Literature DB >> 33773862

Willingness to Vaccinate Against COVID-19 in the U.S.: Representative Longitudinal Evidence From April to October 2020.

Michael Daly1, Eric Robinson2.   

Abstract

INTRODUCTION: Vaccines against COVID-19 have been developed in unprecedented time. However, the effectiveness of any vaccine is dictated by the proportion of the population willing to be vaccinated. This observational population-based study examines intentions to be vaccinated against COVID-19 throughout the pandemic.
METHODS: In November 2020, longitudinal data from a nationally representative sample of 7,547 U.S. adults enrolled in the Understanding America Study were analyzed using multinomial logistic regression. Participants reported being willing, undecided, and unwilling to get vaccinated against COVID-19 across 13 assessments conducted from April to October 2020. Public attitudes to vaccination against COVID-19 were also assessed on a 4-point Likert-type scale.
RESULTS: Willingness to vaccinate declined from 71% in April to 53.6% in October. This was explained by an increase in the percentage of participants undecided about vaccinating (from 10.5% to 14.4%) and the proportion of the sample unwilling to vaccinate (from 18.5% to 32%). The population subgroups most likely to be undecided/unwilling to vaccinate were those without a degree (undecided: RR=2.47, 95% CI=2.04, 3.00; unwilling: RR=1.92, 95% CI=1.67, 2.20), Black participants (undecided: RR=2.18, 95% CI=1.73, 2.74; unwilling: RR=1.98, 95% CI=1.63, 2.42), and female participants (undecided: RR=1.41, 95% CI=1.20, 1.65; unwilling: RR=1.29, 95% CI=1.14, 1.46). Participants who were older or were on higher incomes were least likely to be undecided or unwilling to vaccinate. Concerns about potential side effects of a vaccine were common.
CONCLUSIONS: Intentions to be vaccinated against COVID-19 have declined rapidly during the pandemic, and close to half of Americans are undecided or unwilling to be vaccinated.
Copyright © 2021 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Entities:  

Year:  2021        PMID: 33773862      PMCID: PMC7883746          DOI: 10.1016/j.amepre.2021.01.008

Source DB:  PubMed          Journal:  Am J Prev Med        ISSN: 0749-3797            Impact factor:   5.043


INTRODUCTION

As of the middle of February 2021, the coronavirus disease 2019 (COVID-19) pandemic has been responsible for >2.3 million deaths worldwide. Vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been developed in an unprecedented time, and there are now multiple vaccines that have been shown to be effective in preventing symptomatic COVID-19 infections. The U.S. Food and Drug Administration (FDA) has issued emergency use authorization for the mass roll out of the Pfizer–BioNTech and Moderna COVID-19 vaccines, and other candidates may be approved for distribution in the near future. However, the overall effectiveness of any vaccine is dictated, at least in part, by the proportion of the population willing to be vaccinated. Simulation studies suggest that at least three quarters of the population may need to be vaccinated to extinguish the ongoing COVID-19 pandemic. , During the early stages of the pandemic (March–June), studies of small samples of European and Australian adults suggested that the majority of surveyed people reported that they would be vaccinated when a widely available vaccine was available. , Similarly, a nationally representative study of adults in China conducted in March found that 9 in 10 persons would accept a vaccine when available. U.S. studies conducted early in the pandemic found that between 58% and 86% of adults reported that they were likely to be vaccinated against COVID-19. , 9, 10, 11 However, the rise of fake news during the pandemic has been widely acknowledged, , and widespread misinformation about the pandemic may have been damaging to the public uptake of measures designed to reduce the spread of the virus (e.g., mask wearing, social distancing) and the willingness to vaccinate. , , In addition, because the speed at which COVID-19 vaccines have been developed has been unparalleled and this has been widely reported, , this may have made the public more hesitant about accepting a vaccine when available. , Furthermore, research indicates that in some countries, the public trust in government handling of the COVID-19 crisis has been affected negatively, and this too may have detrimentally affected intentions to follow public health guidance. The COVID-19 pandemic has had a disproportionately large impact on ethnic minorities and groups from lower socioeconomic backgrounds, and as infections will likely continue to be socially patterned, understanding whether population demographics determine the willingness to vaccinate will also be important. For example, research examining previous influenza vaccination programs has found that vaccination intentions and uptake are reduced among more disadvantaged groups. , Initial research examining COVID-19 vaccination intentions has produced mixed findings on the role of demographic predictors, which may be due to a reliance to date on relatively small and nonrepresentative samples. , , This study examines the estimates of the proportion of the U.S. general population that would be willing to use a vaccine when available. In addition, this study examines whether the estimates of vaccination uptake collected much earlier in the pandemic have changed over time. Furthermore, this study seeks to understand whether the intentions to vaccinate are socially patterned and more or less likely in specific population subgroups. This information will provide an empirical basis for directing public health messages at those who are least likely to vaccinate. , To do this, this research made use of data from the Understanding America Study (UAS), a large nationally representative panel of U.S. adults who have reported their vaccine intentions on 13 occasions from the outbreak of the pandemic through October 2020.

