ABSTRACT
Background
Men who have sex with men (MSM), a population bearing the greatest HIV burden in many countries, may also be vulnerable to COVID-19. COVID-19 vaccines are essential to containing the pandemic. However, vaccine hesitancy may compromise vaccine coverage. We aimed to understand the uptake of COVID-19 vaccine and factors associated with COVID-19 vaccine hesitancy among HIV-infected MSM in mainland China.
Methods
A cross-sectional online survey among HIV-infected MSM was conducted between 13 and 21 February 2021 in mainland China. Variables including demographics, mental health status, HIV characteristics, and knowledge of and attitudes toward COVID-19 pandemic and COVID-19 vaccine were collected. Chi-square tests and multivariable logistic regression were used to analyze factors associated with COVID-19 vaccine hesitancy.
Results
A total of 1295 participants were included. The median age was 29.3 years (interquartile range [IQR] 25.2–34.0 years). The uptake of COVID-19 vaccine was 8.7%. Two main reasons for receiving vaccines were “regarded vaccination as self-health protection” (67.3%) and “trust in domestic medical technology” (67.3%). Among participants who did not initiate vaccination, concern about side effects (46.4%) and disclosure of HIV infection (38.6%) were top two reasons, and 47.2% had higher vaccine hesitancy. Men who had with high antiretroviral therapy (ART) adherence (adjusted odds ratio [aOR] 0.53, 95% confidence interval [CI] 0.35–0.80), often (0.26, 0.17–0.40) or sometimes (0.46, 0.31–0.67) paid attention to information about the COVID-19 vaccine, preferred domestic vaccines (0.37, 0.24–0.59), thought the pandemic had moderate (0.58, 0.38–0.90) and moderately severe or severe impact (0.54, 0.38–0.78) on immunity, who were waiting for vaccination programs organized at workplace (0.60, 0.44–0.81) and who were unaware of where to get COVID-19 vaccine (0.61, 0.45–0.82) had lower degree of COVID-19 vaccine hesitancy. Men who were concerned about the efficacy (1.72, 1.16–2.54) and side effects (2.44, 1.78–3.35) had higher degree of COVID-19 vaccine hesitancy.
Conclusion
COVID-19 vaccine uptake among HIV-infected MSM is still suboptimal. Understanding influencing factors of vaccine hesitancy among this group and making tailored measures to alleviate hesitancy would help improve the coverage of COVID-19 vaccination in this population.
KEYWORDS: COVID-19 vaccine, hesitancy, uptake, MSM, HIV, China
Introduction
The raging COVID-19 pandemic caused by SARS‑CoV‑2 has been a major global public health threat. COVID-19 vaccines are expected to contain the pandemic to the largest extent. As of 24 July 2021, 18 vaccines were authorized by at least one national regulatory authority for public use.1 Many countries have implemented phased distribution plans that prioritize those at the highest risk of complications, such as the elderly, and those at high risk of exposure and transmission, such as healthcare workers.2 As of 24 July 2021, just under 4 billion doses of COVID‑19 vaccines have been administered worldwide.3 In China, authorities officially launched a vaccination program for winter-spring period on 15 December 2020, which targeted at several key populations including workers engaging in the cold chain industry, customs, healthcare, and public transport and fresh produce markets.4 This program was the first part of a “step by step plan” of COVID-19 vaccination,5 and free vaccination has been introduced nationwide as the second part since 9 January 2021.6 As of 9 June 2021, China has approved six domestic vaccine candidates. There are four inactivated vaccines (Sinopharm (Beijing), Sinopharm (Wuhan), Sinovac and Minhai Biotechnology Co), one adenovirus vector vaccine (CanSino) and one recombinant protein subunit vaccine (Anhui Zhifei Longcom).7 Nearly 1.5 billion doses of COVID-19 vaccines have been administered across China as of 15 July.8 Surveillance data from China CDC show that the incidence of general and abnormal reactions of China’s COVID-19 vaccines is lower than the average reported level of other kinds of vaccines in 2019.9
