COVID-19 vaccine booster dose hesitancy among key groups: A cross-sectional study

ABSTRACT

Vaccination is an important tool for controlling the spread of coronavirus disease. Notably, it is important to achieve higher vaccine booster coverage across key groups – including front-line workers who could be exposed to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and those who live and work in crowded places – to prevent or reduce the risk of severe infection and poor disease outcomes. The purpose of the study was to understand the COVID-19 vaccine booster hesitancy among key groups in Luzhou, China, to analyze its influencing factors, and to provide scientific basis and theoretical guidance for the implementation of targeted intervention. Guided by the “3Cs” model, a self-designed questionnaire was prepared through a literature search using the Delphi method. All questionnaires were completed online through a QR code. Among the 548 participants, 173 had vaccine hesitation, accounting for 31.6%. Indeed, the scores for perceived safety, expected vaccine effectiveness, and trust in the vaccine delivery system were all lower in the hesitance group than in the non-hesitance group. However, the scores for low necessity were higher in the hesitance group. The factors influencing booster hesitancy were examined, and the probability of hesitancy decreased by 72.2% and 62.5% for every 1-point increase in the confidence and safety scores, respectively. Meanwhile, the probability of hesitancy increased by 25.8% for every 1-point increase in the low necessity score. Although the COVID-19 vaccine booster hesitancy reported in the study was relatively low, a large gap remains in the willingness to receive COVID-19 vaccination in China. Therefore, the state and relevant departments should take targeted measures to help reduce vaccine hesitancy among the public and enable smooth progress in the large-scale COVID-19 vaccine booster campaign in the future.

KEYWORDS:

• COVID-19
• vaccine booster hesitancy
• “3Cs” model

Introduction

Coronavirus disease 2019 (COVID-19) has plagued the world for more than two years now, threatening public health and hindering normal social life. Vaccination is the most economical and effective approach for preventing and controlling infectious diseases, including COVID-19.¹ However, vaccine hesitancy – defined as a delay in acceptance or refusal of vaccines, despite the availability of vaccine services – remains a major challenge.^2,3 Vaccine hesitancy is complex and context-specific, and varies with time, region, and the type of vaccine. It is influenced by factors such as complacency, convenience, and confidence.⁴ While some individuals are eager to receive all vaccines and some reject all vaccines, individuals with vaccine hesitancy lie within the continuum between these extremes. The group of vaccine-hesitant individuals includes those who refuse certain vaccines while accepting others, delay their vaccinations, or accept vaccinations but still have concerns.⁵ A study investigated the willingness of healthcare workers and outpatients to receive COVID-19 vaccination in Taiwan, and the results showed that people’s willingness was generally low, 23.4% (healthcare workers) and 30.7% (outpatients), respectively, which may be mainly because the COVID-19 epidemic was not serious in Taiwan at the time of the study survey.⁶ In addition, the results of a similar survey conducted in Iran showed that 32% of healthcare workers were vaccine hesitancy and that trust in the healthcare system may be the main factor， however, it is worth noting that effective education about these factors can reduce healthcare workers’ concerns about COVID-19 vaccination and thus increase vaccination rates.⁷ Fan et al⁸ showed that university students have positive attitudes toward COVID-19 vaccination, with knowledge of COVID-19 and perceived risk of COVID-19 as influencing factors, which were in good agreement with other studies.⁹ The 3Cs model (confidence, complacency, and convenience) is a vaccine hesitancy framework proposed by the WHO in 2011. The confidence dimension refers to the trust in the effectiveness and safety of vaccines, in the system that delivers them, and in the motivations of vaccination policymakers. The complacency dimension refers to the perception that vaccination is not a necessary preventive action. Finally, the convenience dimension refers to the availability and accessibility of vaccines,^2,10,11 which is affected by physical availability, affordability and cost-effectiveness, geographical accessibility, the ability to understand the need for vaccines (language and health literacy), and the convenience of immunization services.