METHODS

Study Sample

This study utilized data collected as part of the UAS, a nationally representative longitudinal study of adults aged ≥18 years. The UAS is a probability-based sample recruited through address-based sampling from the U.S. Postal Service Computerized Delivery Sequence file containing all U.S. postal addresses. Participants complete surveys online, and those without Internet access are provided with tablet computers and Internet access. Surveys were administered in English and Spanish, and participants were compensated with approximately $20 for 30 minutes of survey time. Of 8,547 UAS participants eligible to take part in the COVID-19 tracking study, 7,547 participated and provided data. The UAS COVID-19 tracking study has been utilized to examine the changes in personal and social reactions, risk perception, , and mental health in response to the pandemic. Vaccination intentions were assessed in 13 of the 15 waves of the assessment conducted every 2 weeks between April 1, 2020 and October 31, 2020. The number of participants and observations per survey month are shown in Appendix Table 1 (available online). The percentage of participants providing willingness to vaccinate data was lowest in June (74.1%) and relatively stable in other months (ranging from 81.8% to 88.1%) (Appendix Table 1, available online). In total, participants provided 80,060 observations across the 13 survey waves (average response rate of 81.6% among COVID-19 tracking study participants). A small portion (2%) of observations were omitted because they were submitted after October 31 or were missing vaccination intentions or covariate data, leaving a total of 78,453 observations (10.4 per participant). The UAS weights were applied to adjust for unequal probabilities of selection into the UAS. Post-stratification weights were also incorporated to provide a correction for nonresponse by aligning each survey wave with the distribution of demographic characteristics of the U.S. population (Angrisani M, Center for Economic and Social Research (CESR), unpublished observations, 2019). The UAS was approved by the University of Southern California Human Subjects Committee IRB, and informed consent was obtained from all participants (through computer link). The Maynooth University Social Research Ethics Sub-Committee does not require ethical approval to be granted for the secondary use of anonymous data, such as the data used in this study.

Measures

In each survey wave, participants indicated how likely there were to get vaccinated for COVID-19 when a vaccine becomes available to the public on a 5-point scale. Participants were classified as either (1) undecided (responses of unsure), (2) unwilling to vaccinate (responses of somewhat or very unlikely to vaccinate), or (3) willing to vaccinate (responses of somewhat or very likely to vaccinate). Vaccination intentions were predicted by the month of the survey (April, May, June, July, August, September, and October) and a set of demographic variables: age (18–34, 35–44, 50–64, ≥65 years), sex (male, female), race/ethnicity (White, Hispanic, Black, other race/ethnicity), household income (≤$40,000/$40,000–$100,000/≥$100,000 gross per annum), college degree (versus none), and the presence of a chronic health condition (present versus not present). Specifically, participants indicated whether they had been diagnosed with the following conditions: diabetes, cancer, heart disease, kidney disease, asthma, chronic lung disease, or an autoimmune disease. Participants also reported their level of agreement (from 1=strongly disagree to 4=strongly agree), with 9 items assessing their attitudes toward a potential vaccine (Table 1 provides items in full) in late October (October 14‒31). Questions assessed the participant's beliefs that the COVID-19 vaccine would be beneficial, important for personal and community health, and a good way to protect from COVID-19. Participants also indicated whether they agreed that approved vaccines would be effective and whether they were concerned about the lack of long-term follow-up information, and potential side effects of a COVID-19 vaccine were assessed (e.g., I think the COVID-19 vaccine might cause lasting health problems for me).
Table 1

