Identifying High-Risk Cardiac Arrest Neighborhoods Using Social Vulnerability Index and Geospatial Analysis

Abstract

BACKGROUND: Identifying high-risk locations for out-of-hospital cardiac arrest (OHCA) Is essential for targeted community Interventions. We aimed to use the Social Vulnerability Index (SVI) and geospatial mapping of OHCA data to locate high-risk neighborhoods in Birmingham, Alabama, for community training programs. METHODS: A retrospective observational analysis was conducted using nontraumatlc OHCA cases In adults (>18years) in Birmingham from January 1, 2020 to December 31, 2023. Census tracts served as proxies for neighborhoods. A 5-step process Identified high-risk tracts: (1) OHCA Incidents were geocoded in ArcGIS and assigned a geographic Identifier by census tract; (2) SVI data were merged with each record; (3) the Getls-Ord GI* statistic Identified a hot spot with 99% confidence; (4) tracts with an SVI >90th percentile within the hot spot were flagged; and (5) excess relative risk rates were calculated and stratified by quintiles. The primary outcome was high-risk census tracts defined by hot spot location, high SVI, and high relative risk. RESULTS: A total of 966 OHCA cases from 115 census tracts were included. Hot spot analysis Identified 30 tracts (26.1%) with high-risk characteristics. Within these, 17 tracts had an SVI >90th percentile, and 10 tracts had an excess relative risk In the top quintile. Hot spot tracts had a higher proportion of Black residents and lower cardiopulmonary resuscitation rates. No significant difference in survival outcomes were observed; however, the overall neurologically intact survival was 1.2%. CONCLUSIONS: Multiple neighborhoods In Birmingham exhibit extreme levels of social vulnerability and excess relative risk of OHCA, making them ideal candidates for community training Initiatives.