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Such a measure would facilitate the assignment of cases to common groups and be useful in outbreak investigations of diseases that potentially share the same source. This paper presents a model\u2010based approach, which on the basis of available location data, provides a measure of the strength of association between cases in space and time and which is used to designate and visualise the most likely groupings of cases. The method was developed as a prospective surveillance tool to signal potential outbreaks, but it may also be used to explore groupings of cases in outbreak investigations. We demonstrate the method by using a historical case series of Legionnaires\u2019 disease amongst residents of England and Wales. Copyright \u00a9 2013 John Wiley &amp; Sons, Ltd.<\/jats:p>","DOI":"10.1002\/sim.5765","type":"journal-article","created":{"date-parts":[[2013,3,12]],"date-time":"2013-03-12T21:52:41Z","timestamp":1363125161000},"page":"3522-3538","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["A case\u2010association cluster detection and visualisation tool with an application to Legionnaires\u2019 disease"],"prefix":"10.1002","volume":"32","author":[{"given":"P.","family":"Sansom","sequence":"first","affiliation":[{"name":"Microbial Risk Assessment, Emergency Response Department Health Protection Agency  Porton Down, Salisbury Wiltshire, SP4 0JG U.K."},{"name":"College of Engineering, Mathematics and Physical Sciences University of Exeter  Harrison Building, Streatham Campus, North Park Road Exeter EX4 4QF U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"V. 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