Selecting Essential Information for Biosurveillance - A Multi-Criteria Decision Analysis
Abstract
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Mar 09, 2014
- Source ID
- 10.5210/ojphi.v6i1.5165
Entities
People
- Alina Deshpande
- Andrea Hengartner
- Kirsten Taylor-mccabe
- Kristen Margevicius
- Lauren A Castro
- Mac Brown
- Nicholas Generous
- W. Brent Daniel