Albert Kim
Often media reports of a large number of cases of a disease within a small geographic area stoke public demand for investigation by health officials. The detection of such spatial clustering of diseases can be cast as a statistical problem for which numerous methodologies have been developed.
One popular method is the method of Kulldorff where multiple circles (whose radii are defined by population size) are superimposed onto a map of the study region. For each circle, the observed number of cases is compared to the expected number of cases, with circles with more cases than expected being labeled as potential clusters. Measures of the statistical significance of the excesses are obtained via Monte Carlo simulation under the null hypothesis. However, this method is frequentist in nature and hence suffers from drawbacks due to miscalibration of p-values and multiple testing.
