Skip to main content
Download PDF
  • Research article
  • Open access
  • Published:

COVID-19 vaccine hesitancy among different population groups in China: a national multicenter online survey

BMC Infectious Diseases volume 22, Article number: 153 (2022) Cite this article

Abstract

Background

COVID-19 vaccine has been available in China since the beginning of the 2021, however, certain numbers of people are reluctant for some reasons to vaccinate. The high vaccine coverage is crucial for controlling disease transmission, however, the vaccine hesitancy might be a barrier to the establishment of sufficient herd immunization. This study aims to investigate the prevalence of the COVID-19 vaccine hesitancy among different population groups, and explore common barriers and facilitators to vaccination decisions.

Methods

The current survey was performed among Chinese students, public health professionals, medical workers and general population from January to March 2021 from seven cities in China. The questionnaire contained sociodemographic information, concerns about infection with COVID-19, general vaccination behaviors and attitudes, the General Vaccine Hesitancy Scale, the COVID-19 Vaccine Hesitancy Scale and other potential factors. Univariate analysis was conducted by chi-squared test, and variables significant at P < 0.10 were then included in a multivariable regression model.

Results

The prevalence of COVID-19 vaccine hesitancy was 15.6% in our study, and 23.9% of students, 21.2% of the general population, 13.1% of medical workers, and 10.4% of public health professionals had vaccine hesitancy. The results of multivariate analysis indicated that participants who had received negative information of COVID-19 vaccine (OR: 1.563, 95% CI: 1.229–1.986) and who had doubts about the information source (OR: 2.157, 95% CI: 1.697–2.742) were more likely to have vaccine hesitancy. While those who needed transparent information about COVID-19 vaccine (OR: 0.722, 95% CI: 0.535–0.973) and who would get COVID-19 vaccine if doctors recommended (OR: 0.176, 95% CI: 0.132–0.234) were less likely to have COVID-19 vaccine hesitancy.

Conclusions

Given recommendations from medical workers about vaccination can motivate people to accept COVID-19 vaccination, appropriate training in knowledge about vaccines and communication skills are necessary for them to increase public’s willingness of vaccination. Reducing the spread of misinformation and disseminating facts in a timely and accurate way will likely reduce vaccine hesitancy. Moreover, to establish suitable communication strategies and information exchange platforms between the government and the public and a warning system on infodemic would be helpful to improve public’s confidence in vaccination.

Peer Review reports

Background

COVID-19 (coronavirus disease 2019) was first noticed in late 2019 and is still ravaging the world currently [1]. It caused an unprecedented crisis for global public health and enormous disease burden while severely disrupting societies and economies. Since actions such as compulsory mask wearing, lockdowns and social distancing have exhausted the world from the beginning of the pandemic, effective COVID-19 vaccine is the most powerful way to curb the disease [2, 3]. Vaccination was recognized as one of the most successful public health measures, and have contributed to the decline in mortality and morbidity of various infectious diseases [4]. Herd immunization with vaccination may protect the general public against COVID-19 infection and hence stop generating large outbreak. However, certain number of people are still reluctant to receive the vaccination due to vaccine hesitancy, which leads to a relatively low vaccination coverage [5].

Vaccine hesitancy refers to delay in acceptance or refusal of vaccination despite availability of vaccination services and is complex and context specific, varying across time, place, and vaccines [6]. Vaccine hesitancy can result in apparently increases in outbreaks, morbidity and mortality of some vaccine-preventable diseases. Indeed, the concept of “vaccine hesitancy” has been considered by the World Health Organization (WHO) as “one of the top-ten threats to global health” [7]. Previous studies reported that 88.6% respondents from China would take a “proven, safe and effective vaccine”, 76.63% of Chinese healthcare workers would accept the vaccine, and approximately 68% of participants in the United States were supportive of being vaccinated for COVID-19 [8,9,10,11,12]. Moreover, an online survey found that about one-third of the participants in Turkey and 14% in the UK were unsure about getting COVID-19 vaccine [13]. In general, some people have hesitated or will hesitate to get COVID-19 vaccine for certain reasons, these reasons may be related to their own experience, knowledge of vaccines, and previous immunization behavior, including low perceived infectious risk, worry about possible side effects, “wait and see” attitude, concerns about safety and efficacy, and concerns over the short period of time of vaccine development, etc. [14,15,16,17,18,19,20,21].

China started rolling out COVID-19 vaccines in late 2020, prioritizing healthcare and other front-line workers and those with high-risk health conditions. Subsequently, vaccination in China was available to people aged 18 years and older and then to those aged 3–11 years. As of 8 December 2021, approximately 2575 million vaccine doses have been administered [22]. However, a portion of the public still have COVID-19 vaccine hesitancy and the prevalence of hesitancy among different populations is not clear. It is of importance to investigate the prevalence of public’s hesitancy on COVID-19 vaccines and related factors in China, and address the needs in implementing evidence-based interventions to increase the vaccination rate.

