to achieve designer release kinetics.

Population dynamics in an intermittent refuge

NASA Astrophysics Data System (ADS)

Colombo, E. H.; Anteneodo, C.

2016-10-01

Population dynamics is constrained by the environment, which needs to obey certain conditions to support population growth. We consider a standard model for the evolution of a single species population density, which includes reproduction, competition for resources, and spatial spreading, while subject to an external harmful effect. The habitat is spatially heterogeneous, there existing a refuge where the population can be protected. Temporal variability is introduced by the intermittent character of the refuge. This scenario can apply to a wide range of situations, from a laboratory setting where bacteria can be protected by a blinking mask from ultraviolet radiation, to large-scale ecosystems, like a marine reserve where there can be seasonal fishing prohibitions. Using analytical and numerical tools, we investigate the asymptotic behavior of the total population as a function of the size and characteristic time scales of the refuge. We obtain expressions for the minimal size required for population survival, in the slow and fast time scale limits.

Haplotype-Based Genome-Wide Prediction Models Exploit Local Epistatic Interactions Among Markers

PubMed Central

Jiang, Yong; Schmidt, Renate H.; Reif, Jochen C.

2018-01-01

Genome-wide prediction approaches represent versatile tools for the analysis and prediction of complex traits. Mostly they rely on marker-based information, but scenarios have been reported in which models capitalizing on closely-linked markers that were combined into haplotypes outperformed marker-based models. Detailed comparisons were undertaken to reveal under which circumstances haplotype-based genome-wide prediction models are superior to marker-based models. Specifically, it was of interest to analyze whether and how haplotype-based models may take local epistatic effects between markers into account. Assuming that populations consisted of fully homozygous individuals, a marker-based model in which local epistatic effects inside haplotype blocks were exploited (LEGBLUP) was linearly transformable into a haplotype-based model (HGBLUP). This theoretical derivation formally revealed that haplotype-based genome-wide prediction models capitalize on local epistatic effects among markers. Simulation studies corroborated this finding. Due to its computational efficiency the HGBLUP model promises to be an interesting tool for studies in which ultra-high-density SNP data sets are studied. Applying the HGBLUP model to empirical data sets revealed higher prediction accuracies than for marker-based models for both traits studied using a mouse panel. In contrast, only a small subset of the traits analyzed in crop populations showed such a benefit. Cases in which higher prediction accuracies are observed for HGBLUP than for marker-based models are expected to be of immediate relevance for breeders, due to the tight linkage a beneficial haplotype will be preserved for many generations. In this respect the inheritance of local epistatic effects very much resembles the one of additive effects. PMID:29549092

Haplotype-Based Genome-Wide Prediction Models Exploit Local Epistatic Interactions Among Markers.

PubMed

Jiang, Yong; Schmidt, Renate H; Reif, Jochen C

2018-05-04

Genome-wide prediction approaches represent versatile tools for the analysis and prediction of complex traits. Mostly they rely on marker-based information, but scenarios have been reported in which models capitalizing on closely-linked markers that were combined into haplotypes outperformed marker-based models. Detailed comparisons were undertaken to reveal under which circumstances haplotype-based genome-wide prediction models are superior to marker-based models. Specifically, it was of interest to analyze whether and how haplotype-based models may take local epistatic effects between markers into account. Assuming that populations consisted of fully homozygous individuals, a marker-based model in which local epistatic effects inside haplotype blocks were exploited (LEGBLUP) was linearly transformable into a haplotype-based model (HGBLUP). This theoretical derivation formally revealed that haplotype-based genome-wide prediction models capitalize on local epistatic effects among markers. Simulation studies corroborated this finding. Due to its computational efficiency the HGBLUP model promises to be an interesting tool for studies in which ultra-high-density SNP data sets are studied. Applying the HGBLUP model to empirical data sets revealed higher prediction accuracies than for marker-based models for both traits studied using a mouse panel. In contrast, only a small subset of the traits analyzed in crop populations showed such a benefit. Cases in which higher prediction accuracies are observed for HGBLUP than for marker-based models are expected to be of immediate relevance for breeders, due to the tight linkage a beneficial haplotype will be preserved for many generations. In this respect the inheritance of local epistatic effects very much resembles the one of additive effects. Copyright © 2018 Jiang et al.

Modelling southern elephant seals Mirounga leonina using an individual-based model coupled with a dynamic energy budget

PubMed Central

Melbourne-Thomas, Jessica; Corney, Stuart P.; McMahon, Clive R.; Hindell, Mark A.

2018-01-01

Higher trophic-level species are an integral component of any marine ecosystem. Despite their importance, methods for representing these species in end-to-end ecosystem models often have limited representation of life histories, energetics and behaviour. We built an individual-based model coupled with a dynamic energy budget for female southern elephant seals Mirounga leonina to demonstrate a method for detailed representation of marine mammals. We aimed to develop a model which could i) simulate energy use and life histories, as well as breeding traits of southern elephant seals in an emergent manner, ii) project a stable population over time, and iii) have realistic population dynamics and structure based on emergent life history features (such as age at first breeding, lifespan, fecundity and (yearling) survival). We evaluated the model’s ability to represent a stable population over long time periods (>10 generations), including the sensitivity of the emergent properties to variations in key parameters. Analyses indicated that the model is sensitive to changes in resource availability and energy requirements for the transition from pup to juvenile, and juvenile to adult stage. This was particularly the case for breeding success and yearling survival. This model is suitable for use as a standalone tool for investigating the impacts of changes to behaviour and population responses of southern elephant seals. PMID:29596456

Modeling Climate Change and Sturgeon Populations in the Missouri River

USGS Publications Warehouse

Wildhaber, Mark L.

2010-01-01

The U.S. Geological Survey (USGS) Columbia Environmental Research Center (CERC), in collaboration with researchers from the University of Missouri and Iowa State University, is conducting research to address effects of climate change on sturgeon populations (Scaphirhynchus spp.) in the Missouri River. The CERC is conducting laboratory, field, and modeling research to identify causative factors for the responses of fish populations to natural and human-induced environmental changes and using this information to understand sensitivity of sturgeon populations to potential climate change in the Missouri River drainage basin. Sturgeon response information is being used to parameterize models predicting future population trends. These models will provide a set of tools for natural resource managers to assess management strategies in the context of global climate change. This research complements and builds on the ongoing Comprehensive Sturgeon Research Program (CSRP) at the CERC. The CSRP is designed to provide information critical to restoration of the Missouri River ecosystem and the endangered pallid sturgeon (S. albus). Current research is being funded by USGS through the National Climate Change Wildlife Science Center (NCCWSC) and the Science Support Partnership (SSP) Program that is held by the USGS and the U.S. Fish and Wildlife Service. The national mission of the NCCWSC is to improve the capacity of fish and wildlife agencies to respond to climate change and to address high-priority climate change effects on fish and wildlife. Within the national context, the NCCWSC research on the Missouri River focuses on temporal and spatial downscaling and associated uncertainty in modeling climate change effects on sturgeon species in the Missouri River. The SSP research focuses on improving survival and population estimates for pallid sturgeon population models.

Predictive Modeling of Rice Yellow Stem Borer Population Dynamics under Climate Change Scenarios in Indramayu

NASA Astrophysics Data System (ADS)

Nurhayati, E.; Koesmaryono, Y.; Impron

2017-03-01

Rice Yellow Stem Borer (YSB) is one of the major insect pests in rice plants that has high attack intensity in rice production center areas, especially in West Java. This pest is consider as holometabola insects that causes rice damage in the vegetative phase (deadheart) as well as generative phase (whitehead). Climatic factor is one of the environmental factors influence the pattern of dynamics population. The purpose of this study was to develop a predictive modeling of YSB pest dynamics population under climate change scenarios (2016-2035 period) using Dymex Model in Indramayu area, West Java. YSB modeling required two main components, namely climate parameters and YSB development lower threshold of temperature (To) to describe YSB life cycle in every phase. Calibration and validation test of models showed the coefficient of determination (R2) between the predicted results and observations of the study area were 0.74 and 0.88 respectively, which was able to illustrate the development, mortality, transfer of individuals from one stage to the next life also fecundity and YSB reproduction. On baseline climate condition, there was a tendency of population abundance peak (outbreak) occured when a change of rainfall intensity in the rainy season transition to dry season or the opposite conditions was happen. In both of application of climate change scenarios, the model outputs were generated well and able to predict the pattern of YSB population dynamics with a the increasing trend of specific population numbers, generation numbers per season and also shifting pattern of populations abundance peak in the future climatic conditions. These results can be adopted as a tool to predict outbreak and to give early warning to control YSB pest more effectively.

Dynamics of newly established elk populations

USGS Publications Warehouse

Sargeant, G.A.; Oehler, M.W.

2007-01-01

The dynamics of newly established elk (Cervus elaphus) populations can provide insights about maximum sustainable rates of reproduction, survival, and increase. However, data used to estimate rates of increase typically have been limited to counts and rarely have included complementary estimates of vital rates. Complexities of population dynamics cannot be understood without considering population processes as well as population states. We estimated pregnancy rates, survival rates, age ratios, and sex ratios for reintroduced elk at Theodore Roosevelt National Park, North Dakota, USA; combined vital rates in a population projection model; and compared model projections with observed elk numbers and population ratios. Pregnancy rates in January (early in the second trimester of pregnancy) averaged 54.1% (SE = 5.4%) for subadults and 91.0% (SE = 1.7%) for adults, and 91.6% of pregnancies resulted in recruitment at 8 months. Annual survival rates of adult females averaged 0.96 (95% CI = 0.94-0.98) with hunting included and 0.99 (95% CI = 0.97-0.99) with hunting excluded from calculations. Our fitted model explained 99.8% of past variation in population estimates and represents a useful new tool for short-term management planning. Although we found no evidence of temporal variation in vital rates, variation in population composition caused substantial variation in projected rates of increase (??=1.20-1.36). Restoring documented hunter harvests and removals of elk by the National Park Service led to a potential rate of ?? = 1.26. Greater rates of increase substantiated elsewhere were within the expected range of chance variation, given our model and estimates of vital rates. Rates of increase realized by small elk populations are too variable to support inferences about habitat quality or density dependence.

Modeling of Electric Demand for Sustainable Energy and Management in India Using Spatio-Temporal DMSP-OLS Night-Time Data.

PubMed

Tripathy, Bismay Ranjan; Sajjad, Haroon; Elvidge, Christopher D; Ting, Yu; Pandey, Prem Chandra; Rani, Meenu; Kumar, Pavan

2018-04-01

Changes in the pattern of electric power consumption in India have influenced energy utilization processes and socio-economic development to greater extent during the last few decades. Assessment of spatial distribution of electricity consumption is, thus, essential for projecting availability of energy resource and planning its infrastructure. This paper makes an attempt to model the future electricity demand for sustainable energy and its management in India. The nighttime light database provides a good approximation of availability of energy. We utilized defense meteorological satellite program-operational line-scan system (DMSP-OLS) nighttime satellite data, electricity consumption (1993-2013), gross domestic product (GDP) and population growth to construct the model. We also attempted to examine the sensitiveness of electricity consumption to GDP and population growth. The results revealed that the calibrated DMSP and model has provided realistic information on the electric demand with respect to GDP and population, with a better accuracy of r 2  = 0.91. The electric demand was found to be more sensitive to GDP (r = 0.96) than population growth (r = 0.76) as envisaged through correlation analysis. Hence, the model proved to be useful tool in predicting electric demand for its sustainable use and management.

Modeling of Electric Demand for Sustainable Energy and Management in India Using Spatio-Temporal DMSP-OLS Night-Time Data

NASA Astrophysics Data System (ADS)

Tripathy, Bismay Ranjan; Sajjad, Haroon; Elvidge, Christopher D.; Ting, Yu; Pandey, Prem Chandra; Rani, Meenu; Kumar, Pavan

2018-04-01

Changes in the pattern of electric power consumption in India have influenced energy utilization processes and socio-economic development to greater extent during the last few decades. Assessment of spatial distribution of electricity consumption is, thus, essential for projecting availability of energy resource and planning its infrastructure. This paper makes an attempt to model the future electricity demand for sustainable energy and its management in India. The nighttime light database provides a good approximation of availability of energy. We utilized defense meteorological satellite program-operational line-scan system (DMSP-OLS) nighttime satellite data, electricity consumption (1993-2013), gross domestic product (GDP) and population growth to construct the model. We also attempted to examine the sensitiveness of electricity consumption to GDP and population growth. The results revealed that the calibrated DMSP and model has provided realistic information on the electric demand with respect to GDP and population, with a better accuracy of r 2 = 0.91. The electric demand was found to be more sensitive to GDP ( r = 0.96) than population growth ( r = 0.76) as envisaged through correlation analysis. Hence, the model proved to be useful tool in predicting electric demand for its sustainable use and management.

ELECTRA © Launch and Re-Entry Safety Analysis Tool

NASA Astrophysics Data System (ADS)

Lazare, B.; Arnal, M. H.; Aussilhou, C.; Blazquez, A.; Chemama, F.

2010-09-01

French Space Operation Act gives as prime objective to National Technical Regulations to protect people, properties, public health and environment. In this frame, an independent technical assessment of French space operation is delegated to CNES. To perform this task and also for his owns operations CNES needs efficient state-of-the-art tools for evaluating risks. The development of the ELECTRA© tool, undertaken in 2007, meets the requirement for precise quantification of the risks involved in launching and re-entry of spacecraft. The ELECTRA© project draws on the proven expertise of CNES technical centers in the field of flight analysis and safety, spaceflight dynamics and the design of spacecraft. The ELECTRA© tool was specifically designed to evaluate the risks involved in the re-entry and return to Earth of all or part of a spacecraft. It will also be used for locating and visualizing nominal or accidental re-entry zones while comparing them with suitable geographic data such as population density, urban areas, and shipping lines, among others. The method chosen for ELECTRA© consists of two main steps: calculating the possible reentry trajectories for each fragment after the spacecraft breaks up; calculating the risks while taking into account the energy of the fragments, the population density and protection afforded by buildings. For launch operations and active re-entry, the risk calculation will be weighted by the probability of instantaneous failure of the spacecraft and integrated for the whole trajectory. ELECTRA©’s development is today at the end of the validation phase, last step before delivery to users. Validation process has been performed in different ways: numerical application way for the risk formulation; benchmarking process for casualty area, level of energy of the fragments entries and level of protection housing module; best practices in space transportation industries concerning dependability evaluation; benchmarking process for world population repartition leading to the choice of a worldwide used model called GPW V3. Then, the complementary part for validation has been numerous system tests, most of them by comparison with already existing tools, operationally used for example into the European Space port in French Guyana. The purpose of this article is to review the method and models chosen by CNES for describing physical phenomena and the results of validation process including comparison with other risk assessment tools.

Use of an Inverse Method for Time Series to Estimate the Dynamics of and Management Strategies for the Box Jellyfish Carybdea marsupialis.

PubMed

Bordehore, Cesar; Fuentes, Verónica L; Segarra, Jose G; Acevedo, Melisa; Canepa, Antonio; Raventós, Josep

2015-01-01

Frequently, population ecology of marine organisms uses a descriptive approach in which their sizes and densities are plotted over time. This approach has limited usefulness for design strategies in management or modelling different scenarios. Population projection matrix models are among the most widely used tools in ecology. Unfortunately, for the majority of pelagic marine organisms, it is difficult to mark individuals and follow them over time to determine their vital rates and built a population projection matrix model. Nevertheless, it is possible to get time-series data to calculate size structure and densities of each size, in order to determine the matrix parameters. This approach is known as a "demographic inverse problem" and it is based on quadratic programming methods, but it has rarely been used on aquatic organisms. We used unpublished field data of a population of cubomedusae Carybdea marsupialis to construct a population projection matrix model and compare two different management strategies to lower population to values before year 2008 when there was no significant interaction with bathers. Those strategies were by direct removal of medusae and by reducing prey. Our results showed that removal of jellyfish from all size classes was more effective than removing only juveniles or adults. When reducing prey, the highest efficiency to lower the C. marsupialis population occurred when prey depletion affected prey of all medusae sizes. Our model fit well with the field data and may serve to design an efficient management strategy or build hypothetical scenarios such as removal of individuals or reducing prey. TThis This sdfsdshis method is applicable to other marine or terrestrial species, for which density and population structure over time are available.

Landscape genetics as a tool for conservation planning: predicting the effects of landscape change on gene flow.

PubMed

van Strien, Maarten J; Keller, Daniela; Holderegger, Rolf; Ghazoul, Jaboury; Kienast, Felix; Bolliger, Janine

2014-03-01

For conservation managers, it is important to know whether landscape changes lead to increasing or decreasing gene flow. Although the discipline of landscape genetics assesses the influence of landscape elements on gene flow, no studies have yet used landscape-genetic models to predict gene flow resulting from landscape change. A species that has already been severely affected by landscape change is the large marsh grasshopper (Stethophyma grossum), which inhabits moist areas in fragmented agricultural landscapes in Switzerland. From transects drawn between all population pairs within maximum dispersal distance (< 3 km), we calculated several measures of landscape composition as well as some measures of habitat configuration. Additionally, a complete sampling of all populations in our study area allowed incorporating measures of population topology. These measures together with the landscape metrics formed the predictor variables in linear models with gene flow as response variable (F(ST) and mean pairwise assignment probability). With a modified leave-one-out cross-validation approach, we selected the model with the highest predictive accuracy. With this model, we predicted gene flow under several landscape-change scenarios, which simulated construction, rezoning or restoration projects, and the establishment of a new population. For some landscape-change scenarios, significant increase or decrease in gene flow was predicted, while for others little change was forecast. Furthermore, we found that the measures of population topology strongly increase model fit in landscape genetic analysis. This study demonstrates the use of predictive landscape-genetic models in conservation and landscape planning.

Moving across the border: Modeling migratory bat populations

USGS Publications Warehouse

Ruscena, Wiederholt; López-Hoffman, Laura; Cline, Jon; Medellin, Rodrigo; Cryan, Paul M.; Russell, Amy; McCracken, Gary; Diffendorfer, Jay; Semmens, Darius J.

2013-01-01

The migration of animals across long distances and between multiple habitats presents a major challenge for conservation. For the migratory Mexican free-tailed bat (Tadarida brasiliensis mexicana), these challenges include identifying and protecting migratory routes and critical roosts in two countries, the United States and Mexico. Knowledge and conservation of bat migratory routes is critical in the face of increasing threats from climate change and wind turbines that might decrease migratory survival. We employ a new modeling approach for bat migration, network modeling, to simulate migratory routes between winter habitat in southern Mexico and summer breeding habitat in northern Mexico and the southwestern United States. We use the model to identify key migratory routes and the roosts of greatest conservation value to the overall population. We measure roost importance by the degree to which the overall bat population declined when the roost was removed from the model. The major migratory routes—those with the greatest number of migrants—were between winter habitat in southern Mexico and summer breeding roosts in Texas and the northern Mexican states of Sonora and Nuevo Leon. The summer breeding roosts in Texas, Sonora, and Nuevo Leon were the most important for maintaining population numbers and network structure – these are also the largest roosts. This modeling approach contributes to conservation efforts by identifying the most influential areas for bat populations, and can be used as a tool to improve our understanding of bat migration for other species. We anticipate this approach will help direct coordination of habitat protection across borders.

An ancestry informative marker set for determining continental origin: validation and extension using human genome diversity panels

PubMed Central

Nassir, Rami; Kosoy, Roman; Tian, Chao; White, Phoebe A; Butler, Lesley M; Silva, Gabriel; Kittles, Rick; Alarcon-Riquelme, Marta E; Gregersen, Peter K; Belmont, John W; De La Vega, Francisco M; Seldin, Michael F

2009-01-01

Background Case-control genetic studies of complex human diseases can be confounded by population stratification. This issue can be addressed using panels of ancestry informative markers (AIMs) that can provide substantial population substructure information. Previously, we described a panel of 128 SNP AIMs that were designed as a tool for ascertaining the origins of subjects from Europe, Sub-Saharan Africa, Americas, and East Asia. Results In this study, genotypes from Human Genome Diversity Panel populations were used to further evaluate a 93 SNP AIM panel, a subset of the 128 AIMS set, for distinguishing continental origins. Using both model-based and relatively model-independent methods, we here confirm the ability of this AIM set to distinguish diverse population groups that were not previously evaluated. This study included multiple population groups from Oceana, South Asia, East Asia, Sub-Saharan Africa, North and South America, and Europe. In addition, the 93 AIM set provides population substructure information that can, for example, distinguish Arab and Ashkenazi from Northern European population groups and Pygmy from other Sub-Saharan African population groups. Conclusion These data provide additional support for using the 93 AIM set to efficiently identify continental subject groups for genetic studies, to identify study population outliers, and to control for admixture in association studies. PMID:19630973

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].

AquaCrop-OS: A tool for resilient management of land and water resources in agriculture

NASA Astrophysics Data System (ADS)

Foster, Timothy; Brozovic, Nicholas; Butler, Adrian P.; Neale, Christopher M. U.; Raes, Dirk; Steduto, Pasquale; Fereres, Elias; Hsiao, Theodore C.

2017-04-01

Water managers, researchers, and other decision makers worldwide are faced with the challenge of increasing food production under population growth, drought, and rising water scarcity. Crop simulation models are valuable tools in this effort, and, importantly, provide a means of quantifying rapidly crop yield response to water, climate, and field management practices. Here, we introduce a new open-source crop modelling tool called AquaCrop-OS (Foster et al., 2017), which extends the functionality of the globally used FAO AquaCrop model. Through case studies focused on groundwater-fed irrigation in the High Plains and Central Valley of California in the United States, we demonstrate how AquaCrop-OS can be used to understand the local biophysical, behavioural, and institutional drivers of water risks in agricultural production. Furthermore, we also illustrate how AquaCrop-OS can be combined effectively with hydrologic and economic models to support drought risk mitigation and decision-making around water resource management at a range of spatial and temporal scales, and highlight future plans for model development and training. T. Foster, et al. (2017) AquaCrop-OS: An open source version of FAO's crop water productivity model. Agricultural Water Management. 181: 18-22. http://dx.doi.org/10.1016/j.agwat.2016.11.015.

A review of the key genetic tools to assist imperiled species conservation: analyzing West Indian manatee populations

USGS Publications Warehouse

Bonde, Robert K.; McGuire, Peter M.; Hunter, Margaret E.

2012-01-01

Managers faced with decisions on threatened and endangered wildlife populations often are lacking detailed information about the species of concern. Integration of genetic applications will provide management teams with a better ability to assess and monitor recovery efforts on imperiled species. The field of molecular biology continues to progress rapidly and many tools are currently available. Presently, little guidance is available to assist researchers and managers with the appropriate selection of genetic tools to study the status of wild manatee populations. We discuss several genetic tools currently employed in the application of conservation genetics, and address the utility of using these tools to determine population status to aid in conservation efforts. As an example, special emphasis is focused on the endangered West Indian manatee (Order Sirenia). All four extant species of sirenians are imperiled throughout their range, predominately due to anthropogenic sources; therefore, the need for genetic information on their population status is direly needed.

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.

A modelling tool for policy analysis to support the design of efficient and effective policy responses for complex public health problems.

PubMed

Atkinson, Jo-An; Page, Andrew; Wells, Robert; Milat, Andrew; Wilson, Andrew

2015-03-03

In the design of public health policy, a broader understanding of risk factors for disease across the life course, and an increasing awareness of the social determinants of health, has led to the development of more comprehensive, cross-sectoral strategies to tackle complex problems. However, comprehensive strategies may not represent the most efficient or effective approach to reducing disease burden at the population level. Rather, they may act to spread finite resources less intensively over a greater number of programs and initiatives, diluting the potential impact of the investment. While analytic tools are available that use research evidence to help identify and prioritise disease risk factors for public health action, they are inadequate to support more targeted and effective policy responses for complex public health problems. This paper discusses the limitations of analytic tools that are commonly used to support evidence-informed policy decisions for complex problems. It proposes an alternative policy analysis tool which can integrate diverse evidence sources and provide a platform for virtual testing of policy alternatives in order to design solutions that are efficient, effective, and equitable. The case of suicide prevention in Australia is presented to demonstrate the limitations of current tools to adequately inform prevention policy and discusses the utility of the new policy analysis tool. In contrast to popular belief, a systems approach takes a step beyond comprehensive thinking and seeks to identify where best to target public health action and resources for optimal impact. It is concerned primarily with what can be reasonably left out of strategies for prevention and can be used to explore where disinvestment may occur without adversely affecting population health (or equity). Simulation modelling used for policy analysis offers promise in being able to better operationalise research evidence to support decision making for complex problems, improve targeting of public health policy, and offers a foundation for strengthening relationships between policy makers, stakeholders, and researchers.

Functional Investigations of HNF1A Identify Rare Variants as Risk Factors for Type 2 Diabetes in the General Population

PubMed Central

Najmi, Laeya Abdoli; Aukrust, Ingvild; Flannick, Jason; Molnes, Janne; Burtt, Noel; Molven, Anders; Groop, Leif; Altshuler, David; Johansson, Stefan; Njølstad, Pål Rasmus

2017-01-01

Variants in HNF1A encoding hepatocyte nuclear factor 1α (HNF-1A) are associated with maturity-onset diabetes of the young form 3 (MODY 3) and type 2 diabetes. We investigated whether functional classification of HNF1A rare coding variants can inform models of diabetes risk prediction in the general population by analyzing the effect of 27 HNF1A variants identified in well-phenotyped populations (n = 4,115). Bioinformatics tools classified 11 variants as likely pathogenic and showed no association with diabetes risk (combined minor allele frequency [MAF] 0.22%; odds ratio [OR] 2.02; 95% CI 0.73–5.60; P = 0.18). However, a different set of 11 variants that reduced HNF-1A transcriptional activity to <60% of normal (wild-type) activity was strongly associated with diabetes in the general population (combined MAF 0.22%; OR 5.04; 95% CI 1.99–12.80; P = 0.0007). Our functional investigations indicate that 0.44% of the population carry HNF1A variants that result in a substantially increased risk for developing diabetes. These results suggest that functional characterization of variants within MODY genes may overcome the limitations of bioinformatics tools for the purposes of presymptomatic diabetes risk prediction in the general population. PMID:27899486

Development and validation of a fine-motor assessment tool for use with young children in a Chinese population.

PubMed

Siu, Andrew M H; Lai, Cynthia Y Y; Chiu, Amy S M; Yip, Calvin C K

2011-01-01

Most of the fine-motor assessment tools used in Hong Kong have been designed in Western countries, so there is a need to develop a standardized assessment which is relevant to the culture and daily living tasks of the local (that is, Chinese) population. This study aimed to (1) develop a fine-motor assessment tool (the Hong Kong Preschool Fine-Motor Developmental Assessment [HK-PFMDA]) for use with young children in a Chinese population and (2) examine the HK-PFMDA's psychometric properties. The HK-PFMDA was developed by a group of occupational therapists specializing in the area of developmental disabilities in Hong Kong. A panel of 21 experts reviewed the content validity of the instrument. Rasch item analysis was used to examine the model fit of items against the rating scale model, and to explore the dimensionality of the test. Intra- and interrater reliability, convergent validity, and criterion-related validity were examined. The participants included 783 children without disabilities, 45 with autistic spectrum disorder, and 35 with developmental delay. The Rasch analysis suggested that the 87-item HK-PFMDA had a unidimensional structure, as the items explained most (91.6%) of the variance. The HK-PFMDA demonstrated excellent intra- (ICC = .99) and interrater reliability (ICC = .99), and internal consistency (α ranging from .83 to .92). In terms of validity, the HK-PFMDA had significant positive correlations with both age and the convergent measures of the Peabody Developmental Motor Scales (PDMS-2). A set of normative data for local children aged from birth to 6 years was established. The HK-PFMDA has shown excellent psychometric properties and is suitable for clinical application by occupational therapists in the assessment of fine-motor skills development of young children in Chinese populations. Copyright © 2010 Elsevier Ltd. All rights reserved.

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.

Pharmacometrics in pregnancy: An unmet need.

