Selecting Essential Information for Biosurveillance – A Multi-Criteria Decision Analysis – International Society for Disease Surveillance


Thursday, December 12, 2013; 12:30 – 12:50pm


Grand Ballroom B


Eric Nicholas Generous, Los Alamos National Laboratory

Abstract Summary

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.

Abstract (pdf)

Abstract Citation

Online Journal of Public Health Informatics. 2014; 6(1). 

Presentation (pdf)