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Currently there is a worldwide warning for H5N1 avian influenza spreading as epidemic in humans as seasonal influenza, and possibly causing a pandemic of unprecedented proportions. Here we'll show you how epidemiological surveillance data for emerging infectious diseases can be used in real time to detect shifts in transmissibility with quantified uncertainty, as well as to perform running time estimates of new cases and guide logistics allocations. We propose a Bayesian model for real time estimation of the effective reproduction number and show how to use such inferences to conduct significance tests on future epidemiological data for emerging infectious diseases, which often have large relative case number fluctuations over time. We use the methodology to place limits on the latest transmissibility of H5N1 influenza in humans and establish a statistical basis for monitoring its evolution in real time.
Source link: https://www.osti.gov/biblio/1627350
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