Assunção, Renato MartinsCosta, Marcelo AzevedoTavares, Andréa IabrudiFerreira, Sabino José2012-11-122012-11-122006ASSUNÇÃO, 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. 201210970258http://www.repositorio.ufop.br/handle/123456789/1766Disease 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.en-USDisease clustersScan statisticsSpatial clusterSpatial statisticsArtigo publicado em periodico