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

BACKGROUND: 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 dise...

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Autores principales: Grefenstette, John J, Brown, Shawn T, Rosenfeld, Roni, DePasse, Jay, Stone, Nathan TB, Cooley, Phillip C, Wheaton, William D, Fyshe, Alona, Galloway, David D, Sriram, Anuroop, Guclu, Hasan, Abraham, Thomas, Burke, Donald S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3852955/
https://www.ncbi.nlm.nih.gov/pubmed/24103508
http://dx.doi.org/10.1186/1471-2458-13-940
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author Grefenstette, John J
Brown, Shawn T
Rosenfeld, Roni
DePasse, Jay
Stone, Nathan TB
Cooley, Phillip C
Wheaton, William D
Fyshe, Alona
Galloway, David D
Sriram, Anuroop
Guclu, Hasan
Abraham, Thomas
Burke, Donald S
author_facet Grefenstette, John J
Brown, Shawn T
Rosenfeld, Roni
DePasse, Jay
Stone, Nathan TB
Cooley, Phillip C
Wheaton, William D
Fyshe, Alona
Galloway, David D
Sriram, Anuroop
Guclu, Hasan
Abraham, Thomas
Burke, Donald S
author_sort Grefenstette, John J
collection PubMed
description BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.
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spelling pubmed-38529552013-12-07 FRED (A Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations Grefenstette, John J Brown, Shawn T Rosenfeld, Roni DePasse, Jay Stone, Nathan TB Cooley, Phillip C Wheaton, William D Fyshe, Alona Galloway, David D Sriram, Anuroop Guclu, Hasan Abraham, Thomas Burke, Donald S BMC Public Health Software BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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. BioMed Central 2013-10-08 /pmc/articles/PMC3852955/ /pubmed/24103508 http://dx.doi.org/10.1186/1471-2458-13-940 Text en Copyright © 2013 Grefenstette et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Grefenstette, John J
Brown, Shawn T
Rosenfeld, Roni
DePasse, Jay
Stone, Nathan TB
Cooley, Phillip C
Wheaton, William D
Fyshe, Alona
Galloway, David D
Sriram, Anuroop
Guclu, Hasan
Abraham, Thomas
Burke, Donald S
FRED (A Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations
title FRED (A Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations
title_full FRED (A Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations
title_fullStr FRED (A Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations
title_full_unstemmed FRED (A Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations
title_short FRED (A Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations
title_sort fred (a framework for reconstructing epidemic dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3852955/
https://www.ncbi.nlm.nih.gov/pubmed/24103508
http://dx.doi.org/10.1186/1471-2458-13-940
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