Validation of Analytic Methods for Combining Evidence Sources in Biosurveillance
PDF

How to Cite

Burkom, H., Elbert, Y., Ramac-Thomas, L., & Cuellar, C. (2014). Validation of Analytic Methods for Combining Evidence Sources in Biosurveillance. Online Journal of Public Health Informatics, 6(1). https://doi.org/10.5210/ojphi.v6i1.5201

Abstract

To manage an increasingly complex data environment, a fusion module based on Bayesian networks (BN) was developed for the Dept. of Defense (DoD) Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE).  Subsequent efforts have produced a full fusion-enabled version of ESSENCE for beta testing and further upgrades. The current presentation describes advances to formalize the network training, calibrate the component alerting algorithms and decision nodes together, and implement a validation strategy. A cross-validation strategy produced consistent threshold combinations yielding 88% sensitivity from reported events, a 10-15% improvement over the original demonstration module.
https://doi.org/10.5210/ojphi.v6i1.5201
PDF
Authors own copyright of their articles appearing in the Online Journal of Public Health Informatics. Readers may copy articles without permission of the copyright owner(s), as long as the author and OJPHI are acknowledged in the copy and the copy is used for educational, not-for-profit purposes. Share-alike: when posting copies or adaptations of the work, release the work under the same license as the original. For any other use of articles, please contact the copyright owner. The journal/publisher is not responsible for subsequent uses of the work, including uses infringing the above license. It is the author's responsibility to bring an infringement action if so desired by the author.