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Since the development of the COVID-19 vaccinations, questions surrounding race have been prominent in the literature on vaccine uptake. Early in the vaccine rollout, public health officials were concerned with the relatively lower rates of uptake among certain racial/ethnic minority groups. We suggest that this may also be patterned by racial/ethnic residential segregation, which previous work has demonstrated to be an important factor for both health and access to health care.

In this study, we examine county-level vaccination rates, racial/ethnic composition, and residential segregation across the U.S. We compile data from several sources, including the American Community Survey (ACS) and Centers for Disease Control (CDC) measured at the county level.

We find that just looking at the associations between racial/ethnic composition and vaccination rates, both percent Black and percent White are significant and negative, meaning that higher percentages of these groups in a county are associated with lower vaccination rates, whereas the opposite is the case for percent Latino. When we factor in segregation, as measured by the index of dissimilarity, the patterns change somewhat. Dissimilarity itself was not significant in the models across all groups, but when interacted with race/ethnic composition, it moderates the association. For both percent Black and percent White, the interaction with the Black-White dissimilarity index is significant and negative, meaning that it deepens the negative association between composition and the vaccination rate.

The analysis is only limited to county-level measures of racial/ethnic composition and vaccination rates, so we are unable to see at the individual-level who is getting vaccinated.

We find that segregation moderates the association between racial/ethnic composition and vaccination rates, suggesting that local race relations in a county helps contextualize the compositional effects of race/ethnicity.

This study compared different types of full-time caregiver (e.g., children, older adults, COVID-19 patients) and subgroups (e.g., disability, race/ethnicity, sexual orientation) in the United States during the COVID-19 pandemic for potentially meaningful distinctions.

Data from the 9,854 full-time caregivers identified in Phase 3.2 (July 21–October 11, 2021) of the US Census Household Pulse Survey (HPS) were analyzed in this study using multinomial logistic regression to examine relationships between caregiver types, marginalized subgroups, generation, and vaccination status.

The prevalence of caregiving was low, but the type of full-time caregiving performed varied by demographic group (i.e., disability, race/ethnicity, sexual orientation, gender, generation, and vaccination status). The relative risk of being a COVID-19 caregiver remained significant for being a member of each of the marginalized groups examined after all adjustments.

To date, the HPS has not been analyzed to predict the type of full-time informal caregiving performed during the COVID-19 pandemic or their characteristics. Research limitations of this analysis include the cross-sectional, experimental dataset employed, as well as some variable measurement issues.

Prior informal caregiver research has often focused on the experiences of those caring for older adults or children with special healthcare needs. It may be instructive to learn whether and how informal caregivers excluded from paid employment during infectious disease outbreaks vary in meaningful ways from those engaged in other full-time caregiving. Because COVID-19 magnified equity concerns, examining demographic differences may also facilitate customization of pathways to post-caregiving workforce integration.