Vaccine hesitancy is widespread in various countries/regions around the world. In 2019, the WHO included vaccine hesitancy among the ten biggest threats to global health.¹² A systematic review by Yasmin¹³ showed that vaccine acceptance rates varied from a low of 12% to a high of 91.4% in the United States, demographic characteristics are an important factor influencing vaccine acceptance. Specifically, vaccine acceptance varies by region in the United States, with relatively higher acceptance of COVID-19 among males and lower acceptance among Blacks/African-Americans and pregnant or breastfeeding women. Another systematic review and meta-analysis by Shikha¹⁴ showed that although their findings of 60.1% acceptance of COVID-19 vaccine, vaccine hesitancy was widespread and highly variable across countries/regions globally, with very low vaccine intention among the general population, especially in countries in the Eastern Mediterranean region, in contrast to the Western Pacific region. Many studies show a very strong negative correlation between vaccine hesitancy and vaccination rates.¹⁵ Vaccination, a key public health practice,¹⁶ can greatly reduce disease, disability, and death¹⁷ as long as population vaccination rates reach a certain level. The generation of herd immunity also can reduce the infection in unvaccinated individuals, further reducing disease risk.^18,19 The COVID-19 vaccine has been demonstrated to reduce the incidence of COVID-19 and decrease symptom severity and mortality rates in infected individuals. In addition, studies have shown that COVID-19 vaccine uptake is beneficial as prior evidence shows that COVID-19 vaccine uptake is associated with better quality of life.²⁰ Therefore, the effective control of the COVID-19 pandemic is highly dependent on global vaccination rates. However, with the continuous development of COVID-19 vaccines in various countries, vaccinate hesitancy among the public has become a growing concern. In order to improve vaccination rates, it is important to understand the factors that contribute to hesitancy regarding COVID-19 vaccination. Since the launch of the COVID-19 vaccination program in China in the autumn of 2020, few studies have examined the hesitancy regarding COVID-19 vaccines in the country. More specifically, vaccine booster hesitancy for COVID-19 has not been examined in China.

To address this gap, we conducted this study in China from February 2022 to March 2022. Given that the first batch of vaccinations were conducted among individuals aged 18–59 years in China, the present study was conducted in this group. Moreover, since the first phase of COVID-19 booster vaccination in China was focused on key groups, only individuals from key groups were enrolled. This included customs inspection and quarantine personnel, transportation personnel, college students, medical and healthcare personnel, public security, firefighters, individuals working in catering, logistics, and enterprises, and other relevant key personnel who could be exposed to SARS-CoV-2, and those who live and work in crowded places. The purpose of the study was to understand the COVID-19 vaccine booster hesitancy among key groups in Luzhou, China, and to analyze its influencing factors.

Respondents and method

Respondents

This study was approved by the Ethics Committee of Affiliated Hospital of Southwest Medical University (KY2022171).

Key groups for COVID-19 vaccination in Luzhou, China were selected as the subjects of the study. The inclusion criteria were as follows: age 18–59 years, ability to communicate appropriately, independent completion of questionnaire, and lack of contraindications to vaccination. The exclusion criteria are as follows: People who are not required by the state to receive booster shots. The sample size was calculated using the formula for cross-sectional surveys, i.e., n = (Z(1-α/2)/δ)²p(1-p) (Z: standard normal distribution; α: significance level; δ: distance from Mean to Limit (s);p: proportion). Based on the vaccination willingness observed in medical and health personnel in Zhejiang province (p = 27.65%)²¹ and by considering α = 0.05 and δ = 5%, the required sample size was found to be n = 308 people. The survey was conducted using online questionnaires. A total of 602 questionnaires were distributed, and 548 correctly completed questionnaires were collected (response rate = 91%).

Methods

Tools

A self-reported questionnaire was designed based on a literature review and experts’ opinions.^11,22,23 The questionnaire consisted of two parts: the basic information survey and the COVID-19 Vaccine Hesitancy Scale. The basic information questionnaire included questions on sex, age, marital status, education, whether the participants were medical workers, their type of current residence, self-assessed health status, whether their relatives had a medical background or were engaged in related work, their current illnesses, past medical history, and vaccine hesitancy. The COVID-19 Vaccine Hesitancy Scale, guided by the “3Cs” model, was self-designed based on a literature review, interviews with residents, and expert consultation. It included three dimensions – confidence, complacency, and convenience – and participants were instructed to respond to each point using a 5-point Likert scale (1, completely disagree; 2, largely disagree; 3, somewhat agree; 4, largely agree; and 5, completely agree). In the complacency domain, the question regarding vaccine necessity was scored in the opposite manner, i.e., with 1 corresponding to “completely agree” and 5 corresponding to “completely disagree.”²⁴ The reverse scoring was developed to transform a high score in the complacency domain into the corresponding low score. Confidence was measured by perceived vaccine safety and the effectiveness of and confidence in the vaccine provision system. Complacency was measured based on the perceived necessity of the vaccine and severity of COVID-19. Convenience was measured according to the perceived convenience of vaccination. In this study, the reliability of the “3Cs” model was measured, and the results showed that the Cronbach’s α value was 0.692.