We hypothesized that there were people in China who were hesitant about the COVID-19 vaccine, and the prevalence of COVID-19 vaccine hesitancy among different population groups varied. Therefore, the present study aims to: (1) investigate the prevalence of vaccine hesitancy towards the COVID-19 vaccine among different population groups from seven geographical territories of China; (2) explore the characteristics of different groups about vaccine hesitancy and their common barriers and facilitators to vaccination decisions.

Methods

Study design and participants

The current study was performed from January to March 2021 among Chinese from seven cities (from Henan Province, Sichuan Province, Shandong Province, Guangdong Province, Inner Mongolia, Xinjiang Uygur Autonomous Region, and Liaoning Province respectively) located in seven geographical territories of China by distributing an online structural questionnaire via an investigation platform named Wenjuanxing. The participants were recruited from four different population groups, including students, public health professionals, medical workers and general population.

The sample size was calculated using a margin of error of 5%, a confidence level of 95%, a response rate of 50% and a previous estimate rate of vaccine hesitancy of 32.2%, giving a minimum sample size of 671 [23, 24]. The snowball sampling was used to recruit the potential study participants. We initially invited investigators from the seven cooperative institutions, and they distributed the questionnaire to the people meeting the inclusion criteria.

The eligibility criteria included age more than or equal to 18 and an ability to read, understand and complete an online questionnaire. Those who were younger than 18, had barriers to use mobile phone or computer, or had cognitive impairment were excluded. The medical workers were recruited from hospital departments such as respiratory and critical care medicine, general surgery, and nephrology department, while hospital administrators were excluded from medical workers group in our study. The public health professionals were recruited from local CDCs in China, most from the communicable disease control and prevention department, immunization program department and preventive health department. The student group was recruited from students enrolled in universities. To confirm the quality of the online survey, the members of research team were trained on data collection and inclusion criteria procedure.

Measurements

The survey questionnaire contained sociodemographic information, concerns about infection with COVID-19, general vaccination behavior and attitudes, the General Vaccine Hesitancy Scale, the COVID-19 Vaccine Hesitancy Scale and other potential factors of vaccine hesitancy.

Sociodemographic information

Sociodemographic variables included age, gender, ethnicity, residence place, marital status, education level, household income (during past 1 year), smoking and drinking history, and COVID-19 test results.

Concerns about infection with COVID-19

We assessed the concerns of participants about infection with COVID-19 by a 3-items scale, including “I am scared about getting infected with COVID-19” “The possibility of getting infected with COVID-19 in the future concerns me” and “I don’t really worry about getting infected with COVID-19”. This 3-item scale was developed and utilized from several studies, participants responded to each item on a 5-point Likert-type scale (1 = strongly disagree to 5 = strongly agree) [25, 26]. After reverse coded the last item, the three items were highly correlated with satisfactory reliability (Cronbach’s α = 0.702).

The General Vaccine Hesitancy Scale

The General Vaccine Hesitancy Scale composed of 10 items which was revised on the base of previous studies [27, 28]. In this study, we used the 10 items of the Vaccine Hesitancy Scale (VHS) developed by the SAGE Working Group on Vaccine Hesitancy that are measured on a five-point Likert-type rating scale ranging from “strongly disagree” to “strongly agree”. Corresponding changes were made to the wordings of the 10 items to make the study participants fully understand the meanings. We reversed seven items in the scoring of the scale so that higher scores indicated more hesitancy on all items. The reliability of the General Vaccine Hesitancy Scale was satisfactory in our study (Cronbach’s α = 0.930).

The COVID-19 Vaccine Hesitancy Scale

The COVID-19 Vaccine Hesitancy Scale was measured by 15 items based on previous studies to identify vaccine-hesitant parents [29, 30]. We collapsed responses of scale items into 3 categories: hesitant responses, “not sure or don’t know”, and non-hesitant responses. The specific items and scoring rules of this scale can be found in Additional file 1: Table S1. The raw total score was calculated by summing each item’s score, ranging from 0 to 30. We used simple linear transformation to convert this raw score to a 0–100 scale, the score was higher than or equal to 50 was indicated having COVID-19 vaccine hesitancy [30]. The Cronbach’s alpha of the 15-item scale in the current study was 0.755.

General vaccination behavior and attitudes

The questionnaire used a series of questions to investigate respondents’ vaccination history, including the following items: “Do you agree that vaccines can protect you from diseases?” “Do you agree that you will get all vaccines that National Immunization Program or government recommended?” “Have you ever hesitated to get vaccination?” “Have you ever refused to get vaccination?” “Have you ever hesitated or refused to be get Pneumococcal Vaccine?” “Have you ever hesitated or refused to get Influenza Vaccine?”.

