Determinants of COVID-19 vaccine acceptance in the US

Abstract

Background: The COVID-19 pandemic continues to adversely affect the U.S., which leads globally in total cases and deaths. As COVID-19 vaccines are under development, public health officials and policymakers need to create strategic vaccine-acceptance messaging to effectively control the pandemic and prevent thousands of additional deaths.

Methods: Using an online platform, we surveyed the U.S. adult population in May 2020 to understand risk perceptions about the COVID-19 pandemic, acceptance of a COVID-19 vaccine, and trust in sources of information. These factors were compared across basic demographics.

Findings: Of the 672 participants surveyed, 450 (67%) said they would accept a COVID-19 vaccine if it is recommended for them. Males (72%) compared to females, older adults (≥55 years; 78%) compared to younger adults, Asians (81%) compared to other racial and ethnic groups, and college and/or graduate degree holders (75%) compared to people with less than a college degree were more likely to accept the vaccine. When comparing reported influenza vaccine uptake to reported acceptance of the COVID-19 vaccine: 1) participants who did not complete high school had a very low influenza vaccine uptake (10%), while 60% of the same group said they would accept the COVID-19 vaccine; 2) unemployed participants reported lower influenza uptake and lower COVID-19 vaccine acceptance when compared to those employed or retired; and, 3) Black Americans reported lower influenza vaccine uptake and lower COVID-19 vaccine acceptance than all other racial groups reported in our study. Lastly, we identified geographic differences with Department of Health and Human Services (DHHS) regions 2 (New York) and 5 (Chicago) reporting less than 50 percent COVID-19 vaccine acceptance.

Interpretation: Although our study found a 67% acceptance of a COVID-19 vaccine, there were noticeable demographic and geographical disparities in vaccine acceptance. Before a COVID-19 vaccine is introduced to the U.S., public health officials and policymakers must prioritize effective COVID-19 vaccine-acceptance messaging for all Americans, especially those who are most vulnerable.

Keywords: COVID-19; Evidence-based messaging; Health disparities; Vaccine acceptance.

Conflict of interest statement

All authors declare no conflict of interest.

© 2020 The Authors.

Figures

Fig. 1

Participants enrollment in the survey. A total of 2,010 participants were invited to participate of which 938 were eligible to participate. Of these 938, 672 participants (72%) completed the survey. Eligible for survey: Participants who were 18 years and older, could read English, and had a working CloudResearch account. Quota overfill: Eligible participants who were unable to participate because the strata they were associated with was already adequately represented. As the survey was meant to be representative of the U.S. population, if certain strata reached its quota based on our sample size, other participants in that strata became ineligible to participate in the survey. Eligible to participate: Eligible participants who could complete the survey after removing ineligible and quota overfill participants from the invited participants.

Fig. 2

Comparison by demographic categories of the percent of the sample who reported receiving the influenza vaccine to those would reported they would accept the COVID-19 vaccine, Abbreviations: AI/AN: American Indian/Alaska Native, NH/PI: Native Hawaiian/Pacific Islander, Grad: Graduate or Professional Degree, *Age is listed in years.

Fig. 3

Comparison of COVID-19 vaccine acceptance (A) to reported influenza vaccine uptake (B) in the U.S. by Department of Health and Human Services region.

Fig. 4

Graph showing the% acceptance of COVID-19 vaccine plotted against the% coverage for influenza vaccine by state. The solid line is the line of best fit using linear regression (coefficient: 0·19; 95% CI: (-)0.19 – 0·57).

Fig. 5

ROC curve for the model logit (COVID-19 vaccine acceptance) = β0 + β1 age (26–35) + β2 age (36–45) + β3 age (46–55) + β4 age (55+) + β5 gender + β6 race (AI) + β7 race (Asian) + β8 race (PI) + β9 race (white) + β10 education (HS) + β11 education (SC) + β12 education (Col) + β13 education (GS).