Research evaluating the use of spatial data for surveillance purposes is ongoing and evolving. As spatial methods evolve, it is important to characterize their effectiveness in real-world settings. Assessing the performance of surveillance systems has been difficult because there has been a paucity of data from real bioterrorism events. Recent efforts to assess surveillance system performance have focused on injecting synthetic outbreak data (signal) into actual background visit data. These studies focused on either temporal data, a single syndrome category, or a single bioterrorism agent. We are unaware of prior studies evaluating the performance of spatial outbreak detection for multiple syndrome categories in an operational surveillance system.
Objective
To characterize the performance of a spatial scan statistic, we used SaTScan to measure the sensitivity and positive predictive value for detecting simulated outbreaks having varying size, case density, and syndrome type.