ArticleEpidemic Simulation for Syndromic SurveillanceClarke, Thomas L. PhD; Liberman, Aaron PhD; Wang, Morgan PhD; Nieves, Kourtney PhD; Cattani, Jacqueline PhD; Sumner, Jennifer MSAuthor Information Author Affiliations: Institute for Simulation and Training (Dr Clarke), Department of Statistics (Dr Wang), and College of Health and Public Affairs (Drs Liberman, Nieves, and Ms Sumner), University of Central Florida, Orlando, Florida; and Center for Biological Defense, University of South Florida, Tampa, Florida (Dr Cattani). Corresponding author: Thomas L. Clarke, PhD, Institute for Simulation and Training, University of Central Florida, 3100 Technology Parkway Orlando, FL 32826 ([email protected]). The Health Care Manager: October 2007 - Volume 26 - Issue 4 - p 297-302 doi: 10.1097/01.HCM.0000299246.76312.f6 Buy Metrics Abstract This article reports on a project to develop a simulation-based test bed for the BioDefend Syndromic Surveillance System. BioDefend is a system that data mines syndrome reports from emergency rooms and so forth to produce early alerts of epidemic onset. An existing large-scale epidemic simulation will be adapted to provide synthetic reports of syndromes associated with extremely rare events such as pandemics and bioterrorism. The Spatiotemporal Epidemiological Modeler will be used as the basis of the test bed. Results from the much simpler Spatiotemporal Epidemiological Modeler simulation will be validated by comparison against results from the more complex Epidemiological Simulation System. These synthesized reports will be used to test BioDefend's ability to detect epidemic outbreaks and to evaluate its data-mining algorithm. The development of an optimal algorithm for processing syndrome reports to provide reliable epidemic early warnings is a difficult research problem that the test bed should help address. © 2007 Lippincott Williams & Wilkins, Inc.