ABSTRACT
This study aimed to explore the dynamic trends and determinants of COVID-19 vaccine hesitancy among adults in China from 2021 to 2022, providing evidence for targeted vaccination strategies under different epidemic control phases. We conducted four large-scale, anonymous, cross-sectional online surveys in January 2021, June 2021, January 2022, and June 2022. Adults aged 18 and older were recruited nationwide, with demographic weighting based on the 2020 National Census. Vaccine hesitancy was defined according to WHO SAGE guidelines. Multilevel regression and post-stratification (MRP) were applied to estimate standardized provincial-level vaccine hesitancy rates, and multilevel logistic models were used to examine influencing factors, including sociodemographic characteristics and constructs from the health belief model (HBM). Adjusted vaccine hesitancy rates showed a U-shaped trend: 33.78% in January 2021, dropping to 11.33% in June 2021, rising slightly to 16.13% in January 2022, and rebounding to 31.72% in June 2022. Hesitancy was initially driven by concerns over vaccine safety, while later stages reflected reduced risk perception and vaccination fatigue. Younger adults, women, urban residents, and those with higher education levels were more likely to exhibit hesitancy. HBM factors – particularly perceived safety and effectiveness – were significant early drivers but diminished in influence over time. Vaccine hesitancy among Chinese adults fluctuated with changes in pandemic context and public perception, shifting from safety concerns to complacency. Sustained public health efforts are needed to address psychological, social, and contextual barriers to vaccination, especially in later phases of epidemic control. Tailored strategies based on population subgroups and behavioral insights are essential to mitigate hesitancy and maintain high vaccination coverage.
KEYWORDS: COVID-19, vaccine hesitancy, health belief model, cross-sectional survey
Introduction
The unprecedented global rollout of COVID-19 vaccines has been a critical component of the public health response to the pandemic. While the rapid development and deployment of vaccines have enabled countries to mitigate the spread of SARS-CoV-2 and reduce associated morbidity and mortality, vaccine hesitancy has emerged as a persistent barrier to achieving optimal population-level protection.1,2 The World Health Organization (WHO) identified vaccine hesitancy as one of the top 10 threats to global health even prior to the COVID-19 pandemic.3 In the context of COVID-19, vaccine hesitancy presents a dynamic and multifactorial challenge that evolves alongside shifting epidemiological conditions, public perceptions, and policy environments.4–6
In China, the COVID-19 vaccination campaign began in late 2020 with the emergency approval of domestically developed inactivated vaccines. Unlike many countries experiencing severe outbreaks during early vaccine deployment, China maintained relatively low levels of community transmission through stringent containment measures.7,8 This unique epidemiological context may have shaped public attitudes toward vaccination in distinct ways. Initially, limited perceived urgency and concerns over vaccine safety contributed to substantial levels of hesitancy.9 As the campaign expanded and policy shifted toward widespread coverage and booster administration, new factors – including pandemic fatigue, low perceived risk, and declining social influence – became increasingly relevant.10
Despite the importance of understanding vaccine hesitancy, few studies in China have examined its evolution over time using large-scale, population-representative data. Most existing research relies on single-time-point surveys or focuses on specific subpopulations, limiting insights into how hesitancy trends fluctuate across different stages of the pandemic and among various demographic groups.9,11 Moreover, empirical evidence is lacking regarding how psychological constructs, such as those outlined in the Health Belief Model (HBM), interact with sociodemographic characteristics to influence hesitancy across different temporal contexts.12,13
To address these gaps, this study draws on data from four consecutive national cross-sectional surveys conducted between January 2021 and June 2022, covering critical stages of China’s vaccination campaign – from initial rollout to booster administration and normalized epidemic control. The objective of this study is to assess the dynamic trends in vaccine hesitancy among adults in China during different phases of the COVID-19 pandemic, and to identify key demographic and psychological factors associated with hesitancy, thereby informing more nuanced and context-sensitive public health interventions.
Methods
Study population
From 2021 to 2022, an anonymous online survey was administered every six months to collect information from Chinese residents regarding their COVID-19 vaccination status and intentions. Four cross-sectional surveys were conducted nationwide in January 2021, June 2021, January 2022, and June 2022, respectively.
