{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T15:46:42Z","timestamp":1787240802945,"version":"build-2736575974"},"reference-count":32,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2013,1,1]],"date-time":"2013-01-01T00:00:00Z","timestamp":1356998400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Health\ufffdServ\ufffdInsights"],"published-print":{"date-parts":[[2013,1]]},"abstract":"<jats:p>The field of medical geographic information systems (Medical GIS) has become extremely useful in understanding the bigger picture of public health. The discipline holds a substantial capacity to understand not only differences, but also similarities in population health all over the world. The main goal of marrying the disciplines of medical geography, public health and informatics is to understand how countless health issues impact populations, and the trends by which these populations are affected. From the 1990s to today, this practical approach has become a valued and progressive system in analyzing medical and epidemiological phenomena ranging from cholera to cancer. The instruments supporting this field include geographic information systems (GIS), disease surveillance, big data, and analytical approaches like the Geographical Analysis Machine (GAM), Dynamic Continuous Area Space Time Analysis (DYCAST), cellular automata, agent-based modeling, spatial statistics and self-organizing maps. The positive effects on disease mapping have proven to be tremendous as these instruments continue to have a great impact on the mission to improve worldwide health care. While traditional uses of GIS in public health are static and lacking real-time components, implementing a space-time animation in these instruments will be monumental as technology and data continue to grow.<\/jats:p>","DOI":"10.4137\/hsi.s10471","type":"journal-article","created":{"date-parts":[[2013,11,19]],"date-time":"2013-11-19T15:39:52Z","timestamp":1384875592000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":102,"title":["Use of GIS Mapping as a Public Health Tool\u2013-From Cholera to Cancer"],"prefix":"10.4137","volume":"6","author":[{"given":"George J.","family":"Musa","sequence":"first","affiliation":[{"name":"Child Psychiatric Epidemiology Group, Columbia University, New York State Psychiatric Group;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Po-Huang","family":"Chiang","sequence":"additional","affiliation":[{"name":"National Health Research Institutes, Taiwan, Republic of China (ROC)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tyler","family":"Sylk","sequence":"additional","affiliation":[{"name":"Child Psychiatric Epidemiology Group, Columbia University, New York State Psychiatric Group;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rachel","family":"Bavley","sequence":"additional","affiliation":[{"name":"Child Psychiatric Epidemiology Group, Columbia University, New York State Psychiatric Group;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"William","family":"Keating","sequence":"additional","affiliation":[{"name":"Child Psychiatric Epidemiology Group, Columbia University, New York State Psychiatric Group;"},{"name":"Department of Geography, Hunter College, City University of New York, NYC, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bereketab","family":"Lakew","sequence":"additional","affiliation":[{"name":"Child Psychiatric Epidemiology Group, Columbia University, New York State Psychiatric Group;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui-Chen","family":"Tsou","sequence":"additional","affiliation":[{"name":"National Health Research Institutes, Taiwan, Republic of China (ROC)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christina W.","family":"Hoven","sequence":"additional","affiliation":[{"name":"Child Psychiatric Epidemiology Group, Columbia University, New York State Psychiatric Group;"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2013,11,19]]},"reference":[{"key":"bibr1-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.1016\/S0277-9536(01)00210-6"},{"key":"bibr2-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.1016\/S0277-9536(99)00344-5"},{"key":"bibr3-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.2307\/1790244"},{"key":"bibr4-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.2307\/210033"},{"key":"bibr5-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.2307\/210990"},{"issue":"4","key":"bibr6-HSI.S10471","first-page":"379","volume":"67","author":"Meade M.S.","year":"1977","journal-title":"American Geographical Society."},{"key":"bibr7-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(88)90352-2"},{"key":"bibr8-HSI.S10471","doi-asserted-by":"crossref","unstructured":"A Mark 1 Geographical Analysis Machine for the automated analysis of point data sets STAN OPENSHAW, MARTIN CHARLTON, COLIN WYMER, ALAN CRAFT International Journal of Geographical Information Systems Vol. 1, Iss. 4, 1987.","DOI":"10.1080\/02693798708927821"},{"key":"bibr9-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-publhealth-031811-124655"},{"key":"bibr10-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.3201\/eid0202.960202"},{"key":"bibr11-HSI.S10471","unstructured":"AlbertD.P., GeslerW.M., HornerR.D. Geographic Information Systems in Health Services Research 2000."},{"key":"bibr12-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.1186\/1476-072X-7-63"},{"key":"bibr13-HSI.S10471","volume-title":"GIS and Public Health.","author":"Gromley E.K.","year":"2002"},{"key":"bibr14-HSI.S10471","volume-title":"GIS and Health.","author":"Wilkinson P.","year":"1998"},{"key":"bibr15-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.publhealth.24.012902.141012"},{"key":"bibr16-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.1111\/j.0033-0124.1982.00261.x"},{"key":"bibr17-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.1559\/152304007781002190"},{"key":"bibr18-HSI.S10471","author":"Chiang P.C.","year":"2013","journal-title":"5th International Conference on Medical Geology; 2nd Symposium on Advances in Geospatial Technologies for Health."},{"key":"bibr19-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.1007\/s101090050035"},{"key":"bibr20-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.1023\/B:JOMS.0000032850.04124.33"},{"key":"bibr21-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.1078\/1438-4639-00145"},{"key":"bibr22-HSI.S10471","unstructured":"KopecekP. Geographic information systems and healthcare. Healthcare Informatics. Available at www.pages.drexel.edu\/~pk347\/eport\/GIS%20and%20Healthcare.doc; 648\u2013900. Accessed September 21, 2013."},{"key":"bibr23-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kwg046"},{"key":"bibr24-HSI.S10471","first-page":"27","author":"Kwan M.P.","year":"2004","journal-title":"Spatially Integrated Social Science."},{"key":"bibr25-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.1016\/S0968-090X(00)00017-6"},{"key":"bibr26-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.1007\/s101090300104"},{"key":"bibr27-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.1111\/j.1538-4632.1998.tb00396.x"},{"key":"bibr28-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.1111\/0033-0124.00158"},{"key":"bibr29-HSI.S10471","unstructured":"ManyikaJ., ChuiM., BrownB. Big data: The next frontier for innovation, competition, and productivity. 2011; McKinsey Global Institute. Available at http:\/\/www.mckinsey.com\/insights\/business_technology\/big_data_the_next_frontier_for_innovation. Accessed September 21, 2013."},{"key":"bibr30-HSI.S10471","doi-asserted-by":"publisher","DOI":"10.12794\/tef.2006.209"},{"key":"bibr31-HSI.S10471","unstructured":"SAS. What Is Big Data? 2013; Available at http:\/\/www.sas.com\/big-data. Accessed May 22, 2013."},{"key":"bibr32-HSI.S10471","first-page":"1","author":"Zia K.","year":"2013","journal-title":"Simulation."}],"container-title":["Health Services Insights"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.4137\/HSI.S10471","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.4137\/HSI.S10471","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.4137\/HSI.S10471","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T08:09:33Z","timestamp":1777450173000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.4137\/HSI.S10471"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,1]]},"references-count":32,"alternative-id":["10.4137\/HSI.S10471"],"URL":"https:\/\/doi.org\/10.4137\/hsi.s10471","relation":{},"ISSN":["1178-6329","1178-6329"],"issn-type":[{"value":"1178-6329","type":"print"},{"value":"1178-6329","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,1]]},"article-number":"HSI.S10471"}}