With the development and gradual access of COVID-19 vaccines, herd immunity would be expected to form by mass vaccination, which has been regarded as a successful method for curbing the spread of many infectious diseases.10 However, vaccine hesitancy, defined as delay in acceptance or refusal of vaccination despite availability of vaccination services,11 can hinder the achievement of herd immunity.12 It has adverse effect not only directly on the implementation of immunization programs but also on the scope of which people can be protected by vaccines.13 Vaccine hesitancy has become a growing threat globally and may cause further outbreaks of infection.14
In fact, before COVID-19 vaccines were approved numerous studies measured the willingness of potential COVID-19 vaccination. Acceptance rate varied extensively among countries, ranging from 23.6% in Kuwait to 97.0% in Ecuador.15 Estimated 68.4% of the global population are willing to be vaccinated16 and acceptance rate was found 91.3% in China, which was higher than most countries worldwide.15 Nevertheless, the willingness may not completely represent actual uptake.17,18 Vaccine hesitancy is one of the important determinants influencing the process between willingness and actual behavior, which might be related to individual attitudes, vaccine attributes and political factors.19 Vaccine hesitancy is a continuum18 rather than labeling individuals simply as “in favor of the vaccine” or “against the vaccine.”20 Hence, this might be more convincing in assessing vaccine hesitancy.
The World Health Organization (WHO) states that people under health conditions affecting immunity are susceptible to SARS‑CoV‑2.21 Compared with HIV-uninfected individuals, HIV-infected individuals were more likely to be infected with SARS‑CoV‑222 and have 30% higher severe or fatal COVID-19 outcome23 and mortality.24 Furthermore, a recent study from South Africa showed that HIV-infected individuals diagnosed with SARS‑CoV‑2 who were with comorbidities, not on antiretroviral therapy (ART), with a history of immune suppression (CD4 count <200 cells per μL), with a history of a viral load of 1000 copies per mL or more were with worse COVID-19 in-hospital outcome.25 Men who have sex with men (MSM), a population bearing the greatest HIV burden in many countries26 may also be vulnerable to SARS‑CoV‑2. Inadequate HIV prevention services or treatment interruption27 may worsen immunity for HIV-infected MSM and consequently increasing potential risk of SARS‑CoV‑2. Hence, COVID-19 vaccination may need to prioritize MSM, especially HIV-infected MSM as a vulnerable group.
Considering vaccination programs have been accessible in many countries, it is crucial to understand the actual implementation of COVID-19 vaccination in this population and possible reasons for reluctance or refusal of the vaccine so as to make tailored preventive strategies for this group. Our study aimed to understand the uptake and hesitancy relevant to COVID-19 vaccination among HIV-infected MSM in mainland China.
Methods
Study design and participants
We conducted a cross-sectional online survey between 13 and 21 February 2021. Individuals were recruited by convenience sampling through Li Hui Shi Kong, an online WeChat official account with over 76,000 HIV-infected subscribers from various regions in the country. A web-based, self-administered anonymous questionnaire was developed using the online survey platform Wenjuanxing (https://www.wjx.cn). Study information together with inclusion criteria and the quick response (QR) code of questionnaire was posted via Li Hui Shi Kong. Interested participants scanned the QR code to access the questionnaire. At the end of survey, participants were directed to a lottery page to win a random reimbursement ranging from RMB 10–130 (USD 1 ≈ RMB 6.4).
Eligibility criteria were as follows: 1) born male; 2) had male–male sex in the past; 3) self-reported HIV-positive; 4) consented to participate in the survey (chose “I agree” option before starting the survey). Participants would be excluded if 1) time to complete the questionnaire was less than 5 minutes; 2) the same option was selected for all items; 3) gave wrong answer to the quality control question (Is Beijing, Shenzhen, Guangzhou or Shanghai China’s capital?); 4) answered with logically contradictory options.
