SaTScan™ - Spatial and Space-Time Scan Statistics

The SaTScan™ software analyzes spatial, temporal and space-time point data using the spatial, temporal, or space-time scan statistic. Versions 1 and 2 were originally developed by Martin Kulldorff when he was a member of the Biometry Research Group, Division of Cancer Prevention, NCI. His development of Version 3.0 was partly funded by NCI, through the Statistical Research and Applications Branch of the Division of Cancer Control and Population Sciences and partly by the Alfred P. Sloan FoundationExternal Website Policy. To obtain the latest version of SaTScan visit www.satscan.orgExternal Website Policy.

SaTScan is designed for any of the following interrelated purposes:

  • To evaluate reported spatial or space-time disease clusters, to see if they are statistically significant.
  • To test whether a disease is randomly distributed over space, over time or over space and time.
  • To perform geographical surveillance of disease, to detect areas of significantly high or low rates.
  • To perform repeated time-periodic disease surveillance for the early detection of disease outbreaks.

SaTScan uses either a Poisson-based model, where the number of events in an area is Poisson distributed according to a known underlying population at risk; a Bernoulli model, with 0/1 event data such as cases and controls; or a space-time Permutation model, using only case data. For all models, SaTScan adjusts for the underlying inhomogeneity of a background population. For the Poisson model, it can also adjust for any number of categorical covariates provided by the user.

The program may also be used for similar problems in other fields such as archaeology, astronomy, criminology, ecology, economics, engineering, genetics, geography, geology, history or zoology.