Epidemic Simulation for Syndromic Surveillance

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.