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.

References in zbMATH (referenced in 28 articles )

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  1. Silva, Ivair R.; Duczmal, Luiz; Kulldorff, Martin: Confidence intervals for spatial scan statistic (2021)
  2. Kurihara, Koji; Ishioka, Fumio; Kajinishi, Shoji: Spatial and temporal clustering based on the echelon scan technique and software analysis (2020)
  3. Allévius, Benjamin; Höhle, Michael: An unconditional space-time scan statistic for ZIP-distributed data (2019)
  4. Ishioka, Fumio; Kawahara, Jun; Mizuta, Masahiro; Minato, Shin-ichi; Kurihara, Koji: Evaluation of hotspot cluster detection using spatial scan statistic based on exact counting (2019)
  5. Veloso, Bráulio M.; Correa, Thais R.; Prates, Marcos O.; Oliveira, Gabriel F.; Tavares, Andréa I.: \textitMAD-STEC: a method for multiple automatic detection of space-time emerging clusters (2017)
  6. Maëlle Salmon; Dirk Schumacher; Michael Höhle: Monitoring Count Time Series in R: Aberration Detection in Public Health Surveillance (2016) not zbMATH
  7. Sharpnack, James; Arias-Castro, Ery: Exact asymptotics for the scan statistic and fast alternatives (2016)
  8. Sinha, Arun Kumar; Kumar, Mukesh: Poverty analysis using scan statistic methods (2016)
  9. Srivastava, Pankaj; Sinha, Arun Kumar: Spatial analysis of AFP surveillance strategy for polio eradication in India (2016)
  10. Markus Loecher; Karl Ropkins: RgoogleMaps and loa: Unleashing R Graphics Power on Map Tiles (2015) not zbMATH
  11. Forbes, Florence; Charras-Garrido, Myriam; Azizi, Lamiae; Doyle, Senan; Abrial, David: Spatial risk mapping for rare disease with hidden Markov fields and variational EM (2013)
  12. Wan, You; Pei, Tao; Zhou, Chenghu; Jiang, Yong; Qu, Chenxu; Qiao, Youlin: ACOMCD: A multiple cluster detection algorithm based on the spatial scan statistic and ant colony optimization (2012) ioport
  13. Tango, Toshiro; Takahashi, Kunihiko; Kohriyama, Kazuaki: A space-time scan statistic for detecting emerging outbreaks (2011)
  14. Cook, Andrea J.; Li, Yi; Arterburn, David; Tiwari, Ram C.: Spatial cluster detection for weighted outcomes using cumulative geographic residuals (2010)
  15. Jiang, Xia; Cooper, Gregory F.: A real-time temporal Bayesian architecture for event surveillance and its application to patient-specific multiple disease outbreak detection (2010) ioport
  16. Jiang, Xia; Neill, Daniel B.; Cooper, Gregory F.: A Bayesian network model for spatial event surveillance (2010) ioport
  17. Assunção, Renato; Correa, Thais: Surveillance to detect emerging space-time clusters (2009)
  18. Chan, Hock Peng: Detection of spatial clustering with average likelihood ratio test statistics (2009)
  19. Huang, Lan; Tiwari, Ram C.; Zou, Zhaohui; Kulldorff, Martin; Feuer, Eric J.: Weighted normal spatial scan statistic for heterogeneous population data (2009)
  20. Liang, Shengde; Carlin, Bradley P.; Gelfand, Alan E.: Analysis of Minnesota colon and rectum cancer point patterns with spatial and nonspatial covariate information (2009)

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