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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...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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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. |
format | Online Article Text |
id | pubmed-3852955 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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