PubMed

Ke, Alice Ban; Rostami-Hodjegan, Amin; Zhao, Ping; Unadkat, Jashvant D

2014-01-01

Pregnant women and their fetuses are orphan populations with respect to the safety and efficacy of drugs. Physiological and absorption, distribution, metabolism, and excretion (ADME) changes during pregnancy can significantly affect drug pharmacokinetics (PK) and may necessitate dose adjustment. Here, the specific aspects related to the design, execution, and analysis of clinical studies in pregnant women are discussed, underlining the unmet need for top-down pharmacometrics analyses and bottom-up modeling approaches. The modeling tools that support data analysis for the pregnancy population are reviewed, with a focus on physiologically based pharmacokinetics (PBPK) and population pharmacokinetics (POP-PK). By integrating physiological data, preclinical data, and clinical data (e.g., via POP-PK) to quantify anticipated changes in the PK of drugs during pregnancy, the PBPK approach allows extrapolation beyond the previously studied model drugs to other drugs with well-characterized ADME characteristics. Such a systems pharmacology approach can identify drugs whose PK may be altered during pregnancy, guide rational PK study design, and support dose adjustment for pregnant women.

An integral projection model with YY-males and application to evaluating grass carp control

USGS Publications Warehouse

Erickson, Richard A.; Eager, Eric A.; Brey, Marybeth; Hansen, Michael J.; Kocovsky, Patrick

2017-01-01

Invasive fish species disrupt ecosystems and cause economic damage. Several methods have been discussed to control populations of invasive fish including the release of YY-males. YY-males are fish that have 2 male chromosomes compared to a XY-male. When YY-males mate, they only produce male (XY) offspring. This decreases the female proportion of the population and can, in theory, eradicate local populations by biasing the sex-ratio. YY-males have been used as a population control tool for brook trout in montane streams and lakes in Idaho, USA. The YY-male control method has been discussed for grass carp in Lake Erie, North America. We developed and presented an integral projection model for grass carp to model the use of YY-males as a control method for populations in this lake. Using only the YY-male control method, we found that high levels of YY-males would need to be release annually to control the species. Specifically, these levels were the same order of magnitude as the baseline adult population (e.g., 1000 YY-males needed to be released annual for 20 years to control a baseline adult population of 2500 grass carp). These levels may not be reasonable or obtainable for fisheries managers given the impacts of YY-males on aquatic vegetation and other constraints of natural resource management.

Modeling effects of traffic and landscape characteristics on ambient nitrogen dioxide levels in Connecticut

NASA Astrophysics Data System (ADS)

Skene, Katherine J.; Gent, Janneane F.; McKay, Lisa A.; Belanger, Kathleen; Leaderer, Brian P.; Holford, Theodore R.

2010-12-01

An integrated exposure model was developed that estimates nitrogen dioxide (NO 2) concentration at residences using geographic information systems (GIS) and variables derived within residential buffers representing traffic volume and landscape characteristics including land use, population density and elevation. Multiple measurements of NO 2 taken outside of 985 residences in Connecticut were used to develop the model. A second set of 120 outdoor NO 2 measurements as well as cross-validation were used to validate the model. The model suggests that approximately 67% of the variation in NO 2 levels can be explained by: traffic and land use primarily within 2 km of a residence; population density; elevation; and time of year. Potential benefits of this model for health effects research include improved spatial estimations of traffic-related pollutant exposure and reduced need for extensive pollutant measurements. The model, which could be calibrated and applied in areas other than Connecticut, has importance as a tool for exposure estimation in epidemiological studies of traffic-related air pollution.

3D-Printed specimens as a valuable tool in anatomy education: A pilot study.

PubMed

Garas, Monique; Vaccarezza, Mauro; Newland, George; McVay-Doornbusch, Kylie; Hasani, Jamila

2018-06-06

Three-dimensional (3D) printing is a modern technique of creating 3D-printed models that allows reproduction of human structures from MRI and CT scans via fusion of multiple layers of resin materials. To assess feasibility of this innovative resource as anatomy educational tool, we conducted a preliminary study on Curtin University undergraduate students to investigate the use of 3D models for anatomy learning as a main goal, to assess the effectiveness of different specimen types during the sessions and personally preferred anatomy learning tools among students as secondary aim. The study consisted of a pre-test, exposure to test (anatomical test) and post-test survey. During pre-test, all participants (both without prior experience and experienced groups) were given a brief introduction on laboratory safety and study procedure thus participants were exposed to 3D, wet and plastinated specimens of the heart, shoulder and thigh to identify the pinned structures (anatomical test). Then, participants were provided a post-test survey containing five questions. In total, 23 participants completed the anatomical test and post-test survey. A larger number of participants (85%) achieved right answers for 3D models compared to wet and plastinated materials, 74% of population selected 3D models as the most usable tool for identification of pinned structures and 45% chose 3D models as their preferred method of anatomy learning. This preliminary small-size study affirms the feasibility of 3D-printed models as a valuable asset in anatomy learning and shows their capability to be used adjacent to cadaveric materials and other widely used tools in anatomy education. Copyright © 2018 Elsevier GmbH. All rights reserved.

Impact of different policies on unhealthy dietary behaviors in an urban adult population: an agent-based simulation model.

PubMed

Zhang, Donglan; Giabbanelli, Philippe J; Arah, Onyebuchi A; Zimmerman, Frederick J

2014-07-01

Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model. Simulations were performed to contrast the potential effects of various policies on the evolution of dietary decisions. Our model showed that a 20% increase in taxes on fast foods would lower the probability of fast-food consumption by 3 percentage points, whereas improving the visibility of positive social norms by 10%, either through community-based or mass-media campaigns, could improve the consumption of fruits and vegetables by 7 percentage points and lower fast-food consumption by 6 percentage points. Zoning policies had no significant impact. Interventions emphasizing healthy eating norms may be more effective than directly targeting food prices or regulating local food outlets. Agent-based modeling may be a useful tool for testing the population-level effects of various policies within complex systems.

A coupled biophysical model for the distribution of the great scallop Pecten maximus in the English Channel

NASA Astrophysics Data System (ADS)

Le Goff, Clément; Lavaud, Romain; Cugier, Philippe; Jean, Fred; Flye-Sainte-Marie, Jonathan; Foucher, Eric; Desroy, Nicolas; Fifas, Spyros; Foveau, Aurélie

2017-03-01

In this paper we used a modelling approach integrating both physical and biological constraints to understand the biogeographical distribution of the great scallop Pecten maximus in the English Channel during its whole life cycle. A 3D bio-hydrodynamical model (ECO-MARS3D) providing environmental conditions was coupled to (i) a population dynamics model and (ii) an individual ecophysiological model (Dynamic Energy Budget model). We performed the coupling sequentially, which underlined the respective role of biological and physical factors in defining P. maximus distribution in the English Channel. Results show that larval dispersion by hydrodynamics explains most of the scallop distribution and enlighten the main known hotspots for the population, basically corresponding to the main fishing areas. The mechanistic description of individual bioenergetics shows that food availability and temperature control growth and reproduction and explain how populations may maintain themselves in particular locations. This last coupling leads to more realistic densities and distributions of adults in the English Channel. The results of this study improves our knowledge on the stock and distribution dynamics of P. maximus, and provides grounds for useful tools to support management strategies.

Innovative Stormwater Quality Tools by SARA for Holistic Watershed Master Planning

NASA Astrophysics Data System (ADS)

Thomas, S. M.; Su, Y. C.; Hummel, P. R.

2016-12-01

Stormwater management strategies such as Best Management Practices (BMP) and Low-Impact Development (LID) have increasingly gained attention in urban runoff control, becoming vital to holistic watershed master plans. These strategies can help address existing water quality impairments and support regulatory compliance, as well as guide planning and management of future development when substantial population growth and urbanization is projected to occur. However, past efforts have been limited to qualitative planning due to the lack of suitable tools to conduct quantitative assessment. The San Antonio River Authority (SARA), with the assistance of Lockwood, Andrews & Newnam, Inc. (LAN) and AQUA TERRA Consultants (a division of RESPEC), developed comprehensive hydrodynamic and water quality models using the Hydrological Simulation Program-FORTRAN (HSPF) for several urban watersheds in the San Antonio River Basin. These models enabled watershed management to look at water quality issues on a more refined temporal and spatial scale than the limited monitoring data. They also provided a means to locate and quantify potential water quality impairments and evaluate the effects of mitigation measures. To support the models, a suite of software tools were developed. including: 1) SARA Timeseries Utility Tool for managing and processing of large model timeseries files, 2) SARA Load Reduction Tool to determine load reductions needed to achieve screening levels for each modeled constituent on a sub-basin basis, and 3) SARA Enhanced BMP Tool to determine the optimal combination of BMP types and units needed to achieve the required load reductions. Using these SARA models and tools, water quality agencies and stormwater professionals can determine the optimal combinations of BMP/LID to accomplish their goals and save substantial stormwater infrastructure and management costs. The tools can also help regulators and permittees evaluate the feasibility of achieving compliance using BMP/LID. The project has gained national attention, being showcased in multiple newsletters, professional magazines, and conference presentations. The project also won the Texas American Council of Engineering Companies (ACEC) Gold Medal Award and the ACEC National Recognition Award in 2016.

Development and weighting of a life cycle assessment screening model

NASA Astrophysics Data System (ADS)

Bates, Wayne E.; O'Shaughnessy, James; Johnson, Sharon A.; Sisson, Richard

2004-02-01

Nearly all life cycle assessment tools available today are high priced, comprehensive and quantitative models requiring a significant amount of data collection and data input. In addition, most of the available software packages require a great deal of training time to learn how to operate the model software. Even after this time investment, results are not guaranteed because of the number of estimations and assumptions often necessary to run the model. As a result, product development, design teams and environmental specialists need a simplified tool that will allow for the qualitative evaluation and "screening" of various design options. This paper presents the development and design of a generic, qualitative life cycle screening model and demonstrates its applicability and ease of use. The model uses qualitative environmental, health and safety factors, based on site or product-specific issues, to sensitize the overall results for a given set of conditions. The paper also evaluates the impact of different population input ranking values on model output. The final analysis is based on site or product-specific variables. The user can then evaluate various design changes and the apparent impact or improvement on the environment, health and safety, compliance cost and overall corporate liability. Major input parameters can be varied, and factors such as materials use, pollution prevention, waste minimization, worker safety, product life, environmental impacts, return of investment, and recycle are evaluated. The flexibility of the model format will be discussed in order to demonstrate the applicability and usefulness within nearly any industry sector. Finally, an example using audience input value scores will be compared to other population input results.

Evaluation of an existing screening tool for psoriatic arthritis in people with psoriasis and the development of a new instrument: the Psoriasis Epidemiology Screening Tool (PEST) questionnaire.

PubMed

Ibrahim, G H; Buch, M H; Lawson, C; Waxman, R; Helliwell, P S

2009-01-01

To evaluate an existing tool (the Swedish modification of the Psoriasis Assessment Questionnaire) and to develop a new instrument to screen for psoriatic arthritis in people with psoriasis. The starting point was a community-based survey of people with psoriasis using questionnaires developed from the literature. Selected respondents were examined and additional known cases of psoriatic arthritis were included in the analysis. The new instrument was developed using univariate statistics and a logistic regression model, comparing people with and without psoriatic arthritis. The instruments were compared using receiver operating curve (ROC) curve analysis. 168 questionnaires were returned (response rate 27%) and 93 people attended for examination (55% of questionnaire respondents). Of these 93, twelve were newly diagnosed with psoriatic arthritis during this study. These 12 were supplemented by 21 people with known psoriatic arthritis. Just 5 questions were found to be significant predictors of psoriatic arthritis in this population. Figures for sensitivity and specificity were 0.92 and 0.78 respectively, an improvement on the Alenius tool (sensitivity and specificity, 0.63 and 0.72 respectively). A new screening tool for identifying people with psoriatic arthritis has been developed. Five simple questions demonstrated good sensitivity and specificity in this population but further validation is required.

Population growth, interest rate, and housing tax in the transitional China

NASA Astrophysics Data System (ADS)

He, Ling-Yun; Wen, Xing-Chun

2017-03-01

This paper combines and develops the models in Lastrapes (2002) and Mankiw and Weil (1989), which enables us to analyze the effects of interest rate and population growth shocks on housing price in one integrated framework. Based on this model, we carry out policy simulations to examine whether the housing (stock or flow) tax reduces the housing price fluctuations caused by interest rate or population growth shocks. Simulation results imply that the choice of housing tax tools depends on the kind of shock that housing market faces. In the situation where the housing price volatility is caused by the population growth shock, the flow tax can reduce the volatility of housing price while the stock tax makes no difference to it. If the shock is resulting from the interest rate, the policy maker should not impose any kind of the housing taxes. Furthermore, the effect of one kind of the housing tax can be strengthened by that of the other type of housing tax.

Clinical Decision Support Tools for Selecting Interventions for Patients with Disabling Musculoskeletal Disorders: A Scoping Review.

PubMed

Gross, Douglas P; Armijo-Olivo, Susan; Shaw, William S; Williams-Whitt, Kelly; Shaw, Nicola T; Hartvigsen, Jan; Qin, Ziling; Ha, Christine; Woodhouse, Linda J; Steenstra, Ivan A

2016-09-01

Purpose We aimed to identify and inventory clinical decision support (CDS) tools for helping front-line staff select interventions for patients with musculoskeletal (MSK) disorders. Methods We used Arksey and O'Malley's scoping review framework which progresses through five stages: (1) identifying the research question; (2) identifying relevant studies; (3) selecting studies for analysis; (4) charting the data; and (5) collating, summarizing and reporting results. We considered computer-based, and other available tools, such as algorithms, care pathways, rules and models. Since this research crosses multiple disciplines, we searched health care, computing science and business databases. Results Our search resulted in 4605 manuscripts. Titles and abstracts were screened for relevance. The reliability of the screening process was high with an average percentage of agreement of 92.3 %. Of the located articles, 123 were considered relevant. Within this literature, there were 43 CDS tools located. These were classified into 3 main areas: computer-based tools/questionnaires (n = 8, 19 %), treatment algorithms/models (n = 14, 33 %), and clinical prediction rules/classification systems (n = 21, 49 %). Each of these areas and the associated evidence are described. The state of evidentiary support for CDS tools is still preliminary and lacks external validation, head-to-head comparisons, or evidence of generalizability across different populations and settings. Conclusions CDS tools, especially those employing rapidly advancing computer technologies, are under development and of potential interest to health care providers, case management organizations and funders of care. Based on the results of this scoping review, we conclude that these tools, models and systems should be subjected to further validation before they can be recommended for large-scale implementation for managing patients with MSK disorders.

Assessing local capacity to expand rural breast cancer screening and patient navigation: An iterative mixed-method tool.

PubMed

Inrig, Stephen J; Higashi, Robin T; Tiro, Jasmin A; Argenbright, Keith E; Lee, Simon J Craddock

2017-04-01

Despite federal funding for breast cancer screening, fragmented infrastructure and limited organizational capacity hinder access to the full continuum of breast cancer screening and clinical follow-up procedures among rural-residing women. We proposed a regional hub-and-spoke model, partnering with local providers to expand access across North Texas. We describe development and application of an iterative, mixed-method tool to assess county capacity to conduct community outreach and/or patient navigation in a partnership model. Our tool combined publicly-available quantitative data with qualitative assessments during site visits and semi-structured interviews. Application of our tool resulted in shifts in capacity designation in 10 of 17 county partners: 8 implemented local outreach with hub navigation; 9 relied on the hub for both outreach and navigation. Key factors influencing capacity: (1) formal linkages between partner organizations; (2) inter-organizational relationships; (3) existing clinical service protocols; (4) underserved populations. Qualitative data elucidate how our tool captured these capacity changes. Our capacity assessment tool enabled the hub to establish partnerships with county organizations by tailoring support to local capacity and needs. Absent a vertically integrated provider network for preventive services in these rural counties, our tool facilitated a virtually integrated regional network to extend access to breast cancer screening to underserved women. Copyright © 2016 Elsevier Ltd. All rights reserved.

Models with Men and Women: Representing Gender in Dynamic Modeling of Social Systems.

PubMed

Palmer, Erika; Wilson, Benedicte

2018-04-01

Dynamic engineering models have yet to be evaluated in the context of feminist engineering ethics. Decision-making concerning gender in dynamic modeling design is a gender and ethical issue that is important to address regardless of the system in which the dynamic modeling is applied. There are many dynamic modeling tools that operationally include the female population, however, there is an important distinction between females and women; it is the difference between biological sex and the social construct of gender, which is fluid and changes over time and geography. The ethical oversight in failing to represent or misrepresenting gender in model design when it is relevant to the model purpose can have implications for model validity and policy model development. This paper highlights this gender issue in the context of feminist engineering ethics using a dynamic population model. Women are often represented in this type of model only in their biological capacity, while lacking their gender identity. This illustrative example also highlights how language, including the naming of variables and communication with decision-makers, plays a role in this gender issue.

GOSSIP, a New VO Compliant Tool for SED Fitting

NASA Astrophysics Data System (ADS)

Franzetti, P.; Scodeggio, M.; Garilli, B.; Fumana, M.; Paioro, L.

2008-08-01

We present GOSSIP (Galaxy Observed-Simulated SED Interactive Program), a new tool developed to perform SED fitting in a simple, user friendly and efficient way. GOSSIP automatically builds-up the observed SED of an object (or a large sample of objects) combining magnitudes in different bands and eventually a spectrum; then it performs a χ^2 minimization fitting procedure versus a set of synthetic models. The fitting results are used to estimate a number of physical parameters like the Star Formation History, absolute magnitudes, stellar mass and their Probability Distribution Functions. User defined models can be used, but GOSSIP is also able to load models produced by the most commonly used synthesis population codes. GOSSIP can be used interactively with other visualization tools using the PLASTIC protocol for communications. Moreover, since it has been developed with large data sets applications in mind, it will be extended to operate within the Virtual Observatory framework. GOSSIP is distributed to the astronomical community from the PANDORA group web site (http://cosmos.iasf-milano.inaf.it/pandora/gossip.html).

A model of motor performance during surface penetration: from physics to voluntary control.

PubMed

Klatzky, Roberta L; Gershon, Pnina; Shivaprabhu, Vikas; Lee, Randy; Wu, Bing; Stetten, George; Swendsen, Robert H

2013-10-01

The act of puncturing a surface with a hand-held tool is a ubiquitous but complex motor behavior that requires precise force control to avoid potentially severe consequences. We present a detailed model of puncture over a time course of approximately 1,000 ms, which is fit to kinematic data from individual punctures, obtained via a simulation with high-fidelity force feedback. The model describes puncture as proceeding from purely physically determined interactions between the surface and tool, through decline of force due to biomechanical viscosity, to cortically mediated voluntary control. When fit to the data, it yields parameters for the inertial mass of the tool/person coupling, time characteristic of force decline, onset of active braking, stopping time and distance, and late oscillatory behavior, all of which the analysis relates to physical variables manipulated in the simulation. While the present data characterize distinct phases of motor performance in a group of healthy young adults, the approach could potentially be extended to quantify the performance of individuals from other populations, e.g., with sensory-motor impairments. Applications to surgical force control devices are also considered.

The simcyp population based simulator: architecture, implementation, and quality assurance.

PubMed

Jamei, Masoud; Marciniak, Steve; Edwards, Duncan; Wragg, Kris; Feng, Kairui; Barnett, Adrian; Rostami-Hodjegan, Amin

2013-01-01

Developing a user-friendly platform that can handle a vast number of complex physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models both for conventional small molecules and larger biologic drugs is a substantial challenge. Over the last decade the Simcyp Population Based Simulator has gained popularity in major pharmaceutical companies (70% of top 40 - in term of R&D spending). Under the Simcyp Consortium guidance, it has evolved from a simple drug-drug interaction tool to a sophisticated and comprehensive Model Based Drug Development (MBDD) platform that covers a broad range of applications spanning from early drug discovery to late drug development. This article provides an update on the latest architectural and implementation developments within the Simulator. Interconnection between peripheral modules, the dynamic model building process and compound and population data handling are all described. The Simcyp Data Management (SDM) system, which contains the system and drug databases, can help with implementing quality standards by seamless integration and tracking of any changes. This also helps with internal approval procedures, validation and auto-testing of the new implemented models and algorithms, an area of high interest to regulatory bodies.

Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement

PubMed Central

Spindel, J E; Begum, H; Akdemir, D; Collard, B; Redoña, E; Jannink, J-L; McCouch, S

2016-01-01

To address the multiple challenges to food security posed by global climate change, population growth and rising incomes, plant breeders are developing new crop varieties that can enhance both agricultural productivity and environmental sustainability. Current breeding practices, however, are unable to keep pace with demand. Genomic selection (GS) is a new technique that helps accelerate the rate of genetic gain in breeding by using whole-genome data to predict the breeding value of offspring. Here, we describe a new GS model that combines RR-BLUP with markers fit as fixed effects selected from the results of a genome-wide-association study (GWAS) on the RR-BLUP training data. We term this model GS + de novo GWAS. In a breeding population of tropical rice, GS + de novo GWAS outperformed six other models for a variety of traits and in multiple environments. On the basis of these results, we propose an extended, two-part breeding design that can be used to efficiently integrate novel variation into elite breeding populations, thus expanding genetic diversity and enhancing the potential for sustainable productivity gains. PMID:26860200

The reading of components of diabetic retinopathy: an evolutionary approach for filtering normal digital fundus imaging in screening and population based studies.

PubMed

Tang, Hongying Lilian; Goh, Jonathan; Peto, Tunde; Ling, Bingo Wing-Kuen; Al Turk, Lutfiah Ismail; Hu, Yin; Wang, Su; Saleh, George Michael

2013-01-01

In any diabetic retinopathy screening program, about two-thirds of patients have no retinopathy. However, on average, it takes a human expert about one and a half times longer to decide an image is normal than to recognize an abnormal case with obvious features. In this work, we present an automated system for filtering out normal cases to facilitate a more effective use of grading time. The key aim with any such tool is to achieve high sensitivity and specificity to ensure patients' safety and service efficiency. There are many challenges to overcome, given the variation of images and characteristics to identify. The system combines computed evidence obtained from various processing stages, including segmentation of candidate regions, classification and contextual analysis through Hidden Markov Models. Furthermore, evolutionary algorithms are employed to optimize the Hidden Markov Models, feature selection and heterogeneous ensemble classifiers. In order to evaluate its capability of identifying normal images across diverse populations, a population-oriented study was undertaken comparing the software's output to grading by humans. In addition, population based studies collect large numbers of images on subjects expected to have no abnormality. These studies expect timely and cost-effective grading. Altogether 9954 previously unseen images taken from various populations were tested. All test images were masked so the automated system had not been exposed to them before. This system was trained using image subregions taken from about 400 sample images. Sensitivities of 92.2% and specificities of 90.4% were achieved varying between populations and population clusters. Of all images the automated system decided to be normal, 98.2% were true normal when compared to the manual grading results. These results demonstrate scalability and strong potential of such an integrated computational intelligence system as an effective tool to assist a grading service.

Patient Populations, Clinical Associations, and System Efficiency in Healthcare Delivery System

NASA Astrophysics Data System (ADS)

Liu, Yazhuo

The efforts to improve health care delivery usually involve studies and analysis of patient populations and healthcare systems. In this dissertation, I present the research conducted in the following areas: identifying patient groups, improving treatments for specific conditions by using statistical as well as data mining techniques, and developing new operation research models to increase system efficiency from the health institutes' perspective. The results provide better understanding of high risk patient groups, more accuracy in detecting disease' correlations and practical scheduling tools that consider uncertain operation durations and real-life constraints.

Molecular Tools for Investigating the Gut Microbiota

NASA Astrophysics Data System (ADS)

Lay, Christophe

The “microbial world within us” (Zoetendal et al., 2006) is populated by a complex society of indigenous microorganisms that feature different “ethnic” populations. Those microbial cells thriving within us are estimated to outnumber human body cells by a factor of ten to one. Insights into the relation between the intestinal microbial community and its host have been gained through gnotobiology. Indeed, the influence of the gut microbiota upon human development, physiology, immunity, and nutrition has been inferred by comparing gnotoxenic and axenic murine models (Hooper et al., 1998, 2002, 2003; Hooper and Gordon, 2001).

Toward Rigorous Parameterization of Underconstrained Neural Network Models Through Interactive Visualization and Steering of Connectivity Generation

PubMed Central

Nowke, Christian; Diaz-Pier, Sandra; Weyers, Benjamin; Hentschel, Bernd; Morrison, Abigail; Kuhlen, Torsten W.; Peyser, Alexander

2018-01-01

Simulation models in many scientific fields can have non-unique solutions or unique solutions which can be difficult to find. Moreover, in evolving systems, unique final state solutions can be reached by multiple different trajectories. Neuroscience is no exception. Often, neural network models are subject to parameter fitting to obtain desirable output comparable to experimental data. Parameter fitting without sufficient constraints and a systematic exploration of the possible solution space can lead to conclusions valid only around local minima or around non-minima. To address this issue, we have developed an interactive tool for visualizing and steering parameters in neural network simulation models. In this work, we focus particularly on connectivity generation, since finding suitable connectivity configurations for neural network models constitutes a complex parameter search scenario. The development of the tool has been guided by several use cases—the tool allows researchers to steer the parameters of the connectivity generation during the simulation, thus quickly growing networks composed of multiple populations with a targeted mean activity. The flexibility of the software allows scientists to explore other connectivity and neuron variables apart from the ones presented as use cases. With this tool, we enable an interactive exploration of parameter spaces and a better understanding of neural network models and grapple with the crucial problem of non-unique network solutions and trajectories. In addition, we observe a reduction in turn around times for the assessment of these models, due to interactive visualization while the simulation is computed. PMID:29937723

Optimal Measurement Interval for Emergency Department Crowding Estimation Tools.

PubMed

Wang, Hao; Ojha, Rohit P; Robinson, Richard D; Jackson, Bradford E; Shaikh, Sajid A; Cowden, Chad D; Shyamanand, Rath; Leuck, JoAnna; Schrader, Chet D; Zenarosa, Nestor R

2017-11-01

Emergency department (ED) crowding is a barrier to timely care. Several crowding estimation tools have been developed to facilitate early identification of and intervention for crowding. Nevertheless, the ideal frequency is unclear for measuring ED crowding by using these tools. Short intervals may be resource intensive, whereas long ones may not be suitable for early identification. Therefore, we aim to assess whether outcomes vary by measurement interval for 4 crowding estimation tools. Our eligible population included all patients between July 1, 2015, and June 30, 2016, who were admitted to the JPS Health Network ED, which serves an urban population. We generated 1-, 2-, 3-, and 4-hour ED crowding scores for each patient, using 4 crowding estimation tools (National Emergency Department Overcrowding Scale [NEDOCS], Severely Overcrowded, Overcrowded, and Not Overcrowded Estimation Tool [SONET], Emergency Department Work Index [EDWIN], and ED Occupancy Rate). Our outcomes of interest included ED length of stay (minutes) and left without being seen or eloped within 4 hours. We used accelerated failure time models to estimate interval-specific time ratios and corresponding 95% confidence limits for length of stay, in which the 1-hour interval was the reference. In addition, we used binomial regression with a log link to estimate risk ratios (RRs) and corresponding confidence limit for left without being seen. Our study population comprised 117,442 patients. The time ratios for length of stay were similar across intervals for each crowding estimation tool (time ratio=1.37 to 1.30 for NEDOCS, 1.44 to 1.37 for SONET, 1.32 to 1.27 for EDWIN, and 1.28 to 1.23 for ED Occupancy Rate). The RRs of left without being seen differences were also similar across intervals for each tool (RR=2.92 to 2.56 for NEDOCS, 3.61 to 3.36 for SONET, 2.65 to 2.40 for EDWIN, and 2.44 to 2.14 for ED Occupancy Rate). Our findings suggest limited variation in length of stay or left without being seen between intervals (1 to 4 hours) regardless of which of the 4 crowding estimation tools were used. Consequently, 4 hours may be a reasonable interval for assessing crowding with these tools, which could substantially reduce the burden on ED personnel by requiring less frequent assessment of crowding. Copyright © 2017 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Modelling proteins' hidden conformations to predict antibiotic resistance

NASA Astrophysics Data System (ADS)

Hart, Kathryn M.; Ho, Chris M. W.; Dutta, Supratik; Gross, Michael L.; Bowman, Gregory R.

2016-10-01

TEM β-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models to identify hidden conformations and explore their role in determining TEM's specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometric footprinting and confirm our models' prediction that increased cefotaxime activity correlates with reduced Ω-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design.

The migraine ACE model: evaluating the impact on time lost and medical resource Use.