Repeated cross-sectional surveys were employed to examine population-level changes in vaccine hesitancy across different phases of the COVID-19 pandemic. This design allows timely assessment of evolving attitudes using nationally representative samples, with vaccine hesitancy rates weighted according to provincial census data, while avoiding attrition common in the longitudinal study. Survey weights were determined based on publicly available demographic distributions (by province, gender, age, and education level) from the National Bureau of Statistics and provincial statistical bureaus (see “The Seventh National Population Census of 2020,” https://www.stats.gov.cn/sj/pcsj/rkpc/d7c/202303/P020230301403217959330), ensuring a geographically representative sample across genders and age groups throughout China.
Participants included adults aged 18 y or older who had been residing in the same region for over three months and were not part of a migrant population. Eligible participants had no reading comprehension impairments, serious mental illness, or intellectual disabilities, and provided informed consent to participate voluntarily.
Data collection
This multi-stage cross-sectional study collected data on vaccine hesitancy, reasons underlying hesitancy, and basic sociodemographic characteristics.
In this study, the primary outcome was vaccine hesitancy, which was defined as exhibiting either actual hesitation behavior (such as delaying or refusing vaccination despite accessibility) or a tendency toward such behavior (reluctance or hesitancy even if vaccination is feasible, or intention to delay/refuse when not yet eligible). This definition was consistent with the framework established by the WHO’s SAGE Working Group on Vaccine Hesitancy.
Data were collected at four distinct time points, corresponding to four national cross-sectional surveys conducted in January 2021 (Survey 1), June 2021 (Survey 2), January 2022 (Survey 3), and June 2022 (Survey 4). Sociodemographic information was collected, including age, gender, education level, and region. Age was categorized into three groups: 20–44 y, 45–59 y, and 60 y or older. Gender was classified as male or female. Place of residence was designated as either urban or rural. Educational attainment was grouped into three levels: junior high school or below, high school, and bachelor’s degree or above.
Additionally, the study measured the determinants of vaccine hesitancy, based on the Health Belief Model (HBM). These included perceived severity, referring to the individual’s assessment of the seriousness of COVID-19 symptoms and potential sequelae; perceived susceptibility, reflecting the perceived likelihood of contracting COVID-19; perceived effectiveness, indicating whether individuals believed the vaccine could effectively prevent infection; and perceived safety, referring to confidence in the vaccine’s safety profile. Furthermore, cues to action were captured, referring to external influences such as recommendations from others or observations of others’ vaccination behaviors, which may prompt individuals to consider vaccination. To identify the primary driver of vaccination decision-making, respondents were asked to select one most influential factor from five HBM constructs (perceived safety, effectiveness, severity, susceptibility, and cues to action) (Supplementary Questionnaire).
Statistical analysis
The study employed multilevel regression and post-stratification (MRP) to adjust estimates of vaccine hesitancy rates. For each of the four cross-sectional surveys, a multilevel regression model was constructed to estimate the probability of vaccine hesitancy (either behavior or tendency) at the provincial and individual levels, accounting for four key covariates: age, gender, urban-rural residence, and education level. These probabilities were then reweighted according to the national population distributions to produce weighted vaccine hesitancy rates, which were analyzed to observe dynamic changes across the four survey periods. A binary logistic regression with proportional odds assumptions was fitted to model vaccine hesitancy.14 Post-stratification estimation was then performed using age (3 levels), gender (2), region (2) and education (3), from which regionally weighted MRP estimates for China were derived.
Results
Sociodemographic characteristics
The distribution of respondents across the four survey periods from January 2021 to June 2022 is shown in Table 1. The sample sizes varied: 8514 in January 2021, 2520 in June 2021, 6414 in January 2022, and 7148 in June 2022. Overall, the majority of participants were aged 20–44 (64.39%), held a university degree or higher (59.24%), and were female (62.61%). Urban participants outnumbered rural ones (64.27%). Participants were drawn from all provinces in mainland China (excluding Hong Kong, Macao, and Taiwan), and were categorized into four major economic regions. The East and West had the highest representation (35.29% and 29.81%, respectively), followed by the Central (21.71%) and Northeast (13.20%) regions.
Table 1.
