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Seong Sun Kim 1 Article
A review of mathematical models and strategies for Pandemic Influenza Control.
Seong Sun Kim, Sang Won Lee, Bo Youl Choi
Korean J Epidemiol. 2008;30(2):156-167.   Published online December 31, 2008
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AbstractAbstract PDF
Despite many countries' current effort to make mathematical models for pandemic influenza (PI) and predict the impact of an outbreak, natural history of PI is remains incomplete, so that any assumption or model is unable to completely predict the impact. Our objective is to review and summarize previous studies on parameters and models of PI, and to make suggestions for the controls in order to decrease the impact of PI. We searched PubMed to retrieve literature about the PI model systematically . Reference lists and review papers on the topic were searched, as well. We found 35 articles that examined the PI model over the period of May 2003 to August 2008. We reviewed modelling methods that were focused on the PI, and their parameters i.e. latent period, and basic reproductive number (R0). Then, we summarized PI controls: antivirals, vaccines, and social distancing. Recent studies showed with mathematical models that Targeted Antiviral Prophylaxis (TAP) is the best strategy for containing PI at the source. In case of an outbreak, quick measures of social distancing, including therapeutic and prophylatic antiviral for cases and closing contacts - school closure, workplace closure, border quarantine, and home isolation - were found to be most effective. We reviewed strengths and weaknesses of models that are adaptable in Korea, and summarized their parameters. It is our hope that these strategies with various interventions give important information for future preparation for and response to PI in Korea.


Citations to this article as recorded by  
  • Stochastic methods for epidemic models: An application to the 2009 H1N1 influenza outbreak in Korea
    Hyojung Lee, Sunmi Lee, Chang Hyeong Lee
    Applied Mathematics and Computation.2016; 286: 232.     CrossRef

Epidemiol Health : Epidemiology and Health