Spatial Analysis of Mental Health Outcomes in US Counties

Author(s): Biraj Neupane

This comprehensive spatial analysis investigates the complex relationships between mental health outcomes with two primary composite indices , the Social Vulnerability Index (SVI) computed as the average of normalized social determinant variables, and the Comorbidity Risk Index (CRI) calculated as the means of normalized chronic health condition variables, providing multidimensional vulnerability scores for comprehensive analysis. Using advanced geospatial statistical methods including Local Indicators of Spatial Association (LISA) and Geographically Weighted Regression (GWR), we identify significant clusters of depression and mental distress, model spatially varying relationships, and simulate targeted policy interventions with Monte Carlo methods. Our findings reveal distinct geographic patterns in mental health burdens and provide evidence-based insights for optimizing public health resource allocation through spatially-targeted interventions.

Keywords: Depression, GWR, LISA, mental distress, mental health, USA

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Biraj Neupane

University of Illinois at Urbana-Champaign




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