Demographic characteristics and vaccine hesitancy in the four cross-sectional surveys.
| Variable | 2021.1 (S1) |
2021.6 (S2) |
2022.1 (S3) |
2022.6 (S4) |
Overall |
|||||
|---|---|---|---|---|---|---|---|---|---|---|
| Sample | Frequency (%) | Sample | Frequency (%) | Sample | Frequency (%) | Sample | Frequency (%) | Sample | Frequency (%) | |
| Age | ||||||||||
| 20–44 y | 6596 | 2175 (32.97) | 1478 | 140 (9.47) | 5205 | 1047 (20.12) | 2559 | 934 (36.50) | 15,838 | 4296 (27.12) |
| 45–59 y | 1656 | 521 (31.46) | 935 | 85 (9.09) | 1176 | 154 (13.10) | 1901 | 534 (28.09) | 5668 | 1294 (22.83) |
| ≥60 y | 262 | 110 (41.98) | 107 | 15 (14.02) | 33 | 4 (12.12) | 2688 | 698 (25.97) | 3090 | 837 (26.76) |
| Education level | ||||||||||
| Junior high school or below | 462 | 147 (31.82) | 204 | 23 (11.27) | 2207 | 435 (19.71) | 3304 | 785 (23.76) | 6177 | 1390 (22.50) |
| High school | 769 | 220 (28.61) | 219 | 17 (7.76) | 1216 | 253 (20.81) | 1645 | 531 (32.28) | 3849 | 1021 (26.53) |
| Bachelor’s degree or above | 7283 | 2439 (33.49) | 2097 | 200 (9.54) | 2991 | 517 (17.29) | 2199 | 850 (38.65) | 14,570 | 4006 (27.49) |
| Sex | ||||||||||
| Male | 3094 | 864 (27.93) | 1122 | 94 (8.38) | 1849 | 323 (17.47) | 3131 | 920 (29.38) | 9196 | 2201 (23.93) |
| Female | 5420 | 1942 (35.83) | 1398 | 146 (10.44) | 4565 | 882 (19.32) | 4017 | 1246 (31.02) | 15,400 | 4216 (27.38) |
| Area | ||||||||||
| Urban | 6716 | 2300 (34.25) | 2124 | 208 (9.79) | 4158 | 767 (18.45) | 2810 | 1089 (38.75) | 15,808 | 4364 (27.61) |
| Rural | 1798 | 506 (28.14) | 396 | 32 (8.08) | 2256 | 438 (19.41) | 4338 | 1077 (24.83) | 8788 | 2053 (23.36) |
| Economic region | ||||||||||
| East | 4101 | 1445 (35.24) | 1250 | 144 (11.52) | 1758 | 299 (17.01) | 1570 | 328 (20.89) | 8679 | 2216 (25.53) |
| Central | 1204 | 370 (30.73) | 393 | 32 (8.14) | 2411 | 482 (19.99) | 1331 | 235 (17.66) | 5339 | 1119 (20.96) |
| West | 2861 | 858 (29.99) | 645 | 44 (6.82) | 1637 | 339 (20.71) | 2189 | 776 (35.45) | 7332 | 2017 (27.51) |
| Northeast | 348 | 133 (38.22) | 232 | 20 (8.62) | 608 | 85 (13.98) | 2058 | 827 (40.18) | 3246 | 1065 (32.81) |
To ensure comparability across survey rounds, post-stratification weights were applied using provincial census data. The weighting parameters used for provincial adjustment are listed in Supplementary Table 1. As there were substantial discrepancies between the national demographic structure and the study sample, standardized weights were used to adjust vaccine hesitancy rates accordingly.
Weighted vaccine hesitancy rates over time and by region
Based on the four cross-sectional surveys, the unweighted national vaccine hesitancy rates were: 32.96% in January 2021, decreasing to 9.52% in June 2021, remaining relatively low at 18.79% in January 2022, and increasing again to 30.30% in June 2022. After post-stratification using logistic regression based on national demographic parameters, the adjusted vaccine hesitancy rates were as follows: 34% (95% CI: 33%–35%) in January 2021; 11% (95% CI: 10%–13%) in June 2021; 16% (95% CI: 15%–17%) in January 2022; 32% (95% CI: 31%–32%) in June 2022. See Figure 1(A) for detailed trends before and after weighting. The overall trend shows an initial decline in hesitancy followed by a rebound. Regional analysis revealed similar patterns across China’s four major economic zones (Figures 1(B–E)). In the East, hesitancy dropped from 27.54% to 10.06% between January and June 2021, but rose again to 19.55% by June 2022. The Central region showed a decrease from 20.64% to 7.53% and remained around 15% through 2022. The West saw hesitancy drop sharply from 26.64% to 4.51%, then rise again to 25.67%. The Northeast had the highest baseline hesitancy at 35.56% in early 2021, dropped to 14.23% in June 2021, but rose again to 36.07% by June 2022. In summary, the Northeast consistently showed the highest hesitancy, while the Central region had the lowest. The East and Central showed relatively stable trends (fluctuations < 20%), while the West and Northeast exhibited greater variability.