PubMed

Caro, J J; Caro, G; Getsios, D; Raggio, G; Burrows, M; Black, L

2000-04-01

To describe the Migraine Adaptive Cost-Effectiveness Model in the context of an analysis of a simulated population of Canadian patients with migraine. The high prevalence of migraine and its substantial impact on patients' ability to function normally present a significant economic burden to society. In light of the recent availability of improved pharmaceutical treatments, a model was developed to assess their economic impact. The Migraine Adaptive Cost-Effectiveness Model incorporates the costs of time lost from both work and nonwork activities, as well as medical resource and medication use. Using Monte Carlo techniques, the model simulates the experience of a population of patients with migraine over the course of 1 year. As an example, analyses of a Canadian population were carried out using data from a multinational trial, surveys, national statistics, and the available literature. Using customary therapy, mean productivity losses (amounting to 84 hours of paid work time, 48 hours of unpaid work time, and 113 hours of leisure time lost) were estimated to cost $1949 (in 1997 Canadian dollars) per patient, with medical expenditures adding an average of $280 to the cost of illness. With customary treatment patterns, the costs of migraine associated with reduced functional capacity are substantial. The migraine model represents a flexible tool for the economic evaluation of different migraine treatments in various populations.

Cost effectiveness of pediatric pneumococcal conjugate vaccines: a comparative assessment of decision-making tools.

PubMed

Chaiyakunapruk, Nathorn; Somkrua, Ratchadaporn; Hutubessy, Raymond; Henao, Ana Maria; Hombach, Joachim; Melegaro, Alessia; Edmunds, John W; Beutels, Philippe

2011-05-12

Several decision support tools have been developed to aid policymaking regarding the adoption of pneumococcal conjugate vaccine (PCV) into national pediatric immunization programs. The lack of critical appraisal of these tools makes it difficult for decision makers to understand and choose between them. With the aim to guide policymakers on their optimal use, we compared publicly available decision-making tools in relation to their methods, influential parameters and results. The World Health Organization (WHO) requested access to several publicly available cost-effectiveness (CE) tools for PCV from both public and private provenance. All tools were critically assessed according to the WHO's guide for economic evaluations of immunization programs. Key attributes and characteristics were compared and a series of sensitivity analyses was performed to determine the main drivers of the results. The results were compared based on a standardized set of input parameters and assumptions. Three cost-effectiveness modeling tools were provided, including two cohort-based (Pan-American Health Organization (PAHO) ProVac Initiative TriVac, and PneumoADIP) and one population-based model (GlaxoSmithKline's SUPREMES). They all compared the introduction of PCV into national pediatric immunization program with no PCV use. The models were different in terms of model attributes, structure, and data requirement, but captured a similar range of diseases. Herd effects were estimated using different approaches in each model. The main driving parameters were vaccine efficacy against pneumococcal pneumonia, vaccine price, vaccine coverage, serotype coverage and disease burden. With a standardized set of input parameters developed for cohort modeling, TriVac and PneumoADIP produced similar incremental costs and health outcomes, and incremental cost-effectiveness ratios. Vaccine cost (dose price and number of doses), vaccine efficacy and epidemiology of critical endpoint (for example, incidence of pneumonia, distribution of serotypes causing pneumonia) were influential parameters in the models we compared. Understanding the differences and similarities of such CE tools through regular comparisons could render decision-making processes in different countries more efficient, as well as providing guiding information for further clinical and epidemiological research. A tool comparison exercise using standardized data sets can help model developers to be more transparent about their model structure and assumptions and provide analysts and decision makers with a more in-depth view behind the disease dynamics. Adherence to the WHO guide of economic evaluations of immunization programs may also facilitate this process. Please see related article: http://www.biomedcentral.com/1741-7007/9/55.

The Value of SysML Modeling During System Operations: A Case Study

NASA Technical Reports Server (NTRS)

Dutenhoffer, Chelsea; Tirona, Joseph

2013-01-01

System models are often touted as engineering tools that promote better understanding of systems, but these models are typically created during system design. The Ground Data System (GDS) team for the Dawn spacecraft took on a case study to see if benefits could be achieved by starting a model of a system already in operations. This paper focuses on the four steps the team undertook in modeling the Dawn GDS: defining a model structure, populating model elements, verifying that the model represented reality, and using the model to answer system-level questions and simplify day-to-day tasks. Throughout this paper the team outlines our thought processes and the system insights the model provided.

The value of SysML modeling during system operations: A case study

NASA Astrophysics Data System (ADS)

Dutenhoffer, C.; Tirona, J.

System models are often touted as engineering tools that promote better understanding of systems, but these models are typically created during system design. The Ground Data System (GDS) team for the Dawn spacecraft took on a case study to see if benefits could be achieved by starting a model of a system already in operations. This paper focuses on the four steps the team undertook in modeling the Dawn GDS: defining a model structure, populating model elements, verifying that the model represented reality, and using the model to answer system-level questions and simplify day-to-day tasks. Throughout this paper the team outlines our thought processes and the system insights the model provided.

Population and habitat viability assessments for Golden-cheeked Warblers and Black-capped Vireos: Usefulness to Partners in Flight Conservation Planning

USGS Publications Warehouse

Beardmore, C.J.; Hatfield, J.S.; Bonney, Rick; Pashley, David N.; Cooper, Robert; Niles, Larry

2000-01-01

Golden-cheeked Warblers and Black-capped Vireos are Neotropical migratory birds that are federally listed as endangered. Recovery plans for both species advise the use of viability modeling as a tool for setting specific recovery and management targets. Population and Habitat Viability Assessment workshops were conducted to develop population targets and conservation recommendations for these species. Results of the workshops were based on modeling demographic and environmental factors, as well as discussions of management issues, management options, and public outreach strategies. The approach is intended to be iterative, and to be tracked by research and monitoring efforts. This paper discusses the consensus-building workshop process and how the approach could be useful to Partners in Flight. Population and Habitat Viability Assessments (PHVA) were used to develop population targets and conservation recommendations for Golden-cheeked Warblers (Dendroica chrysoparia) and Black-capped Vireos (Vireo atricapillus). This paper explains what PHVAs are, discusses how they are conducted, describes the general results that are produced, and suggests how Partners in Flight (PIF) might use a similar process for bird conservation planning. Detailed results of the assessments are not discussed here; however they can be found elsewhere (U. S. Fish and Wildlife Service 1996a, U. S. Fish and Wildlife Service 1996b). PHVAs were considered for Golden-cheeked Warblers and Black-capped Vireos because they are controversial, endangered species, and the species? recovery plans list PHVAs as tools to develop recovery recommendations. The U. S. Fish and Wildlife Service (USFWS) realized that the data needed to perform PHVAs for these species is limited, but that various conservation efforts, such as the Balcones Canyonlands Conservation Plan and other endeavors, were proceeding without benefit of the biological summarization and guidance that a PHVA could provide.

Range Systems Simulation for the NASA Shuttle: Emphasis on Disaster and Prevention Management During Lift-Off

NASA Technical Reports Server (NTRS)

Rabelo, Lisa; Sepulveda, Jose; Moraga, Reinaldo; Compton, Jeppie; Turner, Robert

2005-01-01

This article describes a decision-making system composed of a number of safety and environmental models for the launch phase of a NASA Space Shuttle mission. The components of this distributed simulation environment represent the different systems that must collaborate to establish the Expectation of Casualties (E(sub c)) caused by a failed Space Shuttle launch and subsequent explosion (accidental or instructed) of the spacecraft shortly after liftoff. This decision-making tool employs Space Shuttle reliability models, trajectory models, a blast model, weather dissemination systems, population models, amount and type of toxicants, gas dispersion models, human response functions to toxicants, and a geographical information system. Since one of the important features of this proposed simulation environment is to measure blast, toxic, and debris effects, the clear benefits is that it can help safety managers not only estimate the population at risk, but also to help plan evacuations, make sheltering decisions, establish the resources required to provide aid and comfort, and mitigate damages in case of a disaster.

Model for teaching population health and community-based care across diverse clinical experiences.

PubMed

Van Dyk, Elizabeth J; Valentine-Maher, Sarah K; Tracy, Janet P

2015-02-01

The pillars constructivist model is designed to offer a unifying clinical paradigm to support consistent learning opportunities across diverse configurations of community and public health clinical sites. Thirty-six students and six faculty members participated in a mixed methods evaluation to assess the model after its inaugural semester of implementation. The evaluation methods included a rating scale that measures the model's ability to provide consistent learning opportunities at both population health and direct care sites, a case study to measure student growth within the five conceptual pillars, and a faculty focus group. Results revealed that the model served as an effective means of clinical education to support the use of multiple, small-scale public health sites. Although measurements of student growth within the pillars are inconclusive, the findings suggest efficacy. The authors recommend the continued use of the pillars constructivist model in baccalaureate programs, with further study of the author-designed evaluation tools. Copyright 2015, SLACK Incorporated.

Eco-genetic modeling of contemporary life-history evolution.

PubMed

Dunlop, Erin S; Heino, Mikko; Dieckmann, Ulf

2009-10-01

We present eco-genetic modeling as a flexible tool for exploring the course and rates of multi-trait life-history evolution in natural populations. We build on existing modeling approaches by combining features that facilitate studying the ecological and evolutionary dynamics of realistically structured populations. In particular, the joint consideration of age and size structure enables the analysis of phenotypically plastic populations with more than a single growth trajectory, and ecological feedback is readily included in the form of density dependence and frequency dependence. Stochasticity and life-history trade-offs can also be implemented. Critically, eco-genetic models permit the incorporation of salient genetic detail such as a population's genetic variances and covariances and the corresponding heritabilities, as well as the probabilistic inheritance and phenotypic expression of quantitative traits. These inclusions are crucial for predicting rates of evolutionary change on both contemporary and longer timescales. An eco-genetic model can be tightly coupled with empirical data and therefore may have considerable practical relevance, in terms of generating testable predictions and evaluating alternative management measures. To illustrate the utility of these models, we present as an example an eco-genetic model used to study harvest-induced evolution of multiple traits in Atlantic cod. The predictions of our model (most notably that harvesting induces a genetic reduction in age and size at maturation, an increase or decrease in growth capacity depending on the minimum-length limit, and an increase in reproductive investment) are corroborated by patterns observed in wild populations. The predicted genetic changes occur together with plastic changes that could phenotypically mask the former. Importantly, our analysis predicts that evolutionary changes show little signs of reversal following a harvest moratorium. This illustrates how predictions offered by eco-genetic models can enable and guide evolutionarily sustainable resource management.

Modeling Mosquito-Borne Disease Spread in U.S. Urbanized Areas: The Case of Dengue in Miami

PubMed Central

Robert, Michael A.; Christofferson, Rebecca C.; Silva, Noah J. B.; Vasquez, Chalmers; Mores, Christopher N.; Wearing, Helen J.

2016-01-01

Expansion of mosquito-borne pathogens into more temperate regions of the world necessitates tools such as mathematical models for understanding the factors that contribute to the introduction and emergence of a disease in populations naïve to the disease. Often, these models are not developed and analyzed until after a pathogen is detected in a population. In this study, we develop a spatially explicit stochastic model parameterized with publicly available U.S. Census data for studying the potential for disease spread in Urbanized Areas of the United States. To illustrate the utility of the model, we specifically study the potential for introductions of dengue to lead to autochthonous transmission and outbreaks in a population representative of the Miami Urbanized Area, where introductions of dengue have occurred frequently in recent years. We describe seasonal fluctuations in mosquito populations by fitting a population model to trap data provided by the Miami-Dade Mosquito Control Division. We show that the timing and location of introduced cases could play an important role in determining both the probability that local transmission occurs as well as the total number of cases throughout the entire region following introduction. We show that at low rates of clinical presentation, small outbreaks of dengue could go completely undetected during a season, which may confound mitigation efforts that rely upon detection. We discuss the sensitivity of the model to several critical parameter values that are currently poorly characterized and motivate the collection of additional data to strengthen the predictive power of this and similar models. Finally, we emphasize the utility of the general structure of this model in studying mosquito-borne diseases such as chikungunya and Zika virus in other regions. PMID:27532496

Water Planning in Phoenix: Managing Risk in the Face of Climatic Uncertainty

NASA Astrophysics Data System (ADS)

Gober, P.

2009-12-01

The Decision Center for a Desert City (DCDC) was founded in 2004 to develop scientifically-credible support tools to improve water management decisions in the face of growing climatic uncertainty and rapid urbanization in metropolitan Phoenix. At the center of DCDC's effort is WaterSim, a model that integrates information about water supply from groundwater, the Colorado River, and upstream watersheds and water demand from land use change and population growth. Decision levers enable users to manipulate model outcomes in response to climate change scenarios, drought conditions, population growth rates, technology innovations, lifestyle changes, and policy decisions. WaterSim allows users to examine the risks of water shortage from global climate change, the tradeoffs between groundwater sustainability and lifestyle choices, the effects of various policy decisions, and the consequences of delaying policy for the exposure to risk. WaterSim is an important point of contact for DCDC’s relationships with local decision makers. Knowledge, tools, and visualizations are co-produced—by scientists and policy makers, and the Center’s social scientists mine this co-production process for new insights about model development and application. WaterSim is less a static scientific product and more a dynamic process of engagement between decision makers and scientists.

An Investigation of the Effectiveness of Computer Simulation Programs as Tutorial Tools for Teaching Population Ecology at University.

ERIC Educational Resources Information Center

Korfiatis, K.; Papatheodorou, E.; Paraskevopoulous, S.; Stamou, G. P.

1999-01-01

Describes a study of the effectiveness of computer-simulation programs in enhancing biology students' familiarity with ecological modeling and concepts. Finds that computer simulations improved student comprehension of ecological processes expressed in mathematical form, but did not allow a full understanding of ecological concepts. Contains 28…

Causal inference and the data-fusion problem

PubMed Central

Bareinboim, Elias; Pearl, Judea

2016-01-01

We review concepts, principles, and tools that unify current approaches to causal analysis and attend to new challenges presented by big data. In particular, we address the problem of data fusion—piecing together multiple datasets collected under heterogeneous conditions (i.e., different populations, regimes, and sampling methods) to obtain valid answers to queries of interest. The availability of multiple heterogeneous datasets presents new opportunities to big data analysts, because the knowledge that can be acquired from combined data would not be possible from any individual source alone. However, the biases that emerge in heterogeneous environments require new analytical tools. Some of these biases, including confounding, sampling selection, and cross-population biases, have been addressed in isolation, largely in restricted parametric models. We here present a general, nonparametric framework for handling these biases and, ultimately, a theoretical solution to the problem of data fusion in causal inference tasks. PMID:27382148

Collective learning modeling based on the kinetic theory of active particles.

PubMed

Burini, D; De Lillo, S; Gibelli, L

2016-03-01

This paper proposes a systems approach to the theory of perception and learning in populations composed of many living entities. Starting from a phenomenological description of these processes, a mathematical structure is derived which is deemed to incorporate their complexity features. The modeling is based on a generalization of kinetic theory methods where interactions are described by theoretical tools of game theory. As an application, the proposed approach is used to model the learning processes that take place in a classroom. Copyright © 2015 Elsevier B.V. All rights reserved.

Osteoporosis risk prediction using machine learning and conventional methods.

PubMed

Kim, Sung Kean; Yoo, Tae Keun; Oh, Ein; Kim, Deok Won

2013-01-01

A number of clinical decision tools for osteoporosis risk assessment have been developed to select postmenopausal women for the measurement of bone mineral density. We developed and validated machine learning models with the aim of more accurately identifying the risk of osteoporosis in postmenopausal women, and compared with the ability of a conventional clinical decision tool, osteoporosis self-assessment tool (OST). We collected medical records from Korean postmenopausal women based on the Korea National Health and Nutrition Surveys (KNHANES V-1). The training data set was used to construct models based on popular machine learning algorithms such as support vector machines (SVM), random forests (RF), artificial neural networks (ANN), and logistic regression (LR) based on various predictors associated with low bone density. The learning models were compared with OST. SVM had significantly better area under the curve (AUC) of the receiver operating characteristic (ROC) than ANN, LR, and OST. Validation on the test set showed that SVM predicted osteoporosis risk with an AUC of 0.827, accuracy of 76.7%, sensitivity of 77.8%, and specificity of 76.0%. We were the first to perform comparisons of the performance of osteoporosis prediction between the machine learning and conventional methods using population-based epidemiological data. The machine learning methods may be effective tools for identifying postmenopausal women at high risk for osteoporosis.

Using classical population genetics tools with heterochroneous data: time matters!

PubMed

Depaulis, Frantz; Orlando, Ludovic; Hänni, Catherine

2009-01-01

New polymorphism datasets from heterochroneous data have arisen thanks to recent advances in experimental and microbial molecular evolution, and the sequencing of ancient DNA (aDNA). However, classical tools for population genetics analyses do not take into account heterochrony between subsets, despite potential bias on neutrality and population structure tests. Here, we characterize the extent of such possible biases using serial coalescent simulations. We first use a coalescent framework to generate datasets assuming no or different levels of heterochrony and contrast most classical population genetic statistics. We show that even weak levels of heterochrony ( approximately 10% of the average depth of a standard population tree) affect the distribution of polymorphism substantially, leading to overestimate the level of polymorphism theta, to star like trees, with an excess of rare mutations and a deficit of linkage disequilibrium, which are the hallmark of e.g. population expansion (possibly after a drastic bottleneck). Substantial departures of the tests are detected in the opposite direction for more heterochroneous and equilibrated datasets, with balanced trees mimicking in particular population contraction, balancing selection, and population differentiation. We therefore introduce simple corrections to classical estimators of polymorphism and of the genetic distance between populations, in order to remove heterochrony-driven bias. Finally, we show that these effects do occur on real aDNA datasets, taking advantage of the currently available sequence data for Cave Bears (Ursus spelaeus), for which large mtDNA haplotypes have been reported over a substantial time period (22-130 thousand years ago (KYA)). Considering serial sampling changed the conclusion of several tests, indicating that neglecting heterochrony could provide significant support for false past history of populations and inappropriate conservation decisions. We therefore argue for systematically considering heterochroneous models when analyzing heterochroneous samples covering a large time scale.

Robust Identification of Local Adaptation from Allele Frequencies

PubMed Central

Günther, Torsten; Coop, Graham

2013-01-01

Comparing allele frequencies among populations that differ in environment has long been a tool for detecting loci involved in local adaptation. However, such analyses are complicated by an imperfect knowledge of population allele frequencies and neutral correlations of allele frequencies among populations due to shared population history and gene flow. Here we develop a set of methods to robustly test for unusual allele frequency patterns and correlations between environmental variables and allele frequencies while accounting for these complications based on a Bayesian model previously implemented in the software Bayenv. Using this model, we calculate a set of “standardized allele frequencies” that allows investigators to apply tests of their choice to multiple populations while accounting for sampling and covariance due to population history. We illustrate this first by showing that these standardized frequencies can be used to detect nonparametric correlations with environmental variables; these correlations are also less prone to spurious results due to outlier populations. We then demonstrate how these standardized allele frequencies can be used to construct a test to detect SNPs that deviate strongly from neutral population structure. This test is conceptually related to FST and is shown to be more powerful, as we account for population history. We also extend the model to next-generation sequencing of population pools—a cost-efficient way to estimate population allele frequencies, but one that introduces an additional level of sampling noise. The utility of these methods is demonstrated in simulations and by reanalyzing human SNP data from the Human Genome Diversity Panel populations and pooled next-generation sequencing data from Atlantic herring. An implementation of our method is available from http://gcbias.org. PMID:23821598

Constructing stage-structured matrix population models from life tables: comparison of methods

PubMed Central

Diaz-Lopez, Jasmin

2017-01-01

A matrix population model is a convenient tool for summarizing per capita survival and reproduction rates (collectively vital rates) of a population and can be used for calculating an asymptotic finite population growth rate (λ) and generation time. These two pieces of information can be used for determining the status of a threatened species. The use of stage-structured population models has increased in recent years, and the vital rates in such models are often estimated using a life table analysis. However, potential bias introduced when converting age-structured vital rates estimated from a life table into parameters for a stage-structured population model has not been assessed comprehensively. The objective of this study was to investigate the performance of methods for such conversions using simulated life histories of organisms. The underlying models incorporate various types of life history and true population growth rates of varying levels. The performance was measured by comparing differences in λ and the generation time calculated using the Euler-Lotka equation, age-structured population matrices, and several stage-structured population matrices that were obtained by applying different conversion methods. The results show that the discretization of age introduces only small bias in λ or generation time. Similarly, assuming a fixed age of maturation at the mean age of maturation does not introduce much bias. However, aggregating age-specific survival rates into a stage-specific survival rate and estimating a stage-transition rate can introduce substantial bias depending on the organism’s life history type and the true values of λ. In order to aggregate survival rates, the use of the weighted arithmetic mean was the most robust method for estimating λ. Here, the weights are given by survivorship curve after discounting with λ. To estimate a stage-transition rate, matching the proportion of individuals transitioning, with λ used for discounting the rate, was the best approach. However, stage-structured models performed poorly in estimating generation time, regardless of the methods used for constructing the models. Based on the results, we recommend using an age-structured matrix population model or the Euler-Lotka equation for calculating λ and generation time when life table data are available. Then, these age-structured vital rates can be converted into a stage-structured model for further analyses. PMID:29085763

Constructing stage-structured matrix population models from life tables: comparison of methods.

PubMed

Fujiwara, Masami; Diaz-Lopez, Jasmin

2017-01-01

A matrix population model is a convenient tool for summarizing per capita survival and reproduction rates (collectively vital rates) of a population and can be used for calculating an asymptotic finite population growth rate ( λ ) and generation time. These two pieces of information can be used for determining the status of a threatened species. The use of stage-structured population models has increased in recent years, and the vital rates in such models are often estimated using a life table analysis. However, potential bias introduced when converting age-structured vital rates estimated from a life table into parameters for a stage-structured population model has not been assessed comprehensively. The objective of this study was to investigate the performance of methods for such conversions using simulated life histories of organisms. The underlying models incorporate various types of life history and true population growth rates of varying levels. The performance was measured by comparing differences in λ and the generation time calculated using the Euler-Lotka equation, age-structured population matrices, and several stage-structured population matrices that were obtained by applying different conversion methods. The results show that the discretization of age introduces only small bias in λ or generation time. Similarly, assuming a fixed age of maturation at the mean age of maturation does not introduce much bias. However, aggregating age-specific survival rates into a stage-specific survival rate and estimating a stage-transition rate can introduce substantial bias depending on the organism's life history type and the true values of λ . In order to aggregate survival rates, the use of the weighted arithmetic mean was the most robust method for estimating λ . Here, the weights are given by survivorship curve after discounting with λ . To estimate a stage-transition rate, matching the proportion of individuals transitioning, with λ used for discounting the rate, was the best approach. However, stage-structured models performed poorly in estimating generation time, regardless of the methods used for constructing the models. Based on the results, we recommend using an age-structured matrix population model or the Euler-Lotka equation for calculating λ and generation time when life table data are available. Then, these age-structured vital rates can be converted into a stage-structured model for further analyses.

Using stylized agent-based models for population-environment research: A case study from the Galápagos Islands

PubMed Central

Miller, Brian W.; Breckheimer, Ian; McCleary, Amy L.; Guzmán-Ramirez, Liza; Caplow, Susan C.; Jones-Smith, Jessica C.; Walsh, Stephen J.

2010-01-01

Agent Based Models (ABMs) are powerful tools for population-environment research but are subject to trade-offs between model complexity and abstraction. This study strikes a compromise between abstract and highly specified ABMs by designing a spatially explicit, stylized ABM and using it to explore policy scenarios in a setting that is facing substantial conservation and development challenges. Specifically, we present an ABM that reflects key Land Use / Land Cover (LULC) dynamics and livelihood decisions on Isabela Island in the Galápagos Archipelago of Ecuador. We implement the model using the NetLogo software platform, a free program that requires relatively little programming experience. The landscape is composed of a satellite-derived distribution of a problematic invasive species (common guava) and a stylized representation of the Galápagos National Park, the community of Puerto Villamil, the agricultural zone, and the marine area. The agent module is based on publicly available data and household interviews, and represents the primary livelihoods of the population in the Galápagos Islands – tourism, fisheries, and agriculture. We use the model to enact hypothetical agricultural subsidy scenarios aimed at controlling invasive guava and assess the resulting population and land cover dynamics. Findings suggest that spatially explicit, stylized ABMs have considerable utility, particularly during preliminary stages of research, as platforms for (1) sharpening conceptualizations of population-environment systems, (2) testing alternative scenarios, and (3) uncovering critical data gaps. PMID:20539752

Using stylized agent-based models for population-environment research: A case study from the Galápagos Islands.

PubMed

Miller, Brian W; Breckheimer, Ian; McCleary, Amy L; Guzmán-Ramirez, Liza; Caplow, Susan C; Jones-Smith, Jessica C; Walsh, Stephen J

2010-05-01

Agent Based Models (ABMs) are powerful tools for population-environment research but are subject to trade-offs between model complexity and abstraction. This study strikes a compromise between abstract and highly specified ABMs by designing a spatially explicit, stylized ABM and using it to explore policy scenarios in a setting that is facing substantial conservation and development challenges. Specifically, we present an ABM that reflects key Land Use / Land Cover (LULC) dynamics and livelihood decisions on Isabela Island in the Galápagos Archipelago of Ecuador. We implement the model using the NetLogo software platform, a free program that requires relatively little programming experience. The landscape is composed of a satellite-derived distribution of a problematic invasive species (common guava) and a stylized representation of the Galápagos National Park, the community of Puerto Villamil, the agricultural zone, and the marine area. The agent module is based on publicly available data and household interviews, and represents the primary livelihoods of the population in the Galápagos Islands - tourism, fisheries, and agriculture. We use the model to enact hypothetical agricultural subsidy scenarios aimed at controlling invasive guava and assess the resulting population and land cover dynamics. Findings suggest that spatially explicit, stylized ABMs have considerable utility, particularly during preliminary stages of research, as platforms for (1) sharpening conceptualizations of population-environment systems, (2) testing alternative scenarios, and (3) uncovering critical data gaps.

DataHigh: Graphical user interface for visualizing and interacting with high-dimensional neural activity

PubMed Central

Cowley, Benjamin R.; Kaufman, Matthew T.; Butler, Zachary S.; Churchland, Mark M.; Ryu, Stephen I.; Shenoy, Krishna V.; Yu, Byron M.

2014-01-01

Objective Analyzing and interpreting the activity of a heterogeneous population of neurons can be challenging, especially as the number of neurons, experimental trials, and experimental conditions increases. One approach is to extract a set of latent variables that succinctly captures the prominent co-fluctuation patterns across the neural population. A key problem is that the number of latent variables needed to adequately describe the population activity is often greater than three, thereby preventing direct visualization of the latent space. By visualizing a small number of 2-d projections of the latent space or each latent variable individually, it is easy to miss salient features of the population activity. Approach To address this limitation, we developed a Matlab graphical user interface (called DataHigh) that allows the user to quickly and smoothly navigate through a continuum of different 2-d projections of the latent space. We also implemented a suite of additional visualization tools (including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses) and an optional tool for performing dimensionality reduction. Main results To demonstrate the utility and versatility of DataHigh, we used it to analyze single-trial spike count and single-trial timecourse population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded using single electrodes. Significance DataHigh was developed to fulfill a need for visualization in exploratory neural data analysis, which can provide intuition that is critical for building scientific hypotheses and models of population activity. PMID:24216250

DataHigh: graphical user interface for visualizing and interacting with high-dimensional neural activity

NASA Astrophysics Data System (ADS)

Cowley, Benjamin R.; Kaufman, Matthew T.; Butler, Zachary S.; Churchland, Mark M.; Ryu, Stephen I.; Shenoy, Krishna V.; Yu, Byron M.

2013-12-01

Objective. Analyzing and interpreting the activity of a heterogeneous population of neurons can be challenging, especially as the number of neurons, experimental trials, and experimental conditions increases. One approach is to extract a set of latent variables that succinctly captures the prominent co-fluctuation patterns across the neural population. A key problem is that the number of latent variables needed to adequately describe the population activity is often greater than 3, thereby preventing direct visualization of the latent space. By visualizing a small number of 2-d projections of the latent space or each latent variable individually, it is easy to miss salient features of the population activity. Approach. To address this limitation, we developed a Matlab graphical user interface (called DataHigh) that allows the user to quickly and smoothly navigate through a continuum of different 2-d projections of the latent space. We also implemented a suite of additional visualization tools (including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses) and an optional tool for performing dimensionality reduction. Main results. To demonstrate the utility and versatility of DataHigh, we used it to analyze single-trial spike count and single-trial timecourse population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded using single electrodes. Significance. DataHigh was developed to fulfil a need for visualization in exploratory neural data analysis, which can provide intuition that is critical for building scientific hypotheses and models of population activity.