Investigation method

The questionnaires (with QR codes) were generated using an online questionnaire tool. After convenience sampling, questionnaires were collected by scanning codes on site at key locations such as hospitals, transportation hubs, market supervision bureaus, schools, and colleges from March 12–22, 2021. The participants were fully informed about the study before they filled the questionnaires, and they filled the questionnaires voluntarily after providing informed consent.

Determination of vaccine hesitancy

According to previous studies⁵ and the definition of vaccine hesitancy,²⁵ the population was divided into two groups: vaccination recipients and vaccine hesitant individuals. Vaccination recipients were those who had a firm idea of vaccination and had been vaccinated with the COVID-19 booster. Vaccine hesitant individuals were: (1) Those who chose any of the first 5 options to the question “Please select your willingness to undergo vaccination according to your actual situation:” refuse all, refuse but unsure, refuse some, delay, accept some, accept but unsure, and accept all; this was based on the WHO definition of vaccine hesitancy;²⁶ (2) Those who were vaccinated but once had the idea of vaccine hesitancy and delayed it; (3) Those who refused the COVID-19 vaccine booster for reasons other than contraindications to vaccination.

Quality control

(1) Quality control items were set, and if any wrong answer was detected, the questionnaire was rendered invalid. (2) The questionnaire was tested multiple times before it was issued. The time for completion was determined to be at least 2 minutes. Thus, questionnaires that took less than 2 minutes to complete were considered invalid. (3) All questionnaires where the participants chose the same option for all questions were treated as invalid questionnaires. (4) Automated notifications were sent if the participants did not fill all the items before submission.

Statistical analysis

The statistical analyses were conducted by using the software SPSS Statistics version 25.0. If the quantitative data obeyed normal distribution, they were described as the mean±standard deviation. Qualitative data were described as sample numbers and percentages. The t-test was used to compare the scores for the 3C dimensions between the hesitance and non-hesitance groups. A multivariate logistic regression model was used to analyze the factors influencing hesitancy. P ≤ .05 was considered statistically significant.

Results

General information

A total of 548 valid questionnaires were collected. A majority of these 548 respondents were under the age of 40 years, accounting for 72.8% of the sample. Moreover, 426 were female (77.7%), 45.1% had a bachelor’s degree or above, and 59.9% were married. The most common range of monthly family income was below 6000 yuan (62.6%). Further, 63.5% lived in cities, 42.3% were medical professionals, 41.6% had family members working in the medical field, and 74.1% self-reported good health (Table 1).

Table 1. Differences in vaccine hesitancy according to sociodemographic characteristics.

Variable	Investigators (n)	Non-hesitancy [n (%)]	Hesitancy [n (%)]
Age (y)
18–29	243	147(39.2)	96(55.5)
30–39	156	100(26.7)	56(32.4)
40–49	66	58(15.5)	8(4.6)
≥50	83	70(18.7)	13(7.5)
Sex
Male	122	79(21.1)	43(24.9)
Female	426	296(78.9)	130(75.1)
Education
Secondary education and below	201	140(37.3)	61(35.3)
Higher education	347	235(62.7)	112(64.7)
Marital status
Married	328	240(64.0)	88(50.9)
Unmarried	220	135(36.0)	85(49.1)
Monthly income (yuan)
<6 000	343	230(61.3)	113(65.4)
6 000–9 999	122	90(24.0)	32(18.5)
≥10 000	83	55(14.7)	28(16.2)
Place of residence
City	348	244(65.1)	104(60.1)
Others	200	131(34.9)	69(39.9)
Healthcare worker
Yes	232	163(43.5)	69(39.9)
No	316	212(56.5)	104(60.1)
Relative with a medical background
Yes	228	166(44.3)	62(35.8)
No	320	209(55.7)	111(64.2)
Self-reported health
Good	406	274(73.1)	132(76.3)
Fair/Poor	142	101(26.9)	41(23.7)
Total	548	375	173

COVID-19 vaccination and hesitancy

Of the participants in this study, 403 were vaccinated, while 173 (31.6%) participants showed vaccination hesitancy. The confidence and convenience scores of the hesitancy group were significantly lower than those of the non-hesitancy group. However, there was no statistically significant difference in the complacency score between the two groups. More notably, within the confidence and complacency domain, the scores for vaccine safety, vaccine effectiveness, and trust in the vaccine delivery system were lower in the hesitance group than in the non-hesitance group. However, the low necessity scores were significantly higher in the hesitance group. Meanwhile, there was no statistically significant difference in the severity scores between the two groups (Table 2).

