Benchmarking of temporal surveillance techniques is a critical step in the development of an effective syndromic surveillance system. Unfortunately, holding “bakeoffs” to blindly compare approaches is a difficult and often fruitless enterprise, in part due to the parameters left to the final user for tuning. In this paper, we demonstrate how common analytical development and analysis may be coupled with realistic data sets to provide insight and robustness when selecting a surveillance technique.
OBJECTIVE
This paper compares the robustness and performance of three temporal surveillance techniques using a twofold approach: 1) a unifying statistical analysis to establish their common features and differences, and 2) a benchmarking on respiratory, influenza-like ill-nesses, upper GI, and lower GI complaint time series from the Harvard Pilgrim Health Care (HPHC).