DataHigh: graphical user interface for visualizing and interacting with high-dimensional neural activity.

PubMed

Cowley, Benjamin R; Kaufman, Matthew T; Butler, Zachary S; Churchland, Mark M; Ryu, Stephen I; Shenoy, Krishna V; Yu, Byron M

2013-12-01

Analyzing and interpreting the activity of a heterogeneous population of neurons can be challenging, especially as the number of neurons, experimental trials, and experimental conditions increases. One approach is to extract a set of latent variables that succinctly captures the prominent co-fluctuation patterns across the neural population. A key problem is that the number of latent variables needed to adequately describe the population activity is often greater than 3, thereby preventing direct visualization of the latent space. By visualizing a small number of 2-d projections of the latent space or each latent variable individually, it is easy to miss salient features of the population activity. To address this limitation, we developed a Matlab graphical user interface (called DataHigh) that allows the user to quickly and smoothly navigate through a continuum of different 2-d projections of the latent space. We also implemented a suite of additional visualization tools (including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses) and an optional tool for performing dimensionality reduction. To demonstrate the utility and versatility of DataHigh, we used it to analyze single-trial spike count and single-trial timecourse population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded using single electrodes. DataHigh was developed to fulfil a need for visualization in exploratory neural data analysis, which can provide intuition that is critical for building scientific hypotheses and models of population activity.

Rasch analysis of Stamps's Index of Work Satisfaction in nursing population.

PubMed

Ahmad, Nora; Oranye, Nelson Ositadimma; Danilov, Alyona

2017-01-01

One of the most commonly used tools for measuring job satisfaction in nursing is the Stamps Index of Work Satisfaction. Several studies have reported on the reliability of the Stamps' tool based on traditional statistical model. The aim of this study was to apply the Rasch model to examine the adequacy of Stamps's Index of Work Satisfaction for measuring nurses' job satisfaction cross-culturally and to determine the validity and reliability of the instrument using the Rasch criteria. A secondary data analysis was conducted on a sample of 556 registered nurses from two countries. The RUMM 2030 software was used to analyse the psychometric properties of the Index of Work Satisfaction. The persons mean location of -0.018 approximated the items mean of 0.00, suggesting a good alignment of the measure and the traits being measured. However, at the items level, some items were misfiting to the Rasch model.

Food Web Bioaccumulation Model for Resident Killer Whales from the Northeastern Pacific Ocean as a Tool for the Derivation of PBDE-Sediment Quality Guidelines.

PubMed

Alava, Juan José; Ross, Peter S; Gobas, Frank A P C

2016-01-01

Resident killer whale populations in the NE Pacific Ocean are at risk due to the accumulation of pollutants, including polybrominated diphenyl ethers (PBDEs). To assess the impact of PBDEs in water and sediments in killer whale critical habitat, we developed a food web bioaccumulation model. The model was designed to estimate PBDE concentrations in killer whales based on PBDE concentrations in sediments and the water column throughout a lifetime of exposure. Calculated and observed PBDE concentrations exceeded the only toxicity reference value available for PBDEs in marine mammals (1500 μg/kg lipid) in southern resident killer whales but not in northern resident killer whales. Temporal trends (1993-2006) for PBDEs observed in southern resident killer whales showed a doubling time of ≈5 years. If current sediment quality guidelines available in Canada for polychlorinated biphenyls are applied to PBDEs, it can be expected that PBDE concentrations in killer whales will exceed available toxicity reference values by a large margin. Model calculations suggest that a PBDE concentration in sediments of approximately 1.0 μg/kg dw produces PBDE concentrations in resident killer whales that are below the current toxicity reference value for 95 % of the population, with this value serving as a precautionary benchmark for a management-based approach to reducing PBDE health risks to killer whales. The food web bioaccumulation model may be a useful risk management tool in support of regulatory protection for killer whales.

Utility of existing diabetes risk prediction tools for young black and white adults: Evidence from the Bogalusa Heart Study.

PubMed

Pollock, Benjamin D; Hu, Tian; Chen, Wei; Harville, Emily W; Li, Shengxu; Webber, Larry S; Fonseca, Vivian; Bazzano, Lydia A

2017-01-01

To evaluate several adult diabetes risk calculation tools for predicting the development of incident diabetes and pre-diabetes in a bi-racial, young adult population. Surveys beginning in young adulthood (baseline age ≥18) and continuing across multiple decades for 2122 participants of the Bogalusa Heart Study were used to test the associations of five well-known adult diabetes risk scores with incident diabetes and pre-diabetes using separate Cox models for each risk score. Racial differences were tested within each model. Predictive utility and discrimination were determined for each risk score using the Net Reclassification Index (NRI) and Harrell's c-statistic. All risk scores were strongly associated (p<.0001) with incident diabetes and pre-diabetes. The Wilson model indicated greater risk of diabetes for blacks versus whites with equivalent risk scores (HR=1.59; 95% CI 1.11-2.28; p=.01). C-statistics for the diabetes risk models ranged from 0.79 to 0.83. Non-event NRIs indicated high specificity (non-event NRIs: 76%-88%), but poor sensitivity (event NRIs: -23% to -3%). Five diabetes risk scores established in middle-aged, racially homogenous adult populations are generally applicable to younger adults with good specificity but poor sensitivity. The addition of race to these models did not result in greater predictive capabilities. A more sensitive risk score to predict diabetes in younger adults is needed. Copyright © 2017 Elsevier Inc. All rights reserved.

An area-level model of vehicle-pedestrian injury collisions with implications for land use and transportation planning.

PubMed

Wier, Megan; Weintraub, June; Humphreys, Elizabeth H; Seto, Edmund; Bhatia, Rajiv

2009-01-01

There is growing awareness among urban planning, public health, and transportation professionals that design decisions and investments that promote walking can be beneficial for human and ecological health. Planners need practical tools to consider the impact of development on pedestrian safety, a key requirement for the promotion of walking. Simple bivariate models have been used to predict changes in vehicle-pedestrian injury collisions based on changes in traffic volume. We describe the development of a multivariate, area-level regression model of vehicle-pedestrian injury collisions based on environmental and population data in 176 San Francisco, California census tracts. Predictor variables examined included street, land use, and population characteristics, including commute behaviors. The final model explained approximately 72% of the systematic variation in census-tract vehicle-pedestrian injury collisions and included measures of traffic volume, arterial streets without transit, land area, proportion of land area zoned for neighborhood commercial and residential-neighborhood commercial uses, employee and resident populations, proportion of people living in poverty and proportion aged 65 and older. We have begun to apply this model to predict area-level change in vehicle-pedestrian injury collisions associated with land use development and transportation planning decisions.

Assortative mating and mutation diffusion in spatial evolutionary systems

NASA Astrophysics Data System (ADS)

Paley, C. J.; Taraskin, S. N.; Elliott, S. R.

2010-04-01

The influence of spatial structure on the equilibrium properties of a sexual population model defined on networks is studied numerically. Using a small-world-like topology of the networks as an investigative tool, the contributions to the fitness of assortative mating and of global mutant spread properties are considered. Simple measures of nearest-neighbor correlations and speed of spread of mutants through the system have been used to confirm that both of these dynamics are important contributory factors to the fitness. It is found that assortative mating increases the fitness of populations. Quick global spread of favorable mutations is shown to be a key factor increasing the equilibrium fitness of populations.

Modeling Gene-Environment Interactions With Quasi-Natural Experiments.

PubMed

Schmitz, Lauren; Conley, Dalton

2017-02-01

This overview develops new empirical models that can effectively document Gene × Environment (G×E) interactions in observational data. Current G×E studies are often unable to support causal inference because they use endogenous measures of the environment or fail to adequately address the nonrandom distribution of genes across environments, confounding estimates. Comprehensive measures of genetic variation are incorporated into quasi-natural experimental designs to exploit exogenous environmental shocks or isolate variation in environmental exposure to avoid potential confounders. In addition, we offer insights from population genetics that improve upon extant approaches to address problems from population stratification. Together, these tools offer a powerful way forward for G×E research on the origin and development of social inequality across the life course. © 2015 Wiley Periodicals, Inc.

The Potential Impact of Preventive HIV Vaccines in China: Results and Benefits of a Multi-Province Modeling Collaboration

PubMed Central

Harmon, Thomas; Guo, Wei; Stover, John; Wu, Zunyou; Kaufman, Joan; Schneider, Kammerle; Liu, Li; Feng, Liao; Schwartländer, Bernard

2015-01-01

China’s commitment to implementing established and emerging HIV/AIDS prevention and control strategies has led to substantial gains in terms of access to antiretroviral treatment and prevention services, but the evolving and multifaceted HIV/AIDS epidemic in China highlights the challenges of maintaining that response. This study presents modeling results exploring the potential impact of HIV vaccines in the Chinese context at varying efficacy and coverage rates, while further exploring the potential implications of vaccination programs aimed at reaching populations at highest risk of HIV infection. A preventive HIV vaccine would add a powerful tool to China’s response, even if not 100% efficacious or available to the full population. PMID:26344945

Cultural hitchhiking on the wave of advance of beneficial technologies.

PubMed

Ackland, Graeme J; Signitzer, Markus; Stratford, Kevin; Cohen, Morrel H

2007-05-22

The wave-of-advance model was introduced to describe the spread of advantageous genes in a population. It can be adapted to model the uptake of any advantageous technology through a population, such as the arrival of neolithic farmers in Europe, the domestication of the horse, and the development of the wheel, iron tools, political organization, or advanced weaponry. Any trait that preexists alongside the advantageous one could be carried along with it, such as genetics or language, regardless of any intrinsic superiority. Decoupling of the advantageous trait from other "hitchhiking" traits depends on its adoption by the preexisting population. Here, we adopt a similar wave-of-advance model based on food production on a heterogeneous landscape with multiple populations. Two key results arise from geographic inhomogeneity: the "subsistence boundary," land so poor that the wave of advance is halted, and the temporary "diffusion boundary" where the wave cannot move into poorer areas until its gradient becomes sufficiently large. At diffusion boundaries, farming technology may pass to indigenous people already in those poorer lands, allowing their population to grow and resist encroachment by farmers. Ultimately, this adoption of technology leads to the halt in spread of the hitchhiking trait and establishment of a permanent "cultural boundary" between distinct cultures with equivalent technology.

Cultural hitchhiking on the wave of advance of beneficial technologies

PubMed Central

Ackland, Graeme J.; Signitzer, Markus; Stratford, Kevin; Cohen, Morrel H.

2007-01-01

The wave-of-advance model was introduced to describe the spread of advantageous genes in a population. It can be adapted to model the uptake of any advantageous technology through a population, such as the arrival of neolithic farmers in Europe, the domestication of the horse, and the development of the wheel, iron tools, political organization, or advanced weaponry. Any trait that preexists alongside the advantageous one could be carried along with it, such as genetics or language, regardless of any intrinsic superiority. Decoupling of the advantageous trait from other “hitchhiking” traits depends on its adoption by the preexisting population. Here, we adopt a similar wave-of-advance model based on food production on a heterogeneous landscape with multiple populations. Two key results arise from geographic inhomogeneity: the “subsistence boundary,” land so poor that the wave of advance is halted, and the temporary “diffusion boundary” where the wave cannot move into poorer areas until its gradient becomes sufficiently large. At diffusion boundaries, farming technology may pass to indigenous people already in those poorer lands, allowing their population to grow and resist encroachment by farmers. Ultimately, this adoption of technology leads to the halt in spread of the hitchhiking trait and establishment of a permanent “cultural boundary” between distinct cultures with equivalent technology. PMID:17517663

Linking intended visitation to regional economic impact models of bison and elk management

USGS Publications Warehouse

Loomis, J.; Caughlan, L.

2004-01-01

This article links intended National Park visitation estimates to regional economic models to calculate the employment impacts of alternative bison and elk management strategies. The survey described alternative National Elk Refuge (NER) management actions and the effects on elk and bison populations at the NER and adjacent Grand Teton National Park (GTNP). Park visitors were then asked if they would change their number of visits with each potential management action. Results indicate there would be a 10% decrease in visitation if bison populations were reduced from 600 to 400 animals and elk populations were reduced in GTNP and the NER. The related decrease in jobs in Teton counties of Wyoming and Idaho is estimated at 5.5%. Adopting a “no active management” option of never feeding elk and bison on the NER yields about one-third the current bison population (200 bison) and about half the elk population. Visitors surveyed about this management option would take about 20% fewer trips, resulting in an 11.3% decrease in employment. Linking intended visitation surveys and regional economic models represents a useful tool for natural resource planners who must present the consequences of potential actions in Environmental Impact Statements and plans to the public and decision makers prior to any action being implemented.

Evolution and population genetics of exotic and reemerging pathogens: traditional and novel tools and approaches

Treesearch

N.J. Grünwald; E.M. Goss

2011-01-01

Given human population growth and accelerated global trade, the rate of emergence of exotic plant pathogens is bound to increase. Understanding the processes that lead to the emergence of new pathogens can help manage emerging epidemics. Novel tools for analyzing population genetic variation can be used to infer the evolutionary history of populations or species,...

Using demography and movement behavior to predict range expansion of the southern sea otter.

USGS Publications Warehouse

Tinker, M.T.; Doak, D.F.; Estes, J.A.

2008-01-01

In addition to forecasting population growth, basic demographic data combined with movement data provide a means for predicting rates of range expansion. Quantitative models of range expansion have rarely been applied to large vertebrates, although such tools could be useful for restoration and management of many threatened but recovering populations. Using the southern sea otter (Enhydra lutris nereis) as a case study, we utilized integro-difference equations in combination with a stage-structured projection matrix that incorporated spatial variation in dispersal and demography to make forecasts of population recovery and range recolonization. In addition to these basic predictions, we emphasize how to make these modeling predictions useful in a management context through the inclusion of parameter uncertainty and sensitivity analysis. Our models resulted in hind-cast (1989–2003) predictions of net population growth and range expansion that closely matched observed patterns. We next made projections of future range expansion and population growth, incorporating uncertainty in all model parameters, and explored the sensitivity of model predictions to variation in spatially explicit survival and dispersal rates. The predicted rate of southward range expansion (median = 5.2 km/yr) was sensitive to both dispersal and survival rates; elasticity analysis indicated that changes in adult survival would have the greatest potential effect on the rate of range expansion, while perturbation analysis showed that variation in subadult dispersal contributed most to variance in model predictions. Variation in survival and dispersal of females at the south end of the range contributed most of the variance in predicted southward range expansion. Our approach provides guidance for the acquisition of further data and a means of forecasting the consequence of specific management actions. Similar methods could aid in the management of other recovering populations.

The effect of stochiastic technique on estimates of population viability from transition matrix models

USGS Publications Warehouse

Kaye, T.N.; Pyke, David A.

2003-01-01

Population viability analysis is an important tool for conservation biologists, and matrix models that incorporate stochasticity are commonly used for this purpose. However, stochastic simulations may require assumptions about the distribution of matrix parameters, and modelers often select a statistical distribution that seems reasonable without sufficient data to test its fit. We used data from long-term (5a??10 year) studies with 27 populations of five perennial plant species to compare seven methods of incorporating environmental stochasticity. We estimated stochastic population growth rate (a measure of viability) using a matrix-selection method, in which whole observed matrices were selected at random at each time step of the model. In addition, we drew matrix elements (transition probabilities) at random using various statistical distributions: beta, truncated-gamma, truncated-normal, triangular, uniform, or discontinuous/observed. Recruitment rates were held constant at their observed mean values. Two methods of constraining stage-specific survival to a??100% were also compared. Different methods of incorporating stochasticity and constraining matrix column sums interacted in their effects and resulted in different estimates of stochastic growth rate (differing by up to 16%). Modelers should be aware that when constraining stage-specific survival to 100%, different methods may introduce different levels of bias in transition element means, and when this happens, different distributions for generating random transition elements may result in different viability estimates. There was no species effect on the results and the growth rates derived from all methods were highly correlated with one another. We conclude that the absolute value of population viability estimates is sensitive to model assumptions, but the relative ranking of populations (and management treatments) is robust. Furthermore, these results are applicable to a range of perennial plants and possibly other life histories.

Survey of Technologies Relevant to Defense From Near-Earth Objects

NASA Technical Reports Server (NTRS)

Adams, R. B.; Alexander, R.; Bonometti, J.; Chapman, J.; Fincher, S.; Hopkins, R.; Kalkstein, M.; Polsgrove, T.; Statham, G.; White, S.

2004-01-01

Several recent near-miss encounters with asteroids and comets have focused attention on the threat of a catastrophic impact with the Earth. This Technical Publication reviews the historical impact record and current understanding of the number and location of near-Earth objects (NEOs) to address their impact probability. Various ongoing projects intended to survey and catalog the NEO population are also reviewed. Details are given of a Marshall Space Flight Center-led study intended to develop and assess various candidate systems for protection of the Earth against NEOs. Details of analytical tools, trajectory tools, and a tool that was created to model both the undeflected inbound path of an NEO as well as the modified, postdeflection path are given. A representative selection of these possible options was modeled and evaluated. It is hoped that this study will raise the level of attention about this very real threat and also demonstrate that successful defense is both possible and practicable, provided appropriate steps are taken.

A web application to support telemedicine services in Brazil.

PubMed

Barbosa, Ana Karina P; de A Novaes, Magdala; de Vasconcelos, Alexandre M L

2003-01-01

This paper describes a system that has been developed to support Telemedicine activities in Brazil, a country that has serious problems in the delivery of health services. The system is a part of the broader Tele-health Project that has been developed to make health services more accessible to the low-income population in the northeast region. The HealthNet system is based upon a pilot area that uses fetal and pediatric cardiology. This article describes both the system's conceptual model, including the tele-diagnosis and second medical opinion services, as well as its architecture and development stages. The system model describes both collaborating tools used asynchronously, such as discussion forums, and synchronous tools, such as videoconference services. Web and free-of-charge tools are utilized for implementation, such as Java and MySQL database. Furthermore, an interface with Electronic Patient Record (EPR) systems using Extended Markup Language (XML) technology is also proposed. Finally, considerations concerning the development and implementation process are presented.

A generalised individual-based algorithm for modelling the evolution of quantitative herbicide resistance in arable weed populations.

PubMed

Liu, Chun; Bridges, Melissa E; Kaundun, Shiv S; Glasgow, Les; Owen, Micheal Dk; Neve, Paul

2017-02-01

Simulation models are useful tools for predicting and comparing the risk of herbicide resistance in weed populations under different management strategies. Most existing models assume a monogenic mechanism governing herbicide resistance evolution. However, growing evidence suggests that herbicide resistance is often inherited in a polygenic or quantitative fashion. Therefore, we constructed a generalised modelling framework to simulate the evolution of quantitative herbicide resistance in summer annual weeds. Real-field management parameters based on Amaranthus tuberculatus (Moq.) Sauer (syn. rudis) control with glyphosate and mesotrione in Midwestern US maize-soybean agroecosystems demonstrated that the model can represent evolved herbicide resistance in realistic timescales. Sensitivity analyses showed that genetic and management parameters were impactful on the rate of quantitative herbicide resistance evolution, whilst biological parameters such as emergence and seed bank mortality were less important. The simulation model provides a robust and widely applicable framework for predicting the evolution of quantitative herbicide resistance in summer annual weed populations. The sensitivity analyses identified weed characteristics that would favour herbicide resistance evolution, including high annual fecundity, large resistance phenotypic variance and pre-existing herbicide resistance. Implications for herbicide resistance management and potential use of the model are discussed. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Using occupancy models to understand the distribution of an amphibian pathogen, Batrachochytrium dendrobatidis

USGS Publications Warehouse

Adams, Michael J.; Chelgren, Nathan; Reinitz, David M.; Cole, Rebecca A.; Rachowicz, L.J.; Galvan, Stephanie; Mccreary, Brome; Pearl, Christopher A.; Bailey, Larissa L.; Bettaso, Jamie B.; Bull, Evelyn L.; Leu, Matthias

2010-01-01

Batrachochytrium dendrobatidis is a fungal pathogen that is receiving attention around the world for its role in amphibian declines. Study of its occurrence patterns is hampered by false negatives: the failure to detect the pathogen when it is present. Occupancy models are a useful but currently underutilized tool for analyzing detection data when the probability of detecting a species is <1. We use occupancy models to evaluate hypotheses concerning the occurrence and prevalence of B. dendrobatidis and discuss how this application differs from a conventional occupancy approach. We found that the probability of detecting the pathogen, conditional on presence of the pathogen in the anuran population, was related to amphibian development stage, day of the year, elevation, and human activities. Batrachochytrium dendrobatidis was found throughout our study area but was only estimated to occur in 53.4% of 78 populations of native amphibians and 66.4% of 40 populations of nonnative Rana catesbeiana tested. We found little evidence to support any spatial hypotheses concerning the probability that the pathogen occurs in a population, but did find evidence of some taxonomic variation. We discuss the interpretation of occupancy model parameters, when, unlike a conventional occupancy application, the number of potential samples or observations is finite.

A laboratory-calibrated model of coho salmon growth with utility for ecological analyses

USGS Publications Warehouse

Manhard, Christopher V.; Som, Nicholas A.; Perry, Russell W.; Plumb, John M.

2018-01-01

We conducted a meta-analysis of laboratory- and hatchery-based growth data to estimate broadly applicable parameters of mass- and temperature-dependent growth of juvenile coho salmon (Oncorhynchus kisutch). Following studies of other salmonid species, we incorporated the Ratkowsky growth model into an allometric model and fit this model to growth observations from eight studies spanning ten different populations. To account for changes in growth patterns with food availability, we reparameterized the Ratkowsky model to scale several of its parameters relative to ration. The resulting model was robust across a wide range of ration allocations and experimental conditions, accounting for 99% of the variation in final body mass. We fit this model to growth data from coho salmon inhabiting tributaries and constructed ponds in the Klamath Basin by estimating habitat-specific indices of food availability. The model produced evidence that constructed ponds provided higher food availability than natural tributaries. Because of their simplicity (only mass and temperature are required as inputs) and robustness, ration-varying Ratkowsky models have utility as an ecological tool for capturing growth in freshwater fish populations.

Population genetics of autopolyploids under a mixed mating model and the estimation of selfing rate.

PubMed

Hardy, Olivier J

2016-01-01

Nowadays, the population genetics analysis of autopolyploid species faces many difficulties due to (i) limited development of population genetics tools under polysomic inheritance, (ii) difficulties to assess allelic dosage when genotyping individuals and (iii) a form of inbreeding resulting from the mechanism of 'double reduction'. Consequently, few data analysis computer programs are applicable to autopolyploids. To contribute bridging this gap, this article first derives theoretical expectations for the inbreeding and identity disequilibrium coefficients under polysomic inheritance in a mixed mating model. Moment estimators of these coefficients are proposed when exact genotypes or just markers phenotypes (i.e. allelic dosage unknown) are available. This led to the development of estimators of the selfing rate based on adult genotypes or phenotypes and applicable to any even-ploidy level. Their statistical performances and robustness were assessed by numerical simulations. Contrary to inbreeding-based estimators, the identity disequilibrium-based estimator using phenotypes is robust (absolute bias generally < 0.05), even in the presence of double reduction, null alleles or biparental inbreeding due to isolation by distance. A fairly good precision of the selfing rate estimates (root mean squared error < 0.1) is already achievable using a sample of 30-50 individuals phenotyped at 10 loci bearing 5-10 alleles each, conditions reachable using microsatellite markers. Diallelic markers (e.g. SNP) can also perform satisfactorily in diploids and tetraploids but more polymorphic markers are necessary for higher ploidy levels. The method is implemented in the software SPAGeDi and should contribute to reduce the lack of population genetics tools applicable to autopolyploids. © 2015 John Wiley & Sons Ltd.

Assessing multimedia/multipathway exposures to inorganic arsenic at population and individual level using MERLIN-Expo.

PubMed

Van Holderbeke, Mirja; Fierens, Tine; Standaert, Arnout; Cornelis, Christa; Brochot, Céline; Ciffroy, Philippe; Johansson, Erik; Bierkens, Johan

2016-10-15

In this study, we report on model simulations performed using the newly developed exposure tool, MERLIN-Expo, in order to assess inorganic arsenic (iAs) exposure to adults resulting from past emissions by non-ferrous smelters in Belgium (Northern Campine area). Exposure scenarios were constructed to estimate external iAs exposure as well as the toxicologically relevant As (tAs, i.e., iAs, MMA and DMA) body burden in adults living in the vicinity of the former industrial sites as compared to adults living in adjacent areas and a reference area. Two scenarios are discussed: a first scenario studying exposure to iAs at the aggregated population level and a second scenario studying exposure at the individual level for a random sub-sample of subjects in each of the three different study areas. These two scenarios only differ in the type of human related input data (i.e., time-activity data, ingestion rates and consumption patterns) that were used, namely averages (incl. probability density functions, PDFs) in the simulation at population level and subject-specific values in the simulation at individual level. The model predictions are shown to be lower than the corresponding biomonitoring data from the monitoring campaign. Urinary tAs levels in adults, irrespective of the area they lived in, were under-predicted by MERLIN-Expo by 40% on average. The model predictions for individual adults, by contrast, under-predict the biomonitoring data by 7% on average, but with more important under-predictions for subjects at the upper end of exposure. Still, average predicted urinary tAs levels from the simulations at population level and at individual level overlap, and, at least for the current case, lead to similar conclusions. These results constitute a first and partial verification of the model performance of MERLIN-Expo when dealing with iAs in a complex site-specific exposure scenario, and demonstrate the robustness of the modelling tool for these situations. Copyright © 2016 Elsevier B.V. All rights reserved.

Astronaut Bone Medical Standards Derived from Finite Element (FE) Models of QCT Scans from Population Studies

NASA Technical Reports Server (NTRS)

Sibonga, J. D.; Feiveson, A. H.

2014-01-01

This work was accomplished in support of the Finite Element [FE] Strength Task Group, NASA Johnson Space Center [JSC], Houston, TX. This group was charged with the task of developing rules for using finite-element [FE] bone-strength measures to construct operating bands for bone health that are relevant to astronauts following exposure to spaceflight. FE modeling is a computational tool used by engineers to estimate the failure loads of complex structures. Recently, some engineers have used this tool to characterize the failure loads of the hip in population studies that also monitored fracture outcomes. A Directed Research Task was authorized in July, 2012 to investigate FE data from these population studies to derive these proposed standards of bone health as a function of age and gender. The proposed standards make use of an FE-based index that integrates multiple contributors to bone strength, an expanded evaluation that is critical after an astronaut is exposed to spaceflight. The current index of bone health used by NASA is the measurement of areal BMD. There was a concern voiced by a research and clinical advisory panel that the sole use of areal BMD would be insufficient to fully evaluate the effects of spaceflight on the hip. Hence, NASA may not have a full understanding of fracture risk, both during and after a mission, and may be poorly estimating in-flight countermeasure efficacy. The FE Strength Task Group - composed of principal investigators of the aforementioned population studies and of FE modelers -donated some of its population QCT data to estimate of hip bone strength by FE modeling for this specific purpose. Consequently, Human Health Countermeasures [HHC] has compiled a dataset of FE hip strengths, generated by a single FE modeling approach, from human subjects (approx.1060) with ages covering the age range of the astronauts. The dataset has been analyzed to generate a set of FE strength cutoffs for the following scenarios: a) Qualify an applicant for astronaut candidacy, b) Qualify an astronaut for a long-duration (LD) mission, c) Qualify a veteran LD astronaut for a second LD mission, and d) Establish a non-permissible, minimum hip strength following a given mission architecture. This abstract will present the FE-based standards accepted by the FE Strength Task Group for its recommendation to HHC in January 2015.

