Scan Statistic Cluster Detection

The spatial scan statistic, introduced by Martin Kulldorff in 1997, is a method for detecting and testing the significance of spatial clusters of events such as disease cases. It moves windows of many sizes and positions across the study region, treating each window as a candidate cluster, and scores it by a likelihood ratio comparing the rate of events inside the window to the rate outside. The window with the highest score is the most likely cluster, and its significance is assessed by Monte Carlo simulation, giving a principled answer to the recurring question of whether an apparent hotspot is real or chance.