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An approach to and web-based tool for infectious disease outbreak intervention analysis
Infectious diseases are a leading cause of death globally. Decisions surrounding how to control an infectious disease outbreak currently rely on a subjective process involving surveillance and expert opinion. However, there are many situations where neither may be available. Modeling can fill gaps i...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5394686/ https://www.ncbi.nlm.nih.gov/pubmed/28417983 http://dx.doi.org/10.1038/srep46076 |
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author | Daughton, Ashlynn R. Generous, Nicholas Priedhorsky, Reid Deshpande, Alina |
author_facet | Daughton, Ashlynn R. Generous, Nicholas Priedhorsky, Reid Deshpande, Alina |
author_sort | Daughton, Ashlynn R. |
collection | PubMed |
description | Infectious diseases are a leading cause of death globally. Decisions surrounding how to control an infectious disease outbreak currently rely on a subjective process involving surveillance and expert opinion. However, there are many situations where neither may be available. Modeling can fill gaps in the decision making process by using available data to provide quantitative estimates of outbreak trajectories. Effective reduction of the spread of infectious diseases can be achieved through collaboration between the modeling community and public health policy community. However, such collaboration is rare, resulting in a lack of models that meet the needs of the public health community. Here we show a Susceptible-Infectious-Recovered (SIR) model modified to include control measures that allows parameter ranges, rather than parameter point estimates, and includes a web user interface for broad adoption. We apply the model to three diseases, measles, norovirus and influenza, to show the feasibility of its use and describe a research agenda to further promote interactions between decision makers and the modeling community. |
format | Online Article Text |
id | pubmed-5394686 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53946862017-04-20 An approach to and web-based tool for infectious disease outbreak intervention analysis Daughton, Ashlynn R. Generous, Nicholas Priedhorsky, Reid Deshpande, Alina Sci Rep Article Infectious diseases are a leading cause of death globally. Decisions surrounding how to control an infectious disease outbreak currently rely on a subjective process involving surveillance and expert opinion. However, there are many situations where neither may be available. Modeling can fill gaps in the decision making process by using available data to provide quantitative estimates of outbreak trajectories. Effective reduction of the spread of infectious diseases can be achieved through collaboration between the modeling community and public health policy community. However, such collaboration is rare, resulting in a lack of models that meet the needs of the public health community. Here we show a Susceptible-Infectious-Recovered (SIR) model modified to include control measures that allows parameter ranges, rather than parameter point estimates, and includes a web user interface for broad adoption. We apply the model to three diseases, measles, norovirus and influenza, to show the feasibility of its use and describe a research agenda to further promote interactions between decision makers and the modeling community. Nature Publishing Group 2017-04-18 /pmc/articles/PMC5394686/ /pubmed/28417983 http://dx.doi.org/10.1038/srep46076 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Daughton, Ashlynn R. Generous, Nicholas Priedhorsky, Reid Deshpande, Alina An approach to and web-based tool for infectious disease outbreak intervention analysis |
title | An approach to and web-based tool for infectious disease outbreak intervention analysis |
title_full | An approach to and web-based tool for infectious disease outbreak intervention analysis |
title_fullStr | An approach to and web-based tool for infectious disease outbreak intervention analysis |
title_full_unstemmed | An approach to and web-based tool for infectious disease outbreak intervention analysis |
title_short | An approach to and web-based tool for infectious disease outbreak intervention analysis |
title_sort | approach to and web-based tool for infectious disease outbreak intervention analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5394686/ https://www.ncbi.nlm.nih.gov/pubmed/28417983 http://dx.doi.org/10.1038/srep46076 |
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