Demographic Determinants and Geographical Variability of COVID-19 Vaccine Hesitancy in Underserved Communities: Cross-sectional Study.

BACKGROUND: COVID-19 hospitalizations and deaths disproportionately affect underserved and minority populations, emphasizing that vaccine hesitancy can be an especially important public health risk factor in these populations. OBJECTIVE: This study aims to characterize COVID-19 vaccine hesitancy in underserved diverse populations. METHODS: The Minority and Rural Coronavirus Insights Study (MRCIS) recruited a convenience sample of adults (age≥18, N=3735) from federally qualified health centers (FQHCs) in California, the Midwest (Illinois/Ohio), Florida, and Louisiana and collected baseline data in November 2020-April 2021. Vaccine hesitancy status was defined as a response of "no" or "undecided" to the question "Would you get a coronavirus vaccine if it was available?" ("yes" categorized as not hesitant). Cross-sectional descriptive analyses and logistic regression models examined vaccine hesitancy prevalence by age, gender, race/ethnicity, and geography. The expected vaccine hesitancy estimates for the general population were calculated for the study counties using published county-level data. Crude associations with demographic characteristics within each region were assessed using the chi-square test. The main effect model included age, gender, race/ethnicity, and geographical region to estimate adjusted odds ratios (ORs) and 95% CIs. Interactions between geography and each demographic characteristic were evaluated in separate models. RESULTS: The strongest vaccine hesitancy variability was by geographic region: California, 27.8% (range 25.0%-30.6%); the Midwest, 31.4% (range 27.3%-35.4%); Louisiana, 59.1% (range 56.1%-62.1%); and Florida, 67.3% (range 64.3%-70.2%). The expected estimates for the general population were lower: 9.7% (California), 15.3% (Midwest), 18.2% (Florida), and 27.0% (Louisiana). The demographic patterns also varied by geography. An inverted U-shaped age pattern was found, with the highest prevalence among ages 25-34 years in Florida (n=88, 80.0%,) and Louisiana (n=54, 79.4%; P<.05). Females were more hesitant than males in the Midwest (n= 110, 36.4% vs n= 48, 23.5%), Florida (n=458, 71.6% vs n=195, 59.3%), and Louisiana (n= 425, 66.5% vs. n=172, 46.5%; P<.05). Racial/ethnic differences were found in California, with the highest prevalence among non-Hispanic Black participants (n=86, 45.5%), and in Florida, with the highest among Hispanic (n=567, 69.3%) participants (P<.05), but not in the Midwest and Louisiana. The main effect model confirmed the U-shaped association with age: strongest association with age 25-34 years (OR 2.29, 95% CI 1.74-3.01). Statistical interactions of gender and race/ethnicity with the region were significant, following the pattern found by the crude analysis. Compared to males in California, the associations with the female gender were strongest in Florida (OR=7.88, 95% CI 5.96-10.41) and Louisiana (OR=6.09, 95% CI 4.55-8.14). Compared to non-Hispanic White participants in California, the strongest associations were found with being Hispanic in Florida (OR=11.18, 95% CI 7.01-17.85) and Black in Louisiana (OR=8.94, 95% CI 5.53-14.47). However, the strongest race/ethnicity variability was observed within California and Florida: the ORs varied 4.6- and 2-fold between racial/ethnic groups in these regions, respectively. CONCLUSIONS: These findings highlight the role of local contextual factors in driving vaccine hesitancy and its demographic patterns.

The Impact of COVID-19 on African American Communities in the United States.

Purpose: The purpose of this ecological study was to understand the impact of the density of African American (AA) communities on coronavirus disease 2019 (COVID-19) prevalence and death rate within the three most populous counties in each U.S. state and territory (n=152). Methods: An ecological design was employed for the study. The top three most populous counties of each U.S. state and territory were included in analyses for a final sample size of n=152 counties. Confirmed COVID-19 cases and deaths that were accumulated between January 22, 2020 and April 12, 2020 in each of the three most populous counties in each U.S. state and territory were included. Linear regression was used to determine the association between AA density and COVID-19 prevalence (defined as the percentage of cases for the county population), and death rate (defined as number of deaths per 100,000 population). The models were adjusted for median age and poverty. Results: There was a direct association between AA density and COVID-19 prevalence; COVID-19 prevalence increased 5% for every 1% increase in county AA density (p<0.01). There was also an association between county AA density and COVID-19 deaths; the death rate increased 2 per 100,000 for every percentage increase in county AA density (p=0.02). Conclusion: These findings indicate that communities with a high AA density have been disproportionately burdened with COVID-19. To help develop effective interventions and programs that address this disparity, further study is needed to understand social determinants of health driving inequities for this community.