Purpose

SaTScan™ is a free software that analyzes spatial, temporal and space-time data using the spatial, temporal, or space-time scan statistics. It is designed for any of the following interrelated purposes:

• Perform geographical surveillance of disease, to detect spatial or space-time disease clusters, and to see if they are statistically significant.
• Test whether a disease is randomly distributed over space, over time or over space and time.
• Evaluate the statistical significance of disease cluster alarms.
• Perform repeated time-periodic disease surveillance for early detection of disease outbreaks.

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

Data Types and Methods

SaTScan uses either a Poisson-based model, where the number of events in a geographical 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; a space-time permutation model, using only case data; an ordinal model, for ordered categorical data; an exponential model for survival time data with or without censored variables; or a normal model for other types of continuous data. The data may be either aggregated at the census tract, zip code, county or other geographical level, or there may be unique coordinates for each observation. SaTScan adjusts for the underlying spatial inhomogeneity of a background population. It can also adjust for any number of categorical covariates provided by the user, as well as for temporal trends, known space-time clusters and missing data. It is possible to scan multiple data sets simultaneously to look for clusters that occur in one or more of them.

Developers and Funders

The SaTScan™ software was developed by Martin Kulldorff together with Information Management Services Inc. Financial support for SaTScan has been received from the following institutions:

• National Cancer Institute, Division of Cancer Prevention, Biometry Branch [v1.0, 2.0, 2.1]
• National Cancer Institute, Division of Cancer Control and Population Sciences, Statistical Research and Applications Branch [v3.0 (part), v6.1 (part), 8.0 (part), v9.0 (part)]
• Alfred P. Sloan Foundation, through grant to the New York Academy of Medicine [SaTScan v3.0 (part), 3.1, 4.0, 5.0, 5.1] and the Fund for Public Health in New York City [v10.0 (part)]
• Centers for Disease Control and Prevention, through Association of American Medical Colleges Cooperative Agreement award number MM-0870 [SaTScan v6.0, 6.1 (part)] and ELC CARES grant NU50CK000517-01-09 [v10.0 (part)]
• National Institute of Child Health and Development, through grant #RO1HD048852 [7.0, 8.0, 9.0 (part)]
• National Cancer Institute, Division of Cancer Epidemiology and Genetics [v9.0 (part)]
• National Institute of General Medical Sciences, through a Modelling Infectious Disease Agent Studies grant #U01GM076672.[v9.0 (part),9.1]
• CDC Foundation, through a grant to the Fund for Public Health in NYC [v10.0 (part]]

Their financial support is greatly appreciated. The contents of SaTScan are the responsibility of the developer and do not necessarily reflect the official views of the funders.