Literature DB >> 23824973

A spatial scan statistic for compound Poisson data.

Rhonda J Rosychuk1, Hsing-Ming Chang.   

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.
Copyright © 2013 John Wiley & Sons, Ltd.

Keywords:  cluster detection; compound Poisson; spatial scan; surveillance

Mesh:

Year:  2013        PMID: 23824973     DOI: 10.1002/sim.5891

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  1 in total

1.  A log-Weibull spatial scan statistic for time to event data.

Authors:  Iram Usman; Rhonda J Rosychuk
Journal:  Int J Health Geogr       Date:  2018-06-13       Impact factor: 3.918

  1 in total

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