Table 2. Average scores of 548 respondents in each dimension of the 3cs model.

Dimension	Total (n = 548)	Vaccine hesitancy		t	p
		Yes (n = 173)	No (n = 375)
Confidence	4.37 ± 0.78	3.86 ± 0.86	4.61 ± 0.62	10.272	<.001
Safety	4.37 ± 0.80	3.85 ± 0.88	4.61 ± 0.63	10.218	<.001
Effective	4.32 ± 0.91	3.77 ± 1.00	4.57 ± 0.73	9.421	<.001
Trust in the vaccine delivery system	4.43 ± 0.78	3.97 ± 0.86	4.64 ± 0.63	9.123	<.001
Complacency	2.54 ± 1.04	2.65 ± 0.92	2.48 ± 1.09	1.824	.069
Necessity	1.80 ± 1.11	2.13 ± 1.07	1.65 ± 1.10	4.801	<.001
Severity	3.27 ± 1.52	3.17 ± 1.27	3.32 ± 1.62	1.214	.225
Convenience	4.24 ± 1.02	3.88 ± 0.94	4.41 ± 1.01	5.770	<.001

Trust in the vaccine delivery system comprises vaccine reliability, safety at vaccination venue, and reliability of vaccination personnel.

Factors influencing hesitancy for COVID-19 vaccination

Model 1 analysis showed that only confidence had a statistically significant impact on vaccine hesitancy after adjusting for age, sex, education, and other factors. Higher scores indicated lower vaccine hesitancy. Each 1-point increase in the confidence score was associated with a 72.2% decrease in the probability of vaccine hesitancy.

Model 2 analysis showed that safety and necessity had a statistically significant impact on vaccine hesitancy after adjustment for age, sex, education, and other factors. Higher scores for safety were related with lower hesitancy (62.5% decrease in hesitancy for every 1-point increase in the score), while higher scores for necessity indicated a higher possibility of hesitancy (25.8% increase in hesitancy for every 1-point increase in the score) (Table 3).

Table 3. Logistic regression analysis of factors affecting COVID-19 vaccine hesitancy.

Variable	B	S.E	Wald	p	OR	95%CI
Model 1
Confidence	−1.279	0.183	48.665	<.001	0.278	0.194–0.399
Complacency	0.210	0.111	3.555	.059	1.234	0.992–1.535
Convenience	−0.025	0.144	0.030	.863	0.975	0.736–1.293
Model2
Safety	−0.982	0.269	13.326	<.001	0.375	0.221–0.635
Effectiveness	−0.386	0.215	3.217	.073	0.680	0.446–1.036
Trust in the vaccine delivery system	0.187	0.318	0.346	.556	1.206	0.646–2.250
Necessity	0.230	0.104	4.873	.027	1.258	1.026–1.543
Severity	0.026	0.084	0.095	.759	1.026	0.870–1.211
Convenience	−0.050	0.148	0.115	.735	0.951	0.711–1.272

Model 1: dimensions of confidence, complacency, and convenience were involved.

Model 2: all six sub-dimensions were involved. Additionally, factors such as age, sex, education, marital status, monthly family income, place of residence, occupation (healthcare related or not), any relatives with a medical background, and health status (self-reported) were calibrated in both models.

Reason: the subjects of this study were all working staff. Relevant national departments and units recommend booster vaccination for key groups in key industries as long as there are no exceptions such as contraindications.

Discussion

The 3Cs model is considered one of the most effective models for the analysis of vaccine hesitancy due to its simple concept and ease of application.² Higher levels of perceived vaccine safety, effectiveness, and confidence in the vaccine delivery system are associated with lower levels of vaccination hesitancy.^24,27 Moreover, the higher the perceived necessity of vaccination and higher the severity of COVID-19 (i.e., lower complacency), the lower the vaccine hesitancy. In this study, the 3Cs model was used to investigate the COVID-19 vaccine booster hesitancy among key groups in Luzhou, China, and the results were consistent with these previous findings.^28,29

