nonparametric intensity bounds for the delineation of spatial clusters文档.pdf

Oliveira et al. International Journal of Health Geographics 2011, 10:1 INTERNATIONAL JOURNAL /content/10/1/1 OF HEALTH GEOGRAPHICS METHODOLOGY Open Access Nonparametric intensity bounds for the delineation of spatial clusters 1,2 1* 3 4 Fernando LP Oliveira , Luiz H Duczmal , André LF Cançado , Ricardo Tavares Abstract Background: There is considerable uncertainty in the disease rate estimation for aggregated area maps, especially for small population areas. As a consequence the delineation of local clustering is subject to substantial variation. Consider the most likely disease cluster produced by any given method, like SaTScan, for the detection and inference of spatial clusters in a map divided into areas; if this cluster is found to be statistically significant, what could be said of the external areas adjacent to the cluster? Do we have enough information to exclude them from a health program of prevention? Do all the areas inside the cluster have the same importance from a practitioner perspective? Results: We propose a method to measure the plausibility of each area being part of a possible localized anomaly in the map. In this work we assess the problem of finding error bounds for the delineation of spatial clusters in maps of areas with known populations and observed number of cases. A given map with the vector of real data (the number of observed cases for each area) shall be considered as just one of the possible realizations of the random variable vector with an unknown expected number of cases. The method is tested in numerical simulations and applied for three different real data maps for sharply and diffusely delineated