RE-PLAN: An Extensible Software Architecture to Facilitate Disaster Response Planning

PubMed Central

O’Neill, Martin; Mikler, Armin R.; Indrakanti, Saratchandra; Tiwari, Chetan; Jimenez, Tamara

2014-01-01

Computational tools are needed to make data-driven disaster mitigation planning accessible to planners and policymakers without the need for programming or GIS expertise. To address this problem, we have created modules to facilitate quantitative analyses pertinent to a variety of different disaster scenarios. These modules, which comprise the REsponse PLan ANalyzer (RE-PLAN) framework, may be used to create tools for specific disaster scenarios that allow planners to harness large amounts of disparate data and execute computational models through a point-and-click interface. Bio-E, a user-friendly tool built using this framework, was designed to develop and analyze the feasibility of ad hoc clinics for treating populations following a biological emergency event. In this article, the design and implementation of the RE-PLAN framework are described, and the functionality of the modules used in the Bio-E biological emergency mitigation tool are demonstrated. PMID:25419503

Theory and Design Tools For Studies of Reactions to Abrupt Changes in Noise Exposure

NASA Technical Reports Server (NTRS)

Fields, James M.; Ehrlich, Gary E.; Zador, Paul; Shepherd, Kevin P. (Technical Monitor)

2000-01-01

Study plans, a pre-tested questionnaire, a sample design evaluation tool, a community publicity monitoring plan, and a theoretical framework have been developed to support combined social/acoustical surveys of residents' reactions to an abrupt change in environmental noise, Secondary analyses of more than 20 previous surveys provide estimates of three parameters of a study simulation model; within individual variability, between study wave variability, and between neighborhood variability in response to community noise. The simulation model predicts the precision of the results from social surveys of reactions to noise, including changes in noise. When the study simulation model analyzed the population distribution, noise exposure environments and feasible noise measurement program at a proposed noise change survey site, it was concluded that the site could not yield sufficient precise estimates of human reaction model to justify conducting a survey. Additional secondary analyses determined that noise reactions are affected by the season of the social survey.

Sea-level rise modeling handbook: Resource guide for coastal land managers, engineers, and scientists

USGS Publications Warehouse

Doyle, Thomas W.; Chivoiu, Bogdan; Enwright, Nicholas M.

2015-08-24

Global sea level is rising and may accelerate with continued fossil fuel consumption from industrial and population growth. In 2012, the U.S. Geological Survey conducted more than 30 training and feedback sessions with Federal, State, and nongovernmental organization (NGO) coastal managers and planners across the northern Gulf of Mexico coast to evaluate user needs, potential benefits, current scientific understanding, and utilization of resource aids and modeling tools focused on sea-level rise. In response to the findings from the sessions, this sea-level rise modeling handbook has been designed as a guide to the science and simulation models for understanding the dynamics and impacts of sea-level rise on coastal ecosystems. The review herein of decision-support tools and predictive models was compiled from the training sessions, from online research, and from publications. The purpose of this guide is to describe and categorize the suite of data, methods, and models and their design, structure, and application for hindcasting and forecasting the potential impacts of sea-level rise in coastal ecosystems. The data and models cover a broad spectrum of disciplines involving different designs and scales of spatial and temporal complexity for predicting environmental change and ecosystem response. These data and models have not heretofore been synthesized, nor have appraisals been made of their utility or limitations. Some models are demonstration tools for non-experts, whereas others require more expert capacity to apply for any given park, refuge, or regional application. A simplified tabular context has been developed to list and contrast a host of decision-support tools and models from the ecological, geological, and hydrological perspectives. Criteria were established to distinguish the source, scale, and quality of information input and geographic datasets; physical and biological constraints and relations; datum characteristics of water and land components; utility options for setting sea-level rise and climate change scenarios; and ease or difficulty of storing, displaying, or interpreting model output. Coastal land managers, engineers, and scientists can benefit from this synthesis of tools and models that have been developed for projecting causes and consequences of sea-level change on the landscape and seascape.

A Zero- and K-Inflated Mixture Model for Health Questionnaire Data

PubMed Central

Finkelman, Matthew D.; Green, Jennifer Greif; Gruber, Michael J.; Zaslavsky, Alan M.

2011-01-01

In psychiatric assessment, Item Response Theory (IRT) is a popular tool to formalize the relation between the severity of a disorder and associated responses to questionnaire items. Practitioners of IRT sometimes make the assumption of normally distributed severities within a population; while convenient, this assumption is often violated when measuring psychiatric disorders. Specifically, there may be a sizable group of respondents whose answers place them at an extreme of the latent trait spectrum. In this article, a zero- and K-inflated mixture model is developed to account for the presence of such respondents. The model is fitted using an expectation-maximization (E-M) algorithm to estimate the percentage of the population at each end of the continuum, concurrently analyzing the remaining “graded component” via IRT. A method to perform factor analysis for only the graded component is introduced. In assessments of oppositional defiant disorder and conduct disorder, the zero- and K-inflated model exhibited better fit than the standard IRT model. PMID:21365673

Genealogical and evolutionary inference with the human Y chromosome.

PubMed

Stumpf, M P; Goldstein, D B

2001-03-02

Population genetics has emerged as a powerful tool for unraveling human history. In addition to the study of mitochondrial and autosomal DNA, attention has recently focused on Y-chromosome variation. Ambiguities and inaccuracies in data analysis, however, pose an important obstacle to further development of the field. Here we review the methods available for genealogical inference using Y-chromosome data. Approaches can be divided into those that do and those that do not use an explicit population model in genealogical inference. We describe the strengths and weaknesses of these model-based and model-free approaches, as well as difficulties associated with the mutation process that affect both methods. In the case of genealogical inference using microsatellite loci, we use coalescent simulations to show that relatively simple generalizations of the mutation process can greatly increase the accuracy of genealogical inference. Because model-free and model-based approaches have different biases and limitations, we conclude that there is considerable benefit in the continued use of both types of approaches.

Cloud Model Bat Algorithm

PubMed Central

Zhou, Yongquan; Xie, Jian; Li, Liangliang; Ma, Mingzhi

2014-01-01

Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of cloud model to depict the qualitative concept: “bats approach their prey.” Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the cloud model bat algorithm has good performance on functions optimization. PMID:24967425

Human factors model concerning the man-machine interface of mining crewstations

NASA Technical Reports Server (NTRS)

Rider, James P.; Unger, Richard L.

1989-01-01

The U.S. Bureau of Mines is developing a computer model to analyze the human factors aspect of mining machine operator compartments. The model will be used as a research tool and as a design aid. It will have the capability to perform the following: simulated anthropometric or reach assessment, visibility analysis, illumination analysis, structural analysis of the protective canopy, operator fatigue analysis, and computation of an ingress-egress rating. The model will make extensive use of graphics to simplify data input and output. Two dimensional orthographic projections of the machine and its operator compartment are digitized and the data rebuilt into a three dimensional representation of the mining machine. Anthropometric data from either an individual or any size population may be used. The model is intended for use by equipment manufacturers and mining companies during initial design work on new machines. In addition to its use in machine design, the model should prove helpful as an accident investigation tool and for determining the effects of machine modifications made in the field on the critical areas of visibility and control reach ability.

The impact of eliminating within-country inequality in health coverage on maternal and child mortality: a Lives Saved Tool analysis.

PubMed

Clermont, Adrienne

2017-11-07

Inequality in healthcare across population groups in low-income countries is a growing topic of interest in global health. The Lives Saved Tool (LiST), which uses health intervention coverage to model maternal, neonatal, and child health outcomes such as mortality rates, can be used to analyze the impact of within-country inequality. Data from nationally representative household surveys (98 surveys conducted between 1998 and 2014), disaggregated by wealth quintile, were used to create a LiST analysis that models the impact of scaling up health intervention coverage for the entire country from the national average to the rate of the top wealth quintile (richest 20% of the population). Interventions for which household survey data are available were used as proxies for other interventions that are not measured in surveys, based on co-delivery of intervention packages. For the 98 countries included in the analysis, 24-32% of child deaths (including 34-47% of neonatal deaths and 16-19% of post-neonatal deaths) could be prevented by scaling up national coverage of key health interventions to the level of the top wealth quintile. On average, the interventions with most unequal coverage rates across wealth quintiles were those related to childbirth in health facilities and to water and sanitation infrastructure; the most equally distributed were those delivered through community-based mass campaigns, such as vaccines, vitamin A supplementation, and bednet distribution. LiST is a powerful tool for exploring the policy and programmatic implications of within-country inequality in low-income, high-mortality-burden countries. An "Equity Tool" app has been developed within the software to make this type of analysis easily accessible to users.

An epidemiologic simulation model of the spread and control of highly pathogenic avian influenza (H5N1) among commercial and backyard poultry flocks in South Carolina, United States.

PubMed

Patyk, Kelly A; Helm, Julie; Martin, Michael K; Forde-Folle, Kimberly N; Olea-Popelka, Francisco J; Hokanson, John E; Fingerlin, Tasha; Reeves, Aaron

2013-07-01

Epidemiologic simulation modeling of highly pathogenic avian influenza (HPAI) outbreaks provides a useful conceptual framework with which to estimate the consequences of HPAI outbreaks and to evaluate disease control strategies. The purposes of this study were to establish detailed and informed input parameters for an epidemiologic simulation model of the H5N1 strain of HPAI among commercial and backyard poultry in the state of South Carolina in the United States using a highly realistic representation of this poultry population; to estimate the consequences of an outbreak of HPAI in this population with a model constructed from these parameters; and to briefly evaluate the sensitivity of model outcomes to several parameters. Parameters describing disease state durations; disease transmission via direct contact, indirect contact, and local-area spread; and disease detection, surveillance, and control were established through consultation with subject matter experts, a review of the current literature, and the use of several computational tools. The stochastic model constructed from these parameters produced simulated outbreaks ranging from 2 to 111 days in duration (median 25 days), during which 1 to 514 flocks were infected (median 28 flocks). Model results were particularly sensitive to the rate of indirect contact that occurs among flocks. The baseline model established in this study can be used in the future to evaluate various control strategies, as a tool for emergency preparedness and response planning, and to assess the costs associated with disease control and the economic consequences of a disease outbreak. Published by Elsevier B.V.

Sequential updating of a new dynamic pharmacokinetic model for caffeine in premature neonates.

PubMed

Micallef, Sandrine; Amzal, Billy; Bach, Véronique; Chardon, Karen; Tourneux, Pierre; Bois, Frédéric Y

2007-01-01

Caffeine treatment is widely used in nursing care to reduce the risk of apnoea in premature neonates. To check the therapeutic efficacy of the treatment against apnoea, caffeine concentration in blood is an important indicator. The present study was aimed at building a pharmacokinetic model as a basis for a medical decision support tool. In the proposed model, time dependence of physiological parameters is introduced to describe rapid growth of neonates. To take into account the large variability in the population, the pharmacokinetic model is embedded in a population structure. The whole model is inferred within a Bayesian framework. To update caffeine concentration predictions as data of an incoming patient are collected, we propose a fast method that can be used in a medical context. This involves the sequential updating of model parameters (at individual and population levels) via a stochastic particle algorithm. Our model provides better predictions than the ones obtained with models previously published. We show, through an example, that sequential updating improves predictions of caffeine concentration in blood (reduce bias and length of credibility intervals). The update of the pharmacokinetic model using body mass and caffeine concentration data is studied. It shows how informative caffeine concentration data are in contrast to body mass data. This study provides the methodological basis to predict caffeine concentration in blood, after a given treatment if data are collected on the treated neonate.

keep your models up-to-date: connecting community mapping data to complex urban flood modelling

NASA Astrophysics Data System (ADS)

Winsemius, Hessel; Eilander, Dirk; Ward, Philip; Diaz Loaiza, Andres; Iliffe, Mark; Mawanda, Shaban; Luo, Tianyi; Kimacha, Nyambiri; Chen, Jorik

2017-04-01

The world is urbanizing rapidly. According to the United Nation's World Urbanization Prospect, 50% of the global population already lives in urban areas today. This number is expected to grow to 66% by 2050. The rapid changes in these urban environments go hand in hand with rapid changes in natural hazard risks, in particular in informal unplanned neighbourhoods. In Dar Es Salaam - Tanzania, flood risk dominates and given the rapid changes in the city, continuous updates of detailed street level hazard and risk mapping are needed to adequately support decision making for urban planning, infrastructure design and disaster response. Over the past years, the Ramani Huria and Zuia Mafuriko projects have mapped the most flood prone neighbourhoods, including roads, buildings, drainage and land use and contributed data to the open-source OpenStreetMap database. In this contribution, we will demonstrate how we mobilize these contributed data to establish dynamic flood models for Dar Es Salaam and keep these up-to-date by making a direct link between the data, and model schematization. The tools automatically establish a sound 1D drainage network as well as a high resolution terrain dataset, by fusing the OpenStreetMap data with existing lower resolution terrain data such as the globally available satellite based SRTM 30. It then translates these fully automatically into the inputs required for the D-HYDRO modeling suite. Our tools are built such that community and stakeholder knowledge can be included in the model details through workshops with the tools so that missing essential information about the city's details can be augmented on-the-fly. This process creates a continuous dialogue between members of the community that collect data, and stakeholders requiring data for flood models. Moreover, used taxonomy and data filtering can be configured to conditions in other cities, making the tools generic and scalable. The tools are made available open-source.

Validation of Bengali perceived stress scale among LGBT population.

PubMed

Mozumder, Muhammad Kamruzzaman

2017-08-29

Lesbian, gay, bisexual and transgender (LGBT) population encounter more stressful life circumstances compared to general population. Perceived Stress Scale (PSS) can be a useful tool for measuring their stress. However, psychometric properties of PSS have never been tested on LGBT population. This cross sectional study employed a two-stage sampling strategy to collect data from 296 LGBT participants from six divisional districts of Bangladesh. Exploratory (EFA) and confirmatory factor analysis (CFA) were carried out on PSS 10 along with analysis of reliability and validity. EFA revealed a two-factor structure of PSS for LGBT population explaining 43.55% - 51.45% of total variance. This measurement model was supported by multiple fit indices during CFA. Acceptable Cronbach's alpha indicated internal consistency reliability and high correlations with Self Reporting Questionnaire 20 demonstrated construct validity of PSS 10 for LGBT population. This study provided evidence of satisfactory psychometric properties of Bengali PSS 10 in terms of factor structure, internal consistency and validity among LGBT population.

Suicide Risk Screening Tools and the Youth Population.

PubMed

Patterson, Sharon

2016-08-01

The use of suicide risk screening tools is a critical component of a comprehensive approach to suicide risk assessment. Since nurses frequently spend more time with patients than any other healthcare professional, they are in key positions to detect and prevent suicidal behavior in youth. To inform nurses about suicide risk screening tools for the youth population. Suicide risk screening tools are research-based standardized instruments that are used to identify people who may be at risk for suicide. A literature search was performed using the Athabasca University Library Resource, the databases of the Cumulative Index to Nursing and Allied Health Literature, ScienceDirect, and Google Scholar. Nurses are cautioned to utilize suicide risk screening tools as only part of the suicide risk assessment in youth populations and avoid the danger of relying on tools that may result in a blind application of evidence to the detriment of clinical experience and judgement. © 2016 Wiley Periodicals, Inc.

Influenza vaccination coverage estimates in the fee-for service Medicare beneficiary population 2006 - 2016: Using population-based administrative data to support a geographic based near real-time tool.

PubMed

Shen, Angela K; Warnock, Rob; Brereton, Stephaeno; McKean, Stephen; Wernecke, Michael; Chu, Steve; Kelman, Jeffrey A

2018-04-11

Older adults are at great risk of developing serious complications from seasonal influenza. We explore vaccination coverage estimates in the Medicare population through the use of administrative claims data and describe a tool designed to help shape outreach efforts and inform strategies to help raise influenza vaccination rates. This interactive mapping tool uses claims data to compare vaccination levels between geographic (i.e., state, county, zip code) and demographic (i.e., race, age) groups at different points in a season. Trends can also be compared across seasons. Utilization of this tool can assist key actors interested in prevention - medical groups, health plans, hospitals, and state and local public health authorities - in supporting strategies for reaching pools of unvaccinated beneficiaries where general national population estimates of coverage are less informative. Implementing evidence-based tools can be used to address persistent racial and ethnic disparities and prevent a substantial number of influenza cases and hospitalizations.

A geographic analysis of population density thresholds in the influenza pandemic of 1918-19.

PubMed

Chandra, Siddharth; Kassens-Noor, Eva; Kuljanin, Goran; Vertalka, Joshua

2013-02-20

Geographic variables play an important role in the study of epidemics. The role of one such variable, population density, in the spread of influenza is controversial. Prior studies have tested for such a role using arbitrary thresholds for population density above or below which places are hypothesized to have higher or lower mortality. The results of such studies are mixed. The objective of this study is to estimate, rather than assume, a threshold level of population density that separates low-density regions from high-density regions on the basis of population loss during an influenza pandemic. We study the case of the influenza pandemic of 1918-19 in India, where over 15 million people died in the short span of less than one year. Using data from six censuses for 199 districts of India (n=1194), the country with the largest number of deaths from the influenza of 1918-19, we use a sample-splitting method embedded within a population growth model that explicitly quantifies population loss from the pandemic to estimate a threshold level of population density that separates low-density districts from high-density districts. The results demonstrate a threshold level of population density of 175 people per square mile. A concurrent finding is that districts on the low side of the threshold experienced rates of population loss (3.72%) that were lower than districts on the high side of the threshold (4.69%). This paper introduces a useful analytic tool to the health geographic literature. It illustrates an application of the tool to demonstrate that it can be useful for pandemic awareness and preparedness efforts. Specifically, it estimates a level of population density above which policies to socially distance, redistribute or quarantine populations are likely to be more effective than they are for areas with population densities that lie below the threshold.

A geographic analysis of population density thresholds in the influenza pandemic of 1918–19

PubMed Central

2013-01-01

Background Geographic variables play an important role in the study of epidemics. The role of one such variable, population density, in the spread of influenza is controversial. Prior studies have tested for such a role using arbitrary thresholds for population density above or below which places are hypothesized to have higher or lower mortality. The results of such studies are mixed. The objective of this study is to estimate, rather than assume, a threshold level of population density that separates low-density regions from high-density regions on the basis of population loss during an influenza pandemic. We study the case of the influenza pandemic of 1918–19 in India, where over 15 million people died in the short span of less than one year. Methods Using data from six censuses for 199 districts of India (n=1194), the country with the largest number of deaths from the influenza of 1918–19, we use a sample-splitting method embedded within a population growth model that explicitly quantifies population loss from the pandemic to estimate a threshold level of population density that separates low-density districts from high-density districts. Results The results demonstrate a threshold level of population density of 175 people per square mile. A concurrent finding is that districts on the low side of the threshold experienced rates of population loss (3.72%) that were lower than districts on the high side of the threshold (4.69%). Conclusions This paper introduces a useful analytic tool to the health geographic literature. It illustrates an application of the tool to demonstrate that it can be useful for pandemic awareness and preparedness efforts. Specifically, it estimates a level of population density above which policies to socially distance, redistribute or quarantine populations are likely to be more effective than they are for areas with population densities that lie below the threshold. PMID:23425498

Animal Models for HIV Cure Research.

PubMed

Policicchio, Benjamin B; Pandrea, Ivona; Apetrei, Cristian

2016-01-01

The HIV-1/AIDS pandemic continues to spread unabated worldwide, and no vaccine exists within our grasp. Effective antiretroviral therapy (ART) has been developed, but ART cannot clear the virus from the infected patient. A cure for HIV-1 is badly needed to stop both the spread of the virus in human populations and disease progression in infected individuals. A safe and effective cure strategy for human immunodeficiency virus (HIV) infection will require multiple tools, and appropriate animal models are tools that are central to cure research. An ideal animal model should recapitulate the essential aspects of HIV pathogenesis and associated immune responses, while permitting invasive studies, thus allowing a thorough evaluation of strategies aimed at reducing the size of the reservoir (functional cure) or eliminating the reservoir altogether (sterilizing cure). Since there is no perfect animal model for cure research, multiple models have been tailored and tested to address specific quintessential questions of virus persistence and eradication. The development of new non-human primate and mouse models, along with a certain interest in the feline model, has the potential to fuel cure research. In this review, we highlight the major animal models currently utilized for cure research and the contributions of each model to this goal.

Animal Models for HIV Cure Research

PubMed Central

Policicchio, Benjamin B.; Pandrea, Ivona; Apetrei, Cristian

2016-01-01

The HIV-1/AIDS pandemic continues to spread unabated worldwide, and no vaccine exists within our grasp. Effective antiretroviral therapy (ART) has been developed, but ART cannot clear the virus from the infected patient. A cure for HIV-1 is badly needed to stop both the spread of the virus in human populations and disease progression in infected individuals. A safe and effective cure strategy for human immunodeficiency virus (HIV) infection will require multiple tools, and appropriate animal models are tools that are central to cure research. An ideal animal model should recapitulate the essential aspects of HIV pathogenesis and associated immune responses, while permitting invasive studies, thus allowing a thorough evaluation of strategies aimed at reducing the size of the reservoir (functional cure) or eliminating the reservoir altogether (sterilizing cure). Since there is no perfect animal model for cure research, multiple models have been tailored and tested to address specific quintessential questions of virus persistence and eradication. The development of new non-human primate and mouse models, along with a certain interest in the feline model, has the potential to fuel cure research. In this review, we highlight the major animal models currently utilized for cure research and the contributions of each model to this goal. PMID:26858716

Impact of Different Policies on Unhealthy Dietary Behaviors in an Urban Adult Population: An Agent-Based Simulation Model

PubMed Central

Giabbanelli, Philippe J.; Arah, Onyebuchi A.; Zimmerman, Frederick J.

2014-01-01

Objectives. Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. Methods. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model. Simulations were performed to contrast the potential effects of various policies on the evolution of dietary decisions. Results. Our model showed that a 20% increase in taxes on fast foods would lower the probability of fast-food consumption by 3 percentage points, whereas improving the visibility of positive social norms by 10%, either through community-based or mass-media campaigns, could improve the consumption of fruits and vegetables by 7 percentage points and lower fast-food consumption by 6 percentage points. Zoning policies had no significant impact. Conclusions. Interventions emphasizing healthy eating norms may be more effective than directly targeting food prices or regulating local food outlets. Agent-based modeling may be a useful tool for testing the population-level effects of various policies within complex systems. PMID:24832414

Mandibular canine: A tool for sex identification in forensic odontology.

PubMed

Kumawat, Ramniwas M; Dindgire, Sarika L; Gadhari, Mangesh; Khobragade, Pratima G; Kadoo, Priyanka S; Yadav, Pradeep

2017-01-01

The aim of this study was to investigate the accuracy of mandibular canine index (MCI) and mandibular mesiodistal odontometrics in sex identification in the age group of 17-25 years in central Indian population. The study sample comprised total 300 individuals (150 males and 150 females) of an age group ranging from 17 to 25 years of central Indian population. The maximum mesiodistal diameter of mandibular canines, the linear distance between the tips of mandibular canines, was measured using digital vernier caliper on the study models. Overall sex could be predicted accurately in 79.66% (81.33% males and 78% females) of the population by MCI. Whereas, considering the mandibular canine width for sex identification, the overall accuracy was 75% for the right mandibular canine and 73% for the left mandibular canine observed. Sexual dimorphism of canine is population specific, and among the Indian population, MCI and mesiodistal dimension of mandibular canine can aid in sex determination.

Ensuring successful introduction of Wolbachia in natural populations of Aedes aegypti by means of feedback control.

PubMed

Bliman, Pierre-Alexandre; Aronna, M Soledad; Coelho, Flávio C; da Silva, Moacyr A H B

2018-04-01

The control of the spread of dengue fever by introduction of the intracellular parasitic bacterium Wolbachia in populations of the vector Aedes aegypti, is presently one of the most promising tools for eliminating dengue, in the absence of an efficient vaccine. The success of this operation requires locally careful planning to determine the adequate number of individuals carrying the Wolbachia parasite that need to be introduced into the natural population. The introduced mosquitoes are expected to eventually replace the Wolbachia-free population and guarantee permanent protection against the transmission of dengue to human. In this study, we propose and analyze a model describing the fundamental aspects of the competition between mosquitoes carrying Wolbachia and mosquitoes free of the parasite. We then use feedback control techniques to devise an introduction protocol that is proved to guarantee that the population converges to a stable equilibrium where the totality of mosquitoes carry Wolbachia.

From cultural traditions to cumulative culture: parameterizing the differences between human and nonhuman culture.

PubMed

Kempe, Marius; Lycett, Stephen J; Mesoudi, Alex

2014-10-21

Diverse species exhibit cultural traditions, i.e. population-specific profiles of socially learned traits, from songbird dialects to primate tool-use behaviours. However, only humans appear to possess cumulative culture, in which cultural traits increase in complexity over successive generations. Theoretically, it is currently unclear what factors give rise to these phenomena, and consequently why cultural traditions are found in several species but cumulative culture in only one. Here, we address this by constructing and analysing cultural evolutionary models of both phenomena that replicate empirically attestable levels of cultural variation and complexity in chimpanzees and humans. In our model of cultural traditions (Model 1), we find that realistic cultural variation between populations can be maintained even when individuals in different populations invent the same traits and migration between populations is frequent, and under a range of levels of social learning accuracy. This lends support to claims that putative cultural traditions are indeed cultural (rather than genetic) in origin, and suggests that cultural traditions should be widespread in species capable of social learning. Our model of cumulative culture (Model 2) indicates that both the accuracy of social learning and the number of cultural demonstrators interact to determine the complexity of a trait that can be maintained in a population. Combining these models (Model 3) creates two qualitatively distinct regimes in which there are either a few, simple traits, or many, complex traits. We suggest that these regimes correspond to nonhuman and human cultures, respectively. The rarity of cumulative culture in nature may result from this interaction between social learning accuracy and number of demonstrators. Copyright © 2014 Elsevier Ltd. All rights reserved.

Comparison of tobacco control scenarios: quantifying estimates of long-term health impact using the DYNAMO-HIA modeling tool.

PubMed

Kulik, Margarete C; Nusselder, Wilma J; Boshuizen, Hendriek C; Lhachimi, Stefan K; Fernández, Esteve; Baili, Paolo; Bennett, Kathleen; Mackenbach, Johan P; Smit, H A

2012-01-01

There are several types of tobacco control interventions/policies which can change future smoking exposure. The most basic intervention types are 1) smoking cessation interventions 2) preventing smoking initiation and 3) implementation of a nationwide policy affecting quitters and starters simultaneously. The possibility for dynamic quantification of such different interventions is key for comparing the timing and size of their effects. We developed a software tool, DYNAMO-HIA, which allows for a quantitative comparison of the health impact of different policy scenarios. We illustrate the outcomes of the tool for the three typical types of tobacco control interventions if these were applied in the Netherlands. The tool was used to model the effects of different types of smoking interventions on future smoking prevalence and on health outcomes, comparing these three scenarios with the business-as-usual scenario. The necessary data input was obtained from the DYNAMO-HIA database which was assembled as part of this project. All smoking interventions will be effective in the long run. The population-wide strategy will be most effective in both the short and long term. The smoking cessation scenario will be second-most effective in the short run, though in the long run the smoking initiation scenario will become almost as effective. Interventions aimed at preventing the initiation of smoking need a long time horizon to become manifest in terms of health effects. The outcomes strongly depend on the groups targeted by the intervention. We calculated how much more effective the population-wide strategy is, in both the short and long term, compared to quit smoking interventions and measures aimed at preventing the initiation of smoking. By allowing a great variety of user-specified choices, the DYNAMO-HIA tool is a powerful instrument by which the consequences of different tobacco control policies and interventions can be assessed.

Comparison of Tobacco Control Scenarios: Quantifying Estimates of Long-Term Health Impact Using the DYNAMO-HIA Modeling Tool

PubMed Central

Kulik, Margarete C.; Nusselder, Wilma J.; Boshuizen, Hendriek C.; Lhachimi, Stefan K.; Fernández, Esteve; Baili, Paolo; Bennett, Kathleen; Mackenbach, Johan P.; Smit, H. A.