Figure 1.
The dynamic tendency of post-stratification vaccine hesitancy rates across the country and the economic regions based on four cross-sectional surveys.
Multilevel cross-sectional analysis of sociodemographic determinants of vaccine hesitancy
Table 2 shows how vaccine hesitancy varied over time across demographic groups. In January 2021, older adults (≥60 y) had significantly higher hesitancy than younger groups (OR = 1.43, 95% CI: 1.14–1.80), but by June 2022, they were less hesitant than those aged 20–40 (OR = 0.69, 95% CI: 0.60–0.79). Education showed inconsistent effects: individuals with a bachelor’s degree or higher had lower hesitancy in January 2022 (OR = 0.84, 95% CI: 0.72–0.98), but higher hesitancy in June 2022 (OR = 1.42, 95% CI: 1.22–1.63) compared to those with junior high or less. Females consistently showed higher hesitancy, but the difference was statistically significant only in January 2021 (OR = 1.42, 95% CI: 1.29–1.56). Rural residents had significantly lower hesitancy than urban ones in both January 2021 (OR = 0.78, 95% CI: 0.69–0.88) and June 2022 (OR = 0.73, 95% CI: 0.66–0.80).
Table 2.
Mixed-effect models of influencing factors of vaccine hesitancy based on four independent cross-sectional surveys.
| Variable | 2021.1 (S1) |
2021.6 (S2) |
2022.1 (S3) |
2022.6 (S4) |
||||
|---|---|---|---|---|---|---|---|---|
| Freq (%) | OR (95% CI) | Freq (%) | OR (95% CI) | Freq (%) | OR (95% CI) | Freq (%) | OR (95% CI) | |
| Random Effect | ||||||||
| Age | ||||||||
| 20–44 y | 2175 (32.97) | 1.00 | 140 (9.47) | 1.00 | 1047 (20.12) | 1.00 | 934 (36.50) | 1.00 |
| 45–59 y | 521 (31.46) | 1.01 (0.91–1.14) | 85 (9.09) | 1.00 (0.75–1.33) | 154 (13.10) | 0.60 (0.50–0.70) | 534 (28.09) | 0.72 (0.64–0.82) |
| ≥60 y | 110 (41.98) | 1.43 (1.14–1.80) | 15 (14.02) | 1.71 (0.92–3.04) | 4 (12.12) | 0.55 (0.15–1.29) | 698 (25.97) | 0.69 (0.60–0.79) |
| Education level | ||||||||
| Junior high school or below | 147 (31.82) | 1.00 | 23 (11.27) | 1.00 | 435 (19.71) | 1.00 | 785 (23.76) | 1.00 |
| High school | 220 (28.61) | 0.80 (0.64–1.04) | 17 (7.76) | 0.64 (0.32–1.20) | 253 (20.81) | 1.10 (0.93–1.31) | 531 (32.28) | 1.40 (1.22–1.59) |
| Bachelor’s degree or above | 2439 (33.49) | 0.89 (0.73–1.10) | 200 (9.54) | 0.80 (0.50–1.33) | 517 (17.29) | 0.84 (0.72–0.98) | 850 (38.65) | 1.42 (1.22–1.63) |
| Sex | ||||||||
| Male | 864 (27.93) | 1.00 | 94 (8.38) | 1.00 | 323 (17.47) | 1.00 | 920 (29.38) | 1.00 |
| Female | 1942 (35.83) | 1.42 (1.29–1.56) | 146 (10.44) | 1.28 (0.99–1.66) | 882 (19.32) | 1.07 (0.92–1.24) | 1246 (31.02) | 0.98 (0.88–1.09) |
| Area | ||||||||
| Urban | 2300 (34.25) | 1.00 | 208 (9.79) | 1.00 | 767 (18.45) | 1.00 | 1089 (38.75) | 1.00 |
| Rural | 506 (28.14) | 0.78 (0.69–0.88) | 32 (8.08) | 0.81 (0.52–1.25) | 438 (19.41) | 0.99 (0.86–1.13) | 1077 (24.83) | 0.73 (0.66–0.80) |
| Fixed Effect | ||||||||
| Economic region | ||||||||
| East | 1445 (35.24) | 1.08 (1.01–1.42) | 144 (11.52) | 1.26 (1.01–7.85) | 299 (17.01) | 1.16 (1.01–2.83) | 328 (20.89) | 1.62 (1.07–9.09) |
| Central | 370 (30.73) | 32 (8.14) | 482 (19.99) | 235 (17.66) | ||||
| West | 858 (29.99) | 44 (6.82) | 339 (20.71) | 776 (35.45) | ||||
