Bayesian Methods for Syndromic Surveillance

Abstract:

OBJECTIVE This paper describes a Bayesian approach to syndromic surveillance. The method provides more interpretable inference than traditional frequentist approaches. Bayesian methods avoid many of the problems associated with alpha levels and multiple comparisons, and make better use of prior information. The technique is illustrated on simulated data.

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