Potential factors of COVID-19 vaccine hesitancy

In this section, the following items were designed to explore the barriers of getting COVID-19 vaccine and related factors of COVID-19 vaccine hesitancy: (1) individual attitudes to COVID-19: “Do you agree that COVID-19 epidemic is a severe problem affecting the health of the community?” “Do you agree that COVID-19 will be a great threat to your health if you are infected?” (2) significant people’s advice: “Do you agree that you will get COVID-19 vaccine if doctors recommend?”, “Do you agree that the advice of your family members or friends will affect your intention of getting COVID-19 vaccine?” (3) information about COVID-19 vaccine: “Do you need transparent information about COVID-19 vaccine development, efficacy and safety?” “Do you have doubts about the source of information about the COVID-19 vaccine?” “Have you ever received negative information about getting the COVID-19 vaccine?” “Would you like to get the COVID-19 vaccine after receiving the negative information about it?” (4) cost or time to get COVID-19 vaccine: “Do you agree that the time costs in waiting for the vaccination or staying at the clinic will be a barrier for you to get COVID-19 vaccine?” “Do you agree that the environment of the clinic will be a barrier for you to get COVID-19 vaccine?” “Do you agree that the cost of going to the clinic will be a barrier for you to get COVID-19 vaccine?” (5) personal conditions: “Do you agree that you have no need of getting COVID-19 vaccine because you are healthy?” “Have you gotten emergency COVID-19 vaccination for some reasons?”.

Statistical analysis

This study described the sociodemographic information by counts and proportions among participants. The chi-squared test was utilized to compared the differences of various factors in different population groups. Survey responses were combined into two categories (having or not having COVID-19 vaccine hesitancy) according to whether the score of the COVID-19 Vaccine Hesitancy Scale was higher than or equal to 50. And ordinal regression models were ran to examine demographic and attitudinal factors predictive of respondents' hesitancy to get vaccinated against COVID-19. To identify suitable candidate variables for regression models, univariate analysis was first conducted by chi-squared test, and variables were significant at P < 0.10 were then included in a multivariable regression model. The level of significance was set at P < 0.05. Data were analyzed by using SPSS version 24.0.

Results

Sociodemographic characteristics

Table 1 summarized the characteristics distributions of participants by different population groups. A total of 4289 respondents (response rate 95.37%) completed the online questionnaire, and 62 questionnaires were excluded due to the age limitations. Of them, there were 2656 (62.8%) medical workers, 753 (17.8%) students, 434 (10.3%) general population, and 384 (9.1%) public health professionals. The mean age was 33.02 years old. In total, 2818 (66.7%) respondents were female, 89.1% of them were Han ethnicity, the majority of participants (85.6%) lived in urban areas and 56.9% of them were married, 41.3% were single. The education level of most of them (93.8%) were college and above. For the household income during the past year, nearly half of them were in 50,000–100,000 Yuan per year. Most of participants self-reported they have not ever smoked (88.3%) or drank (84.6%).

Table 1 Sociodemographic characteristics of participants by different population groups
Full size table

Comparison of general vaccination behavior and vaccine hesitancy among different population groups

Differences of general vaccination behavior and vaccine hesitancy in different population groups were shown in Table 2. For public health professionals, 94.3% of them agreed that vaccines can protect them from diseases, which was higher than that in medical workers (90.5%), students (87.5%) and general population (88.7%). Among medical workers, the majority of them (80.0%) agreed that they will get all vaccines that the National Immunization Program or government recommended, however, a lower proportion was in students (76.5%), general population (72.6%) and public health professionals (75.0%). When the participants were asked about whether they were hesitated to get vaccination, 39.4% of general population were hesitant and it was higher than in other three population groups. Regarding the sorts of vaccines they hesitated or refused, general population ranked the highest on hesitation in receiving pneumococcal vaccine (27.4%) and health workers ranked the highest in refusing pneumococcal vaccine (9.8%). In Comparation of the General Vaccine Hesitancy Scale scores in different groups, medical workers had a higher score (20.33 \(\pm\) 8.59) than students (20.32 \(\pm\) 8.11), general population (19.87 \(\pm\) 7.61) and public health professionals (18.48 \(\pm\) 7.51).

Table 2 Comparison of general vaccination behavior and vaccine hesitancy among different population groups
Full size table

Comparison of COVID-19 vaccine hesitancy and potential factors among different population groups

In this study, 15.6% (661) of participants were observed having COVID-19 vaccine hesitancy. Among different groups, 180 (23.9%) student, 92 (21.2%) general population, 349 (13.1%) medical workers and 40 (10.4%) public health professionals self-reported having COVID-19 vaccine hesitancy. Compared to medical workers, students and public health professionals, the general population had the higher score (10.06 \(\pm\) 1.79) of the concerns about infection with COVID-19. Regarding to the attitudes of respondents to COVID-19 epidemic, 75.8% of public health professionals agreed that COVID-19 epidemic is a severe problem affecting people’s health, which was significantly higher than other groups. And a statistically higher proportion of medical workers (89.9%) agreed that COVID-19 will be a great threat to their health if they infected compared to other 3 groups.

Among different groups, 94.3% of public health professionals would get COVID-19 vaccine if doctors recommend, 57.6% of students’ vaccination intention would be affected by their family members or friends, the ratings were significantly higher. Regarding the responses of the information about COVID-19 vaccine, 90.1% of public health professionals reported they need transparent information about COVID-19 vaccine and 63.5% had received negative information, 42.0% of students had doubts about the source of information. When participants were asked if the time costs in waiting for the vaccination or staying at the clinic would be barriers for them to vaccinate, a higher proportion of students were responded “Yes” compared to other three groups. For public health professionals, 9.6% of them self-reported that they have no need of getting COVID-19 vaccine because they are healthy, however, 42.2% of them had gotten emergency COVID-19 vaccination for some reasons (Table 3).

