A spatial scan statistic for compound Poisson data

Rhonda J. Rosychuk, Hsing Ming Chang

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

The topic of spatial cluster detection gained attention in statistics during the late 1980s and early 1990s. Effort has been devoted to the development of methods for detecting spatial clustering of cases and events in the biological sciences, astronomy and epidemiology. More recently, research has examined detecting clusters of correlated count data associated with health conditions of individuals. Such a method allows researchers to examine spatial relationships of disease-related events rather than just incident or prevalent cases. We introduce a spatial scan test that identifies clusters of events in a study region. Because an individual case may have multiple (repeated) events, we base the test on a compound Poisson model. We illustrate our method for cluster detection on emergency department visits, where individuals may make multiple disease-related visits.

Original languageEnglish
Pages (from-to)5106-5118
Number of pages13
JournalStatistics in Medicine
Volume32
Issue number29
DOIs
Publication statusPublished - 2013 Dec 20

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Statistics and Probability

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