Attitudes Toward Vaccination Against COVID-19 in the Understanding America Study Assessed Between October 14, 2020 and October 31, 2020 (N=5,762)

Full sample
Willing to vaccinateb
Undecided on vaccinationb
Unwilling to vaccinateb
QuestionaAgree (%)Disagree (%)Agree (%)Disagree (%)Agree (%)Disagree (%)Agree (%)Disagree (%)
The COVID vaccine will be important for my health.71.228.893.86.269.130.933.766.3
Getting a COVID vaccine would be a good way to protect me from coronavirus disease.74.225.895.44.671.628.439.360.7
The COVID vaccine will be effective if it is approved by the FDA or CDC.73.726.392.47.671.029.043.156.9
Getting the COVID vaccine will be important for the health of others in my community.79.420.696.13.977.722.351.748.3
The COVID vaccine will be beneficial to me.73.826.295.14.974.325.737.462.6
I will do what my doctor or health care provider recommends about the COVID vaccine.74.525.592.87.270.929.144.755.3
The COVID vaccine will not be around long enough to be sure it is safe.48.151.939.960.158.841.257.342.7
I am concerned about serious side effects of the COVID vaccine.69.730.360.639.481.418.680.219.8
I think the COVID vaccine might cause lasting health problems for me.43.656.426.673.461.538.565.035.0

Note: Estimates are based on weighted data.

Each item was rated on a 4-point scale, with those responding Somewhat or Strongly agree coded as Agree and those responding Somewhat or Strongly disagree coded as Disagree.

Based on responses to the question: How likely are you to get vaccinated for coronavirus once a vaccine is available to the public? In this survey wave (responses between October 14, 2020 and October 31, 2020), 54% of the sample were classified as willing to vaccinate, 14% were classified as undecided, and 32% were classified as unwilling to vaccinate.

CDC, Centers for Disease Control and Prevention; FDA, U.S. Food and Drug Administration.

Attitudes Toward Vaccination Against COVID-19 in the Understanding America Study Assessed Between October 14, 2020 and October 31, 2020 (N=5,762) Note: Estimates are based on weighted data. Each item was rated on a 4-point scale, with those responding Somewhat or Strongly agree coded as Agree and those responding Somewhat or Strongly disagree coded as Disagree. Based on responses to the question: How likely are you to get vaccinated for coronavirus once a vaccine is available to the public? In this survey wave (responses between October 14, 2020 and October 31, 2020), 54% of the sample were classified as willing to vaccinate, 14% were classified as undecided, and 32% were classified as unwilling to vaccinate. CDC, Centers for Disease Control and Prevention; FDA, U.S. Food and Drug Administration.

Statistical Analysis

First, investigators examined the trends in vaccination intentions over the period of the study by comparing the prevalence of willingness/being undecided/unwillingness to vaccinate in April and October 2020. To estimate the statistical significance of time trends, multinomial logistic regression analysis was used with robust SEs clustered at the individual level. Those willing to vaccinate were compared with (1) those undecided on vaccination and (2) those unwilling to vaccinate. A series of multinomial logistic regressions were run to identify whether the relative risk (RR) of being undecided or unwilling to vaccinate increased from April to October for the overall sample and for each examined population subgroup. This model contrasts the natural log (Probability [Pr] [unwilling to vaccinate]/Pr[willing to vaccinate]) and the natural log (Pr[undecided on vaccination]/Pr[willing to vaccinate]) estimates across different demographic groups to ascertain relative risk ratios (RRRs). Next, multinomial logistic regression was used to estimate the extent to which survey month and different demographic factors predicted vaccination intentions. A single adjusted analysis was used to estimate the independent effect of each predictor variable (i.e., month of the survey, age, sex, race/ethnicity, educational attainment, income, presence of a chronic condition) controlling for all others. In addition, the authors tested a separate model where interactions between survey month and participant demographics were added to the main model to test whether changes in vaccination intentions over time differed systematically between demographic groups. Finally, in a supplementary sensitivity analysis, the willingness to vaccinate was treated as a continuous outcome (ranging from 1=very likely to vaccinate to 5=very unlikely to vaccinate) examined using ordinary least squares regression with SEs clustered at the individual level. All analyses incorporated the UAS sampling weights to generate nationally representative estimates. RRRs and 95% CIs were estimated using the Stata, version 15.