Table 3 Comparison of COVID-19 vaccine hesitancy and potential factors among different population groups
Full size table

The predictors for COVID-19 vaccine hesitancy among participants

According with results from the multivariate analyses (Table 4), age was significantly associated with hesitancy, with older age being more likely to have COVID-19 vaccine hesitancy (OR: 0.974, 95% CI: 0.956 -0.993). Gender was significantly associated with hesitancy, female was more likely to be hesitant about COVID-19 vaccine than male (OR: 1.331, 95% CI: 1.050–1.687). Among different population groups, there were no statistical differences in the comparison of the other three populations and the general population (all P > 0.05). Those who agreed that the vaccine would protect them from the disease were less hesitant to receive the COVID-19 vaccine (OR: 0.404, 95% CI: 0.301–0.543). Participants who ever hesitated or refused to get vaccination were more likely to be hesitant (P < 0.05). The results showed that respondents' concerns about the infection with COVID-19 were associated with hesitancy, and those with higher self-report scores were more likely to be hesitant (OR: 1.086, 95% CI: 1.032–1.143). Higher scores of the General Vaccine Hesitancy Scale were associated with greater hesitancy towards COVID-19 vaccination (OR: 1.043, 95% CI: 1.029–1.056). Participants who will get COVID-19 vaccine if doctors recommend were less likely to hesitate (OR: 0.176, 95% CI: 0.132–0.234). However, participants whose vaccination intentions would be influenced by recommendations from family and friends were more likely to be hesitant (OR: 1.533, 95% CI: 1.212–1.940). Those who thought that they have no need of getting COVID-19 vaccine because they are healthy were more likely to be hesitant (OR: 1.938, 95% CI: 1.495–2.512). Participants who had doubts about the source of information (OR: 2.517, 95% CI: 1.697–2.742) and received negative information about the vaccine before (OR: 1.563, 95% CI: 1.229–1.986) were more likely to have COVID-19 vaccine hesitancy. Participants who needed transparent information about COVID-19 vaccine and would get COVID-19 vaccine after receiving the negative information were both less likely to be hesitant to get COVID-19 vaccine (P < 0.05).

Table 4 Predictors of COVID-19 vaccine hesitancy among participants (n = 4227)
Full size table

Discussion

In current study, 15.6% of all participants self-reported having COVID-19 vaccine hesitancy, the rate was higher than the rate previously investigated in China (8.7%), however, it was lower than the findings that 22.4% in France, 25.5% in India, 29.2% in Italy and 37.4% in Ethiopia [31,32,33,34]. Among the study participants, the students had the highest rate (23.9%) of hesitancy, followed by general population (21.2%), medical workers (13.1%), and public health professionals (10.4%). Apart from changing attitudes to the increasingly severe COVID-19 pandemic and different study time, different socio-demographic factors, levels of health literacy, particularly with respect to immunization schedules, changes in local health policies and advances in the development of the COVID-19 vaccines may account for the differences on COVID-19 vaccine hesitancy. At present, the COVID-19 vaccine is available in China and the effectiveness of COVID-19 vaccination had been proved, however, this level of hesitancy among the population might be a barrier to the establishment of herd immunity.

The current study demonstrated that there were no significant differences among different populations in terms of the level of vaccine hesitancy. All individuals may have concerns on safety and efficacy issues of COVID-19 vaccination, as the COVID-19 vaccines were not undergone long-term clinical trials as other vaccines, the concern is one source of vaccine hesitancy [35,36,37]. Apart from widespread worries about vaccine safety and effectiveness, previous immunization behaviors can also influence vaccine uptake. Participants who have ever hesitated or refused to get vaccination were more likely to be hesitant for the vaccination against COVID-19 in our study. Similarly, another survey found that whether a person had the flu shot was a prominent determinant of COVID-19 vaccine avoidance [38]. And our results showed that participants who scored higher on the General Vaccine Hesitancy Scale were more likely to have hesitancy about the COVID-19 vaccine. In conclusion, the causes of vaccine hesitancy are complex and various, interventions should be developed to address different populations' hesitancy, especially the common causes. Timely health education and communication conducted by authoritative sources with corresponding explanations about their side effects will be critical to alleviate public concerns about vaccine safety [39, 40]. In addition, targeted interventions for those who have previously hesitated to receive the vaccine to enhance their willingness to undergo vaccination, are also needed.

Recommendations from physicians functioned as a motivator for participants to get vaccinated, and people would get the COVID-19 vaccine if their physicians recommended it. Medical workers always serve as the most trusted advisors and influencers of vaccination decisions, studies also demonstrated that those who valued doctor’s recommendations tended to get vaccinated immediately [31, 41]. However, doctors may be reluctant to spend time discussing vaccination with their patients, or they may feel they do not have enough information to address the issues that arise when recommending vaccines to their patients [42]. And if doctors themselves are hesitant about vaccines, their willingness to recommend vaccines to others may be reduced [43,44,45]. Even worse, their apprehensive attitude toward vaccines may exacerbate patients’ worries and doubts about vaccination [46]. Hence, educational campaigns based on accurate, authoritative knowledge of vaccines, maintaining a trustworthy patient-provider relationship, and training in communication practices might be working for building their own confidence in vaccines and willingness to recommend vaccines to others [43, 47].