It has been demonstrated that the overall rate of hesitancy for COVID-19 vaccination ranges from 31.3% to 84.6%.^30,31 In this study, the rate of hesitancy for the COVID-19 vaccine booster was found to be 31.6%. However, a study that examined COVID-19 vaccine hesitancy among key groups in Luzhou, China in March reported a hesitancy rate of 44.9%,³² we speculate that the reason for this result may be that vaccine hesitancy has decreased with time. Overall, the rate of vaccine hesitancy is relatively low in China, and the rate of COVID-19 vaccine booster vaccine hesitancy was even lower.^33,34 This could be due to four primary reasons. First, since the initial COVID-19 vaccines were introduced into the market in China, basic anti-COVID-19 vaccinations were completed nationwide for people aged 12 and over using inactivated vaccines (2 doses), adenovirus vector vaccines (1 dose), and recombinant subunit vaccines (3 doses).³⁵ These vaccines have been proven to be safe. Second, although the virus is constantly mutating, data from China and the rest of the world show that the COVID-19 vaccine plays a positive role in reducing the disease severity and mortality associated with COVID-19, indicating the good efficacy of vaccines.³⁶ Third, free COVID-19 vaccination has promoted booster vaccination in China. Finally, strong support from national policies and units, including the establishment of vaccination sites in each community and the provision of special personnel for booster vaccination services, has also promoted booster vaccination in the country.³³

In the study, comparisons between the vaccine hesitance and non-hesitance groups showed that confidence and convenience had significant effects on vaccine hesitancy. Hence, the distrust of vaccine safety and effectiveness and low convenience of COVID-19 vaccination and services appear to the affect the willingness of key groups to receive COVID-19 booster vaccines. In this study, complacency was not found to have a statistically significant impact on vaccine hesitancy. This could be because of many reasons. First, given the outbreak of COVID-19 in Wuhan, the several large domestic outbreaks, the designation of COVID-19 as a pandemic, and the unprecedented changes to the way people live, travel, work, etc., citizens could have fully realized the seriousness of COVID-19. Second, the relevant state departments and units at all levels made great efforts to popularize the COVID-19 vaccine booster, helping the public realize that the COVID-19 vaccine is a necessary preventive measure and has decreased disease severity and mortality rates in COVID-19 patients. Third, the study population consisted of key groups, such as medical staff, who have a more comprehensive understanding of COVID-19 and COVID-19 vaccines (including booster shots) due to the nature of their work.

This study found that vaccine confidence is an important factor affecting vaccine hesitancy, mainly owing to suspicions around safety. All small dimension analyses showed that a perception of low necessity is positively correlated with vaccine hesitancy, and a higher score on this aspect indicates a higher rate of vaccine hesitancy. On the one hand, people may take a wait-and-see approach toward the protective effects of COVID-19 vaccines in China. On the other hand, it is unclear whether the booster dose of the vaccine, which is required after an interval of six months and within eight months from the last dose, will have adverse effects. Additionally, in China, the public’s confidence in vaccine safety may have also decreased due to some reports of falsification of vaccine production records.³⁷

Needless to say, some other frameworks or theories have been applied to the study of COVID-19 vaccine hesitancy. Wong et al³⁸ used a health belief model (HBM) to analyze people’s acceptability of the COVID-19 vaccine and willingness to pay. The results of the study showed that 48.2% of people were willing to receive the COVID-19 vaccine, mainly because they believed that vaccination would reduce the risk of infection and that they were less worried about COVID-19. Wang et al³⁹ used the protective motivation theory (PMT) to analyze the factors influencing Chinese university students to receive the COVID-19 vaccine, and the results showed that the self-perceived severity level of COVID-19 among university students was positively correlated with their motivation to receive the COVID-19 vaccine, similar to the application of the theory of planned behavior (TPB).⁴⁰ In addition, some scales have been used to analyze people’s COVID-19 vaccine hesitancy, such as MoVac-COVID19S,^41–43 DrVac-COVID19S,^44,45 VAX scale,⁴⁶ VHS scale⁴⁷ and Vaccine Conspiracy Beliefs Scale (VCBS),⁴⁸ etc. Therefore, we should consider appropriate tools for assessment when conducting studies of population vaccine hesitancy.