RESULTS

Participants were aged 47.2 (SD=16.6) years on average; 52.1% of them were female; 34.2% had a college degree; and 64.1% were White, 17.8% were Hispanic, 12.2% were Black, and 5.9% were Other race/ethnicity (Table 2 ). On average, willingness to vaccinate declined from 71% in April to 53.6% in October. This was explained by an increase in the percentage of participants undecided about vaccinating against COVID-19 (from 10.5% to 14.4%) and the portion of the sample unwilling to vaccinate (from 18.5% to 32%) (Table 2). A decrease in the willingness to vaccinate against COVID-19 between April and October was evident across all examined population subgroups (Table 2).
Table 2

Sample Characteristics of Participants in the UAS (N=7,547, Obs.=78,453) and Vaccination Intentions in April and October 2020

Willing to vaccinatea
Undecided on vaccinationa
Unwilling to vaccinatea
April,October,April,October,April,October,
VariablesSample size (%)%%%%%%
Overall sample71.053.610.514.418.532.0
Age group, years
 18‒342,024 (26.8)65.647.212.916.221.536.6
 35‒492,305 (30.5)67.549.611.515.521.034.9
 50‒641,832 (24.3)73.154.210.615.116.330.7
 ≥651,386 (18.4)79.965.96.010.014.124.0
Sex
 Male3,613 (47.9)75.160.08.211.716.728.3
 Female3,934 (52.1)67.247.612.717.020.135.4
Race/ethnicity
 White4,840 (64.1)74.757.38.613.016.729.7
 Hispanic1,345 (17.8)67.447.512.216.220.536.3
 Black917 (12.2)47.933.822.021.830.144.3
 Other race/ethnicity445 (5.9)86.568.64.011.19.520.4
Education
 No degree4,969 (65.8)65.745.113.118.221.236.7
 College degree2,578 (34.2)81.468.95.47.813.223.4
Income levelb
 Low income2,884 (38.2)64.143.615.621.420.335.0
 Middle income3,007 (40.4)71.655.08.612.119.833.0
 High incomeb1,656 (21.9)81.166.95.67.813.325.4
Chronic conditionc
 No5,060 (67.0)69.552.510.614.219.933.4
 Yes2,446 (32.4)74.155.810.314.915.629.2

Note: Weighted demographic characteristics and vaccination intentions are presented.

Based on responses to the question: How likely are you to get vaccinated for coronavirus once a vaccine is available to the public?

Households earning <$40,000 a year were classified as low income, those earning $40,000‒$100,000 were classified as middle income, and those above this threshold were classified as high income.

Diagnosed with any of the following: diabetes, cancer, heart disease, kidney disease, asthma, chronic lung disease, and an autoimmune disease. A total of 41 participants did not provide chronic illness data and were included using a missing data dummy.

Obs., observations; UAS, Understanding America Study.

Sample Characteristics of Participants in the UAS (N=7,547, Obs.=78,453) and Vaccination Intentions in April and October 2020 Note: Weighted demographic characteristics and vaccination intentions are presented. Based on responses to the question: How likely are you to get vaccinated for coronavirus once a vaccine is available to the public? Households earning <$40,000 a year were classified as low income, those earning $40,000‒$100,000 were classified as middle income, and those above this threshold were classified as high income. Diagnosed with any of the following: diabetes, cancer, heart disease, kidney disease, asthma, chronic lung disease, and an autoimmune disease. A total of 41 participants did not provide chronic illness data and were included using a missing data dummy. Obs., observations; UAS, Understanding America Study. An unadjusted multinomial logistic regression analysis confirmed that from April to October 2020, there was a statistically significant higher risk of being undecided (RRR=1.82, 95% CI=1.62, 2.05) or unwilling (RRR=2.29, 95% CI=2.11, 2.48) to be vaccinated than being willing to get vaccinated (Appendix Table 2, available online). Unadjusted multinomial logistic regression analyses also showed that all population subgroups were more likely to be undecided or unwilling to vaccinate in October than in April (Appendix Table 2, available online). There was also a greater than 2-fold higher relative likelihood of being undecided or unwilling to get the COVID-19 vaccine in October than in April 2020 (undecided: RRR=2.03, 95% CI=1.79, 2.29; unwilling: RRR=2.47, 95% CI=2.27, 2.68) in a fully adjusted model that included controls for participant demographic factors and the presence of chronic illness (Table 3 ). An examination of month-to-month changes confirmed that the likelihood of being undecided or unwilling to vaccinate (versus being willing to vaccinate) increased from April to October (Table 3 and Figure 1 ).
Table 3

