Selecting Essential Information for Biosurveillance - A Multi-Criteria Decision Analysis

Nicholas Generous, Kristen Margevicius, Kirsten Taylor-McCabe, Mac Brown, W. Brent Daniel, Lauren Castro, Andrea Hengartner, Alina Deshpande


This paper proposes the use of Multi-Attribute Utility Theory to address the issue of identifying and selecting essential information for inclusion into a biosurveillance system or process. We developed a decision support framework that can facilitate identifying data streams for use in biosurveillance systems or processes and demonstrated utility by applying the framework to the problem of evaluating data streams for use in an global infectious disease surveillance system.

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Online Journal of Public Health Informatics * ISSN 1947-2579 *