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Title:Measuring the uncertainties of pandemic influenza
Int. J. of Risk Assessment and Management > 2012 Vol.16, No.1/2/3 > pp.1 - 27
Author: Jeanne M. Fair; Dennis R. Powell; Rene J. LeClaire; Leslie M. Moore; Michael L. Wilson; Lori R. Dauelsberg; Michael E. Samsa; Sharon M. DeLand; Gary Hirsch; Brian W. Bush
DOI: 10.1504/12.47550
Abstract: It has become critical to assess the potential range of consequences of a pandemic influenza outbreak given the uncertainty about its disease characteristics while investigating risks and mitigation strategies of vaccines, antivirals, and social distancing measures. Here, we use a simulation model and rigorous experimental design with sensitivity analysis that incorporates uncertainty in the pathogen behaviour and epidemic response to show the extreme variation in the consequences of a potential pandemic outbreak in the USA. Using sensitivity analysis we found the most important disease characteristics are the fraction of the transmission that occur prior to symptoms, the reproductive number, and the length of each disease stage. Using data from the historical pandemics and for potential viral evolution, we show that response planning may underestimate the pandemic consequences by a factor of two or more.
http://www.inderscience.com/info/inarticle.php?artid=47550
Int. J. of Risk Assessment and Management > 2012 Vol.16, No.1/2/3 > pp.1 - 27
Author: Jeanne M. Fair; Dennis R. Powell; Rene J. LeClaire; Leslie M. Moore; Michael L. Wilson; Lori R. Dauelsberg; Michael E. Samsa; Sharon M. DeLand; Gary Hirsch; Brian W. Bush
DOI: 10.1504/12.47550
Abstract: It has become critical to assess the potential range of consequences of a pandemic influenza outbreak given the uncertainty about its disease characteristics while investigating risks and mitigation strategies of vaccines, antivirals, and social distancing measures. Here, we use a simulation model and rigorous experimental design with sensitivity analysis that incorporates uncertainty in the pathogen behaviour and epidemic response to show the extreme variation in the consequences of a potential pandemic outbreak in the USA. Using sensitivity analysis we found the most important disease characteristics are the fraction of the transmission that occur prior to symptoms, the reproductive number, and the length of each disease stage. Using data from the historical pandemics and for potential viral evolution, we show that response planning may underestimate the pandemic consequences by a factor of two or more.
http://www.inderscience.com/info/inarticle.php?artid=47550