Spatial modeling of mental health on outpatient morbidity in Kenya

TL;DR

This study uses spatial modeling to analyze the distribution of mental health issues in Kenya, revealing regional disparities and correlations with infectious diseases, thereby aiding targeted healthcare interventions.

Contribution

It introduces a spatial modeling approach to map mental health distribution and its association with infectious diseases in Kenya, informing resource allocation and policy development.

Findings

Higher mental health disorder prevalence in Western and Nairobi regions

Significant correlation between infectious diseases and mental health issues

Spatial model demonstrated high validity and accuracy

Abstract

A mental health disorder is a clinically significant impairment in a persons intellect, emotional control, or behavior. Mental disorders and outpatient morbidity are a challenge to public health in Kenya. The spatial distribution and study of factors associated with these conditions remain limited. The study aimed to conduct spatial modeling of mental health on outpatient mobility in Kenya. This project used spatial modeling to explore the relationship between infectious diseases and mental disorders. The results showed that mental health issues were not distributed uniformly, with higher frequency found in Western and Nairobi regions. Possible connections between HIV, TB, and STIs with mental health have been suggested by the substantial correlation found between infectious diseases and mental health issues. The spatial model demonstrated excellent validity and accuracy, providing policymakers with a useful tool to better allocate resources and enhance mental health treatments, especially in high-risk locations. In conclusion, the research improved knowledge of the spatial patterns of mental health disorders and guides intervention tactics and healthcare policies in Kenya and other comparable settings. Geographically tailored mental health intervention programs should be developed and implemented in accordance with the high-prevalence areas.