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Applying an Evolutionary Algorithm for the Analysis of Mental Disorders in Macro-urban Areas: The Case of Barcelona

Abstract Spatial analysis is widely used to study geographic patterns of diseases. To locate groups of close spatial units where the treated prevalence is significantly high or low, the latest contribution is a tool based on a Multi-objective Evolutionary Algorithm, which has not yet been used in macro-urban areas: this study is the first attempt for this purpose. To do so, spatial distribution of the treated prevalence of mental disorders in basic health areas was analysed within the Barcelona metropolitan zone during 2009. The results highlight inequitable zones that need further attention, and geographically weighted regression shows that socio-economic factors influence treated prevalence although there may be additional factors involved.