Fast detection of arbitrarily shaped disease clusters.
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Date
2006
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Abstract
Disease cluster detection and evaluation have commonly used spatial statistics methods that scan the map with a fixed circular window to locate candidate clusters. Recently, there has been interest in searching for clusters with arbitrary shape. The circular scan test retains high power of detecting a cluster, but does not necessarily identify the exact regions contained in a non-circular cluster particularly well. We propose, implement and evaluate a new procedure that is fast and produces clusters estimates of arbitrary shape in a rich class of possible cluster candidates. We showed that our methods contain the so-called upper level set method as a particular case. We present a power study of our method and, among other results, the main conclusion is that the likelihood-based arbitrarily shaped scan method is not appropriate to _nd a cluster estimate. When the parameter space includes the set of all possible spatial clusters in a map, a large and discrete parameter space, maximum likely cluster estimates tend to overestimate the true cluster by a large extent. This calls for a new approach different from the maximum likelihood method for this important public health problem.
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Keywords
Disease clusters, Scan statistics, Spatial cluster, Spatial statistics
Citation
ASSUNÇÃO, R. M. et al. Fast detection of arbitrarily shaped disease clusters. Statistics in Medicine, v. 25, n. 1, p. 723-742, 2006. Disponível em: <http://onlinelibrary.wiley.com/doi/10.1002/sim.2411/pdf>. Acesso em: 12 nov. 2012