Results of the Adjusted Multinomial Logistic Regression Analyses Examining Demographic Predictors and Temporal Changes in Indecision and Unwillingness to Vaccinate Against COVID-19 in the U.S. (N=7,547, Obs.=78,453)

VariablesUndecided on vaccination,Unwilling to vaccinate,
RRRa (95% CI)RRRa (95% CI)
Month (ref=April)
 May1.27⁎⁎⁎ (1.15, 1.41)1.54⁎⁎⁎ (1.44, 1.66)
 June1.34⁎⁎⁎ (1.18, 1.52)1.65⁎⁎⁎ (1.51, 1.80)
 July1.47⁎⁎⁎ (1.30, 1.67)1.76⁎⁎⁎ (1.62, 1.91)
 August1.50⁎⁎⁎ (1.33, 1.68)1.97⁎⁎⁎ (1.82, 2.13)
 September1.92⁎⁎⁎ (1.70, 2.16)2.34⁎⁎⁎ (2.16, 2.55)
 October2.03⁎⁎⁎ (1.79, 2.29)2.47⁎⁎⁎ (2.27, 2.68)
Age group, years (ref=18‒34)
 35‒491.07 (0.87, 1.33)1.02 (0.85, 1.21)
 50‒640.88 (0.71, 1.09)0.81* (0.68, 0.97)
 ≥650.49⁎⁎⁎ (0.38, 0.63)0.61⁎⁎⁎ (0.51, 0.74)
Sex (ref=male)
 Female1.41⁎⁎⁎ (1.20, 1.65)1.29⁎⁎⁎ (1.14, 1.46)
Race/ethnicity (ref=White)
 Hispanic1.05 (0.82, 1.35)1.02 (0.84, 1.25)
 Black2.18⁎⁎⁎ (1.73, 2.74)1.98⁎⁎⁎ (1.63, 2.42)
 Other race/ethnicity0.57⁎⁎ (0.40, 0.82)0.52⁎⁎⁎ (0.39, 0.71)
Education (ref=degree)
 No degree2.47⁎⁎⁎ (2.04, 3.00)1.92⁎⁎⁎ (1.67, 2.20)
Income level (ref=low income)b
 Middle income0.58⁎⁎⁎ (0.48, 0.69)1.01 (0.88, 1.16)
 High income0.40⁎⁎⁎ (0.32, 0.50)0.75⁎⁎ (0.63, 0.90)
Chronic conditionc0.96 (0.81, 1.14)0.84* (0.74, 0.96)

Note: Boldface indicates statistical significance (*p<0.05, ⁎⁎p<0.01, ⁎⁎⁎p<0.001).

Estimates are RRRs derived from multinomial logistic regression with SEs adjusted for clustering at the individual level and controlling for all characteristics presented. For all analyses, willing to vaccinate was the outcome reference group.

Households earning <$40,000 a year were classified as low income, those earning $40,000‒$100,000 were classified as middle income, and those above this threshold were classified as high income.

Diagnosed with any of the following: diabetes, cancer, heart disease, kidney disease, asthma, chronic lung disease, and an autoimmune disease.

Obs., observations.

Figure 1

Change in vaccination intentions across the 13 waves of the Understanding America Study conducted between April 1, 2020 and October 31, 2020.

Note: Graph is based on an analysis of 78,453 observations on 7,547 participants. Estimates are predicted probabilities from the marginal effects calculated after a multinomial logistic regression model adjusted for age, sex, race/ethnicity, household income, educational attainment, and the presence of pre-existing health conditions. 95% CIs are presented in gray.