Moreover, our study highlighted the needs of transparent information about COVID-19 vaccine development, efficacy, and safety. During the COVID-19 pandemic, governments and the public were unavoidably exposed to huge amount of rapid and far-reaching spread of questionable information, namely infodemic. Some media or websites exaggerated or made unreliable news on vaccination to attract more followers and negative information will be the possible sources of the increase in mistrust about vaccines[48,49,50]. Participants who received negative information about getting the COVID-19 vaccine were more likely to be hesitant in our study, which is consistent with previous studies [51, 52]. As the role of social media in public health promotion has grown, public health departments can also utilize the Internet for authoritative information dissemination, which will produce a positive impact on public health crises and vaccine campaigns [53, 54]. Medical workers are historically and uniformly important drivers of vaccine uptake, the information from them is generally accepted as authoritative, so the messages they send using social media platforms will be the primary information that informs the public's decision to vaccinate [55]. And they are essential to facilitate the interconnectedness of the general public, medical and public health communities on COVID-19. Therefore, medical workers can provide correct and accurate information, clarify misinformation through Internet to improve public’s confidence in vaccination. What's more noteworthy is that medical workers should be trained in the use of social media and be extremely careful in disseminating their opinions because their opinions are generally considered reliable, misinformation from them will mislead the public into making negative decisions [55]. And establishing suitable information exchange platform between the government and the public would be helpful to create a trustworthy environment, thus increasing the uptake of vaccines.

To overcome vaccine misinformation on social media, public health departments need to accurately monitor the spread of misinformation about vaccination in social media, which will not only help explore people's major concerns but combat false beliefs about vaccination timely. And public health-related authorities should establish an online platform that generates strategic tweets to fill knowledge gaps and leverage authoritative experts or respected celebrities to promote the benefits of vaccines to increase public’s willingness of vaccination [56, 57]. More importantly, educating social media users on how to distinguish reliable information and to encourage them not to circulate false information are helpful for tackling COVID-19-related misinformation [58]. Efforts by the government and public health community to maintain correct and authoritative messaging throughout the vaccine development and administration phases will be an effective measure for us to prevent misinformation from spreading, reduce vaccine hesitancy, and increase vaccination rates.

Limitations

Our survey was conducted before the COVID-19 vaccine became widely available in China. Therefore, differences between the prevalence of hesitancy in our study and the actual vaccination rate later on might exist. However, our study still provided meaningful results in terms of the prevalence and related factors of the vaccine hesitancy among various populations. Although four different population groups were surveyed in our study, the generalizability of our results will still be limited in certain aspects due to the nonprobability sampling we used. Also, the questionnaires were self-reported online, thus the information bias probably existed in this study.

Conclusions

Given information from healthcare professionals about vaccination recommendations will have a positive impact on public health crises and vaccine campaigns, providing appropriate information to them and training on communicating skills are of most important for their own benefit and the public’s. Since the negative information of COVID-19 vaccine could cause and increase vaccine hesitancy, transparent and authoritative information about the vaccine was vital for public to make vaccination decisions. Evidence-based information strategies where the potential benefits and risks of vaccination are properly explained, reducing the spread of misinformation and disseminating facts in a timely and accurate way, will likely reduce vaccine hesitancy.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

CDC:

Centers for Disease Control and Prevention

CI:

Confidence interval

COVID-19:

Coronavirus disease 2019

OR:

Odds ratio

VHS:

Vaccine Hesitancy Scale

WHO:

World Health Organization

References

  1. Romano CM, Chebabo A, Levi JE. Past, present, and future of COVID-19: a review. Braz J Med Biol Res. 2020;53(9):e10475.

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Yang P, Wang X. COVID-19: a new challenge for human beings. Cell Mol Immunol. 2020;17(5):555–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Ansari-Moghaddam A, Seraji M, Sharafi Z, Mohammadi M, Okati-Aliabad H. The protection motivation theory for predict intention of COVID-19 vaccination in Iran: a structural equation modeling approach. BMC Public Health. 2021;21(1):1165.

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Dube E, Laberge C, Guay M, Bramadat P, Roy R, Bettinger J. Vaccine hesitancy: an overview. Hum Vaccin Immunother. 2013;9(8):1763–73.

    PubMed  PubMed Central  Google Scholar 

  5. Launay O. Risks of non-vaccination. Med Mal Infect. 2020;50(1):1–2.

    CAS  PubMed  Google Scholar 

  6. MacDonald NE. Vaccine hesitancy: definition, scope and determinants. Vaccine. 2015;33(34):4161–4.

    Google Scholar 

  7. Dubé E, MacDonald NE. How can a global pandemic affect vaccine hesitancy? Expert Rev Vaccines. 2020;19(10):899–901.

    PubMed  Google Scholar 

  8. Pogue K, Jensen JL, Stancil CK, Ferguson DG, Hughes SJ, Mello EJ, et al. Influences on attitudes regarding potential COVID-19 vaccination in the United States. Vaccines (Basel). 2020;8(4):582.

