PloS one · 2026
Social vulnerability and spatial patterns of COVID-19 mortality: Global implications for respiratory health equity.
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Kearney Gregory D, Obi Ogugua Ndili, Maddipati Veeranna, Levitin Gregory, Hu Guangxiao
Аннотация
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.
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.