Results of the Adjusted Multinomial Logistic Regression Analyses Examining Demographic Predictors and Temporal Changes in Indecision and Unwillingness to Vaccinate Against COVID-19 in the U.S. (N=7,547, Obs.=78,453) Note: Boldface indicates statistical significance (*p<0.05, ⁎⁎p<0.01, ⁎⁎⁎p<0.001). Estimates are RRRs derived from multinomial logistic regression with SEs adjusted for clustering at the individual level and controlling for all characteristics presented. For all analyses, willing to vaccinate was the outcome reference group. Households earning <$40,000 a year were classified as low income, those earning $40,000‒$100,000 were classified as middle income, and those above this threshold were classified as high income. Diagnosed with any of the following: diabetes, cancer, heart disease, kidney disease, asthma, chronic lung disease, and an autoimmune disease. Obs., observations. Change in vaccination intentions across the 13 waves of the Understanding America Study conducted between April 1, 2020 and October 31, 2020. Note: Graph is based on an analysis of 78,453 observations on 7,547 participants. Estimates are predicted probabilities from the marginal effects calculated after a multinomial logistic regression model adjusted for age, sex, race/ethnicity, household income, educational attainment, and the presence of pre-existing health conditions. 95% CIs are presented in gray. When all observations from the 13 survey waves were examined, those without a college degree were at elevated risk of being undecided or unwilling to vaccinate (undecided: RRR=2.47, 95% CI=2.04, 3.00; unwilling: RRR=1.92, 95% CI=1.67, 2.20), as were Black participants (undecided: RRR=2.18, 95% CI=1.73, 2.74; unwilling: RRR=1.98, 95% CI=1.63, 2.42) and female participants (undecided: RRR=1.41, 95% CI=1.20, 1.65; unwilling: RRR=1.29, 95% CI=1.14, 1.46). By contrast, a reduced risk of being undecided or unwilling to vaccinate was found among those aged ≥65 years (undecided: RRR=0.49, 95% CI=0.38, 0.63; unwilling: RRR=0.61, 95% CI=0.51, 0.74), those on high household incomes (undecided: RRR=0.40, 95% CI=0.32, 0.50; unwilling: RRR=0.75, 95% CI=0.63, 0.90), and other race/ethnicity participants (undecided: RRR=0.57, 95% CI=0.40, 0.82; unwilling: RRR=0.52, 95% CI=0.39, 0.71). An examination of the interactions between survey month and individual demographic characteristics did not yield evidence for systematic differences in changes in vaccination intentions over time between demographic groups. Furthermore, very similar associations were identified in a sensitivity analysis where willingness to vaccinate was treated as a continuous variable (Appendix Table 3, available online). Finally, this study examined the attitudes toward the vaccine reported between October 14 and 31, 2020. The majority of the sample (70%–80%) agreed that the COVID-19 vaccine would be personally beneficial, important for personal and community health, a good way to protect from COVID-19, and effective if approved by FDA or the Centers for Disease Control and Prevention (Table 1). However, responses differed markedly between those willing and those unwilling to be vaccinated. For example, whereas 92.4% of those who were willing to be vaccinated agreed that the vaccine would be effective if approved by FDA or Centers for Disease Control and Prevention, only 43.1% of those unwilling to be vaccinated agreed. In the overall sample, it was common for participants to report concerns over the vaccine, and 69.7% agreed that they were concerned about serious side effects of the vaccine. In total, 44% agreed that the vaccine might cause lasting health problems for them. However, such concerns were more prevalent among those unwilling to be vaccinated. For example, 65% of those unwilling to be vaccinated were concerned about lasting health problems resulting from the vaccine compared with 26.6% of those willing to be vaccinated.

