Thursday, December 12, 2013; 12:30 – 12:50pm
Location
Grand Ballroom B
Presenter
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)