Development of a new spatial analysis tool in mental health: identification of highly autocorrelated areas (hot-spots) of schizophrenia using a Multiobjective Evolutionary Algorithm model (MOEA/HS).
Epidemiol Psichiatr Soc
; 19(4): 302-13, 2010.
Article
en En
| MEDLINE
| ID: mdl-21322504
AIMS: This study had two objectives: (1) to design and develop a computer-based tool, called Multi-Objective Evolutionary Algorithm/Hot-Spots (MOEA/HS), to identify and geographically locate highly autocorrelated zones or hot-spots and which merges different methods, and (2) to carry out a demonstration study in a geographical area where previous information about the distribution of schizophrenia prevalence is available and which can therefore be compared. METHODS: Local Indicators of Spatial Aggregation (LISA) models as well as the Bayesian Conditional Autoregressive Model (CAR) were used as objectives in a multicriteria framework when highly autocorrelated zones (hot-spots) need to be identified and geographically located. A Multi-Objective Evolutionary Algorithm (MOEA) model was designed and used to identify highly autocorrelated areas of the prevalence of schizophrenia in Andalusia. Hot-spots were statistically identified using exponential-based QQ-Plots (statistics of extremes). RESULTS: Efficient solutions (Pareto set) from MOEA/HS were analysed statistically and one main hot-spot was identified and spatially located. Our model can be used to identify and locate geographical hot-spots of schizophrenia prevalence in a large and complicated region. CONCLUSIONS: MOEA/HS enables a compromise to be achieved between different econometric methods by highlighting very special zones in complex areas where schizophrenia shows a high autocorrelation.
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Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Esquizofrenia
/
Algoritmos
/
Modelos Estadísticos
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
País/Región como asunto:
Europa
Idioma:
En
Revista:
Epidemiol Psichiatr Soc
Asunto de la revista:
EPIDEMIOLOGIA
/
PSIQUIATRIA
Año:
2010
Tipo del documento:
Article
País de afiliación:
España
Pais de publicación:
Italia