DISCUSSION

In a large nationally representative sample of U.S. adults, intentions to be vaccinated against COVID-19 have declined from a high of 71% of the population in April 2020 to close to only 54% reporting being willing to vaccinate in October 2020. Reporting being undecided or unwilling to vaccinate was more likely among those with lower levels of education and income as well as in female, Black (African American), and younger adults. Concerns about the vaccine causing long-lasting health problems and uncertainty about the benefits of the vaccine were also common. On the basis of the estimates that vaccination coverage of close to 75% may be required to vaccinate to eradicate COVID-19 , , , the present estimates that are close to 50% of the population may be willing to vaccinate are concerning. It will now be critical to better understand the reasons why a large proportion of the population are skeptical about vaccination against COVID-19. Public concerns about the safety of vaccines may be an important driver of the increase in the proportion of the population reporting being unsure or explicitly stating that they will not vaccinate. In line with this, 70% of this study sample reported being concerned about serious side effects of the vaccine, and 44% believed that a vaccine might cause lasting health problems for them. To some extent, these concerns are to be expected given the unprecedented speed at which vaccines have been developed. , However, the rise of anti-vaccination misinformation (e.g., misleading healthcare information, conspiracy theories) and political polarization may also have played a role in explaining this increase.11, 12, 13, 14 It will therefore be critical that accurate safety information is widely and transparently communicated by trusted sources to promote confidence in the scientific decision making underpinning the approval of COVID-19 vaccines. , It will also be important to address social inequalities in vaccination intentions , and to ensure widespread uptake of effective COVID-19 vaccines. In this study, willingness to vaccinate was strikingly lower among more disadvantaged groups (e.g., African Americans and those with lower income and education levels), and these groups have already been disproportionately affected by COVID-19. , Previous research on influenza vaccines also suggests that access issues may prevent minority and disadvantaged groups from being vaccinated. , It will therefore be important to identify the strategies to reduce social inequalities in both vaccination intentions and opportunities to vaccinate. The strengths of this research include the use of a large probability-based nationally representative sample of adults, allowing generalizations to be made to the population. This study also moves beyond previous research6, 7, 8, 9, 10 by including a high-frequency longitudinal assessment of vaccination intentions throughout the pandemic. In addition, participant concerns and perceptions of the benefits of a potential vaccine were assessed to shed light on potential reasons for the low willingness to vaccinate.

Limitations

A limitation of the UAS is the potential lack of representation of those who do not speak either English or Spanish and those not comfortable engaging with online surveys. In addition, this study is limited in its reliance on self-reported intentions about a hypothetical vaccine and the lack of detailed assessment of factors that may explain why vaccination intentions have declined over time in the U.S. However, in advance of the deployment of a COVID-19 vaccine, it has been necessary to rely on intention-based measures that have been shown to predict vaccination behavior. Furthermore, intentions are malleable and represent a target for evidence-based approaches aiming to increase the proportion of the population who are willing to vaccinate. This now represents an urgent public health priority to minimize further loss of life due to the COVID-19 pandemic. It is also essential that research aiming to modify vaccination uptake is theory based and informed by relevant models such as the Health Belief Model, which provides a framework for understanding the factors that may shape vaccination intentions (e.g., perceived benefits and barriers, perceived susceptibility to COVID-19) and future behavior. Finally, now that vaccines are authorized and information on their effectiveness and safety is available, it is crucial that studies track vaccination attitudes (e.g., perceived health benefits and side effects, social norms relating to vaccination) to provide an in-depth understanding of how vaccine intentions and uptake change as vaccines are deployed. Initial research suggests that willingness to vaccinate may have increased in November when the availability of viable vaccines appeared imminent.

CONCLUSIONS

Intentions to be vaccinated against COVID-19 have declined rapidly during the pandemic, and in October 2020, close to half of Americans were undecided or unwilling to be vaccinated. This reduced willingness to vaccinate may undermine the pandemic response and the public health benefits of an effective vaccine.
  26 in total

1.  A postmodern Pandora's box: anti-vaccination misinformation on the Internet.

Authors:  Anna Kata
Journal:  Vaccine       Date:  2009-12-30       Impact factor: 3.641

2.  Explaining the rise and fall of psychological distress during the COVID-19 crisis in the United States: Longitudinal evidence from the Understanding America Study.

Authors:  Eric Robinson; Michael Daly
Journal:  Br J Health Psychol       Date:  2020-12-05

3.  Developing Covid-19 Vaccines at Pandemic Speed.

Authors:  Nicole Lurie; Melanie Saville; Richard Hatchett; Jane Halton
Journal:  N Engl J Med       Date:  2020-03-30       Impact factor: 91.245

4.  Overcoming the knowledge-behavior gap: The effect of evidence-based HPV vaccination leaflets on understanding, intention, and actual vaccination decision.

