Examining the Relationship between Anti-Black Racism, Community and Police Violence, and COVID-19 Vaccination

Abstract

In 2020, the COVID-19 pandemic emerged against a backdrop of long-standing racial inequities that contributed to significant disparities in COVID-19 mortality, morbidity, and eventually, vaccination rates. COVID-19 also converged with two social crises: anti-Black racism and community and police violence. The goal of this study was to examine the associations between community violence, police violence, anti-Black racism, and COVID-19 vaccination. Survey data were collected from a sample of 538 Black residents of Chicago between September 2021 and March 2022. Structural equation modeling was used to test associations between neighborhood violence, police violence, racism, medical mistrust, trust in COVID-related information, depressive symptoms, and having received a COVID-19 vaccination. In line with predictions, neighborhood violence had a significant indirect effect on vaccination via trust in COVID-related information from a personal doctor. Additionally, racism had a significant indirect effect on vaccination via trust in COVID-related information from a personal doctor, as well as via medical mistrust and trust in COVID-related information from a personal doctor. These findings add to the growing body of literature demonstrating the importance of medical mistrust when examining COVID-19 vaccination disparities. Furthermore, this study highlights the importance of considering how social and structural factors such as violence and racism can influence medical mistrust.

Keywords: COVID-19; medical mistrust; racial disparities; racism; vaccination.

Figure 1.

Structural equation model showing associations between experiences of violence and racism, medical mistrust, depressive symptoms, and having received a COVID-19 vaccination among Black Chicago residents (N = 538). The model was a good fit to the data, χ²(131, N = 538) = 243.51, p < .001, RMSEA = 0.04, CFI = 0.98, TLI = 0.98. Unstandardized coefficients are presented. Indicators of latent variables, residual correlations, and demographic covariates (age, gender, income, and underlying health conditions) are not shown. *** p < .001 ** p < .01 * p < .05