Race-ethnicity and COVID-19 Vaccination Beliefs and Intentions: A Cross-Sectional Study among the General Population in the San Francisco Bay Area

  1. Yingjie Weng
  2. Di Lu
  3. Jenna Bollyky
  4. Vivek Jain
  5. Manisha Desai
  6. Christina Lindan
  7. Derek Boothroyd
  8. Timothy Judson
  9. Sarah B. Doernberg
  10. Marisa Holubar
  11. Hannah Sample
  12. Beatrice Huang
  13. Yvonne Maldonado
  14. George W. Rutherford
  15. Kevin Grumbach
  16. on behalf of the California Pandemic Consortium

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Abstract

Objective: The study was designed to compare intentions to receive COVID-19 vaccination by race–ethnicity, to identify beliefs that may mediate the association between race–ethnicity and intention to receive the vaccine and to identify the demographic factors and beliefs most strongly predictive of intention to receive a vaccine. Design: Cross-sectional survey conducted from November 2020 to January 2021, nested within a longitudinal cohort study of the prevalence and incidence of SARS-CoV-2 among a general population-based sample of adults in six San Francisco Bay Area counties (called TrackCOVID). Study Cohort: In total, 3161 participants among the 3935 in the TrackCOVID parent cohort responded. Results: Rates of high vaccine willingness were significantly lower among Black (41%), Latinx (55%), Asian (58%), Multi-racial (59%), and Other race (58%) respondents than among White respondents (72%). Black, Latinx, and Asian respondents were significantly more likely than White respondents to endorse lack of trust of government and health agencies as a reason not to get vaccinated. Participants’ motivations and concerns about COVID-19 vaccination only partially explained racial–ethnic differences in vaccination willingness. Concerns about a rushed government vaccine approval process and potential bad reactions to the vaccine were the two most important factors predicting vaccination intention. Conclusions: Vaccine outreach campaigns must ensure that the disproportionate toll of COVID-19 on historically marginalized racial–ethnic communities is not compounded by inequities in vaccination. Efforts must emphasize messages that speak to the motivations and concerns of groups suffering most from health inequities to earn their trust to support informed decision making.

Article activity feed

  1. Version published to 10.3390/vaccines9121406
  2. Version published to 10.1101/2021.04.26.21255893v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.04.26.21255893: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsField Sample Permit: Study design and population: We conducted a cross-sectional survey9 from late November, 2020 to January, 2021, nested within two longitudinal cohort studies of prevalence and incidence of SARS CoV-2 among (1) community-residing adults (the TrackCOVID study) and (2) medical center employees (the COVID-19 Healthcare Worker Antibody and Reverse Transcription (RT) PCR Tracking study, CHART).
    IRB: The TrackCOVID study was designated as a public health surveillance study and not human subjects research under 45 CFR 46.102(l) by Stanford University School of Medicine Administrative Panel on Human Subjects in Medical Research and UCSF Institutional Review Board; the CHART study protocol was approved by the UCSF Institutional Review Board and the Stanford University School of Medicine Panel on Human Subjects in Medical Research.
    Sex as a biological variablenot detected.
    RandomizationThe TrackCOVID study recruited randomly selected community members residing in six San Francisco Bay Area counties, with enrollment occurring between July and December, 2020.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Participants in both cohorts were sent an electronic survey about COVID-19 vaccination with Research Electronic Data Capture Software (REDCap).
    REDCap
    suggested: (REDCap, RRID:SCR_003445)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Study limitations include sampling dates that were relatively early after the arrival of the Pfizer and Moderna vaccines to the US landscape. As such, they represent early views of healthcare workers and the general public and may not account for shifts in viewpoints, increasing confidence, or other changes in opinions in recent months as the US vaccination campaign has expanded greatly. Our survey sample was drawn from people sufficiently concerned about their risk of COVID-19 and trusting of research to volunteer for studies involving repeated COVID-19 testing. Self-selection may bias our results towards greater willingness to be vaccinated compared with the vaccine willingness of all medical center employees and community residents in the region studied. However, self-selection is less likely to introduce bias when testing associations of variables within the study cohorts, such as associations between race-ethnicity and vaccine intentions or between perceptional factors and intentions. It is striking that even within groups of individuals motivated to participate in longitudinal COVID-19 surveillance, large racial-ethnic differences exist in COVID-19 vaccination intentions and reasons not to get vaccinated. Our sample is from a single region in California, which may limit generalizability. Our survey may not have addressed certain domains that might influence intentions, such as concerns about access to vaccines. Our primary outcome was self-reported vaccine intention and...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a protocol registration statement.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  4. Version published to 10.1101/2021.04.26.21255893v1 on medRxiv