Author:
Daughton Ashlynn R.,Generous Nicholas,Priedhorsky Reid,Deshpande Alina
Abstract
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.
Publisher
Springer Science and Business Media LLC
Reference44 articles.
1. Lopez, A. D. et al. Global and regional burden of disease and risk factors, 2001: systematic analysis of population health data. The Lancet 367, 1747–1757, doi: 10.1016/S0140-6736(06)68770-9 (2006).
2. Abdallah, S. & Panjabi, R. Control of communicable diseases. In Public health guide in emergencies 284–369, 2 edn. http://www.jhsph.edu/research/centers-and-institutes/center-for-refugee-and-disaster-response/publications_tools/publications/_CRDR_ICRC_Public_Health_Guide_Book/Pages_from_Chapter_7_.pdf. (Johns Hopkins Bloomberg School of Public Health, 2008).
3. Murray, C. K. et al. An Approach to Prevention of Infectious Diseases during Military Deployments. Clinical Infectious Diseases 44, 424–430, doi: 10.1086/510680 (2007).
4. Frieden, T. R. et al. A CDC framework for preventing infectious diseases - Sustaining the essentials and innovating for the future. Tech. Rep. Centers for Disease Control and Prevention (CDC) (2011) http://www.cdc.gov/oid/docs/id-framework.pdf (Date of access: 7/27/16).
5. Brauer, F. et al. (eds) Mathematical Epidemiology, vol. 1945 of Lecture Notes in Mathematics (Springer, Berlin Heidelberg, 2008). http://link.springer.com/10.1007/978-3-540-78911-6.
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