2012-01-01

Background There are several types of tobacco control interventions/policies which can change future smoking exposure. The most basic intervention types are 1) smoking cessation interventions 2) preventing smoking initiation and 3) implementation of a nationwide policy affecting quitters and starters simultaneously. The possibility for dynamic quantification of such different interventions is key for comparing the timing and size of their effects. Methods and Results We developed a software tool, DYNAMO-HIA, which allows for a quantitative comparison of the health impact of different policy scenarios. We illustrate the outcomes of the tool for the three typical types of tobacco control interventions if these were applied in the Netherlands. The tool was used to model the effects of different types of smoking interventions on future smoking prevalence and on health outcomes, comparing these three scenarios with the business-as-usual scenario. The necessary data input was obtained from the DYNAMO-HIA database which was assembled as part of this project. All smoking interventions will be effective in the long run. The population-wide strategy will be most effective in both the short and long term. The smoking cessation scenario will be second-most effective in the short run, though in the long run the smoking initiation scenario will become almost as effective. Interventions aimed at preventing the initiation of smoking need a long time horizon to become manifest in terms of health effects. The outcomes strongly depend on the groups targeted by the intervention. Conclusion We calculated how much more effective the population-wide strategy is, in both the short and long term, compared to quit smoking interventions and measures aimed at preventing the initiation of smoking. By allowing a great variety of user-specified choices, the DYNAMO-HIA tool is a powerful instrument by which the consequences of different tobacco control policies and interventions can be assessed. PMID:22384230

Entry one: striving for best practice in professional assessment.

PubMed

English, Justin M; Mykyta, Lu

2002-01-01

The aim of this study was to develop a best practice model of professional assessment to ensure efficient and effective delivery of home-based services to frail and disabled elders. In 2000, an innovative model of professional assessment was introduced by one of Australia's largest providers of home-based care in order to reduce multiple assessments and to reduce the utilisation of assessment as a gatekeeping tool for limiting access to services. Data was analysed from a random sample of 1500 clients drawn from a population of 5000 as well as through the use of a survey tool administered to the Organisation's assessment staff and other key stakeholders. Results revealed that, contrary to popular belief, carer advocacy plays a significant role in the professional assessment process to the point that clients with carers received significantly more services and service time that clients without such support. However, if not monitored, assessment can also be used as a gate-keeping tool as opposed to one that can provide significant benefits to the consumers through comprehensive need articulation. We argue that the "professional" approach does not preclude empowerment and that assessment should not be used as a gate-keeping tool.

Models of Eucalypt phenology predict bat population flux.

PubMed

Giles, John R; Plowright, Raina K; Eby, Peggy; Peel, Alison J; McCallum, Hamish

2016-10-01

Fruit bats (Pteropodidae) have received increased attention after the recent emergence of notable viral pathogens of bat origin. Their vagility hinders data collection on abundance and distribution, which constrains modeling efforts and our understanding of bat ecology, viral dynamics, and spillover. We addressed this knowledge gap with models and data on the occurrence and abundance of nectarivorous fruit bat populations at 3 day roosts in southeast Queensland. We used environmental drivers of nectar production as predictors and explored relationships between bat abundance and virus spillover. Specifically, we developed several novel modeling tools motivated by complexities of fruit bat foraging ecology, including: (1) a dataset of spatial variables comprising Eucalypt-focused vegetation indices, cumulative precipitation, and temperature anomaly; (2) an algorithm that associated bat population response with spatial covariates in a spatially and temporally relevant way given our current understanding of bat foraging behavior; and (3) a thorough statistical learning approach to finding optimal covariate combinations. We identified covariates that classify fruit bat occupancy at each of our three study roosts with 86-93% accuracy. Negative binomial models explained 43-53% of the variation in observed abundance across roosts. Our models suggest that spatiotemporal heterogeneity in Eucalypt-based food resources could drive at least 50% of bat population behavior at the landscape scale. We found that 13 spillover events were observed within the foraging range of our study roosts, and they occurred during times when models predicted low population abundance. Our results suggest that, in southeast Queensland, spillover may not be driven by large aggregations of fruit bats attracted by nectar-based resources, but rather by behavior of smaller resident subpopulations. Our models and data integrated remote sensing and statistical learning to make inferences on bat ecology and disease dynamics. This work provides a foundation for further studies on landscape-scale population movement and spatiotemporal disease dynamics.

Comparing deep learning models for population screening using chest radiography

NASA Astrophysics Data System (ADS)

Sivaramakrishnan, R.; Antani, Sameer; Candemir, Sema; Xue, Zhiyun; Abuya, Joseph; Kohli, Marc; Alderson, Philip; Thoma, George

2018-02-01

According to the World Health Organization (WHO), tuberculosis (TB) remains the most deadly infectious disease in the world. In a 2015 global annual TB report, 1.5 million TB related deaths were reported. The conditions worsened in 2016 with 1.7 million reported deaths and more than 10 million people infected with the disease. Analysis of frontal chest X-rays (CXR) is one of the most popular methods for initial TB screening, however, the method is impacted by the lack of experts for screening chest radiographs. Computer-aided diagnosis (CADx) tools have gained significance because they reduce the human burden in screening and diagnosis, particularly in countries that lack substantial radiology services. State-of-the-art CADx software typically is based on machine learning (ML) approaches that use hand-engineered features, demanding expertise in analyzing the input variances and accounting for the changes in size, background, angle, and position of the region of interest (ROI) on the underlying medical imagery. More automatic Deep Learning (DL) tools have demonstrated promising results in a wide range of ML applications. Convolutional Neural Networks (CNN), a class of DL models, have gained research prominence in image classification, detection, and localization tasks because they are highly scalable and deliver superior results with end-to-end feature extraction and classification. In this study, we evaluated the performance of CNN based DL models for population screening using frontal CXRs. The results demonstrate that pre-trained CNNs are a promising feature extracting tool for medical imagery including the automated diagnosis of TB from chest radiographs but emphasize the importance of large data sets for the most accurate classification.

The accuracy of climate models' simulated season lengths and the effectiveness of grid scale correction factors

DOE PAGES

Winterhalter, Wade E.

2011-09-01

Global climate change is expected to impact biological populations through a variety of mechanisms including increases in the length of their growing season. Climate models are useful tools for predicting how season length might change in the future. However, the accuracy of these models tends to be rather low at regional geographic scales. Here, I determined the ability of several atmosphere and ocean general circulating models (AOGCMs) to accurately simulate historical season lengths for a temperate ectotherm across the continental United States. I also evaluated the effectiveness of regional-scale correction factors to improve the accuracy of these models. I foundmore » that both the accuracy of simulated season lengths and the effectiveness of the correction factors to improve the model's accuracy varied geographically and across models. These results suggest that regional specific correction factors do not always adequately remove potential discrepancies between simulated and historically observed environmental parameters. As such, an explicit evaluation of the correction factors' effectiveness should be included in future studies of global climate change's impact on biological populations.« less

Detecting and modelling delayed density-dependence in abundance time series of a small mammal (Didelphis aurita)

NASA Astrophysics Data System (ADS)

Brigatti, E.; Vieira, M. V.; Kajin, M.; Almeida, P. J. A. L.; de Menezes, M. A.; Cerqueira, R.

2016-02-01

We study the population size time series of a Neotropical small mammal with the intent of detecting and modelling population regulation processes generated by density-dependent factors and their possible delayed effects. The application of analysis tools based on principles of statistical generality are nowadays a common practice for describing these phenomena, but, in general, they are more capable of generating clear diagnosis rather than granting valuable modelling. For this reason, in our approach, we detect the principal temporal structures on the bases of different correlation measures, and from these results we build an ad-hoc minimalist autoregressive model that incorporates the main drivers of the dynamics. Surprisingly our model is capable of reproducing very well the time patterns of the empirical series and, for the first time, clearly outlines the importance of the time of attaining sexual maturity as a central temporal scale for the dynamics of this species. In fact, an important advantage of this analysis scheme is that all the model parameters are directly biologically interpretable and potentially measurable, allowing a consistency check between model outputs and independent measurements.

Computational Modeling of Single Neuron Extracellular Electric Potentials and Network Local Field Potentials using LFPsim.

PubMed

Parasuram, Harilal; Nair, Bipin; D'Angelo, Egidio; Hines, Michael; Naldi, Giovanni; Diwakar, Shyam

2016-01-01

Local Field Potentials (LFPs) are population signals generated by complex spatiotemporal interaction of current sources and dipoles. Mathematical computations of LFPs allow the study of circuit functions and dysfunctions via simulations. This paper introduces LFPsim, a NEURON-based tool for computing population LFP activity and single neuron extracellular potentials. LFPsim was developed to be used on existing cable compartmental neuron and network models. Point source, line source, and RC based filter approximations can be used to compute extracellular activity. As a demonstration of efficient implementation, we showcase LFPs from mathematical models of electrotonically compact cerebellum granule neurons and morphologically complex neurons of the neocortical column. LFPsim reproduced neocortical LFP at 8, 32, and 56 Hz via current injection, in vitro post-synaptic N2a, N2b waves and in vivo T-C waves in cerebellum granular layer. LFPsim also includes a simulation of multi-electrode array of LFPs in network populations to aid computational inference between biophysical activity in neural networks and corresponding multi-unit activity resulting in extracellular and evoked LFP signals.

Generalized Linear Models of Home Activity for Automatic Detection of Mild Cognitive Impairment in Older Adults*

PubMed Central

Akl, Ahmad; Snoek, Jasper; Mihailidis, Alex

2015-01-01

With a globally aging population, the burden of care of cognitively impaired older adults is becoming increasingly concerning. Instances of Alzheimer’s disease and other forms of dementia are becoming ever more frequent. Earlier detection of cognitive impairment offers significant benefits, but remains difficult to do in practice. In this paper, we develop statistical models of the behavior of older adults within their homes using sensor data in order to detect the early onset of cognitive decline. Specifically, we use inhomogenous Poisson processes to model the presence of subjects within different rooms throughout the day in the home using unobtrusive sensing technologies. We compare the distributions learned from cognitively intact and impaired subjects using information theoretic tools and observe statistical differences between the two populations which we believe can be used to help detect the onset of cognitive decline. PMID:25570050

Generalized Linear Models of home activity for automatic detection of mild cognitive impairment in older adults.

PubMed

Akl, Ahmad; Snoek, Jasper; Mihailidis, Alex

2014-01-01

With a globally aging population, the burden of care of cognitively impaired older adults is becoming increasingly concerning. Instances of Alzheimer's disease and other forms of dementia are becoming ever more frequent. Earlier detection of cognitive impairment offers significant benefits, but remains difficult to do in practice. In this paper, we develop statistical models of the behavior of older adults within their homes using sensor data in order to detect the early onset of cognitive decline. Specifically, we use inhomogenous Poisson processes to model the presence of subjects within different rooms throughout the day in the home using unobtrusive sensing technologies. We compare the distributions learned from cognitively intact and impaired subjects using information theoretic tools and observe statistical differences between the two populations which we believe can be used to help detect the onset of cognitive decline.

Relatedness in spatially structured populations with empty sites: An approach based on spatial moment equations.

PubMed

Lion, Sébastien

2009-09-07

Taking into account the interplay between spatial ecological dynamics and selection is a major challenge in evolutionary ecology. Although inclusive fitness theory has proven to be a very useful tool to unravel the interactions between spatial genetic structuring and selection, applications of the theory usually rely on simplifying demographic assumptions. In this paper, I attempt to bridge the gap between spatial demographic models and kin selection models by providing a method to compute approximations for relatedness coefficients in a spatial model with empty sites. Using spatial moment equations, I provide an approximation of nearest-neighbour relatedness on random regular networks, and show that this approximation performs much better than the ordinary pair approximation. I discuss the connection between the relatedness coefficients I define and those used in population genetics, and sketch some potential extensions of the theory.

The potential of statistical shape modelling for geometric morphometric analysis of human teeth in archaeological research

PubMed Central

Fernee, Christianne; Browne, Martin; Zakrzewski, Sonia

2017-01-01

This paper introduces statistical shape modelling (SSM) for use in osteoarchaeology research. SSM is a full field, multi-material analytical technique, and is presented as a supplementary geometric morphometric (GM) tool. Lower mandibular canines from two archaeological populations and one modern population were sampled, digitised using micro-CT, aligned, registered to a baseline and statistically modelled using principal component analysis (PCA). Sample material properties were incorporated as a binary enamel/dentin parameter. Results were assessed qualitatively and quantitatively using anatomical landmarks. Finally, the technique’s application was demonstrated for inter-sample comparison through analysis of the principal component (PC) weights. It was found that SSM could provide high detail qualitative and quantitative insight with respect to archaeological inter- and intra-sample variability. This technique has value for archaeological, biomechanical and forensic applications including identification, finite element analysis (FEA) and reconstruction from partial datasets. PMID:29216199

Modelling proteins’ hidden conformations to predict antibiotic resistance

PubMed Central

Hart, Kathryn M.; Ho, Chris M. W.; Dutta, Supratik; Gross, Michael L.; Bowman, Gregory R.

2016-01-01

TEM β-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models to identify hidden conformations and explore their role in determining TEM’s specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometric footprinting and confirm our models’ prediction that increased cefotaxime activity correlates with reduced Ω-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design. PMID:27708258

Modeling mechanical interactions in growing populations of rod-shaped bacteria

NASA Astrophysics Data System (ADS)

Winkle, James J.; Igoshin, Oleg A.; Bennett, Matthew R.; Josić, Krešimir; Ott, William

2017-10-01

Advances in synthetic biology allow us to engineer bacterial collectives with pre-specified characteristics. However, the behavior of these collectives is difficult to understand, as cellular growth and division as well as extra-cellular fluid flow lead to complex, changing arrangements of cells within the population. To rationally engineer and control the behavior of cell collectives we need theoretical and computational tools to understand their emergent spatiotemporal dynamics. Here, we present an agent-based model that allows growing cells to detect and respond to mechanical interactions. Crucially, our model couples the dynamics of cell growth to the cell’s environment: Mechanical constraints can affect cellular growth rate and a cell may alter its behavior in response to these constraints. This coupling links the mechanical forces that influence cell growth and emergent behaviors in cell assemblies. We illustrate our approach by showing how mechanical interactions can impact the dynamics of bacterial collectives growing in microfluidic traps.

Efficient simulation and likelihood methods for non-neutral multi-allele models.

PubMed

Joyce, Paul; Genz, Alan; Buzbas, Erkan Ozge

2012-06-01

Throughout the 1980s, Simon Tavaré made numerous significant contributions to population genetics theory. As genetic data, in particular DNA sequence, became more readily available, a need to connect population-genetic models to data became the central issue. The seminal work of Griffiths and Tavaré (1994a , 1994b , 1994c) was among the first to develop a likelihood method to estimate the population-genetic parameters using full DNA sequences. Now, we are in the genomics era where methods need to scale-up to handle massive data sets, and Tavaré has led the way to new approaches. However, performing statistical inference under non-neutral models has proved elusive. In tribute to Simon Tavaré, we present an article in spirit of his work that provides a computationally tractable method for simulating and analyzing data under a class of non-neutral population-genetic models. Computational methods for approximating likelihood functions and generating samples under a class of allele-frequency based non-neutral parent-independent mutation models were proposed by Donnelly, Nordborg, and Joyce (DNJ) (Donnelly et al., 2001). DNJ (2001) simulated samples of allele frequencies from non-neutral models using neutral models as auxiliary distribution in a rejection algorithm. However, patterns of allele frequencies produced by neutral models are dissimilar to patterns of allele frequencies produced by non-neutral models, making the rejection method inefficient. For example, in some cases the methods in DNJ (2001) require 10(9) rejections before a sample from the non-neutral model is accepted. Our method simulates samples directly from the distribution of non-neutral models, making simulation methods a practical tool to study the behavior of the likelihood and to perform inference on the strength of selection.

Dietary assessment in minority ethnic groups: a systematic review of instruments for portion-size estimation in the United Kingdom

PubMed Central

Almiron-Roig, Eva; Aitken, Amanda; Galloway, Catherine

2017-01-01

Context: Dietary assessment in minority ethnic groups is critical for surveillance programs and for implementing effective interventions. A major challenge is the accurate estimation of portion sizes for traditional foods and dishes. Objective: The aim of this systematic review was to assess records published up to 2014 describing a portion-size estimation element (PSEE) applicable to the dietary assessment of UK-residing ethnic minorities. Data sources, selection, and extraction: Electronic databases, internet sites, and theses repositories were searched, generating 5683 titles, from which 57 eligible full-text records were reviewed. Data analysis: Forty-two publications about minority ethnic groups (n = 20) or autochthonous populations (n = 22) were included. The most common PSEEs (47%) were combination tools (eg, food models and portion-size lists), followed by portion-size lists in questionnaires/guides (19%) and image-based and volumetric tools (17% each). Only 17% of PSEEs had been validated against weighed data. Conclusions: When developing ethnic-specific dietary assessment tools, it is important to consider customary portion sizes by sex and age, traditional household utensil usage, and population literacy levels. Combining multiple PSEEs may increase accuracy, but such methods require validation. PMID:28340101

Irruptive dynamics of introduced caribou on Adak Island, Alaska: an evaluation of Riney-Caughley model predictions

USGS Publications Warehouse

Ricca, Mark A.; Van Vuren, Dirk H.; Weckerly, Floyd W.; Williams, Jeffrey C.; Miles, A. Keith

2014-01-01

Large mammalian herbivores introduced to islands without predators are predicted to undergo irruptive population and spatial dynamics, but only a few well-documented case studies support this paradigm. We used the Riney-Caughley model as a framework to test predictions of irruptive population growth and spatial expansion of caribou (Rangifer tarandus granti) introduced to Adak Island in the Aleutian archipelago of Alaska in 1958 and 1959. We utilized a time series of spatially explicit counts conducted on this population intermittently over a 54-year period. Population size increased from 23 released animals to approximately 2900 animals in 2012. Population dynamics were characterized by two distinct periods of irruptive growth separated by a long time period of relative stability, and the catalyst for the initial irruption was more likely related to annual variation in hunting pressure than weather conditions. An unexpected pattern resembling logistic population growth occurred between the peak of the second irruption in 2005 and the next survey conducted seven years later in 2012. Model simulations indicated that an increase in reported harvest alone could not explain the deceleration in population growth, yet high levels of unreported harvest combined with increasing density-dependent feedbacks on fecundity and survival were the most plausible explanation for the observed population trend. No studies of introduced island Rangifer have measured a time series of spatial use to the extent described in this study. Spatial use patterns during the post-calving season strongly supported Riney-Caughley model predictions, whereby high-density core areas expanded outwardly as population size increased. During the calving season, caribou displayed marked site fidelity across the full range of population densities despite availability of other suitable habitats for calving. Finally, dispersal and reproduction on neighboring Kagalaska Island represented a new dispersal front for irruptive dynamics and a new challenge for resource managers. The future demography of caribou on both islands is far from certain, yet sustained and significant hunting pressure should be a vital management tool.

The smoke-fireplume model : tool for eventual application to prescribed burns and wildland fires.

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

Brown, D. F.; Dunn, W. E.; Lazaro, M. A.

Land managers are increasingly implementing strategies that employ the use of fire in prescribed burns to sustain ecosystems and plan to sustain the rate of increase in its use over the next five years. In planning and executing expanded use of fire in wildland treatment it is important to estimate the human health and safety consequences, property damage, and the extent of visibility degradation from the resulting conflagration-pyrolysis gases, soot and smoke generated during flaming, smoldering and/or glowing fires. Traditional approaches have often employed the analysis of weather observations and forecasts to determine whether a prescribed burn will affect populations,more » property, or protected Class I areas. However, the complexity of the problem lends itself to advanced PC-based models that are simple to use for both calculating the emissions from the burning of wildland fuels and the downwind dispersion of smoke and other products of pyrolysis, distillation, and/or fuels combustion. These models will need to address the effects of residual smoldering combustion, including plume dynamics and optical effects. In this paper, we discuss a suite of tools that can be applied for analyzing dispersion. These tools include the dispersion models FIREPLUME and SMOKE, together with the meteorological preprocessor SEBMET.« less

Tissue tropisms, infection kinetics, histologic lesions, and antibody response of the MR766 strain of Zika virus in a murine model.

PubMed

Kawiecki, Anna B; Mayton, E Handly; Dutuze, M Fausta; Goupil, Brad A; Langohr, Ingeborg M; Del Piero, Fabio; Christofferson, Rebecca C

2017-04-18

The appearance of severe Zika virus (ZIKV) disease in the most recent outbreak has prompted researchers to respond through the development of tools to quickly characterize transmission and pathology. We describe here another such tool, a mouse model of ZIKV infection and pathogenesis using the MR766 strain of virus that adds to the growing body of knowledge regarding ZIKV kinetics in small animal models. We infected mice with the MR766 strain of ZIKV to determine infection kinetics via serum viremia. We further evaluated infection-induced lesions via histopathology and visualized viral antigen via immunohistochemical labeling. We also investigated the antibody response of recovered animals to both the MR766 and a strain from the current outbreak (PRVABC59). We demonstrate that the IRF3/7 DKO mouse is a susceptible, mostly non-lethal model well suited for the study of infection kinetics, pathological progression, and antibody response. Infected mice presented lesions in tissues that have been associated with ZIKV infection in the human population, such as the eyes, male gonads, and central nervous system. In addition, we demonstrate that infection with the MR766 strain produces cross-neutralizing antibodies to the PRVABC59 strain of the Asian lineage. This model provides an additional tool for future studies into the transmission routes of ZIKV, as well as for the development of antivirals and other therapeutics, and should be included in the growing list of available tools for investigations of ZIKV infection and pathogenesis.

Leveraging Hierarchical Population Structure in Discrete Association Studies

PubMed Central

Carlson, Jonathan; Kadie, Carl; Mallal, Simon; Heckerman, David

2007-01-01

Population structure can confound the identification of correlations in biological data. Such confounding has been recognized in multiple biological disciplines, resulting in a disparate collection of proposed solutions. We examine several methods that correct for confounding on discrete data with hierarchical population structure and identify two distinct confounding processes, which we call coevolution and conditional influence. We describe these processes in terms of generative models and show that these generative models can be used to correct for the confounding effects. Finally, we apply the models to three applications: identification of escape mutations in HIV-1 in response to specific HLA-mediated immune pressure, prediction of coevolving residues in an HIV-1 peptide, and a search for genotypes that are associated with bacterial resistance traits in Arabidopsis thaliana. We show that coevolution is a better description of confounding in some applications and conditional influence is better in others. That is, we show that no single method is best for addressing all forms of confounding. Analysis tools based on these models are available on the internet as both web based applications and downloadable source code at http://atom.research.microsoft.com/bio/phylod.aspx. PMID:17611623

The construction of a decision tool to analyse local demand and local supply for GP care using a synthetic estimation model

PubMed Central

2013-01-01

Background This study addresses the growing academic and policy interest in the appropriate provision of local healthcare services to the healthcare needs of local populations to increase health status and decrease healthcare costs. However, for most local areas information on the demand for primary care and supply is missing. The research goal is to examine the construction of a decision tool which enables healthcare planners to analyse local supply and demand in order to arrive at a better match. Methods National sample-based medical record data of general practitioners (GPs) were used to predict the local demand for GP care based on local populations using a synthetic estimation technique. Next, the surplus or deficit in local GP supply were calculated using the national GP registry. Subsequently, a dynamic internet tool was built to present demand, supply and the confrontation between supply and demand regarding GP care for local areas and their surroundings in the Netherlands. Results Regression analysis showed a significant relationship between sociodemographic predictors of postcode areas and GP consultation time (F [14, 269,467] = 2,852.24; P <0.001). The statistical model could estimate GP consultation time for every postcode area with >1,000 inhabitants in the Netherlands covering 97% of the total population. Confronting these estimated demand figures with the actual GP supply resulted in the average GP workload and the number of full-time equivalent (FTE) GP too much/too few for local areas to cover the demand for GP care. An estimated shortage of one FTE GP or more was prevalent in about 19% of the postcode areas with >1,000 inhabitants if the surrounding postcode areas were taken into consideration. Underserved areas were mainly found in rural regions. Conclusions The constructed decision tool is freely accessible on the Internet and can be used as a starting point in the discussion on primary care service provision in local communities and it can make a considerable contribution to a primary care system which provides care when and where people need it. PMID:24161015

Predictive Risk Modelling to Prevent Child Maltreatment and Other Adverse Outcomes for Service Users: Inside the ‘Black Box’ of Machine Learning

PubMed Central

Gillingham, Philip

2016-01-01

Recent developments in digital technology have facilitated the recording and retrieval of administrative data from multiple sources about children and their families. Combined with new ways to mine such data using algorithms which can ‘learn’, it has been claimed that it is possible to develop tools that can predict which individual children within a population are most likely to be maltreated. The proposed benefit is that interventions can then be targeted to the most vulnerable children and their families to prevent maltreatment from occurring. As expertise in predictive modelling increases, the approach may also be applied in other areas of social work to predict and prevent adverse outcomes for vulnerable service users. In this article, a glimpse inside the ‘black box’ of predictive tools is provided to demonstrate how their development for use in social work may not be straightforward, given the nature of the data recorded about service users and service activity. The development of predictive risk modelling (PRM) in New Zealand is focused on as an example as it may be the first such tool to be applied as part of ongoing reforms to child protection services. PMID:27559213

Predictive Risk Modelling to Prevent Child Maltreatment and Other Adverse Outcomes for Service Users: Inside the 'Black Box' of Machine Learning.

PubMed

Gillingham, Philip

2016-06-01

Recent developments in digital technology have facilitated the recording and retrieval of administrative data from multiple sources about children and their families. Combined with new ways to mine such data using algorithms which can 'learn', it has been claimed that it is possible to develop tools that can predict which individual children within a population are most likely to be maltreated. The proposed benefit is that interventions can then be targeted to the most vulnerable children and their families to prevent maltreatment from occurring. As expertise in predictive modelling increases, the approach may also be applied in other areas of social work to predict and prevent adverse outcomes for vulnerable service users. In this article, a glimpse inside the 'black box' of predictive tools is provided to demonstrate how their development for use in social work may not be straightforward, given the nature of the data recorded about service users and service activity. The development of predictive risk modelling (PRM) in New Zealand is focused on as an example as it may be the first such tool to be applied as part of ongoing reforms to child protection services.

Consensus modeling to develop the farmers' market readiness assessment and decision instrument.

PubMed

Lee, Eunlye; Dalton, Jarrod; Ngendahimana, David; Bebo, Pat; Davis, Ashley; Remley, Daniel; Smathers, Carol; Freedman, Darcy A

2017-09-01

Nutrition-related policy, system, and environmental (PSE) interventions such as farmers' markets have been recommended as effective strategies for promoting healthy diet for chronic disease prevention. Tools are needed to assess community readiness and capacity factors influencing successful farmers' market implementation among diverse practitioners in different community contexts. We describe a multiphase consensus modeling approach used to develop a diagnostic tool for assessing readiness and capacity to implement farmers' market interventions among public health and community nutrition practitioners working with low-income populations in diverse contexts. Modeling methods included the following: phase 1, qualitative study with community stakeholders to explore facilitators and barriers influencing successful implementation of farmers' market interventions in low-income communities; phase 2, development of indicators based on operationalization of qualitative findings; phase 3, assessment of relevance and importance of indicators and themes through consensus conference with expert panel; phase 4, refinement of indicators based on consensus conference; and phase 5, pilot test of the assessment tool. Findings illuminate a range of implementation factors influencing farmers' market PSE interventions and offer guidance for tailoring intervention delivery based on levels of community, practitioner, and organizational readiness and capacity.

From primary care to public health: using Problem-based Learning and the ecological model to teach public health to first year medical students.

PubMed

Hoover, Cora R; Wong, Candice C; Azzam, Amin

2012-06-01

We investigated whether a public health-oriented Problem-Based Learning case presented to first-year medical students conveyed 12 "Population Health Competencies for Medical Students," as recommended by the Association of American Medical Colleges and the Regional Medicine-Public Health Education Centers. A public health-oriented Problem-Based Learning case guided by the ecological model paradigm was developed and implemented among two groups of 8 students at the University of California, Berkeley-UCSF Joint Medical Program, in the Fall of 2010. Using directed content analysis, student-generated written reports were coded for the presence of the 12 population health content areas. Students generated a total of 29 reports, of which 20 (69%) contained information relevant to at least one of the 12 population health competencies. Each of the 12 content areas was addressed by at least one report. As physicians-in-training prepare to confront the challenges of integrating prevention and population health with clinical practice, Problem-Based Learning is a promising tool to enhance medical students' engagement with public health.

