A Computational Approach to Analyzing Spatiotemporal Trends in Gun Violence and Mental Health Disparities among Racialized Communities in US Metropolitan Areas.

Gun violence is a leading cause of death and injuries in the USA, adversely affecting physical and mental health among its survivors. Declared as a public health crisis in 2024, It disproportionately affects African Americans. It is linked to discriminatory policies like "redlining," which fostered racial segregation and systemic inequities, perpetuating cycles of violence and mental health disparities. This study explores the relationships between racial segregation, systemic inequities, gun violence, and mental health through a data-driven, longitudinal study (2005-2021) of Milwaukee, WI, a hyper segregated metropolitan region. Our investigation aims to inform evidence-based, place-sensitive policies to promote social justice, reduce disparities, and foster healthy communities. Utilizing location-based demographic and socio-economic data from the U.S. Census, gun violence data from the Wisconsin Incident-Based Reporting System, and mental health data from the CDC's PLACES dataset, we conduct spatial and temporal analyses and geovisualization in GIS. To understand trends and correlations, we conduct time series decomposition, Mann-Kendall trend tests, and entropy statistics. Our findings indicate that racially segregated neighborhoods experience higher rates of gun violence and poorer mental health outcomes. Predominantly African American neighborhoods exhibit patterns of "consecutive," "sporadic," and "new" hotspots of gun violence, while predominantly white neighborhoods are characterized as "cold spots." Physical and mental health disparities in Milwaukee indicate similar patterns. The results of this study highlight the profound impact of historical and systemic socioeconomic discrimination on contemporary public health issues.