SaTScan

{{Short description|A free software for spatial, temporal, and space-time scan statistics}}

SaTScan is a software tool that employs scan statistics for the spatial and temporal analysis of clusters of events.{{cite web | last1=Kulldorff | first1=Martin|title=SaTScanJ User Guide | year=2022 |url=https://www.satscan.org/cgi-bin/satscan/register.pl/SaTScan_Users_Guide.pdf?todo=process_userguide_download |website=SaTScan |publisher=SaTScan™ |access-date=11 February 2023}}{{cite web |title=SaTScan™ - Spatial and Space-Time Scan Statistics |url=https://surveillance.cancer.gov/satscan/ |website=National Cancer Institute: The Division of Cancer Control and Population Sciences (DCCPS) |access-date=11 February 2023}}{{cite news |last1=Blair |first1=Kimberly |title=UWF students turn quality-of-life data detectives |url=https://www.pnj.com/story/news/2014/10/26/uwf-students-turn-quality-life-data-detectives/17983773/ |access-date=February 11, 2023 |work=Pensacola News Journal |date=October 26, 2014}}{{Cite book | last1 = Glaz | first1 = J. | last2 = Naus | first2 = J. | last3 = Wallenstein | first3 = S. | doi = 10.1007/978-1-4757-3460-7_1 | chapter = Introduction | title = Scan Statistics | series = Springer Series in Statistics | pages = 3–9| year = 2001 | isbn = 978-1-4419-3167-2 }} The software is trademarked by Martin Kulldorff, and was designed originally for public health and epidemiology to identify clusters of cases in both space (geographical location) and time and to perform statistical analysis to determine if these clusters are significantly different from what would be expected by chance{{cite journal |last1=Elias |first1=Johannes |last2=Harmsen |first2=Dag |last3=Claus |first3=Heike |last4=Hellenbrand |first4=Wiebke |last5=Frosch |first5=Matthias |last6=Vogel |first6=Ulrich |title=Spatiotemporal Analysis of Invasive Meningococcal Disease, Germany |journal=Emerging Infectious Diseases |date=2006 |volume=12 |issue=11 |pages=1689–1695 |doi=|url=https://stacks.cdc.gov/view/cdc/16407|pmid=17283618 |pmc=3372358 }}{{cite journal |last1=Yang |first1=Shu-qin |last2=Fang |first2=Zheng-gang |last3=Lv |first3=Cai-xia |last4=An |first4=Shu-yi |last5=Guan |first5=Peng |last6=Huang |first6=De-sheng |last7=Wu |first7=Wei |title=Spatiotemporal cluster analysis of COVID-19 and its relationship with environmental factors at the city level in mainland China |journal=Environmental Science and Pollution Research |date=February 2022 |volume=29 |issue=9 |pages=13386–13395 |doi=10.1007/s11356-021-16600-9|pmid=34595708 |pmc=8483427 |bibcode=2022ESPR...2913386Y }} The software provides a user-friendly interface and a range of statistical methods, making it accessible to researchers and practitioners.{{cite web |title=SaTScan |url=https://www.satscan.org/satscanlicenseagreement.pdf |website=SaTScan License Agreement |publisher=SaTScan™ |access-date=11 February 2023}} While not a full Geographic Information System, the outputs from SaTScan can be integrated with software such as ArcGIS or QGIS to visualize and analyze spatial data, and to map the distribution of various phenomena.

Analysis

SaTScan employs scan statistics to identify clusters of space and time phenomena. Scan statistics use regular shapes (usually circles) of varying sizes to evaluate a study area.{{cite journal |title=A spatial scan statistic |journal=Communications in Statistics – Theory and Methods |first=Martin |last=Kulldorff |volume=26 |issue=6 |date=1997 |pages=1481–1496 |url=http://www.satscan.org/papers/k-cstm1997.pdf|doi=10.1080/03610929708831995 }}{{cite book |last1=Cromley |first1=Ellen K. |last2=McLafferty |first2=Sara L. |title=GIS and Public Health |date=2002 |publisher=The Guilford Press |isbn=1-57230-707-2}} Within each circle, the software computes if the phenomena within the circle is significantly different than expected compared to the area outside the circle.

SaTScan can analyze data retrospectively or prospectively. It can look at the data spatially, temporally, or simultaneously incorporate both space and time. SaTScan can incorporate numerous probability models, including Poisson distribution, Bernoulli distribution, Monte Carlo method, and multinomial distribution. Using these, it can look for areas of higher and lower occurrences of phenomena than expected.

Results are output into a variety of formats, including ESRI Shapefile, HTML, and KML.