There is a gap between the results of this study and previously reports on the willingness to undergo COVID-19 vaccination in China (91.3%),⁴⁹ suggesting that practical differences in vaccination behaviors and willingness remain. In order to effectively prevent and control the COVID-19 pandemic and win the protracted war against the disease, vaccine boosters are important. The following measures are recommended to promote COVID-19 vaccine booster adoption: (1) Complete adhere to the national strategy for guidance of the vaccination framework. Continue to enhance the regulatory management of vaccines, improve the safety guarantee system, and include a supervisory mechanism to ensure vaccine safety. Further, it would be important to monitor the changes in public vaccine hesitancy in real time, provide targeted interventions for immunization projects, and increase the confidence of the public in the vaccine. (2) Actively shape the public’s perception of the reality of the disease and vaccine. Research shows that increasing an individual’s awareness regarding vaccination can effectively reduce the rate of vaccine hesitancy and improve vaccination rates.⁷ Therefore, vaccine information should be obtained through correct channels and the interrelationships of disease susceptibility, disease risk, and vaccination should be clarified. (3) Gradually train medical staff. Medical workers are always at the forefront of the fight against vaccine hesitancy.⁵⁰ While improving their understanding of disease, vaccine, and vaccine hesitancy, attention should also be paid to help them recognize the psychology of vaccine hesitancy, gain effective communication skills, and guide those with vaccine hesitancy in a collaborative manner.⁵¹ (4) Make good use of information technology and mass media. Knowledge of vaccine hygiene should be spread to improve the public’s ability to discriminate information. For immunization service providers, the electronic health records of residents, electronic records of vaccination, and electronic supervision systems for vaccine should be established. It is necessary to standardize the news channels for vaccines and harshly crack down on false and untrue reports and rumors. The Internet has played a great role in spreading anti-vaccination propaganda. Thus, providing accurate information is key to improving awareness and reducing vaccine hesitancy.^52,53 (5) Relevant departments can increase the convenience of booster vaccination, mainly by increasing the availability of vaccines (30.11%), making vaccine protocols accessible and easy to understand (43.4%), and improving the convenience of the vaccination service (52.0%). For example, an adequate vaccine supply should be ensured. Moreover, the public should receive health education to improve vaccination awareness, thus improving rates of booster vaccination. Finally, strategies such as an increase in vaccination sites, flexible vaccination timings, and provisions for the convenience for office workers could also be helpful.

This study provides useful insights into the reasons for vaccine hesitancy. However, there are certain limitations to this study. First, this study was based on a cross-sectional survey and the participants were 18–59 years old. Notably, the survey was not conducted among people for whom booster vaccinations were not recommended at that time, such as minors, older people, and other non-key groups. Therefore, the result of vaccine hesitancy in this study did not involve non-key populations, leading to a lack of data to support their intention to boost vaccination.

However, the participants covered the range of key groups for whom COVID-19 booster vaccination is recommended according to the national policy. Hence, the study has reference value for the follow-up large-scale promotion of COVID-19 vaccine boosters. It is important to understand vaccine hesitancy scientifically, evaluate vaccine hesitancy through effective and reliable tools, take targeted preventive measures, and further conduct larger sample sizes studies to verify.

Conclusions

Although the COVID-19 vaccine booster hesitancy reported in the study was relatively low, a large gap remains in the willingness to receive COVID-19 vaccination in China. Therefore, the state and relevant departments should not only strengthen vaccine safety management, correct public opinion, and improve public confidence in vaccines, but also increase vaccine availability, better understand the vaccinated population, and improve the convenience of the vaccination service and booster vaccination. These measures will help reduce vaccine hesitancy among the public and enable smooth progress in the large-scale COVID-19 vaccine booster campaign in the future.

Abbreviations

COVID-19	=	Coronavirus disease 2019
3Cs	=	confidence, complacency, and convenience
SARS-CoV-2	=	severe acute respiratory syndrome coronavirus 2
CI	=	confidence interval
HBM	=	health belief model
PMT	=	protective motivation theory
TPB	=	theory of planned behavior

Author contributions

Min Huang was responsible for the design and conduct of the study, data collection, and the data analysis. Silin Zheng was the sponsor of the study and was responsible for the quality control during the study. All authors were involved in data interpretation as well as the writing, reviewing, and approving of the manuscript. All research data were available to all the authors, who vouch for its accuracy and completeness.

Acknowledgements

The authors thank all of the participants who volunteered for this study, include the Affiliated Hospital of Southwest Medical University, Southwest Medical University, Luzhou taxi company, Luzhou logistics company and other units and individuals, and the Investigators and study-site personnel.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data are available from the corresponding author on reasonable request.

Additional information

Funding

This research received no specific grant from any funding agency, commercial or not-for-profit sectors.