Characterising resilient and at-risk neighbourhoods with lower-than-expected and higher-than-expected firearm injuries and fatalities in Pittsburgh, Pennsylvania.

Introduction: Firearm injuries and fatalities adversely affect individual and community health and are important public health issues. Identifying factors that protect against firearm violence and related harms is needed. We aimed to identify neighbourhoods with lower-than-expected and higher-than-expected firearm injuries and fatalities based on social vulnerability and their differing structural and social characteristics.

Methods: We used Gun Violence Archive data from the RISE Lab Firearm Injury Data Hub to estimate firearm injury and fatality counts between 2015 and 2020 in Pittsburgh, Pennsylvania. We used a negative binomial regression model to estimate the relationship between the Centers for Disease Control and Prevention's social vulnerability index and firearm injuries and fatalities, and the residual percentile method to identify neighbourhoods with lower (resilient) and higher (at-risk) counts than expected based on social vulnerability. T-tests were used to compare resilient and at-risk neighbourhoods for 158 US Census American Community Survey demographic, socioeconomic, housing and transportation variables.

Results: Resilient neighbourhoods (n=19, bottom quartile residuals) had lower rates of firearm injuries and fatalities (p=0.0002) compared with at-risk neighbourhoods (n=19, top quartile residuals). Resilient and at-risk neighbourhoods differed for 2 (per cent male never married and female widowed) of the variables included in the analyses.

Conclusions: Some neighbourhoods, despite facing risk factors, experienced fewer firearm injuries and fatalities than would be expected based on neighbourhood social vulnerability. Existing sources of secondary data on neighbourhoods may fail to adequately capture potential factors that prevent against firearm violence and to measure resilience in thriving neighbourhoods. Future community-engaged studies are needed to understand and measure neighbourhood-level protective factors.