    CAS  PubMed Central  Google Scholar 

  9. Reiter PL, Pennell ML, Katz ML. Acceptability of a COVID-19 vaccine among adults in the United States: How many people would get vaccinated? Vaccine. 2020;38(42):6500–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Malik AA, McFadden SM, Elharake J, Omer SB. Determinants of COVID-19 vaccine acceptance in the US. EClinicalMedicine. 2020;26:100495.

    PubMed  PubMed Central  Google Scholar 

  11. Lazarus JV, Ratzan SC, Palayew A, Gostin LO, Larson HJ, Rabin K, et al. A global survey of potential acceptance of a COVID-19 vaccine. Nat Med. 2020;27(2):225–8.

    PubMed  Google Scholar 

  12. Sun Y, Chen X, Cao M, Xiang T, Zhang J, Wang P, et al. Will healthcare workers accept a COVID-19 vaccine when it becomes available? A cross-sectional study in China. Front Public Health. 2021;9:664905.

    PubMed  PubMed Central  Google Scholar 

  13. Salali GD, Uysal MS. COVID-19 vaccine hesitancy is associated with beliefs on the origin of the novel coronavirus in the UK and Turkey. Psychol Med. 2020. https://doi.org/10.1017/S0033291720004067.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Fisher KA, Bloomstone SJ, Walder J, Crawford S, Fouayzi H, Mazor KM. Attitudes toward a potential SARS-CoV-2 Vaccine: a survey of U.S. adults. Ann Intern Med. 2020;173(12):964–73.

    PubMed  Google Scholar 

  15. Verger P, Scronias D, Dauby N, Adedzi KA, Gobert C, Bergeat M, et al. Attitudes of healthcare workers towards COVID-19 vaccination: a survey in France and French-speaking parts of Belgium and Canada, 2020. Eurosurveillance. 2021. https://doi.org/10.2807/1560-7917.ES.2021.26.3.2002047.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Lucia VC, Kelekar A, Afonso NM. COVID-19 vaccine hesitancy among medical students. J Public Health (Oxf). 2021;43(3):445–9.

    Google Scholar 

  17. Lim LJ, Lim AJW, Fong KK, Lee CG. Sentiments regarding COVID-19 vaccination among graduate students in Singapore. Vaccines (Basel). 2021;9(10):1141.

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Walker AN, Zhang T, Peng XQ, Ge JJ, Gu H, You H. Vaccine acceptance and its influencing factors: an online cross-sectional study among international college students studying in China. Vaccines (Basel). 2021;9(6):585.

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Leng A, Maitland E, Wang S, Nicholas S, Liu R, Wang J. Individual preferences for COVID-19 vaccination in China. Vaccine. 2021;39(2):247–54.

    CAS  PubMed  Google Scholar 

  20. Ruiz JB, Bell RA. Predictors of intention to vaccinate against COVID-19: Results of a nationwide survey. Vaccine. 2021;39(7):1080–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Alibrahim J, Awad A. COVID-19 vaccine hesitancy among the public in Kuwait: a cross-sectional survey. Int J Environ Res Public Health. 2021;18(16):8836.

    CAS  PubMed  PubMed Central  Google Scholar 

  22. China NHCotPsRo. COVID-19 Vaccination Status. http://www.nhc.gov.cn/xcs/yqfkdt/202112/02052467ced44fe69cba8fbf31293246.shtml. Accessed 09 Nov 2021.

  23. Taherdoost H. Determining sample size; how to calculate survey sample size. Int J Econ Manage Syst. 2017;2:237–9.

  24. Guay M, Gosselin V, Petit G, Baron G, Gagneur A. Determinants of vaccine hesitancy in Quebec: a large population-based survey. Hum Vaccin Immunother. 2019;15(11):2527–33.

    PubMed  PubMed Central  Google Scholar 

  25. Liau A, Zimet GD, Fortenberry JD. Attitudes about human immunodeficiency virus immunization: the influence of health beliefs and vaccine characteristics. Sex Transm Dis. 1998;25(2):76–81.

    CAS  PubMed  Google Scholar 

  26. Head KJ, Kasting ML, Sturm LA, Hartsock JA, Zimet GD. A national survey assessing SARS-CoV-2 vaccination intentions: implications for future public health communication efforts. Sci Commun. 2020;42(5):698–723.

    PubMed Central  Google Scholar 

  27. Larson HJ, Jarrett C, Schulz WS, Chaudhuri M, Zhou Y, Dube E, et al. Measuring vaccine hesitancy: the development of a survey tool. Vaccine. 2015;33(34):4165–75.

    PubMed  Google Scholar 

  28. Shapiro GK, Tatar O, Dube E, Amsel R, Knauper B, Naz A, et al. The vaccine hesitancy scale: psychometric properties and validation. Vaccine. 2018;36(5):660–7.

