Consumer Insights Blog

Who’s More Likely to Receive the COVID-19 Vaccine?

Personal characteristics and situational circumstances are potential explanations for why some people receive the vaccine while others do not.

Therefore, we wanted to understand differences in ethnicity, age, political affiliation, income, gender¹, area lived in, and occupation with regards to vaccination. To examine these potential demographic differences, we analyzed the data from Decision Analyst’s monthly “Consumer Foresight: Beyond The Pandemic” tracker².

Who’s Less Likely To Receive the Vaccine?

People of color³ are .73 times less likely to receive the COVID-19 vaccine than people who are not of color. Individuals who live in rural areas are .65 times less likely to receive the vaccine compared with those who do not live in rural areas. Republicans are .65 times less likely to receive the vaccine than other political affiliations and younger individuals (18 to 64 years) are .35 times less likely to receive the COVID-19 vaccine compared with older (65+) individuals⁴.

Who’s More Likely to Receive the Vaccine?

Alternatively, Democrats are 2.7 times more likely than other political affiliations to receive the vaccine. Individuals who are retired are 1.9 times more likely than those who are not retired to receive the COVID-19 vaccine. Those who work in the professional or medical occupations are 1.9 times more likely to receive the vaccine compared with individuals who do not work in those fields. Older adults (65+) are 1.9 times more likely to receive the vaccine than younger adults. Individuals who identify with the Independent political affiliation are 1.5 times more likely than other political affiliations to receive the vaccine. As income increases⁵, respondents are 1.5 times more likely to receive the vaccine. White people are 1.4 times more likely to receive the COVID-19 vaccine compared to non-white people.

Why Are There Differences?

The vaccine rollout method explains some of these results. Vaccines were first available to those in the medical field, those with underlying health conditions, and those over the age of 65. Each of these populations has a greater risk of contracting COVID-19 and dying from it. This explains why these groups are more likely to receive the vaccine – the vaccine was available to them first and they have the most to lose by not receiving it.

Why are Republicans less likely to be vaccinated, while Democrats and Independents are more likely to be vaccinated? It likely has to do with the differing beliefs that each political affiliation has about COVID-19 and the vaccine. In another blog here, we explain how negative beliefs about COVID and the vaccine, such as the testing process was rushed, the vaccine is dangerous, the vaccine is being used by the government to track us, and COVID was released on purpose, decrease the likelihood of receiving the vaccine. Alternatively, beliefs like being vaccinated shows I care about others, getting the vaccine is the right thing to do, and the vaccine will reduce the chance of contracting COVID-19 all relate to an increase in likelihood to receive the vaccine.

What about racial and ethnic differences? Why are white people more likely to receive the vaccine while people of color are less likely to? Many factors could be influencing this. First, African Americans, American Indians, Asians, and Hispanics all have historical and current-event-related reasons to distrust the government and, therefore, the vaccine.

Second, beliefs about COVID and the vaccine may differ based on race and ethnic background. Indeed, when examining the data gathered from the monthly COVID tracker, we find that people of color agree more strongly with the idea that the vaccine is dangerous, that being vaccinated brings severe side effects, and that there are plenty of reasons to be afraid of the vaccine⁶.

Third, people of color, as well as those who live in rural communities, may have less access to vaccination sites. This may be due to lack of transportation to the site, or it could be due to fewer sites in rural areas and communities of color.

Lastly, another possibility is that people of color are more hesitant to receive the vaccine and, therefore, are waiting to see the outcomes of the vaccine first before making that decision.

Conclusion

Demographic characteristics such as age, race, ethnicity, occupation, income, and political affiliation play a role in why some people choose to receive the vaccine and others do not. The largest differences are found across different political affiliations and racial/ethnic groups. Belief systems contribute to these distinctions. Specifically, negative beliefs about the vaccine help explain why people of color and Republicans are less likely to receive the vaccine⁷. However, other reasons exist too. According to a New York Times article, some individuals may be hesitant to receive the vaccine because they do not know that the vaccination is free, or they believe that they will be billed for it later down the road. There may problems with availability of vaccination sites or inability to get transportation to the site. It is possible that the rollout of the vaccine contributed a great deal to the disparity in vaccination rates among different groups. Hopefully, as vaccination dispersion continues, we find that some of these differences disappear.

Footnote 1: There were no statistically significant differences in vaccination with regards to gender. Therefore, it is not discussed further.

Footnote 2: Data collection for the 17th wave of this tracker began 4/15/2021 and ended 4/19/2021.

Footnote 3: People of color are defined as African American, American Indian, Alaskan Native, Asian, Pacific Islander, Hispanic, or Latin American.

Footnote 4: A binary logistic regression was performed. Twenty percent of the null variance was accounted for by the predictors. Odds ratio (Exp(B)) values are reported.

Footnote 5: By 1 standard deviation.

Footnote 6: These results are obtained from significant ANOVAs at the 95% confidence interval.

Footnote 7: Mediation models using structural equation modeling were performed on the tracker data. Both models explained the data well, CFI=.97 RMSEA=.07. For both models, negative beliefs about the vaccine explained 28% of the variance in the vaccination decision. Mediation, direct, and total effects were significant at the 95% confidence interval.