original manuscript October 2008 (updated May 2009)
Epidemiological interventions aim to control the spread of infectious disease through various mechanisms, each carrying a different associated cost. Here we describe a flexible statistical framework for generating optimal epidemiological interventions that are designed to minimize the total expected cost of an emerging epidemic while simultaneously propagating uncertainty regarding underlying disease parameters through to the decision process. The strategies produced through this framework are adaptive: vaccination schedules are iteratively adjusted to reflect the anticipated trajectory of the epidemic given the current population state and updated parameter estimates. Using simulation studies based on a classic influenza outbreak, we demonstrate adaptive interventions to be both cost- and resource-efficient solutions to the problem of epidemiological control.
Keywords: SIR models, vaccination strategies, adaptive management, MCMC
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