    PubMed  Google Scholar 

  29. Opel DJ, Mangione-Smith R, Taylor JA, Korfiatis C, Wiese C, Catz S, et al. Development of a survey to identify vaccine-hesitant parents: the parent attitudes about childhood vaccines survey. Hum Vaccin. 2011;7(4):419–25.

    PubMed  PubMed Central  Google Scholar 

  30. Opel DJ, Taylor JA, Mangione-Smith R, Solomon C, Zhao C, Catz S, et al. Validity and reliability of a survey to identify vaccine-hesitant parents. Vaccine. 2011;29(38):6598–605.

    PubMed  Google Scholar 

  31. Wang J, Jing R, Lai X, Zhang H, Lyu Y, Knoll MD, et al. Acceptance of COVID-19 vaccination during the COVID-19 pandemic in China. Vaccines (Basel). 2020;8(3):482.

    CAS  PubMed Central  Google Scholar 

  32. Detoc M, Bruel S, Frappe P, Tardy B, Botelho-Nevers E, Gagneux-Brunon A. Intention to participate in a COVID-19 vaccine clinical trial and to get vaccinated against COVID-19 in France during the pandemic. Vaccine. 2020;38(45):7002–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Abebe H, Shitu S, Mose A. Understanding of COVID-19 vaccine knowledge, attitude, acceptance, and determinates of COVID-19 vaccine acceptance among adult population in Ethiopia. Infect Drug Resist. 2021;14:2015–25.

    PubMed  PubMed Central  Google Scholar 

  34. Lazarus JV, Ratzan SC, Palayew A, Gostin LO, Larson HJ, Rabin K, et al. A global survey of potential acceptance of a COVID-19 vaccine. Nat Med. 2021;27(2):225–8.

    CAS  PubMed  Google Scholar 

  35. Yaqub O, Castle-Clarke S, Sevdalis N, Chataway J. Attitudes to vaccination: a critical review. Soc Sci Med. 1982;2014(112):1–11.

    Google Scholar 

  36. Dubé E, Macdonald NE. Chapter 26 - Vaccine Acceptance: Barriers, Perceived Risks, Benefits, and Irrational Beliefs: The Vaccine Book; 2016. https://doi.org/10.1016/B978-0-12-802174-3.00026-6

  37. Edwards B, Biddle N, Gray M, Sollis K. COVID-19 vaccine hesitancy and resistance: Correlates in a nationally representative longitudinal survey of the Australian population. PLoS ONE. 2021;16(3):e0248892.

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Thunström L, Ashworth M, Finnoff D, Newbold SC. Hesitancy toward a COVID-19 vaccine. EcoHealth. 2021;18:1–17.

    Google Scholar 

  39. Larson HJ, Jarrett C, Eckersberger E, Smith DM, Paterson P. Understanding vaccine hesitancy around vaccines and vaccination from a global perspective: a systematic review of published literature, 2007–2012. Vaccine. 2014;32(19):2150–9.

    PubMed  Google Scholar 

  40. Dubé E, MacDonald NE. Vaccine acceptance: barriers, perceived risks, benefits, and irrational beliefs. The Vaccine Book: Elsevier; 2016. p. 507–28.

    Google Scholar 

  41. Lin C, Tu P, Beitsch LM. Confidence and receptivity for COVID-19 vaccines: a rapid systematic review. Vaccines (Basel). 2020;9(1):16.

    PubMed  PubMed Central  Google Scholar 

  42. Dubé E. Addressing vaccine hesitancy: the crucial role of healthcare providers. Clin Microbiol Infect. 2017;23(5):279–80.

    PubMed  Google Scholar 

  43. Paterson P, Meurice F, Stanberry LR, Glismann S, Rosenthal SL, Larson HJ. Vaccine hesitancy and healthcare providers. Vaccine. 2016;34(52):6700–6.

    PubMed  Google Scholar 

  44. Zhang J, While AE, Norman IJ. Nurses’ knowledge and risk perception towards seasonal influenza and vaccination and their vaccination behaviours: a cross-sectional survey. Int J Nurs Stud. 2011;48(10):1281–9.

    PubMed  Google Scholar 

  45. Shekhar R, Sheikh AB, Upadhyay S, Singh M, Kottewar S, Mir H, et al. COVID-19 vaccine acceptance among health care workers in the United States. Vaccines (Basel). 2021;9(2):119.

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Verger P, Fressard L, Collange F, Gautier A, Jestin C, Launay O, et al. Vaccine hesitancy among general practitioners and its determinants during controversies: a national cross-sectional survey in France. EBioMedicine. 2015;2(8):891–7.

    PubMed  PubMed Central  Google Scholar 

  47. Shen SC, Dubey V. Addressing vaccine hesitancy: clinical guidance for primary care physicians working with parents. Can Fam Physician. 2019;65(3):175–81.

    PubMed  Google Scholar 

  48. The Lancet Infectious Diseases. The COVID-19 infodemic. Lancet Infect Dis. 2020;20(8):875.

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Hou Z, Tong Y, Du F, Lu L, Zhao S, Yu K, et al. Assessing COVID-19 vaccine hesitancy, confidence and public engagement: a global social listening study. J Med Internet Res. 2021;23(6):e27632.