Measuring pain in patients undergoing hemodialysis: a review of pain assessment tools

PubMed Central

Upadhyay, Chandani; Cameron, Karen; Murphy, Laura; Battistella, Marisa

2014-01-01

Background Patients undergoing hemodialysis frequently report pain with multifactorial causes, not limited to that experienced directly from hemodialysis treatment. Their pain may be nociceptive, neuropathic, somatic or visceral in nature. Despite this, pain in this population remains under-recognized and under-treated. Although several tools have been used to measure pain in patients undergoing hemodialysis as reported in the literature, none of them have been validated specifically in this population. The objective for this review was to compare and contrast these pain assessment tools and discuss their clinical utility in this patient population. Methods To identify pain assessment tools studied in patients undergoing hemodialysis, a literature search was performed in PubMed and Medline. An expert panel of dialysis and pain clinicians reviewed each tool. Each pain assessment tool was assessed on how it is administered and scored, its psychometric properties such as reliability, validity and responsiveness to change, and its clinical utility in a hemodialysis population. Brief Pain Inventory, McGill Pain Questionnaire, Pain Management Index, Edmonton Symptom Assessment System, Visual Analogue Scale and Faces Pain Scale were evaluated and compared. Results This assessment will help clinicians practicing in nephrology to determine which of these pain assessment tools is best suited for use in their individual clinical practice. PMID:25852910

Planning for smallpox outbreaks

NASA Astrophysics Data System (ADS)

Ferguson, Neil M.; Keeling, Matt J.; John Edmunds, W.; Gani, Raymond; Grenfell, Bryan T.; Anderson, Roy M.; Leach, Steve

2003-10-01

Mathematical models of viral transmission and control are important tools for assessing the threat posed by deliberate release of the smallpox virus and the best means of containing an outbreak. Models must balance biological realism against limitations of knowledge, and uncertainties need to be accurately communicated to policy-makers. Smallpox poses the particular challenge that key biological, social and spatial factors affecting disease spread in contemporary populations must be elucidated largely from historical studies undertaken before disease eradication in 1979. We review the use of models in smallpox planning within the broader epidemiological context set by recent outbreaks of both novel and re-emerging pathogens.

The Health Resources Allocation Model (HRAM) for the 21st century.

PubMed

Maire, Nicolas; Hegnauer, Michael; Nguyen, Dana; Godelmann, Lucas; Hoffmann, Axel; de Savigny, Don; Tanner, Marcel

2012-05-01

The Health Resources Allocation Model (HRAM) is an eLearning tool for health cadres and scientists introducing basic concepts of sub-national, rational district-based health planning and systems thinking under resources constraint. HRAM allows the evaluation of resource allocation strategies in relation to key outcome measures such as coverage, equity of services achieved and number of deaths and disability-adjusted life years (DALYs) prevented. In addition, the model takes into account geographical and demographic characteristics and populations' health seeking behaviour. It can be adapted to different socio-ecological and health system settings.

Behavioral health and health care reform models: patient-centered medical home, health home, and accountable care organization.

PubMed

Bao, Yuhua; Casalino, Lawrence P; Pincus, Harold Alan

2013-01-01

Discussions of health care delivery and payment reforms have largely been silent about how behavioral health could be incorporated into reform initiatives. This paper draws attention to four patient populations defined by the severity of their behavioral health conditions and insurance status. It discusses the potentials and limitations of three prominent models promoted by the Affordable Care Act to serve populations with behavioral health conditions: the Patient-Centered Medical Home, the Health Home initiative within Medicaid, and the Accountable Care Organization. To incorporate behavioral health into health reform, policymakers and practitioners may consider embedding in the reform efforts explicit tools-accountability measures and payment designs-to improve access to and quality of care for patients with behavioral health needs.

Cold induced mortality of the Burmese Python: An explanation via stochastic analysis

NASA Astrophysics Data System (ADS)

Quansah, Emmanuel; Parshad, Rana D.; Mondal, Sumona

2017-02-01

The Burmese python (Python bivitatus) is an invasive species, wreaking havoc on indigenous species in the Florida everglades. Data suggests an exponential growth in their population from 1995 to 2009, with a sharp decline however in 2010-2012 (Dorcas et al., 2012). In Mazzotti et al. (2011) an explanation is provided, citing the unusually cold winter that year, as the primary reason for this decline. We provide a first mathematical model, in the form of a system of stochastic differential equations, that supports the explanation in Mazzotti et al. (2011), by accurately matching the field data presented in Dorcas et al. (2012). More generally, our model provides a tool to predict the population dynamics of rapidly growing alien species, in the advent of climate change.

Behavioral Health and Health Care Reform Models: Patient-Centered Medical Home, Health Home, and Accountable Care Organization

PubMed Central

Bao, Yuhua; Casalino, Lawrence P.; Pincus, Harold Alan

2012-01-01

Discussions of health care delivery and payment reforms have largely been silent about how behavioral health could be incorporated into reform initiatives. This paper draws attention to four patient populations defined by the severity of their behavioral health conditions and insurance status. It discusses the potentials and limitations of three prominent models promoted by the Affordable Care Act to serve populations with behavioral health conditions: the Patient Centered Medical Home, the Health Home initiative within Medicaid, and the Accountable Care Organization. To incorporate behavioral health into health reform, policymakers and practitioners may consider embedding in the reform efforts explicit tools – accountability measures and payment designs – to improve access to and quality of care for patients with behavioral health needs. PMID:23188486

Maximum entropy models as a tool for building precise neural controls.

PubMed

Savin, Cristina; Tkačik, Gašper

2017-10-01

Neural responses are highly structured, with population activity restricted to a small subset of the astronomical range of possible activity patterns. Characterizing these statistical regularities is important for understanding circuit computation, but challenging in practice. Here we review recent approaches based on the maximum entropy principle used for quantifying collective behavior in neural activity. We highlight recent models that capture population-level statistics of neural data, yielding insights into the organization of the neural code and its biological substrate. Furthermore, the MaxEnt framework provides a general recipe for constructing surrogate ensembles that preserve aspects of the data, but are otherwise maximally unstructured. This idea can be used to generate a hierarchy of controls against which rigorous statistical tests are possible. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of a risk assessment tool for projecting individualized probabilities of developing breast cancer for Chinese women.

PubMed

Wang, Yuan; Gao, Ying; Battsend, Munkhzul; Chen, Kexin; Lu, Wenli; Wang, Yaogang

2014-11-01

The optimal approach regarding breast cancer screening for Chinese women is unclear due to the relative low incidence rate. A risk assessment tool may be useful for selection of high-risk subsets of population for mammography screening in low-incidence and resource-limited developing country. The odd ratios for six main risk factors of breast cancer were pooled by review manager after a systematic research of literature. Health risk appraisal (HRA) model was developed to predict an individual's risk of developing breast cancer in the next 5 years from current age. The performance of this HRA model was assessed based on a first-round screening database. Estimated risk of breast cancer increased with age. Increases in the 5-year risk of developing breast cancer were found with the existence of any of included risk factors. When individuals who had risk above median risk (3.3‰) were selected from the validation database, the sensitivity is 60.0% and the specificity is 47.8%. The unweighted area under the curve (AUC) was 0.64 (95% CI = 0.50-0.78). The risk-prediction model reported in this article is based on a combination of risk factors and shows good overall predictive power, but it is still weak at predicting which particular women will develop the disease. It would be very helpful for the improvement of a current model if more population-based prospective follow-up studies were used for the validation.

Cognitive Foundry v. 3.0 (OSS)

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

Basilico, Justin; Dixon, Kevin; McClain, Jonathan

2009-11-18

The Cognitive Foundry is a unified collection of tools designed for research and applications that use cognitive modeling, machine learning, or pattern recognition. The software library contains design patterns, interface definitions, and default implementations of reusable software components and algorithms designed to support a wide variety of research and development needs. The library contains three main software packages: the Common package that contains basic utilities and linear algebraic methods, the Cognitive Framework package that contains tools to assist in implementing and analyzing theories of cognition, and the Machine Learning package that provides general algorithms and methods for populating Cognitive Frameworkmore » components from domain-relevant data.« less

A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit

NASA Technical Reports Server (NTRS)

Kim, K. Han; Young, Karen S.; Bernal, Yaritza; Boppana, Abhishektha; Vu, Linh Q.; Benson, Elizabeth A.; Jarvis, Sarah; Rajulu, Sudhakar L.

2016-01-01

Suboptimal suit fit is a known risk factor for crewmember shoulder injury. Suit fit assessment is however prohibitively time consuming and cannot be generalized across wide variations of body shapes and poses. In this work, we have developed a new design tool based on the statistical analysis of body shape scans. This tool is aimed at predicting the skin deformation and shape variations for any body size and shoulder pose for a target population. This new process, when incorporated with CAD software, will enable virtual suit fit assessments, predictively quantifying the contact volume, and clearance between the suit and body surface at reduced time and cost.

Effectiveness of an image-based sorter to select for kernel color within early segregating hard winter wheat (Triticum aestivum L.) populations

USDA-ARS?s Scientific Manuscript database

Effective mass selection tools are needed to enrich hard winter wheat breeding populations from red wheat × white wheat crosses while maintaining large population sizes in early breeding generations. Tools also are needed to select for white-seeded genotypes or to eliminate white-seeded genotypes wh...

DengueME: A Tool for the Modeling and Simulation of Dengue Spatiotemporal Dynamics †

PubMed Central

de Lima, Tiago França Melo; Lana, Raquel Martins; de Senna Carneiro, Tiago Garcia; Codeço, Cláudia Torres; Machado, Gabriel Souza; Ferreira, Lucas Saraiva; de Castro Medeiros, Líliam César; Davis Junior, Clodoveu Augusto

2016-01-01

The prevention and control of dengue are great public health challenges for many countries, particularly since 2015, as other arboviruses have been observed to interact significantly with dengue virus. Different approaches and methodologies have been proposed and discussed by the research community. An important tool widely used is modeling and simulation, which help us to understand epidemic dynamics and create scenarios to support planning and decision making processes. With this aim, we proposed and developed DengueME, a collaborative open source platform to simulate dengue disease and its vector’s dynamics. It supports compartmental and individual-based models, implemented over a GIS database, that represent Aedes aegypti population dynamics, human demography, human mobility, urban landscape and dengue transmission mediated by human and mosquito encounters. A user-friendly graphical interface was developed to facilitate model configuration and data input, and a library of models was developed to support teaching-learning activities. DengueME was applied in study cases and evaluated by specialists. Other improvements will be made in future work, to enhance its extensibility and usability. PMID:27649226

Tissue chips - innovative tools for drug development and disease modeling.

PubMed

Low, L A; Tagle, D A

2017-09-12

The high rate of failure during drug development is well-known, however recent advances in tissue engineering and microfabrication have contributed to the development of microphysiological systems (MPS), or 'organs-on-chips' that recapitulate the function of human organs. These 'tissue chips' could be utilized for drug screening and safety testing to potentially transform the early stages of the drug development process. They can also be used to model disease states, providing new tools for the understanding of disease mechanisms and pathologies, and assessing effectiveness of new therapies. In the future, they could be used to test new treatments and therapeutics in populations - via clinical trials-on-chips - and individuals, paving the way for precision medicine. Here we will discuss the wide-ranging and promising future of tissue chips, as well as challenges facing their development.

Camera traps and mark-resight models: The value of ancillary data for evaluating assumptions

USGS Publications Warehouse

Parsons, Arielle W.; Simons, Theodore R.; Pollock, Kenneth H.; Stoskopf, Michael K.; Stocking, Jessica J.; O'Connell, Allan F.

2015-01-01

Unbiased estimators of abundance and density are fundamental to the study of animal ecology and critical for making sound management decisions. Capture–recapture models are generally considered the most robust approach for estimating these parameters but rely on a number of assumptions that are often violated but rarely validated. Mark-resight models, a form of capture–recapture, are well suited for use with noninvasive sampling methods and allow for a number of assumptions to be relaxed. We used ancillary data from continuous video and radio telemetry to evaluate the assumptions of mark-resight models for abundance estimation on a barrier island raccoon (Procyon lotor) population using camera traps. Our island study site was geographically closed, allowing us to estimate real survival and in situ recruitment in addition to population size. We found several sources of bias due to heterogeneity of capture probabilities in our study, including camera placement, animal movement, island physiography, and animal behavior. Almost all sources of heterogeneity could be accounted for using the sophisticated mark-resight models developed by McClintock et al. (2009b) and this model generated estimates similar to a spatially explicit mark-resight model previously developed for this population during our study. Spatially explicit capture–recapture models have become an important tool in ecology and confer a number of advantages; however, non-spatial models that account for inherent individual heterogeneity may perform nearly as well, especially where immigration and emigration are limited. Non-spatial models are computationally less demanding, do not make implicit assumptions related to the isotropy of home ranges, and can provide insights with respect to the biological traits of the local population.

Simulated Seasonal Spatio-Temporal Patterns of Soil Moisture, Temperature, and Net Radiation in a Deciduous Forest

NASA Technical Reports Server (NTRS)

Ballard, Jerrell R., Jr.; Howington, Stacy E.; Cinnella, Pasquale; Smith, James A.

2011-01-01

The temperature and moisture regimes in a forest are key components in the forest ecosystem dynamics. Observations and studies indicate that the internal temperature distribution and moisture content of the tree influence not only growth and development, but onset and cessation of cambial activity [1], resistance to insect predation[2], and even affect the population dynamics of the insects [3]. Moreover, temperature directly affects the uptake and metabolism of population from the soil into the tree tissue [4]. Additional studies show that soil and atmospheric temperatures are significant parameters that limit the growth of trees and impose treeline elevation limitation [5]. Directional thermal infrared radiance effects have long been observed in natural backgrounds [6]. In earlier work, we illustrated the use of physically-based models to simulate directional effects in thermal imaging [7-8]. In this paper, we illustrated the use of physically-based models to simulate directional effects in thermal, and net radiation in a adeciduous forest using our recently developed three-dimensional, macro-scale computational tool that simulates the heat and mass transfer interaction in a soil-root-stem systems (SRSS). The SRSS model includes the coupling of existing heat and mass transport tools to stimulate the diurnal internal and external temperatures, internal fluid flow and moisture distribution, and heat flow in the system.

Biophysical and Population Genetic Models Predict the Presence of "Phantom" Stepping Stones Connecting Mid-Atlantic Ridge Vent Ecosystems.

PubMed

Breusing, Corinna; Biastoch, Arne; Drews, Annika; Metaxas, Anna; Jollivet, Didier; Vrijenhoek, Robert C; Bayer, Till; Melzner, Frank; Sayavedra, Lizbeth; Petersen, Jillian M; Dubilier, Nicole; Schilhabel, Markus B; Rosenstiel, Philip; Reusch, Thorsten B H

2016-09-12

Deep-sea hydrothermal vents are patchily distributed ecosystems inhabited by specialized animal populations that are textbook meta-populations. Many vent-associated species have free-swimming, dispersive larvae that can establish connections between remote populations. However, connectivity patterns among hydrothermal vents are still poorly understood because the deep sea is undersampled, the molecular tools used to date are of limited resolution, and larval dispersal is difficult to measure directly. A better knowledge of connectivity is urgently needed to develop sound environmental management plans for deep-sea mining. Here, we investigated larval dispersal and contemporary connectivity of ecologically important vent mussels (Bathymodiolus spp.) from the Mid-Atlantic Ridge by using high-resolution ocean modeling and population genetic methods. Even when assuming a long pelagic larval duration, our physical model of larval drift suggested that arrival at localities more than 150 km from the source site is unlikely and that dispersal between populations requires intermediate habitats ("phantom" stepping stones). Dispersal patterns showed strong spatiotemporal variability, making predictions of population connectivity challenging. The assumption that mussel populations are only connected via additional stepping stones was supported by contemporary migration rates based on neutral genetic markers. Analyses of population structure confirmed the presence of two southern and two hybridizing northern mussel lineages that exhibited a substantial, though incomplete, genetic differentiation. Our study provides insights into how vent animals can disperse between widely separated vent habitats and shows that recolonization of perturbed vent sites will be subject to chance events, unless connectivity is explicitly considered in the selection of conservation areas. Copyright © 2016 Elsevier Ltd. All rights reserved.

Implementation of marine spatial planning in shellfish aquaculture management: modeling studies in a Norwegian fjord.

PubMed

Filgueira, Ramon; Grant, Jon; Strand, Øivind

2014-06-01

Shellfish carrying capacity is determined by the interaction of a cultured species with its ecosystem, which is strongly influenced by hydrodynamics. Water circulation controls the exchange of matter between farms and the adjacent areas, which in turn establishes the nutrient supply that supports phytoplankton populations. The complexity of water circulation makes necessary the use of hydrodynamic models with detailed spatial resolution in carrying capacity estimations. This detailed spatial resolution also allows for the study of processes that depend on specific spatial arrangements, e.g., the most suitable location to place farms, which is crucial for marine spatial planning, and consequently for decision support systems. In the present study, a fully spatial physical-biogeochemical model has been combined with scenario building and optimization techniques as a proof of concept of the use of ecosystem modeling as an objective tool to inform marine spatial planning. The object of this exercise was to generate objective knowledge based on an ecosystem approach to establish new mussel aquaculture areas in a Norwegian fjord. Scenario building was used to determine the best location of a pump that can be used to bring nutrient-rich deep waters to the euphotic layer, increasing primary production, and consequently, carrying capacity for mussel cultivation. In addition, an optimization tool, parameter estimation (PEST), was applied to the optimal location and mussel standing stock biomass that maximize production, according to a preestablished carrying capacity criterion. Optimization tools allow us to make rational and transparent decisions to solve a well-defined question, decisions that are essential for policy makers. The outcomes of combining ecosystem models with scenario building and optimization facilitate planning based on an ecosystem approach, highlighting the capabilities of ecosystem modeling as a tool for marine spatial planning.

Assessing the vulnerability of human and biological communities to changing ecosystem services using a GIS-based multi-criteria decision support tool

USGS Publications Warehouse

Villarreal, Miguel; Norman, Laura M.; Labiosa, William B.

2012-01-01

In this paper we describe an application of a GIS-based multi-criteria decision support web tool that models and evaluates relative changes in ecosystem services to policy and land management decisions. The Santa Cruz Watershed Ecosystem Portfolio (SCWEPM) was designed to provide credible forecasts of responses to ecosystem drivers and stressors and to illustrate the role of land use decisions on spatial and temporal distributions of ecosystem services within a binational (U.S. and Mexico) watershed. We present two SCWEPM sub-models that when analyzed together address bidirectional relationships between social and ecological vulnerability and ecosystem services. The first model employs the Modified Socio-Environmental Vulnerability Index (M-SEVI), which assesses community vulnerability using information from U.S. and Mexico censuses on education, access to resources, migratory status, housing situation, and number of dependents. The second, relating land cover change to biodiversity (provisioning services), models changes in the distribution of terrestrial vertebrate habitat based on multitemporal vegetation and land cover maps, wildlife habitat relationships, and changes in land use/land cover patterns. When assessed concurrently, the models exposed some unexpected relationships between vulnerable communities and ecosystem services provisioning. For instance, the most species-rich habitat type in the watershed, Desert Riparian Forest, increased over time in areas occupied by the most vulnerable populations and declined in areas with less vulnerable populations. This type of information can be used to identify ecological conservation and restoration targets that enhance the livelihoods of people in vulnerable communities and promote biodiversity and ecosystem health.

MI-Sim: A MATLAB package for the numerical analysis of microbial ecological interactions.

PubMed

Wade, Matthew J; Oakley, Jordan; Harbisher, Sophie; Parker, Nicholas G; Dolfing, Jan

2017-01-01

Food-webs and other classes of ecological network motifs, are a means of describing feeding relationships between consumers and producers in an ecosystem. They have application across scales where they differ only in the underlying characteristics of the organisms and substrates describing the system. Mathematical modelling, using mechanistic approaches to describe the dynamic behaviour and properties of the system through sets of ordinary differential equations, has been used extensively in ecology. Models allow simulation of the dynamics of the various motifs and their numerical analysis provides a greater understanding of the interplay between the system components and their intrinsic properties. We have developed the MI-Sim software for use with MATLAB to allow a rigorous and rapid numerical analysis of several common ecological motifs. MI-Sim contains a series of the most commonly used motifs such as cooperation, competition and predation. It does not require detailed knowledge of mathematical analytical techniques and is offered as a single graphical user interface containing all input and output options. The tools available in the current version of MI-Sim include model simulation, steady-state existence and stability analysis, and basin of attraction analysis. The software includes seven ecological interaction motifs and seven growth function models. Unlike other system analysis tools, MI-Sim is designed as a simple and user-friendly tool specific to ecological population type models, allowing for rapid assessment of their dynamical and behavioural properties.

skelesim: an extensible, general framework for population genetic simulation in R.

PubMed

Parobek, Christian M; Archer, Frederick I; DePrenger-Levin, Michelle E; Hoban, Sean M; Liggins, Libby; Strand, Allan E

2017-01-01

Simulations are a key tool in molecular ecology for inference and forecasting, as well as for evaluating new methods. Due to growing computational power and a diversity of software with different capabilities, simulations are becoming increasingly powerful and useful. However, the widespread use of simulations by geneticists and ecologists is hindered by difficulties in understanding these softwares' complex capabilities, composing code and input files, a daunting bioinformatics barrier and a steep conceptual learning curve. skelesim (an R package) guides users in choosing appropriate simulations, setting parameters, calculating genetic summary statistics and organizing data output, in a reproducible pipeline within the R environment. skelesim is designed to be an extensible framework that can 'wrap' around any simulation software (inside or outside the R environment) and be extended to calculate and graph any genetic summary statistics. Currently, skelesim implements coalescent and forward-time models available in the fastsimcoal2 and rmetasim simulation engines to produce null distributions for multiple population genetic statistics and marker types, under a variety of demographic conditions. skelesim is intended to make simulations easier while still allowing full model complexity to ensure that simulations play a fundamental role in molecular ecology investigations. skelesim can also serve as a teaching tool: demonstrating the outcomes of stochastic population genetic processes; teaching general concepts of simulations; and providing an introduction to the R environment with a user-friendly graphical user interface (using shiny). © 2016 John Wiley & Sons Ltd.

skeleSim: an extensible, general framework for population genetic simulation in R

PubMed Central

Parobek, Christian M.; Archer, Frederick I.; DePrenger-Levin, Michelle E.; Hoban, Sean M.; Liggins, Libby; Strand, Allan E.

2016-01-01

Simulations are a key tool in molecular ecology for inference and forecasting, as well as for evaluating new methods. Due to growing computational power and a diversity of software with different capabilities, simulations are becoming increasingly powerful and useful. However, the widespread use of simulations by geneticists and ecologists is hindered by difficulties in understanding these softwares’ complex capabilities, composing code and input files, a daunting bioinformatics barrier, and a steep conceptual learning curve. skeleSim (an R package) guides users in choosing appropriate simulations, setting parameters, calculating genetic summary statistics, and organizing data output, in a reproducible pipeline within the R environment. skeleSim is designed to be an extensible framework that can ‘wrap’ around any simulation software (inside or outside the R environment) and be extended to calculate and graph any genetic summary statistics. Currently, skeleSim implements coalescent and forward-time models available in the fastsimcoal2 and rmetasim simulation engines to produce null distributions for multiple population genetic statistics and marker types, under a variety of demographic conditions. skeleSim is intended to make simulations easier while still allowing full model complexity to ensure that simulations play a fundamental role in molecular ecology investigations. skeleSim can also serve as a teaching tool: demonstrating the outcomes of stochastic population genetic processes; teaching general concepts of simulations; and providing an introduction to the R environment with a user-friendly graphical user interface (using shiny). PMID:27736016

Clinical application of the Melbourne risk prediction tool in a high-risk upper abdominal surgical population: an observational cohort study.

PubMed

Parry, S; Denehy, L; Berney, S; Browning, L

2014-03-01

(1) To determine the ability of the Melbourne risk prediction tool to predict a pulmonary complication as defined by the Melbourne Group Scale in a medically defined high-risk upper abdominal surgery population during the postoperative period; (2) to identify the incidence of postoperative pulmonary complications; and (3) to examine the risk factors for postoperative pulmonary complications in this high-risk population. Observational cohort study. Tertiary Australian referral centre. 50 individuals who underwent medically defined high-risk upper abdominal surgery. Presence of postoperative pulmonary complications was screened daily for seven days using the Melbourne Group Scale (Version 2). Postoperative pulmonary risk prediction was calculated according to the Melbourne risk prediction tool. (1) Melbourne risk prediction tool; and (2) the incidence of postoperative pulmonary complications. Sixty-six percent (33/50) underwent hepatobiliary or upper gastrointestinal surgery. Mean (SD) anaesthetic duration was 377.8 (165.5) minutes. The risk prediction tool classified 84% (42/50) as high risk. Overall postoperative pulmonary complication incidence was 42% (21/50). The tool was 91% sensitive and 21% specific with a 50% chance of correct classification. This is the first study to externally validate the Melbourne risk prediction tool in an independent medically defined high-risk population. There was a higher incidence of pulmonary complications postoperatively observed compared to that previously reported. Results demonstrated poor validity of the tool in a population already defined medically as high risk and when applied postoperatively. This observational study has identified several important points to consider in future trials. Copyright © 2013 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

The application of cure models in the presence of competing risks: a tool for improved risk communication in population-based cancer patient survival.

PubMed

Eloranta, Sandra; Lambert, Paul C; Andersson, Therese M-L; Björkholm, Magnus; Dickman, Paul W

2014-09-01

Quantifying cancer patient survival from the perspective of cure is clinically relevant. However, most cure models estimate cure assuming no competing causes of death. We use a relative survival framework to demonstrate how flexible parametric cure models can be used in combination with competing-risks theory to incorporate noncancer deaths. Under a model that incorporates statistical cure, we present the probabilities that cancer patients (1) have died from their cancer, (2) have died from other causes, (3) will eventually die from their cancer, or (4) will eventually die from other causes, all as a function of time since diagnosis. We further demonstrate how conditional probabilities can be used to update the prognosis among survivors (eg, at 1 or 5 years after diagnosis) by summarizing the proportion of patients who will not die from their cancer. The proposed method is applied to Swedish population-based data for persons diagnosed with melanoma, colon cancer, or acute myeloid leukemia between 1973 and 2007.

Analysis and prediction of pest dynamics in an agroforestry context using Tiko'n, a generic tool to develop food web models

NASA Astrophysics Data System (ADS)

Rojas, Marcela; Malard, Julien; Adamowski, Jan; Carrera, Jaime Luis; Maas, Raúl

2017-04-01

While it is known that climate change will impact future plant-pest population dynamics, potentially affecting crop damage, agroforestry with its enhanced biodiversity is said to reduce the outbreaks of pest insects by providing natural enemies for the control of pest populations. This premise is known in the literature as the natural enemy hypothesis and has been widely studied qualitatively. However, disagreement still exists on whether biodiversity enhancement reduces pest outbreaks, showing the need of quantitatively understanding the mechanisms behind the interactions between pests and natural enemies, also known as trophic interactions. Crop pest models that study insect population dynamics in agroforestry contexts are very rare, and pest models that take trophic interactions into account are even rarer. This may be due to the difficulty of representing complex food webs in a quantifiable model. There is therefore a need for validated food web models that allow users to predict the response of these webs to changes in climate in agroforestry systems. In this study we present Tiko'n, a Python-based software whose API allows users to rapidly build and validate trophic web models; the program uses a Bayesian inference approach to calibrate the models according to field data, allowing for the reuse of literature data from various sources and reducing the need for extensive field data collection. Tiko'n was run using coffee leaf miner (Leucoptera coffeella) and associated parasitoid data from a shaded coffee plantation, showing the mechanisms of insect population dynamics within a tri-trophic food web in an agroforestry system.

Using probability modelling and genetic parentage assignment to test the role of local mate availability in mating system variation.

PubMed

Blyton, Michaela D J; Banks, Sam C; Peakall, Rod; Lindenmayer, David B

2012-02-01

The formal testing of mating system theories with empirical data is important for evaluating the relative importance of different processes in shaping mating systems in wild populations. Here, we present a generally applicable probability modelling framework to test the role of local mate availability in determining a population's level of genetic monogamy. We provide a significance test for detecting departures in observed mating patterns from model expectations based on mate availability alone, allowing the presence and direction of behavioural effects to be inferred. The assessment of mate availability can be flexible and in this study it was based on population density, sex ratio and spatial arrangement. This approach provides a useful tool for (1) isolating the effect of mate availability in variable mating systems and (2) in combination with genetic parentage analyses, gaining insights into the nature of mating behaviours in elusive species. To illustrate this modelling approach, we have applied it to investigate the variable mating system of the mountain brushtail possum (Trichosurus cunninghami) and compared the model expectations with the outcomes of genetic parentage analysis over an 18-year study. The observed level of monogamy was higher than predicted under the model. Thus, behavioural traits, such as mate guarding or selective mate choice, may increase the population level of monogamy. We show that combining genetic parentage data with probability modelling can facilitate an improved understanding of the complex interactions between behavioural adaptations and demographic dynamics in driving mating system variation. © 2011 Blackwell Publishing Ltd.