| Northeast | 133 (38.22) | 20 (8.62) | 85 (13.98) | 827 (40.18) | ||||
The economic region, included as a random effect in the mixed-effects model, showed statistically significant variation across all four survey waves. Table 3 presents the adjusted effects of survey timing, age, education, gender, and residence. Hesitancy dropped from 32.96% in January 2021 to 9.52% in June 2021 (OR = 0.22, 95% CI: 0.19–0.25), rose to 18.79% in January 2022 (OR = 0.49, 95% CI: 0.46–0.53), and returned to near baseline levels by June 2022. The highest hesitancy was among those aged 20–44 (27.12%), with lower rates in those aged 45–59 (OR = 0.82, 95% CI: 0.75–0.88) and ≥60 (OR = 0.79, 95% CI: 0.71–0.86). Individuals with junior high or less had the lowest hesitancy (22.5%), while high school (OR = 1.16, 95% CI: 1.06–1.26) and college-educated individuals (OR = 1.15, 95% CI: 1.06–1.24) had higher rates. Females had higher hesitancy (27.38%) than males (OR = 1.21, 95% CI: 1.14–1.28). Rural residents again showed lower hesitancy than urban ones (OR = 0.75, 95% CI: 0.71–0.80). The Northeast had the highest regional hesitancy (32.81%), while the Central region had the lowest (20.96%).
Table 3.
Mixed-effect model for factors associated with vaccine hesitancy using pooled data from four cross-sectional surveys.
| Variable | Sample | Vaccine hesitancy， Freq (%) |
OR | 95% CI |
|---|---|---|---|---|
| Random Effect | ||||
| Survey wave | ||||
| 2021.1 (S1) | 8514 | 2806 (32.96) | 1.00 | |
| 2021.6 (S2) | 2520 | 240 (9.52) | 0.22 | 0.19–0.25 |
| 2022.1 (S3) | 6414 | 1205 (18.79) | 0.49 | 0.46–0.53 |
| 2022.6 (S4) | 7148 | 2166 (30.30) | 1.09 | 0.97–1.20 |
| Age | ||||
| 20–44 y | 15,838 | 4296 (27.12) | 1.00 | |
| 45–59 y | 5395 | 1294 (22.83) | 0.82 | 0.75–0.88 |
| ≥60 y | 3363 | 837 (26.76) | 0.79 | 0.71–0.86 |
| Education level | ||||
| Junior high school or below | 6177 | 1390 (22.50) | 1.00 | |
| High school | 3849 | 1021 (26.53) | 1.16 | 1.06–1.26 |
| Bachelor’s degree or above | 14,570 | 4006 (27.49) | 1.15 | 1.06–1.24 |
| Sex | ||||
| Male | 9196 | 2201 (23.93) | 1.00 | |
| Female | 15,400 | 4216 (27.38) | 1.21 | 1.14–1.28 |
| Area | ||||
| Urban | 15,808 | 4364 (27.61) | 1.00 | |
| Rural | 8788 | 2053 (23.36) | 0.75 | 0.71–0.80 |
| Fixed Effect | ||||
| Economic region | 1.04 | 1.01–1.15 | ||
| East | 8679 | 2216 (23.53) | ||
| Central | 5339 | 1119 (20.96) | ||
| West | 7332 | 2017 (27.51) | ||
| Northeast | 3246 | 1065 (32.81) |
Multilevel cross-sectional analysis of the dynamic trends of HBM
Trends in Health Belief Model (HBM) determinants across the four surveys are shown in Figure 2(A). Concern about vaccine safety declined sharply from 54.39% in January 2021 to 12.96% in June 2022. Concern about vaccine effectiveness rose from 18.23% to 65.98% over the same period. Perceived severity of illness increased slightly then declined (from 6.31% to 4.70%). Perceived susceptibility remained relatively stable (13.38%–16.67%). Cues to action (influence from others) declined from 6.05% to 1.51%. And trends were consistent across the four economic regions, which were shown in Figure 2(B–E).