    PubMed  PubMed Central  Google Scholar 

  50. Aquino F, Donzelli G, De Franco E, Privitera G, Lopalco PL, Carducci A. The web and public confidence in MMR vaccination in Italy. Vaccine. 2017;35(35):4494–8.

    PubMed  Google Scholar 

  51. Puri N, Coomes EA, Haghbayan H, Gunaratne K. Social media and vaccine hesitancy: new updates for the era of COVID-19 and globalized infectious diseases. Hum Vaccin Immunother. 2020;16(11):2586–93.

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Migriño J Jr, Gayados B, Birol KRJ, De Jesus L, Lopez CW, Mercado WC, et al. Factors affecting vaccine hesitancy among families with children 2 years old and younger in two urban communities in Manila, Philippines. WPSAR. 2020;11(2):20–6.

    PubMed  PubMed Central  Google Scholar 

  53. Donzelli G, Palomba G, Federigi I, Aquino F, Cioni L, Verani M, et al. Misinformation on vaccination: a quantitative analysis of YouTube videos. Hum Vaccin Immunother. 2018;14(7):1654–9.

    PubMed  PubMed Central  Google Scholar 

  54. Kortum P, Edwards C, Richards-Kortum R. The impact of inaccurate Internet health information in a secondary school learning environment. J Med Internet Res. 2008;10(2):e17.

    PubMed  PubMed Central  Google Scholar 

  55. Hernandez RG, Hagen L, Walker K, O’Leary H, Lengacher C. The COVID-19 vaccine social media infodemic: healthcare providers’ missed dose in addressing misinformation and vaccine hesitancy. Hum Vaccin Immunother. 2021;17(9):2962–4.

    CAS  PubMed  Google Scholar 

  56. Al-Metwali BZ, Al-Jumaili AA, Al-Alag ZA, Sorofman B. Exploring the acceptance of COVID-19 vaccine among healthcare workers and general population using health belief model. J Eval Clin Pract. 2021. https://doi.org/10.1111/jep.13581.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Mills M, Rahal C, Brazel D, Yan J, Gieysztor SJ. COVID-19 vaccine deployment: behaviour, ethics, misinformation and policy strategies. London: The Royal Society & The British Academy; 2020.

    Google Scholar 

  58. Gabarron E, Oyeyemi SO, Wynn R. COVID-19-related misinformation on social media: a systematic review. Bull World Health Organ. 2021;99(6):455–63.

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors acknowledge the contributions of all associated workers and students of the seven collaborating institutions for the support in data collection.

Funding

This study was funded by the Asian Regional Special Cooperation Fund of National Health Commission of the People’s Republic of China (BLXM01).

Author information

Authors and Affiliations

  1. School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

    Yiman Huang, Xiaoyou Su, Weijun Xiao, Hao Wang & Mingyu Si

  2. School of Nursing, Jining Medical University, Jining, Shandong, China

    Wenjun Wang

  3. Affiliated Tumor Hospital, Xinjiang Medical University, Urumqi, China

    Xiaofen Gu

  4. Public Health School, Dalian Medical University, Dalian, China

    Li Ma

  5. Department of Clinical Research, The First Affiliated Hospital, Jinan University, Guangzhou, China

    Li Li

  6. Henan Cancer Hospital, Affiliate Cancer Hospital of Zhengzhou University, Zhengzhou, China

    Shaokai Zhang

  7. Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China

    Chunxia Yang

  8. School of Public Health, Department of Clinical Research, Baotou Medical College, Baotou, China

    Yanqin Yu

  9. Department of Cancer Epidemiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 South Panjiayuan, Chaoyang District, Beijing, China

    Youlin Qiao

Authors
  1. Yiman Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaoyou Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Weijun Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hao Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mingyu Si
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Wenjun Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Xiaofen Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Li Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Li Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Shaokai Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Chunxia Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Yanqin Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Youlin Qiao
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

XS, YH prepared the first draft. XS, YQ and YH made substantial contributions to the design of the work. MS, WX and HW substantively revised the draft and provided writing-review. XS, WW, XG, LM, LL, SZ, CY and YY were responsible for the questionnaire survey of people in seven geographical regions of China. XS and YH analyzed the data. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Xiaoyou Su.

Ethics declarations

Ethics approval and consent to participate

This study has been approved by the Ethical Review Committee of Chinese Center for Disease Control and Prevention on December 4th, 2020 (approval number: 202020). An electronic informed consent was provided before the start of the questionnaire survey, upon completion of the informed consent, participants filled in the on-line questionnaire.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: Table S1.

Scale items description (the COVID-19 vaccine hesitancy scale).

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Huang, Y., Su, X., Xiao, W. et al. COVID-19 vaccine hesitancy among different population groups in China: a national multicenter online survey. BMC Infect Dis 22, 153 (2022). https://doi.org/10.1186/s12879-022-07111-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12879-022-07111-0

Keywords

BMC Infectious Diseases

ISSN: 1471-2334

Contact us