Grant Number:	7R01CA165057-09 Interpret this number
Primary Investigator:	Kulldorff, Martin
Organization:	Brigham And Women'S Hospital
Project Title:	SATSCAN: Spatial Scan Statistic Surveillance Software II
Fiscal Year:	2016

DESCRIPTION (provided by applicant): SaTScan is a free statistical disease surveillance software package implementing the spatial, temporal and spatio-temporal scan statistics. It is used by many scientists and public health officials across the United States and around the world for geographical disease cluster detection and evaluation, and for the early detection of disease outbreaks. With the software, it is possible to determine whether disease cases are randomly distributed over space and/or time, or whether there are statistically significant spatial, temporal and/or spatio-temporal clusters with more (or fewer) cases than expected. Critically, it adjusts for the multiple testing inherent in the many possible cluster locations and sizes evaluated, as well as for covariates. As the number of users increase, there is an increasing number of requests for new SaTScan features and functionalities, including integration with geographical information systems and statistical software packages, graphical output functionalities, power evaluation tools, more general analysis options, and easy to use training material. In this project, we propose to further develop and maintain the SaTScan software to fulfill many of these needs.




Border analysis for spatial clusters.
Authors: Oliveira F.L.P. , Cançado A.L.F. , de Souza G. , Moreira G.J.P. , Kulldorff M. .
Source: International Journal Of Health Geographics, 2018-02-17 00:00:00.0; 17(1), p. 5.
EPub date: 2018-02-17 00:00:00.0.
PMID: 29454357
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Geographic Clusters of Basal Cell Carcinoma in a Northern California Health Plan Population.
Authors: Ray G.T. , Kulldorff M. , Asgari M.M. .
Source: Jama Dermatology, 2016-11-01 00:00:00.0; 152(11), p. 1218-1224.
PMID: 27439152
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Daily Reportable Disease Spatiotemporal Cluster Detection, New York City, New York, Usa, 2014-2015
Authors: Greene S.K. , Peterson E.R. , Kapell D. , Fine A.D. , Kulldorff M. .
Source: Emerging Infectious Diseases, 2016 Oct; 22(10), p. 1808-12.
PMID: 27648777
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Local spatial clustering in youths' use of tobacco, alcohol, and marijuana in Boston.
Authors: Duncan D.T. , Rienti M. , Kulldorff M. , Aldstadt J. , Castro M.C. , Frounfelker R. , Williams J.H. , Sorensen G. , Johnson R.M. , Hemenway D. , et al. .
Source: The American Journal Of Drug And Alcohol Abuse, 2016 Jul; 42(4), p. 412-21.
PMID: 27096932
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Public domain small-area cancer incidence data for New York State, 2005-2009.
Authors: Boscoe F.P. , Talbot T.O. , Kulldorff M. .
Source: Geospatial Health, 2016-04-18 00:00:00.0; 11(1), p. 304.
EPub date: 2016-04-18 00:00:00.0.
PMID: 27087033
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Comments on 'a critical look at prospective surveillance using a scan statistic' by T. Correa, M. Costa, and R. Assunção.
Authors: Kulldorff M. , Kleinman K. .
Source: Statistics In Medicine, 2015-03-30 00:00:00.0; 34(7), p. 1094-5.
PMID: 25754922
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Geographical Clusters Of Rape In The United States: 2000-2012
Authors: Amin R. , Nabors N.S. , Nelson A.M. , Saqlain M. , Kulldorff M. .
Source: Statistics And Public Policy (philadelphia, Pa.), 2015; 2(1), p. 87-92.
PMID: 28078318
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Relative risk estimates from spatial and space-time scan statistics: are they biased?
Authors: Prates M.O. , Kulldorff M. , Assunção R.M. .
Source: Statistics In Medicine, 2014-07-10 00:00:00.0; 33(15), p. 2634-44.
EPub date: 2014-07-10 00:00:00.0.
PMID: 24639031
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Influence of spatial resolution on space-time disease cluster detection.
Authors: Jones S.G. , Kulldorff M. .
Source: Plos One, 2012; 7(10), p. e48036.
PMID: 23110167
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