Figure 2.
The dynamic tendency of vaccination drivers based on the health belief model.
After adjusting for age, gender, education, residence, and region in a multilevel mixed-effects model, associations between HBM determinants and hesitancy were examined (Table 4). Vaccine safety was the strongest predictor in January 2021 (OR = 10.17, 95% CI: 9.14–11.32), but its influence declined in June 2021 (OR = 8.28, 95% CI: 6.23–10.99) and June 2022 (OR = 1.24, 95% CI: 1.05–1.47). Perceived effectiveness significantly influenced hesitancy early in 2021 (OR = 7.11, 95% CI: 6.41–7.88; OR = 7.21, 95% CI: 5.43–9.57), but had no statistical association in 2022. Perceived threat reduced hesitancy in 2021 (OR = 0.58, 95% CI: 0.53–0.64; OR = 0.36, 95% CI: 0.43–0.97), but lost significance in 2022. Cues to action strongly influenced hesitancy in 2021 (OR = 5.22, 95% CI: 3.73–7.31; OR = 4.70, 95% CI: 2.18–10.15), but had no significant impact by June 2022.
Table 4.
Multilevel adjusted models of vaccination drivers based on the health belief model.
| Variable | 2021.1 (S1) | 2021.6 (S2) | 2022.1 (S3) | 2022.6 (S4) |
|---|---|---|---|---|
| OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | |
| Perceived vaccine safety | 10.17 (9.14–11.32) | 8.28 (6.23–10.99) | 1.11 (0.95–1.30) | 1.24 (1.05–1.47) |
| Perceived effectiveness | 7.11 (6.41–7.88) | 7.21 (5.43–9.57) | 0.92 (0.81–1.05) | 0.92 (0.83–1.03) |
| Perceived threat | 0.58 (0.53–0.64) | 0.65 (0.43–0.97) | 0.94 (0.72–1.22) | 1.03 (0.80–1.33) |
| Perceived susceptibility | 0.36 (0.29–0.45) | 0.78 (0.47–1.27) | 0.84 (0.69–1.02) | 0.95 (0.82–1.10) |
| Cues to action | 5.22 (3.73–7.31) | 4.70 (2.18–10.15) | 1.37 (0.84–2.24) | 0.82 (0.54–1.26) |
Note: The dependent variable was vaccine hesitancy (the reference group is the group without vaccine hesitancy), the independent variables were each dimension of the health belief model. The adjusted variables were sociodemographic characteristics including age, sex, educational level and area for random effects, and economic region for fixed effects.
Discussion
This study investigates the dynamic trends and determinants of COVID-19 vaccine hesitancy in China over a period from January 2021 to June 2022. The analysis highlights the complex interplay of temporal shifts in shaping vaccine hesitancy, and provides important implications for public health strategies aimed at addressing vaccine hesitancy.
