SPATIAL DISEASE CLUSTERS - DETECTION AND INFERENCE

We present a new method of detection and inference for spatial cluster s of a disease. To avoid ad hoc procedures to test for clustering, we have a clearly defined alternative hypothesis and our test statistic i s based on the likelihood ratio. The proposed test can detect clusters of any size, located anywhere in the study region. It is not restrict ed to clusters that conform to predefined administrative or political borders. The test can be used for spatially aggregated data as well as when exact geographic co-ordinates are known for each individual. We illustrate the method on a data set describing the occurrence of leuka emia in Upstate New York.