Chapter

Detecting Disease Clustering in Time or Space

Lance A. Waller

in Monitoring the Health of Populations

Published in print December 2003 | ISBN: 9780195146493
Published online September 2009 | e-ISBN: 9780199864928 | DOI: http://dx.doi.org/10.1093/acprof:oso/9780195146493.003.0007
Detecting Disease Clustering in Time or Space

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This chapter focuses on the detection of clusters of incidence or prevalence of some health event in time or space. Each statistical test of clustering is based on some mathematical model that provides the type of spatial pattern expected in the absence of clustering. Tests rely on data summaries (statistics) to reveal particular deviations from the null hypothesis (i.e., the model of non-clustering). Different tests are sensitive to different types of clusters. The distinction between tests of clustering and tests to detect clusters, and the distinction between general and focused tests offer broad classes of differing sets of alternative hypotheses. The issue of varying sensitivity between methods to particular types of clusters is particularly important in interpreting the results of different tests applied to the same data. Tests designed to detect different types of clusters may support different conclusions for the same data.

Keywords: public health surveillance; public health monitoring; disease outbreaks; data clusters; spatial clustering; score test; Tango's index

Chapter.  13618 words.  Illustrated.

Subjects: Public Health and Epidemiology

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