Dynamic trends in vaccine hesitancy
The trends in vaccine hesitancy observed over the study period demonstrate a U-shaped pattern, with a significant decline in hesitancy during the early mass vaccination phase, followed by a rebound in later stages. In January 2021, vaccine hesitancy was at its peak (33.78%), largely driven by concerns about vaccine safety and a general lack of trust in the rapidly developed vaccines.15 By June 2021, as vaccine distribution expanded and the mass vaccination was promoted, more individuals received their primary doses with a significant decrease in vaccine hesitancy (11.33%). This sharp decline was likely due to the broad dissemination of vaccination campaigns, increased public awareness, and government-led efforts to alleviate safety concerns.16 The influence of peers and social networks also grew stronger, as more people got vaccinated and began to normalize the behavior.17
In January 2022, as the focus shifted to booster doses, hesitancy rebounded slightly to 16.13%. The rise of the Omicron variant brought concerns about vaccine effectiveness, especially as breakthrough infections became more common.18,19 While initial hesitancy regarding primary vaccination was largely reduced, booster doses faced resistance, particularly among younger individuals who felt they had already completed their vaccination regimen.20 Social influence was less effective during this phase, as most people who had already been vaccinated did not feel the urgency to get a booster.21 The trend peaked in June 2022 (31.72%), reflecting vaccine fatigue and reduced perceived urgency as COVID-19 transmission slowed and restrictions eased. The focus on booster doses weakened as the urgency of vaccination declined, and social influence played a diminished role.22 Psychological fatigue from the prolonged pandemic also contributed to the decline in willingness to receive further doses.23
In terms of HBM determinants, concerns about vaccine safety initially had the strongest impact on hesitancy. In January 2021, 54.39% of respondents were concerned about vaccine safety, which strongly influenced their decisions. However, this concern decreased over time, with a notable decline in safety concerns by June 2022 (12.96%). In contrast, perceived vaccine effectiveness became more prominent as the pandemic progressed.24 The concern about vaccine effectiveness, which was low in January 2021 (18.23%), rose dramatically to 65.98% by June 2022. These shifts reflect the changing public perception as more evidence on vaccine safety and effectiveness emerged, and as new variants and the need for booster doses became more prevalent.25 Other HBM factors, such as perceived severity and susceptibility to COVID-19, exhibited more modest fluctuations. Perceived severity slightly increased but then declined over time, while perceived susceptibility remained relatively stable. Cues to action, such as social influence and the vaccination behaviors of close contacts, had a significant impact in 2021, but this influence diminished as the pandemic waned.26 Notably, in the final survey wave, most HBM constructs were no longer significantly associated with vaccine hesitancy, except for perceived vaccine safety. This likely reflects the transition of COVID-19 into a relatively stable, post-acute phase, during which perceived disease threat and expectations of vaccine effectiveness diminished and showed limited variability across individuals. In contrast, safety concerns remained salient in the context of repeated booster recommendations. These findings suggest that the determinants of vaccine hesitancy are stage-dependent, and that traditional health belief constructs may play a diminishing role as the pandemic context evolves.
Regional and sociodemographic variations in vaccine hesitancy
Regional differences played a crucial role in shaping vaccine hesitancy patterns. The Northeast region consistently exhibited the highest levels of vaccine hesitancy, with rates reaching 36.07% by June 2022, while the Central region had the lowest, at 20.96%. This regional variation is likely due to differences in access to vaccines, the speed of vaccine rollout, and regional health infrastructure.27 The East and West regions exhibited more volatile trends, with fluctuating rates reflecting the uneven pace of vaccine distribution and local social mobilization efforts.28
Sociodemographic factors also significantly influenced vaccine hesitancy. Older adults (≥60 y) exhibited higher hesitancy at the start of the vaccination campaign but showed improved willingness by June 2022, likely due to increasing awareness of the benefits of vaccination in preventing severe disease. On the other hand, younger adults (aged 20–44) initially showed lower hesitancy but experienced a higher rebound in hesitancy later in the study period, possibly due to concerns about the need for booster doses and perceptions of low personal risk.29,30
Educational level also showed variable effects: individuals with a higher level of education exhibited lower hesitancy in the early stages of vaccination, but by mid-2022, higher education was associated with increased hesitancy. The observed reversal in the association between educational level and vaccine hesitancy may reflect changing information environments over time. Individuals with higher education are more likely to actively seek and evaluate diverse information sources, which, in later stages of the pandemic, may increase sensitivity to uncertainty regarding booster effectiveness and long-term vaccine benefits.30–32 As the pandemic progressed, high-education individuals may have been more exposed to both scientific evidence and misinformation, making them more susceptible to conflicting messages.33 This suggests that high education alone does not guarantee higher vaccine acceptance and that greater engagement with diverse information sources may lead to increased hesitancy, particularly in the context of misleading vaccine information and uncertainty about long-term effects.34 Gender and urban-rural differences were also evident, with females and urban residents consistently showing higher hesitancy than males and rural residents.35,36 The differences in hesitancy across these sociodemographic groups underscore the need for tailored public health messaging to address the unique concerns of various populations.
