Early detection of bioterrorism: Monitoring disease using an agent-based model

Abstract

We propose an agent-based model to capture the transmission patterns of diseases caused by bioterrorism attacks or epidemic outbreaks and to differentiate between these two scenarios. Focusing on a region of three cities, we want to detect a bioterrorism attack before a sizeable proportion of the population is infected. Our results indicate that the aggregated infection and death curves in the region can serve as indicators in distinguishing between the two disease scenarios: the slope of the epidemic infection curve will increase initially and decrease afterwards, whereas the slope of the bioterrorism infection curve will strictly decrease. We also conclude that for a bioterrorism outbreak, the bioterrorism source city becomes more dominant as the local working probability pL increases. In contrast, the behavior of individual cities for the epidemic model presents a “time-lag” pattern, especially when pL is large. As pL decreases, the individual city's dynamic curves converge as time progresses.