A Bayesian Biosurveillance Method That Models Unknown Outbreak Diseases

Algorithms for detecting anomalous events can be divided into those that are designed to detect specific diseases and those that are non-specific in what they detect. Specific detection methods determine if patterns in the data are consistent with known outbreak diseases, as for example influenza. These methods are usually Bayesian. Non-specific detection methods attempt broadly to detect deviations from some model of the non-outbreak situation, regardless of which disease might be causing the deviation. Many frequentist outbreak detection methods are non-specific. In this paper, we introduce a Bayesian approach for detecting both specific and non-specific disease outbreaks, and we report a preliminary study of the approach.

• Type: Conference
• Year: 2007
• Where: BIOSURVEILLANCE
• Authors: Yanna Shen, Gregory F. Cooper
• Keywords: BIOSURVEILLANCE 2007, Detection Methods, Non-specific Detection Methods, Non-specific Disease Outbreaks, Security Privacy