Authors:  O Wegwarth; S Kurzenhäuser-Carstens; G Gigerenzer
Journal:  Vaccine       Date:  2014-01-28       Impact factor: 3.641

5.  Reassuring the Public and Clinical Community About the Scientific Review and Approval of a COVID-19 Vaccine.

Authors:  Howard Bauchner; Preeti N Malani; Joshua Sharfstein
Journal:  JAMA       Date:  2020-10-06       Impact factor: 157.335

6.  Attitudes Toward a Potential SARS-CoV-2 Vaccine : A Survey of U.S. Adults.

Authors:  Kimberly A Fisher; Sarah J Bloomstone; Jeremy Walder; Sybil Crawford; Hassan Fouayzi; Kathleen M Mazor
Journal:  Ann Intern Med       Date:  2020-09-04       Impact factor: 25.391

View more
  42 in total

1.  COVID-19: The Pseudo-Environment and the Need for a Paradigm Change.

Authors:  Richard A Stein; Oana Ometa; Thomas R Broker
Journal:  Germs       Date:  2021-12-29

2.  County-Level Social Determinants of Health and COVID-19 in Nursing Homes, United States, June 1, 2020-January 31, 2021.

Authors:  Adam Hege; Sandi Lane; Trent Spaulding; Margaret Sugg; Lakshmi S Iyer
Journal:  Public Health Rep       Date:  2021-11-17       Impact factor: 2.792

3.  A Community-Informed Approach to COVID-19 Vaccine Roll-Out in Under-served Areas in Chicago.

Authors:  Laura DiVirgilio; Arianna Boshara; Bijou R Hunt; Jacquelyn Jacobs; Kate Just; Amy K Johnson
Journal:  Front Public Health       Date:  2022-06-20

4.  Contextualized impacts of an infodemic on vaccine hesitancy: The moderating role of socioeconomic and cultural factors.

Authors:  Fen Lin; Xi Chen; Edmund W Cheng
Journal:  Inf Process Manag       Date:  2022-07-16       Impact factor: 7.466

5.  Hesitant but vaccinated: assessing COVID-19 vaccine hesitancy among the recently vaccinated.

Authors:  Don E Willis; James P Selig; Jennifer A Andersen; Spencer Hall; Emily Hallgren; Mark Williams; Keneshia Bryant-Moore; Pearl A McElfish
Journal:  J Behav Med       Date:  2022-01-15

6.  Factors associated with COVID-19 vaccination intentions among adults in the deep South.

Authors:  Casey L Daniel; Jacob Williams; Rachel Legg; Chelsea McGowen; Jesse Stutzman
Journal:  Vaccine       Date:  2022-01-10       Impact factor: 3.641

7.  Knowledge, attitudes, and behavior of incarcerated people regarding COVID-19 and related vaccination: a survey in Italy.

Authors:  Gabriella Di Giuseppe; Concetta P Pelullo; Raffaele Lanzano; Francesco Napolitano; Maria Pavia
Journal:  Sci Rep       Date:  2022-01-19       Impact factor: 4.379

8.  Coronavirus disease 2019 (COVID-19) vaccine intentions and uptake in a tertiary-care healthcare system: A longitudinal study.

Authors:  Charlesnika T Evans; Benjamin J DeYoung; Elizabeth L Gray; Amisha Wallia; Joyce Ho; Mercedes Carnethon; Teresa R Zembower; Lisa R Hirschhorn; John T Wilkins
Journal:  Infect Control Hosp Epidemiol       Date:  2021-12-27       Impact factor: 6.520

9.  Analysis of social combinations of COVID-19 vaccination: Evidence from a conjoint analysis.

Authors:  Hanako Ohmura
Journal:  PLoS One       Date:  2022-01-21       Impact factor: 3.240

10.  Factors Influencing COVID-19 Vaccination Demand and Intent in Resource-Limited Settings: Based on Health Belief Model.

Authors:  Binyam Tariku Seboka; Delelegn Emwodew Yehualashet; Moges Mareg Belay; Robel Hussen Kabthymer; Helen Ali; Samuel Hailegebreal; Abel Desalegn Demeke; Endris Seid Amede; Getanew Aschalew Tesfa
Journal:  Risk Manag Healthc Policy       Date:  2021-06-28
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.