Background The pandemic highlighted geographic inequities in COVID-19 mortality worldwide, reflecting structural and social vulnerabilities that exacerbated respiratory disease outcomes. The primary aim of this study was to examine the spatial relationship between COVID-19 mortality and communities characterized by greater social disadvantage in North Carolina. This application highlights the value of spatial analytic approaches when considering inequities in respiratory mortality. Methods This study analyzed 25,051 COVID-19 deaths occurring in North Carolina from March 2020 through April 2022 using state vital statistics data and the Centers for Disease Control and Prevention, Social Vulnerability Index data. SaTScan™ was used to identify mortality hot spots, and Moran’s I in ArcGIS Pro was used to assess spatial autocorrelation at the ZIP-Code Tabulation Area level. The Mann–Whitney U test was used to assess differences in social vulnerability index scores in mortality hot spots areas and non-hot spots areas. Results Local bivariate analysis identified moderate spatial clustering characterized by high–high (mortality–vulnerability) hot spots and spatial outliers. In non-parametric testing, COVID-19 mortality hot spot areas had significantly higher, but modestly elevated, median overall social vulnerability index scores compared with non–hot spot areas (0.58 vs. 0.45; p < 0.001). Conclusions Social vulnerability partially explains the observed spatial heterogeneity in COVID-19 mortality (2020–2022), with statistically significant spatial clustering consistently concentrated in areas of higher social vulnerability. This study highlights how pre-existing inequities in healthcare access and social conditions intensified mortality disparities during the pandemic.
Kearney et al. (2026) studied this question.