Spatial Scan Statistic

The spatial scan statistic is a likelihood-ratio method for detecting localized clusters of disease without pre-specifying where they are. Introduced by Martin Kulldorff and Neville Nagarwalla (1995) and generalized by Kulldorff (1997), it slides a circular window of varying size and position across the study region, and for each candidate window compares the observed-to-expected case ratio inside the window against outside it using a likelihood ratio under a Poisson or Bernoulli model. The window that maximizes the likelihood ratio is the most likely cluster, and its statistical significance is obtained by Monte Carlo simulation under the null of no clustering, which correctly accounts for the enormous multiplicity of windows examined. Implemented in the widely used SaTScan software, the method has become the standard tool for screening surveillance data for spatial and space-time disease clusters.