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Title: An approach to and web-based tool for infectious disease outbreak intervention analysis

Abstract

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.

Authors:
 [1];  [1];  [1];  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE; Defense Threat Reduction Agency (DTRA) (United States)
OSTI Identifier:
1360707
Report Number(s):
LA-UR-16-26681
Journal ID: ISSN 2045-2322
Grant/Contract Number:  
AC52-06NA25396; CB10092; DTRA10027
Resource Type:
Accepted Manuscript
Journal Name:
Scientific Reports
Additional Journal Information:
Journal Volume: 7; Journal ID: ISSN 2045-2322
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 97 MATHEMATICS AND COMPUTING; Biological Science

Citation Formats

Daughton, Ashlynn R., Generous, Nicholas, Priedhorsky, Reid, and Deshpande, Alina. An approach to and web-based tool for infectious disease outbreak intervention analysis. United States: N. p., 2017. Web. doi:10.1038/srep46076.
Daughton, Ashlynn R., Generous, Nicholas, Priedhorsky, Reid, & Deshpande, Alina. An approach to and web-based tool for infectious disease outbreak intervention analysis. United States. doi:10.1038/srep46076.
Daughton, Ashlynn R., Generous, Nicholas, Priedhorsky, Reid, and Deshpande, Alina. Tue . "An approach to and web-based tool for infectious disease outbreak intervention analysis". United States. doi:10.1038/srep46076. https://www.osti.gov/servlets/purl/1360707.
@article{osti_1360707,
title = {An approach to and web-based tool for infectious disease outbreak intervention analysis},
author = {Daughton, Ashlynn R. and Generous, Nicholas and Priedhorsky, Reid and Deshpande, Alina},
abstractNote = {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.},
doi = {10.1038/srep46076},
journal = {Scientific Reports},
number = ,
volume = 7,
place = {United States},
year = {2017},
month = {4}
}

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