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

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dc.contributor.authorJosé A. Salinas-Pérez
dc.contributor.authorMaria Luisa Rodero‐Cosano
dc.contributor.authorCarlos R. García‐Alonso
dc.contributor.authorLuis Salvador‐Carulla
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T14:52:16Z
dc.date.available2026-03-22T14:52:16Z
dc.date.issued2015
dc.descriptionCitaciones: 8
dc.description.abstractSpatial 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.
dc.identifier.doi10.1080/17421772.2015.1062125
dc.identifier.urihttps://doi.org/10.1080/17421772.2015.1062125
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/49034
dc.language.isoen
dc.publisherRoutledge
dc.relation.ispartofSpatial Economic Analysis
dc.sourceLoyola University of Congo
dc.subjectMetropolitan area
dc.subjectMacro
dc.subjectGeographically Weighted Regression
dc.subjectGeography
dc.subjectMental health
dc.subjectDistribution (mathematics)
dc.subjectDemography
dc.subjectRegional science
dc.subjectComputer science
dc.subjectCartography
dc.titleApplying an Evolutionary Algorithm for the Analysis of Mental Disorders in Macro-urban Areas: The Case of Barcelona
dc.typearticle

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