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Activity Number:
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455
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Type:
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Invited
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Date/Time:
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Thursday, August 7, 2008 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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| Abstract - #300299 |
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Title:
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A Bayesian SEIR Approach to Modeling Epidemics
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Author(s):
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Vanja Dukic*+ and Greg Dwyer and Bret Elderd
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Companies:
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The University of Chicago and The University of Chicago and The University of Chicago
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Address:
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5841 S Maryland Ave, Chicago, IL, 60637,
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Keywords:
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Epidemics ; SEIR ; Spatial ; Stochastic ; vaccination ; smallpox
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Abstract:
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Recent U.S. public policy debates regarding smallpox vaccination were largely focused on comparing mass versus trace vaccination strategies; namely, whether to vaccinate the entire population or only those who have been in contact with infected individuals. In this talk, we present a Bayesian susceptible-exposed-infected-recovered (SEIR) model and apply it to analyze a set of eight smallpox epidemics in Southwest Native American communities during 1780--1781. The outcome of the model is the posterior distribution of epidemic parameters, after taking into account the population and geographical heterogeneity. We then present a comparison of the two main vaccination strategies based on the posterior predictive distribution of the fatalities under each.
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