History

SaTScan was developed by a group of epidemiologists and statisticians led by Martin Kulldorff, a Swedish biostatistician professor of medicine at Harvard Medical School.{{cite web |title=Martin Kulldorff, Ph.D. |url=https://dc.hillsdale.edu/Academy-for-Science-and-Freedom/Martin-Kulldorf/ |website=Hillsdale College: Washington DC Campus |access-date=11 February 2023}} Version 1.0 of the software was first released in 1997 and has since become a widely used tool in the field of public health research and practice.{{cite web |title=SaTScan Version History |url=https://www.satscan.org/cgi-bin/satscan/register.pl/SaTScan_Version_History.pdf?todo=process_version_history_download |website=SaTScan |publisher=SaTScan™ |access-date=11 February 2023}}

SaTScan was developed in response to a growing need for sophisticated tools to analyze disease outbreaks. Before the development of SaTScan, few tools were available that could effectively analyze the spatial and temporal patterns of disease, making it difficult for public health authorities to respond effectively to outbreaks.

Since its release, SaTScan has been used in many public health research studies, including infectious diseases, cancers, and other conditions. Public health authorities and disease surveillance systems have also adopted the software in many countries, and it has broad applications for other types of data.

SaTScan was used extensively by researchers during the COVID-19 pandemic.{{cite journal |last1=Desjardins |first1=M.R. |last2=Hohl |first2=A. |last3=Delmelle |first3=E.M. |title=Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic: Detecting and evaluating emerging clusters |journal=Applied Geography |date=2020 |volume=118 |page=102202 |doi=10.1016/j.apgeog.2020.102202 |pmid=32287518 |pmc=7139246 |bibcode=2020AppGe.11802202D }}

Applications

=Epidemiology=

SaTScan was originally developed for epidemiology and public health. Since its release, SaTScan has been used in many public health research studies involving GIS, including infectious diseases, cancers, and other conditions. Public health authorities and disease surveillance systems have also adopted the software in many countries.

=Agriculture=

SaTScan can identify areas of high pest or disease risk, informing crop and livestock management and disease control efforts.{{cite journal |last1=Frössling |first1=Jenny |last2=Nødtvedt |first2=Ane |last3=Lindberg |first3=Ann |last4=Björkman |first4=Camilla |title=Spatial analysis of Neospora caninum distribution in dairy cattle from Sweden |journal=Geospatial Health |date=2008 |volume=3 |issue=1 |pages=39–45 |doi=10.4081/gh.2008.230 |pmid=19021107 |doi-access=free }}

=Astronomy=

SaTScan can also be adapted and applied to certain astronomical studies, particularly those that involve analyzing spatial and temporal patterns in astronomical data.{{cite journal |last1=de la Fuente Marcos |first1=R. |last2=de la Fuente Marcos |first2=C. |title=From Star Complexes to the Field: Open Cluster Families |journal=The Astrophysical Journal |date=January 2008 |volume=672 |issue=1 |pages=342–351 |doi=10.1086/524028 |bibcode=2008ApJ...672..342D |s2cid=250775794 |doi-access=free }} For example, SaTScan could identify clustering patterns in the distribution of galaxies or other astronomical objects, such as stars.

=Criminology=

SaTScan can identify hot spots and patterns in crime data, which can assist law enforcement agencies in allocating resources and developing crime reduction strategies.{{cite journal |last1=Zeoli |first1=April M. |last2=Pizarro |first2=Jesenia M. |last3=Grady |first3=Sue C. |last4=Melde |first4=Christopher |title=Homicide as Infectious Disease: Using Public Health Methods to Investigate the Diffusion of Homicide |journal=Justice Quarterly |date=12 Oct 2012 |volume=31 |issue=3 |pages=609–632 |doi=10.1080/07418825.2012.732100|s2cid=70487308 }}

=Environmental monitoring=

SaTScan can identify areas of environmental concern, such as high levels of air pollution or water contamination.{{cite journal |last1=Gao |first1=Jie |last2=Zhang |first2=Zhijie |last3=Hu |first3=Yi |last4=Jianchao |first4=Bian |last5=Jiang |first5=Wen |last6=Xiaoming |first6=Wang |last7=Liqian |first7=Sun |last8=Qingwu |first8=Jiang |title=Geographical Distribution Patterns of Iodine in Drinking-Water and Its Associations with Geological Factors in Shandong Province, China |journal=International Journal of Environmental Research and Public Health |date=2014 |volume=11 |issue=5 |pages=5431–5444 |doi=10.3390/ijerph110505431|pmid=24852390 |pmc=4053898 |doi-access=free }}

=Wildlive surveillance=

SaTScan can identify areas of high risk for wildlife diseases, which can inform disease management and conservation efforts.{{cite journal |last1=Carricondo-Sanchez |first1=David |last2=Odden |first2=Morten |last3=Linnell |first3=John D. C. |last4=Odden |first4=John |title=The range of the mange: Spatiotemporal patterns of sarcoptic mange in red foxes (Vulpes vulpes) as revealed by camera trapping |journal=PLOS ONE |date=April 19, 2017 |volume=12 |issue=4 |pages=e0176200 |doi=10.1371/journal.pone.0176200|pmid=28423011 |doi-access=free |pmc=5397041 |bibcode=2017PLoSO..1276200C }}