This paper is in the following e-collection/theme issue:

Population and Public Health Informatics (100) Use Cases in Human, Animal, and Zoonotic Communicable/Infectious Disease Surveillance (129)

Published on in Vol 3, No 3 (2011):

Probabilistic, Decision-theoretic Disease Surveillance and Control

Probabilistic, Decision-theoretic Disease Surveillance and Control

Probabilistic, Decision-theoretic Disease Surveillance and Control

Authors of this article:

Michael Wagner1 ;   Fuchiang Tsui1 ;   Gregory Cooper1 ;   Jeremy Espino1 ;   Hendrik Harkema1 ;   John Levander1 ;   Ricardo Villamarin1 ;   Ronald Voorhees2 ;   Nicholas Millett1 ;   Christopher Keane2 ;   Anind Dey3 ;   Manik Razdan2 ;   Yang Hu4 ;   Ming Tsai1 ;   Shawn Brown2 ;   Bruce Y Lee2 ;   Anthony Gallagher5 ;   Margaret Potter2
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    The Pittsburgh Center of Excellence in Public Health Informatics has developed a probabilistic, decision-theoretic system for disease surveillance and control for use in Allegheny County, PA and later in Tarrant County, TX. This paper describes the software components of the system and its knowledge bases. The paper uses influenza surveillance to illustrate how the software components transform data collected by the healthcare system into population level analyses and decision analyses of potential outbreak-control measures.