Assessing the effectiveness of biosurveillance via discrete event simulation

Abstract

Bioterrorism is not a new threat, but the potential for disastrous outcomes is greater than it has ever been. In order to confront this threat, biosurveillance systems are utilized to provide early warning of health threats, early detection of health events, and situational awareness of disease activity. To date, there is little known about the performance of such biosurveillance systems in comparison to diagnosis capabilities of medical personnel. In this thesis, a discrete event simulation model of an anthrax outbreak is developed in order to analyze the performance of such biosurveillance systems in comparison to medical personnel. This research found the Early Aberration Reporting System C1 statistical algorithm is useful in early event detection of a bioterror attack. Given an exposed population of 1,000 people, the nominal probability that the algorithm signals first is 31.5% and it is 0.3% for an exposed population of 10,000 people. Given an exposed population of 1,000 people, the nominal time it takes for the algorithm to signal is 3.3 days and 0.38 days for an exposed population of 10,000 people.