Measurement
Demographics, mental health status and HIV characteristics
Demographics were collected including age, gender, sexual orientation, residency, marital status, education, occupation, income, types of health insurance, health-related status (i.e., experience of disability/chronic diseases, frailty). The nine-item Patient Health Questionnaire (PHQ-9) and the seven-item Generalized Anxiety Disorder Scale (GAD-7) were used to assess depression and anxiety status. Viral load of HIV in recent year, HIV transmission route, time since HIV diagnosis, ART adherence measured by the eight-item Morisky Medication Adherence Scale (MMAS-8) were also asked in this survey.
Knowledge of and attitudes toward COVID-19 pandemic and COVID-19 vaccine
Perception of the severity of SARS-CoV-2, frequency of following information about the COVID-19 vaccine, source of COVID-19 vaccine information, preference toward domestic or imported vaccine were collected. Participants were also asked to answer “can ART prevent COVID-19 or not?” and COVID-19 impact on clinical attendance or ART collection/immunity/discrimination and inequity/other psychologic disruptions. The Vaccine Hesitancy Scale (VHS) was applied to measure COVID-19 vaccine hesitancy. The survey also asked reasons to initiate and not to initiate the COVID-19 vaccination.
Statistical analysis
For participants who did not initiate the COVID-19 vaccination, degree of vaccine hesitancy was dichotomized into “lower” and “higher” by the median value of scores of VHS. Chi-square tests were applied to assess differences between participants with lower and higher COVID-19 vaccine hesitancy in related factors of demographics, mental health status and HIV characteristics, and knowledge of and attitudes toward COVID-19 pandemic and COVID-19 vaccine.
Subsequently, multivariable logistic regression was employed to identify factors associated with degree of vaccine hesitancy. Enter method for logistic regression was conducted. Adjusted odds ratio (aOR) and the 95% confidence interval (95% CI) were estimated. Variance inflation factor (VIF) was calculated to ensure independence of each variable in the model. The final model had a mean VIF of 1.33. The outcome of Hosmer and Lemeshow Test (χ2 = 9.4, df = 8, P = 0.31) showed the model had a good fitting degree. All analyses were performed using SPSS 25.0 (IBM Corporation, New York, NY, United States). Statistical significance was set at P< 0.05. Bar graphs were depicted to describe reasons to initiate the COVID-19 vaccination or not and the distribution of each item of VHS by GraphPad Prism 8.0 (GraphPad Software, San Diego, California). Details on scoring methods, validity and reliability of scales can be viewed in Supplemental Files. Validity was calculated through confirmatory factor analysis (CFA) by AMOS 24.0 (IBM Corporation, New York, NY, United States).
Ethics approval
This study was approved by the Ethics Committee of the School of Public Health (Shenzhen), Sun Yat-sen University (Approval number: SYSU-PHS-2020042).
Results
Demographics, mental health status and HIV characteristics
A total of 1411 HIV-infected MSM completed the online survey. After quality control with inclusion and exclusion criteria, 1295 questionnaires were considered valid, with a valid response rate of 91.8%. Geographic distribution was shown in Supplementary File Table S1. Among participants who did not initiate the COVID-19 vaccination (N = 1182), over two-thirds (67.7%) were aged 26–44 years old. Most (89.7%) were cisgender men (10.3% were transgender women). Five hundred and forty-two (45.9%) participants had experience of disability, 406 (34.3%) participants had experience of chronic diseases, 18 (1.5%) participants were frail. Over four-fifths participants (81.3%) of participants had medium or high ART adherence. See Table 1.
Table 1.
