Int J Health Geogr - An exact test to detect geographic aggregations of events.

Tópicos

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Resumo

CKGROUND: Traditional approaches to statistical disease cluster detection focus on the identification of geographic areas with high numbers of incident or prevalent cases of disease. Events related to disease may be more appropriate for analysis than disease cases in some contexts. Multiple events related to disease may be possible for each disease case and the repeated nature of events needs to be incorporated in cluster detection tests.RESULTS: We provide a new approach for the detection of aggregations of events by testing individual administrative areas that may be combined with their nearest neighbours. This approach is based on the exact probabilities for the numbers of events in a tested geographic area. The test is analogous to the cluster detection test given by Besag and Newell and does not require the distributional assumptions of a similar test proposed by Rosychuk et al. Our method incorporates diverse population sizes and population distributions that can differ by important strata. Monte Carlo simulations help assess the overall number of clusters identified. The population and events for each area as well as a nearest neighbour spatial relationship are required. We also provide an alternative test applicable to situations when only the aggregate number of events, and not the number of events per individual, are known. The methodology is illustrated on administrative data of presentations to emergency departments.CONCLUSIONS: We provide a new method for the detection of aggregations of events that does not rely on distributional assumptions and performs well.

Resumo Limpo

ckground tradit approach statist diseas cluster detect focus identif geograph area high number incid preval case diseas event relat diseas may appropri analysi diseas case context multipl event relat diseas may possibl diseas case repeat natur event need incorpor cluster detect testsresult provid new approach detect aggreg event test individu administr area may combin nearest neighbour approach base exact probabl number event test geograph area test analog cluster detect test given besag newel requir distribut assumpt similar test propos rosychuk et al method incorpor divers popul size popul distribut can differ import strata mont carlo simul help assess overal number cluster identifi popul event area well nearest neighbour spatial relationship requir also provid altern test applic situat aggreg number event number event per individu known methodolog illustr administr data present emerg departmentsconclus provid new method detect aggreg event reli distribut assumpt perform well

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