The power of focused tests to detect disease clustering

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Abstract
Statistical tests have been proposed for determining whether incident cases of adverse health effects are ‘clustered’ together. Several procedures, termed ‘focused’, specifically analyse disease surveillance data around pre‐specified putative sources of environmental hazard. Little has been done to compare the performance of various proposed methods on actual models of clustering. Analytic power functions are derived for three tests of focused clustering. These functions are based on the probabilistic structure of the clustering tests and do not require simulation. The three tests are compared with respect to statistical power on hypothetical data where monotone multiplicative increases in disease risk near a putative hazard define disease clusters of varying intensity.