Evaluating Spatial Interaction Models for Regional Mobility in Sub-Saharan Africa

PubMed Central

Wesolowski, Amy; O’Meara, Wendy Prudhomme; Eagle, Nathan; Tatem, Andrew J.; Buckee, Caroline O.

2015-01-01

Simple spatial interaction models of human mobility based on physical laws have been used extensively in the social, biological, and physical sciences, and in the study of the human dynamics underlying the spread of disease. Recent analyses of commuting patterns and travel behavior in high-income countries have led to the suggestion that these models are highly generalizable, and as a result, gravity and radiation models have become standard tools for describing population mobility dynamics for infectious disease epidemiology. Communities in Sub-Saharan Africa may not conform to these models, however; physical accessibility, availability of transport, and cost of travel between locations may be variable and severely constrained compared to high-income settings, informal labor movements rather than regular commuting patterns are often the norm, and the rise of mega-cities across the continent has important implications for travel between rural and urban areas. Here, we first review how infectious disease frameworks incorporate human mobility on different spatial scales and use anonymous mobile phone data from nearly 15 million individuals to analyze the spatiotemporal dynamics of the Kenyan population. We find that gravity and radiation models fail in systematic ways to capture human mobility measured by mobile phones; both severely overestimate the spatial spread of travel and perform poorly in rural areas, but each exhibits different characteristic patterns of failure with respect to routes and volumes of travel. Thus, infectious disease frameworks that rely on spatial interaction models are likely to misrepresent population dynamics important for the spread of disease in many African populations. PMID:26158274

Characterizing the impact of projected changes in climate and ...

EPA Pesticide Factsheets

The impact of climate change on human and environmental health is of critical concern. Population exposures to air pollutants both indoors and outdoors are influenced by a wide range of air quality, meteorological, behavioral, and housing-related factors, many of which are also impacted by climate change. An integrated methodology for modeling changes in human exposures to tropospheric ozone (O3) owing to potential future changes in climate and demographics was implemented by linking existing modeling tools for climate, weather, air quality, population distribution, and human exposure. Human exposure results from the Air Pollutants Exposure Model (APEX) for 12 US cities show differences in daily maximum 8-h (DM8H) exposure patterns and levels by sex, age, and city for all scenarios. When climate is held constant and population demographics are varied, minimal difference in O3 exposures is predicted even with the most extreme demographic change scenario. In contrast, when population is held constant, we see evidence of substantial changes in O3 exposure for the most extreme change in climate. Similarly, we see increases in the percentage of the population in each city with at least one O3 exposure exceedance above 60 p.p.b and 70 p.p.b thresholds for future changes in climate. For these climate and population scenarios, the impact of projected changes in climate and air quality on human exposure to O3 are much larger than the impacts of changing demographics.

Game-Changing Innovations: How Culture Can Change the Parameters of Its Own Evolution and Induce Abrupt Cultural Shifts.

PubMed

Kolodny, Oren; Creanza, Nicole; Feldman, Marcus W

2016-12-01

One of the most puzzling features of the prehistoric record of hominid stone tools is its apparent punctuation: it consists of abrupt bursts of dramatic change that separate long periods of largely unchanging technology. Within each such period, small punctuated cultural modifications take place. Punctuation on multiple timescales and magnitudes is also found in cultural trajectories from historical times. To explain these sharp cultural bursts, researchers invoke such external factors as sudden environmental change, rapid cognitive or morphological change in the hominids that created the tools, or replacement of one species or population by another. Here we propose a dynamic model of cultural evolution that accommodates empirical observations: without invoking external factors, it gives rise to a pattern of rare, dramatic cultural bursts, interspersed by more frequent, smaller, punctuated cultural modifications. Our model includes interdependent innovation processes that occur at different rates. It also incorporates a realistic aspect of cultural evolution: cultural innovations, such as those that increase food availability or that affect cultural transmission, can change the parameters that affect cultural evolution, thereby altering the population's cultural dynamics and steady state. This steady state can be regarded as a cultural carrying capacity. These parameter-changing cultural innovations occur very rarely, but whenever one occurs, it triggers a dramatic shift towards a new cultural steady state. The smaller and more frequent punctuated cultural changes, on the other hand, are brought about by innovations that spur the invention of further, related, technology, and which occur regardless of whether the population is near its cultural steady state. Our model suggests that common interpretations of cultural shifts as evidence of biological change, for example the appearance of behaviorally modern humans, may be unwarranted.

Estimating SIT-driven population reduction in the Mediterranean fruit fly, Ceratitis capitata, from sterile mating.

PubMed

Juan-Blasco, M; Sabater-Muñoz, B; Pla, I; Argilés, R; Castañera, P; Jacas, J A; Ibáñez-Gual, M V; Urbaneja, A

2014-04-01

Area-wide sterile insect technique (SIT) programs assume that offspring reduction of the target population correlates with the mating success of the sterile males released. However, there is a lack of monitoring tools to prove the success of these programs in real-time. Field-cage tests were conducted under the environmental conditions of the Mediterranean coast of Spain to estimate: (a) the mating success of sterile Vienna-8 (V8) Ceratitis capitata males using molecular markers and (b) their efficacy to reduce C. capitata populations under six release ratios of wild females to wild males to V8 males (1:0:0, 1:1:0, 1:1:1, 1:1:5, 1:1:10, and 1:1:20). Statistical models were developed to predict: (a) the number of females captured in traps, (b) sperm ID (sterile or not) in spermathecae of the trapped females, and (c) the viable offspring produced, using release ratio and temperature as predictors. The number of females captured was affected by relative humidity. However, its influence in the model was low. Female captures were significantly higher in ratios 1:0:0 compared to ratios where V8 males were released. The proportion of V8 sperm in spermathecae increased with temperature and with the number of V8 males released, but leveled off between ratios 1:1:10 and 1:1:20. In all seasons, except winter (no offspring), viable offspring increased with temperature and was lowest for ratio 1:1:20. For the first time, a strong negative relationship between proportion of V8 sperm detected by molecular tools and C. capitata offspring was established. The models obtained should contribute to enhance the efficacy of SIT programs against this pest.

Predators, Prey and Habitat Structure: Can Key Conservation Areas and Early Signs of Population Collapse Be Detected in Neotropical Forests?

PubMed

de Thoisy, Benoit; Fayad, Ibrahim; Clément, Luc; Barrioz, Sébastien; Poirier, Eddy; Gond, Valéry

2016-01-01

Tropical forests with a low human population and absence of large-scale deforestation provide unique opportunities to study successful conservation strategies, which should be based on adequate monitoring tools. This study explored the conservation status of a large predator, the jaguar, considered an indicator of the maintenance of how well ecological processes are maintained. We implemented an original integrative approach, exploring successive ecosystem status proxies, from habitats and responses to threats of predators and their prey, to canopy structure and forest biomass. Niche modeling allowed identification of more suitable habitats, significantly related to canopy height and forest biomass. Capture/recapture methods showed that jaguar density was higher in habitats identified as more suitable by the niche model. Surveys of ungulates, large rodents and birds also showed higher density where jaguars were more abundant. Although jaguar density does not allow early detection of overall vertebrate community collapse, a decrease in the abundance of large terrestrial birds was noted as good first evidence of disturbance. The most promising tool comes from easily acquired LiDAR data and radar images: a decrease in canopy roughness was closely associated with the disturbance of forests and associated decreasing vertebrate biomass. This mixed approach, focusing on an apex predator, ecological modeling and remote-sensing information, not only helps detect early population declines in large mammals, but is also useful to discuss the relevance of large predators as indicators and the efficiency of conservation measures. It can also be easily extrapolated and adapted in a timely manner, since important open-source data are increasingly available and relevant for large-scale and real-time monitoring of biodiversity.

Emerging Concepts of Data Integration in Pathogen Phylodynamics.

PubMed

Baele, Guy; Suchard, Marc A; Rambaut, Andrew; Lemey, Philippe

2017-01-01

Phylodynamics has become an increasingly popular statistical framework to extract evolutionary and epidemiological information from pathogen genomes. By harnessing such information, epidemiologists aim to shed light on the spatio-temporal patterns of spread and to test hypotheses about the underlying interaction of evolutionary and ecological dynamics in pathogen populations. Although the field has witnessed a rich development of statistical inference tools with increasing levels of sophistication, these tools initially focused on sequences as their sole primary data source. Integrating various sources of information, however, promises to deliver more precise insights in infectious diseases and to increase opportunities for statistical hypothesis testing. Here, we review how the emerging concept of data integration is stimulating new advances in Bayesian evolutionary inference methodology which formalize a marriage of statistical thinking and evolutionary biology. These approaches include connecting sequence to trait evolution, such as for host, phenotypic and geographic sampling information, but also the incorporation of covariates of evolutionary and epidemic processes in the reconstruction procedures. We highlight how a full Bayesian approach to covariate modeling and testing can generate further insights into sequence evolution, trait evolution, and population dynamics in pathogen populations. Specific examples demonstrate how such approaches can be used to test the impact of host on rabies and HIV evolutionary rates, to identify the drivers of influenza dispersal as well as the determinants of rabies cross-species transmissions, and to quantify the evolutionary dynamics of influenza antigenicity. Finally, we briefly discuss how data integration is now also permeating through the inference of transmission dynamics, leading to novel insights into tree-generative processes and detailed reconstructions of transmission trees. [Bayesian inference; birth–death models; coalescent models; continuous trait evolution; covariates; data integration; discrete trait evolution; pathogen phylodynamics.

Soil-transmitted helminthiasis in Latin America and the Caribbean: modelling the determinants, prevalence, population at risk and costs of control at sub-national level.

PubMed

Colston, Josh; Saboyá, Martha

2013-05-01

We present an example of a tool for quantifying the burden, the population in need of intervention and resources need to contribute for the control of soil-transmitted helminth (STH) infection at multiple administrative levels for the region of Latin America and the Caribbean (LAC). The tool relies on published STH prevalence data along with data on the distribution of several STH transmission determinants for 12,273 sub-national administrative units in 22 LAC countries taken from national censuses. Data on these determinants was aggregated into a single risk index based on a conceptual framework and the statistical significance of the association between this index and the STH prevalence indicators was tested using simple linear regression. The coefficient and constant from the output of this regression was then put into a regression formula that was applied to the risk index values for all of the administrative units in order to model the estimated prevalence of each STH species. We then combine these estimates with population data, treatment thresholds and unit cost data to calculate total control costs. The model predicts an annual cost for the procurement of preventive chemotherapy of around US$ 1.7 million and a total cost of US$ 47 million for implementing a comprehensive STH control programme targeting an estimated 78.7 million school-aged children according to the WHO guidelines throughout the entirety of the countries included in the study. Considerable savings to this cost could potentially be made by embedding STH control interventions within existing health programmes and systems. A study of this scope is prone to many limitations which restrict the interpretation of the results and the uses to which its findings may be put. We discuss several of these limitations.

Predators, Prey and Habitat Structure: Can Key Conservation Areas and Early Signs of Population Collapse Be Detected in Neotropical Forests?

PubMed Central

de Thoisy, Benoit; Fayad, Ibrahim; Clément, Luc; Barrioz, Sébastien; Poirier, Eddy; Gond, Valéry

2016-01-01

Tropical forests with a low human population and absence of large-scale deforestation provide unique opportunities to study successful conservation strategies, which should be based on adequate monitoring tools. This study explored the conservation status of a large predator, the jaguar, considered an indicator of the maintenance of how well ecological processes are maintained. We implemented an original integrative approach, exploring successive ecosystem status proxies, from habitats and responses to threats of predators and their prey, to canopy structure and forest biomass. Niche modeling allowed identification of more suitable habitats, significantly related to canopy height and forest biomass. Capture/recapture methods showed that jaguar density was higher in habitats identified as more suitable by the niche model. Surveys of ungulates, large rodents and birds also showed higher density where jaguars were more abundant. Although jaguar density does not allow early detection of overall vertebrate community collapse, a decrease in the abundance of large terrestrial birds was noted as good first evidence of disturbance. The most promising tool comes from easily acquired LiDAR data and radar images: a decrease in canopy roughness was closely associated with the disturbance of forests and associated decreasing vertebrate biomass. This mixed approach, focusing on an apex predator, ecological modeling and remote-sensing information, not only helps detect early population declines in large mammals, but is also useful to discuss the relevance of large predators as indicators and the efficiency of conservation measures. It can also be easily extrapolated and adapted in a timely manner, since important open-source data are increasingly available and relevant for large-scale and real-time monitoring of biodiversity. PMID:27828993

Emerging Concepts of Data Integration in Pathogen Phylodynamics

PubMed Central

Baele, Guy; Suchard, Marc A.; Rambaut, Andrew; Lemey, Philippe

2017-01-01

Phylodynamics has become an increasingly popular statistical framework to extract evolutionary and epidemiological information from pathogen genomes. By harnessing such information, epidemiologists aim to shed light on the spatio-temporal patterns of spread and to test hypotheses about the underlying interaction of evolutionary and ecological dynamics in pathogen populations. Although the field has witnessed a rich development of statistical inference tools with increasing levels of sophistication, these tools initially focused on sequences as their sole primary data source. Integrating various sources of information, however, promises to deliver more precise insights in infectious diseases and to increase opportunities for statistical hypothesis testing. Here, we review how the emerging concept of data integration is stimulating new advances in Bayesian evolutionary inference methodology which formalize a marriage of statistical thinking and evolutionary biology. These approaches include connecting sequence to trait evolution, such as for host, phenotypic and geographic sampling information, but also the incorporation of covariates of evolutionary and epidemic processes in the reconstruction procedures. We highlight how a full Bayesian approach to covariate modeling and testing can generate further insights into sequence evolution, trait evolution, and population dynamics in pathogen populations. Specific examples demonstrate how such approaches can be used to test the impact of host on rabies and HIV evolutionary rates, to identify the drivers of influenza dispersal as well as the determinants of rabies cross-species transmissions, and to quantify the evolutionary dynamics of influenza antigenicity. Finally, we briefly discuss how data integration is now also permeating through the inference of transmission dynamics, leading to novel insights into tree-generative processes and detailed reconstructions of transmission trees. [Bayesian inference; birth–death models; coalescent models; continuous trait evolution; covariates; data integration; discrete trait evolution; pathogen phylodynamics. PMID:28173504

A COMPARISON OF AIRFLOW PATTERNS FROM THE QUIC MODEL AND AN ATMOSPHERIC WIND TUNNEL FOR A TWO-DIMENSIONAL BUILDING ARRAY AND A MULTI-CITY BLOCK REGION NEAR THE WORLD TRADE CENTER SITE

EPA Science Inventory

Dispersion of pollutants in densely populated urban areas is a research area of clear importance. Currently, few numerical tools exist capable of describing airflow and dispersion patterns in these complex regions in a time efficient manner. (QUIC), Quick Urban & Industrial C...

Development and application of a density dependent matrix ...

EPA Pesticide Factsheets

Ranging along the Atlantic coast from US Florida to the Maritime Provinces of Canada, the Atlantic killifish (Fundulus heteroclitus) is an important and well-studied model organism for understanding the effects of pollutants and other stressors in estuarine and marine ecosystems. Matrix population models are useful tools for ecological risk assessment because they integrate effects across the life cycle, provide a linkage between endpoints observed in the individual and ecological risk to the population as a whole, and project outcomes for many generations in the future. We developed a density dependent matrix population model for Atlantic killifish by modifying a model developed for fathead minnow (Pimephales promelas) that has proved to be extremely useful, e.g. to incorporate data from laboratory studies and project effects of endocrine disrupting chemicals. We developed a size-structured model (as opposed to one that is based upon developmental stages or age class structure) so that we could readily incorporate output from a Dynamic Energy Budget (DEB) model, currently under development. Due to a lack of sufficient data to accurately define killifish responses to density dependence, we tested a number of scenarios realistic for other fish species in order to demonstrate the outcome of including this ecologically important factor. We applied the model using published data for killifish exposed to dioxin-like compounds, and compared our results to those using

An accessible method for implementing hierarchical models with spatio-temporal abundance data

USGS Publications Warehouse

Ross, Beth E.; Hooten, Melvin B.; Koons, David N.

2012-01-01

A common goal in ecology and wildlife management is to determine the causes of variation in population dynamics over long periods of time and across large spatial scales. Many assumptions must nevertheless be overcome to make appropriate inference about spatio-temporal variation in population dynamics, such as autocorrelation among data points, excess zeros, and observation error in count data. To address these issues, many scientists and statisticians have recommended the use of Bayesian hierarchical models. Unfortunately, hierarchical statistical models remain somewhat difficult to use because of the necessary quantitative background needed to implement them, or because of the computational demands of using Markov Chain Monte Carlo algorithms to estimate parameters. Fortunately, new tools have recently been developed that make it more feasible for wildlife biologists to fit sophisticated hierarchical Bayesian models (i.e., Integrated Nested Laplace Approximation, ‘INLA’). We present a case study using two important game species in North America, the lesser and greater scaup, to demonstrate how INLA can be used to estimate the parameters in a hierarchical model that decouples observation error from process variation, and accounts for unknown sources of excess zeros as well as spatial and temporal dependence in the data. Ultimately, our goal was to make unbiased inference about spatial variation in population trends over time.

Development and validation of a risk assessment tool for gastric cancer in a general Japanese population.

PubMed

Iida, Masahiro; Ikeda, Fumie; Hata, Jun; Hirakawa, Yoichiro; Ohara, Tomoyuki; Mukai, Naoko; Yoshida, Daigo; Yonemoto, Koji; Esaki, Motohiro; Kitazono, Takanari; Kiyohara, Yutaka; Ninomiya, Toshiharu

2018-05-01

There have been very few reports of risk score models for the development of gastric cancer. The aim of this study was to develop and validate a risk assessment tool for discerning future gastric cancer risk in Japanese. A total of 2444 subjects aged 40 years or over were followed up for 14 years from 1988 (derivation cohort), and 3204 subjects of the same age group were followed up for 5 years from 2002 (validation cohort). The weighting (risk score) of each risk factor for predicting future gastric cancer in the risk assessment tool was determined based on the coefficients of a Cox proportional hazards model in the derivation cohort. The goodness of fit of the established risk assessment tool was assessed using the c-statistic and the Hosmer-Lemeshow test in the validation cohort. During the follow-up, gastric cancer developed in 90 subjects in the derivation cohort and 35 subjects in the validation cohort. In the derivation cohort, the risk prediction model for gastric cancer was established using significant risk factors: age, sex, the combination of Helicobacter pylori antibody and pepsinogen status, hemoglobin A1c level, and smoking status. The incidence of gastric cancer increased significantly as the sum of risk scores increased (P trend < 0.001). The risk assessment tool was validated internally and showed good discrimination (c-statistic = 0.76) and calibration (Hosmer-Lemeshow test P = 0.43) in the validation cohort. We developed a risk assessment tool for gastric cancer that provides a useful guide for stratifying an individual's risk of future gastric cancer.

Random and non-random mating populations: Evolutionary dynamics in meiotic drive.

PubMed

Sarkar, Bijan

2016-01-01

Game theoretic tools are utilized to analyze a one-locus continuous selection model of sex-specific meiotic drive by considering nonequivalence of the viabilities of reciprocal heterozygotes that might be noticed at an imprinted locus. The model draws attention to the role of viability selections of different types to examine the stable nature of polymorphic equilibrium. A bridge between population genetics and evolutionary game theory has been built up by applying the concept of the Fundamental Theorem of Natural Selection. In addition to pointing out the influences of male and female segregation ratios on selection, configuration structure reveals some noted results, e.g., Hardy-Weinberg frequencies hold in replicator dynamics, occurrence of faster evolution at the maximized variance fitness, existence of mixed Evolutionarily Stable Strategy (ESS) in asymmetric games, the tending evolution to follow not only a 1:1 sex ratio but also a 1:1 different alleles ratio at particular gene locus. Through construction of replicator dynamics in the group selection framework, our selection model introduces a redefining bases of game theory to incorporate non-random mating where a mating parameter associated with population structure is dependent on the social structure. Also, the model exposes the fact that the number of polymorphic equilibria will depend on the algebraic expression of population structure. Copyright © 2015 Elsevier Inc. All rights reserved.

Pu-239 organ specific dosimetric model applied to non-human biota

NASA Astrophysics Data System (ADS)

Kaspar, Matthew Jason

There are few locations throughout the world, like the Maralinga nuclear test site located in south western Australia, where sufficient plutonium contaminate concentration levels exist that they can be utilized for studies of the long-term radionuclide accumulation in non-human biota. The information obtained will be useful for the potential human users of the site while also keeping with international efforts to better understand doses to non-human biota. In particular, this study focuses primarily on a rabbit sample set collected from the population located within the site. Our approach is intended to employ the same dose and dose rate methods selected by the International Commission on Radiological Protection and adapted by the scientific community for similar research questions. These models rely on a series of simplifying assumptions on biota and their geometry; in particular; organisms are treated as spherical and ellipsoidal representations displaying the animal mass and volume. These simplifications assume homogeneity of all animal tissues. In collaborative efforts between Colorado State University and the Australian Nuclear Science and Technology Organisation (ANSTO), we are expanding current knowledge on radionuclide accumulation in specific organs causing organ-specific dose rates, such as Pu-239 accumulating in bone, liver, and lungs. Organ-specific dose models have been developed for humans; however, little has been developed for the dose assessment to biota, in particular rabbits. This study will determine if it is scientifically valid to use standard software, in particular ERICA Tool, as a means to determine organ-specific dosimetry due to Pu-239 accumulation in organs. ERICA Tool is normally applied to whole organisms as a means to determine radiological risk to whole ecosystems. We will focus on the aquatic model within ERICA Tool, as animal organs, like aquatic organisms, can be assumed to lie within an infinite uniform medium. This model would scientifically be valid for radionuclides emitting short-range radiation, as with Pu-239, where the energy is deposited locally. Two MCNPX models have been created and evaluated against ERICA Tool's aquatic model. One MCNPX model replicates ERICA Tool's intrinsic assumptions while the other uses a more realistic animal model adopted by ICRP Publication 108 and ERICA Tool for the organs "infinite" surrounding universe. In addition, the role of model geometry will be analyzed by focusing on four geometry sets for the same organ, including a spherical geometry. ERICA Tool will be compared to MCNPX results within and between each organ geometry set. In addition, the organ absorbed dose rate will be calculated for six rabbits located on the Maralinga nuclear test site as a preliminary test for further investigation. Data in all cases will be compared using percent differences and Student's t-test with respect to ERICA Tool's results and the overall average organ mean absorbed dose rate.

Diffusion Decision Model: Current Issues and History

PubMed Central

Ratcliff, Roger; Smith, Philip L.; Brown, Scott D.; McKoon, Gail

2016-01-01

There is growing interest in diffusion models to represent the cognitive and neural processes of speeded decision making. Sequential-sampling models like the diffusion model have a long history in psychology. They view decision making as a process of noisy accumulation of evidence from a stimulus. The standard model assumes that evidence accumulates at a constant rate during the second or two it takes to make a decision. This process can be linked to the behaviors of populations of neurons and to theories of optimality. Diffusion models have been used successfully in a range of cognitive tasks and as psychometric tools in clinical research to examine individual differences. In this article, we relate the models to both earlier and more recent research in psychology. PMID:26952739

Development of a screening tool using electronic health records for undiagnosed Type 2 diabetes mellitus and impaired fasting glucose detection in the Slovenian population.

PubMed

Štiglic, G; Kocbek, P; Cilar, L; Fijačko, N; Stožer, A; Zaletel, J; Sheikh, A; Povalej Bržan, P

2018-05-01

To develop and validate a simplified screening test for undiagnosed Type 2 diabetes mellitus and impaired fasting glucose for the Slovenian population (SloRisk) to be used in the general population. Data on 11 391 people were collected from the electronic health records of comprehensive medical examinations in five Slovenian healthcare centres. Fasting plasma glucose as well as information related to the Finnish Diabetes Risk Score questionnaire, FINDRISC, were collected for 2073 people to build predictive models. Bootstrapping-based evaluation was used to estimate the area under the receiver-operating characteristic curve performance metric of two proposed logistic regression models as well as the Finnish Diabetes Risk Score model both at recommended and at alternative cut-off values. The final model contained five questions for undiagnosed Type 2 diabetes prediction and achieved an area under the receiver-operating characteristic curve of 0.851 (95% CI 0.850-0.853). The impaired fasting glucose prediction model included six questions and achieved an area under the receiver-operating characteristic curve of 0.840 (95% CI 0.839-0.840). There were four questions that were included in both models (age, sex, waist circumference and blood sugar history), with physical activity selected only for undiagnosed Type 2 diabetes and questions on family history and hypertension drug use selected only for the impaired fasting glucose prediction model. This study proposes two simplified models based on FINDRISC questions for screening of undiagnosed Type 2 diabetes and impaired fasting glucose in the Slovenian population. A significant improvement in performance was achieved compared with the original FINDRISC questionnaire. Both models include waist circumference instead of BMI. © 2018 Diabetes UK.

The use of mist nets as a tool for bird population monitoring

Treesearch

E.H. Dunn; C. John Ralph

2004-01-01

Mist nets are an important tool for population monitoring, here defi ned as assessment of species composition, relative abundance, population size, and demography. We review the strengths and limitations of mist netting for monitoring purposes, based on papers in this volume and other literature. Advantages of using mist nets over aural or visual count methods include...

The effects of tradition on problem solving by two wild populations of bearded capuchin monkeys in a probing task.

PubMed

Cardoso, Raphael Moura; Ottoni, Eduardo B

2016-11-01

The effects of culture on individual cognition have become a core issue among cultural primatologists. Field studies with wild populations provide evidence on the role of social cues in the ontogeny of tool use in non-human primates, and on the transmission of such behaviours over generations through socially biased learning. Recent experimental studies have shown that cultural knowledge may influence problem solving in wild populations of chimpanzees. Here, we present the results from a field experiment comparing the performance of bearded capuchin monkeys (Sapajus libidinosus) from two wild savannah populations with distinct toolkits in a probing task. Only the population that already exhibited the customary use of probing tools succeeded in solving the new problem, suggesting that their cultural repertoire shaped their approach to the new task. Moreover, only this population, which uses stone tools in a broader range of contexts, tried to use them to solve the problem. Social interactions can affect the formation of learning sets and they affect the performance of the monkeys in problem solving. We suggest that behavioural traditions affect the ways non-human primates solve novel foraging problems using tools. © 2016 The Author(s).

Measuring selected PPCPs in wastewater to estimate the population in different cities in China.

PubMed

Gao, Jianfa; O'Brien, Jake; Du, Peng; Li, Xiqing; Ort, Christoph; Mueller, Jochen F; Thai, Phong K

2016-10-15

Sampling and analysis of wastewater from municipal wastewater treatment plants (WWTPs) has become a useful tool for understanding exposure to chemicals. Both wastewater based studies and management and planning of the catchment require information on catchment population in the time of monitoring. Recently, a model has been developed and calibrated using selected pharmaceutical and personal care products (PPCPs) measured in influent wastewater for estimating population in different catchments in Australia. The present study aimed at evaluating the feasibility of utilizing this population estimation approach in China. Twenty-four hour composite influent samples were collected from 31 WWTPs in 17 cities with catchment sizes from 200,000-3,450,000 people representing all seven regions of China. The samples were analyzed for 19 PPCPs using liquid chromatography coupled to tandem mass spectrometry in direct injection mode. Eight chemicals were detected in more than 50% of the samples. Significant positive correlations were found between individual PPCP mass loads and population estimates provided by WWTP operators. Using the PPCP mass load modeling approach calibrated with WWTP operator data, we estimated the population size of each catchment with good agreement with WWTP operator values (between 50-200% for all sites and 75-125% for 23 of the 31 sites). Overall, despite much lower detection and relatively high heterogeneity in PPCP consumption across China the model provided a good estimate of the population contributing to a given wastewater sample. Wastewater analysis could also provide objective PPCP consumption status in China. Copyright © 2016 Elsevier B.V. All rights reserved.