Policy recommendations
The findings of this study highlight the evolving nature of vaccine hesitancy and the need for adaptive public health strategies. To sustain high levels of vaccination coverage, policymakers must address both the temporal and demographic shifts in vaccine hesitancy. Transparent and clear communication on vaccine safety and effectiveness will be crucial in maintaining public trust, especially as the focus shifts to booster doses and emerging variants.37 As concerns about vaccine safety decreased over time, the importance of communicating the effectiveness of vaccines, particularly for boosters, will become more prominent. Clear messaging around the benefits of boosters and their role in controlling the pandemic will be vital to curb rising hesitancy during later stages.38
Targeted interventions should be developed for vulnerable populations and tailored communication strategies should address their specific concerns, such as the risks of severe disease for older adults or providing more accessible, easy-to-understand information for less educated groups.39,40 Social mobilization efforts, leveraging community leaders and trusted figures, will also be crucial in increasing vaccine uptake, especially in regions with high hesitancy.41 The regional disparities in vaccine hesitancy highlighted in this study underscore the need for localized vaccination strategies.42 Areas with high hesitancy should intensify local outreach efforts, collaborate with community organizations, and ensure equitable access to vaccines.
Addressing vaccine fatigue will be a key challenge as the pandemic transitions to a phase of “normalization.”43 In regions with high vaccine coverage, maintaining high booster vaccination rates may be difficult as public urgency decreases.29 To combat this, policies should focus on reducing barriers to booster vaccination, increasing public awareness of the ongoing risks of COVID-19, and providing incentives to encourage continued vaccination.44 In conclusion, the dynamic nature of vaccine hesitancy in China reflects the influence of a range of factors, including time, region, sociodemographic characteristics, and psychological factors. Policymakers must adopt a flexible, multifaceted approach that can adapt to shifting public perceptions and emerging challenges. For example, in regions with persistently high hesitancy, such as the Northeast, localized risk communication and community-based outreach may be prioritized.45,46 Among younger and highly educated groups in later pandemic stages, messaging should focus on clarifying the benefits and necessity of booster vaccination.47 For older adults, interventions emphasizing protection against severe outcomes remain important.48 By targeting specific groups, tailoring communication strategies, and ensuring equitable access to vaccines, public health initiatives can effectively address hesitancy across all stages of the pandemic and strengthen societal resilience.49
Conclusion
This study analyzed four cross-sectional surveys conducted between 2021 and 2022 using multilevel regression and post-stratification weighting to examine the evolving trends and determinants of COVID-19 vaccine hesitancy among Chinese adults. Vaccine hesitancy showed marked temporal fluctuations, with higher rates in January 2021 and June 2022, following a U-shaped trend over time. As the pandemic progressed, public concern increasingly focused on vaccine effectiveness, while attention to safety issues and the influence of others’ vaccination behaviors declined.
Given the observed regional disparities, vaccination strategies should be tailored to provincial contexts and local uptake levels. To better capture the long-term dynamics of vaccine hesitancy, future research should include longitudinal tracking of public perceptions and vaccine outcomes. A dynamic monitoring system would support timely policy adjustments. Additionally, targeted interventions – such as personalized recommendations and subsidies – are needed for high-risk groups, including unvaccinated older adults and low-income populations, to reduce barriers and enhance overall vaccination coverage.
Supplementary Material
Biography
Fuqiang Cui serves as Director and Professor in the Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, China. He is chairman of the Hepatitis Prevention and Control Branch of China Vaccine Industry Association, member of the Expert Steering Committee of China Vaccinology Training Project of Bill Gates Foundation, deputy editor of Journal of Medical Virology.
Funding Statement
The author(s) reported there is no funding associated with the work featured in this article.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
All data relevant to the study are included in the article or uploaded as supplementary information.
Ethical approval
Ethical approval for this study was obtained from the Peking University Biomedical Ethics Committee (IRB00001052-22037).
Supplemental material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/21645515.2026.2634501
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
All data relevant to the study are included in the article or uploaded as supplementary information.