An approach to and web-based tool for infectious disease outbreak intervention analysis
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
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.
- Research Organization:
- Los Alamos National Laboratory (LANL)
- Sponsoring Organization:
- USDOE; Defense Threat Reduction Agency (DTRA) (United States)
- Grant/Contract Number:
- AC52-06NA25396
- OSTI ID:
- 1360707
- Report Number(s):
- LA-UR-16-26681
- Journal Information:
- Scientific Reports, Journal Name: Scientific Reports Vol. 7; ISSN 2045-2322
- Publisher:
- Nature Publishing GroupCopyright Statement
- Country of Publication:
- United States
- Language:
- English
A decision-support framework to optimize border control for global outbreak mitigation
|
journal | February 2019 |
| A decision-support framework to optimize border control for global outbreak mitigation | posted_content | September 2018 |
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