García Alonso, Carlos

Rodero Cosano, María Luisa

Salinas Pérez, José Alberto

The spatial data analysis is a methodology which is widely used to study geographic patterns of
diseases. Some of the most popular and effective tools are Local Indicators of Spatial
Association. Among these, highlight Moran’s I and Getis &Ord’s G

Brújula - Repositorio Institucional

Title: Applying evolutionary algorithm for the study of mental disorder prevalence: the case of the Barcelona metropolitan area.  Authors & affiliations: J.A. Salinas-Pérez*1, M.L. Rodero-Cosano1, C.R. García-Alonso1 1Universidad Loyola Andalucía jsalinas@uloyola.es  Abstract:  The spatial data analysis is a methodology which is widely used to study geographic patterns of diseases. Some of the most popular and effective tools are Local Indicators of Spatial Association. Among these, highlight Moran’s I and Getis &Ord’s G.  The last contribution in this field is a tool based on a Multi-Objective Evolutionary Algorithm, which optimizes the following spatial objectives: i) maximizing (hot spot) or minimizing (cold spot) mental disorders treated prevalence, ii) minimizing standard deviation of the prevalence, iii) minimizing the distance between spatial units.  The algorithm starts to optimize a solution that has been generated randomly by genetic operators (selection, mutation and crossover) in an iterative process by which the solutions are improved in successive generations. The results of each generation are assessed by four fitness functions which highlight the efficiency of the results to solve the spatial problem. The solutions can be different from each fitness function, so the final results will be those identified by at least two functions.  This method has been applied in regional analysis previously, but it has not yet been validated in macro urban areas, being this the first time that it is used for this. To do so, data from the Minimum Data Set for Outpatient Mental Health Centers were analyzed to identify the hot and cold spots of mental disorders prevalence in basic health areas within Barcelona metropolitan zone during 2009. The results obtained are consistent with the solutions of both classical Local Indicators of Spatial Association. View publication stats

Applying evolutionary algorithm for the study of mental disorder prevalence: the case of the Barcelona metropolitan area

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