Demographics, mental health status and HIV characteristics among HIV-infected MSM in China, stratified by degree of vaccine hesitancy
| Variables | Total (N = 1182) n (%) |
Lower vaccine hesitancy (N = 624) n (%) |
Higher vaccine hesitancy (N = 558) n (%) |
P |
|---|---|---|---|---|
| Age, year | 0.036 | |||
| ≤25 | 333 (28.2) | 192 (30.8) | 141 (25.3) | |
| 26–44 | 800 (67.7) | 402 (64.4) | 398 (71.3) | |
| ≥45 | 49 (4.1) | 30 (4.8) | 19 (3.4) | |
| Gender | 0.491 | |||
| Cisgender men | 1060 (89.7) | 556 (89.1) | 504 (90.3) | |
| Transgender women | 122 (10.3) | 68 (10.9) | 54 (9.7) | |
| Sexual orientation | 0.173 | |||
| Heterosexual | 19 (1.6) | 13 (2.1) | 6 (1.1) | |
| Homosexual | 910 (77.0) | 487 (78.0) | 423 (75.8) | |
| Other or not surea | 253 (21.4) | 124 (19.9) | 129 (23.1) | |
| Residencyb | 0.606 | |||
| Local residency | 538 (45.9) | 280 (45.2) | 258 (46.7) | |
| None local residency | 633 (54.1) | 339 (54.8) | 294 (53.3) | |
| Marital status | 0.776 | |||
| Single | 695 (58.8) | 358 (57.4) | 337 (60.4) | |
| Spouse | 114 (9.6) | 62 (9.9) | 52 (9.3) | |
| Boyfriend or male partner | 284 (24.0) | 154 (24.7) | 130 (23.3) | |
| Girlfriend or female partner | 26 (2.2) | 13 (2.1) | 13 (2.3) | |
| Divorce/separation/widower | 63 (5.3) | 37 (5.9) | 26 (4.7) | |
| Education | 0.691 | |||
| High school or below | 279 (23.6) | 143 (22.9) | 136 (24.4) | |
| Bachelor or college | 794 (67.2) | 426 (68.3) | 368 (65.9) | |
| Master or doctor | 109 (9.2) | 55 (8.8) | 54 (9.7) | |
| Occupationc | 0.357 | |||
| Full-time job | 660 (57.7) | 362 (59.8) | 298 (55.4) | |
| Farmers | 25 (2.2) | 15 (2.5) | 10 (1.9) | |
| Students | 113 (9.9) | 63 (10.4) | 50 (9.3) | |
| Freelancers | 203 (17.8) | 96 (15.9) | 107 (19.9) | |
| Self-employed | 51 (4.5) | 25 (4.1) | 26 (4.8) | |
| Unemployed or retired | 91 (8.0) | 44 (7.3) | 47 (8.7) | |
| Income (RMB) | 0.443 | |||
| 0–1999 | 232 (19.6) | 113 (18.1) | 119 (21.3) | |
| 2000–4999 | 475 (40.2) | 261 (41.8) | 214 (38.4) | |
| 5000–9999 | 347 (29.4) | 185 (29.6) | 162 (29.0) | |
| ≥10000 | 128 (10.8) | 65 (10.4) | 63 (11.3) | |
| Types of health insuranced | ||||
| Social health insurance | 1024 (90.1) | 543 (90.5) | 481 (89.7) | 0.667 |
| Business health insurance | 90 (7.9) | 50 (8.3) | 40 (7.5) | 0.588 |
| Other | 85 (7.5) | 43 (7.2) | 42 (7.8) | 0.669 |
| Experience of disability | 0.077 | |||
| Yes | 542 (45.9) | 271 (43.4) | 271 (48.6) | |
| No | 640 (54.1) | 353 (56.6) | 287 (51.4) | |
| Experience of chronic diseases | 0.306 | |||
| Yes | 406 (34.3) | 206 (33.0) | 200 (35.8) | |
| No | 776 (65.7) | 418 (67.0) | 358 (64.2) | |
| Frailty status | 0.202 | |||
| Robust | 440 (37.2) | 239 (38.3) | 201 (36.0) | |
| Prefrail | 724 (61.3) | 379 (60.7) | 345 (61.8) | |
| Frail | 18 (1.5) | 6 (1.0) | 12 (2.2) | |
| Level of depression severity, PHQ-9 score | 0.029 | |||
| Minimal (scores 0–4) | 352 (29.8) | 211 (33.8) | 141 (25.3) | |
| Mild (scores 5–9) | 343 (29.0) | 175 (28.0) | 168 (30.1) | |
| Moderate (scores 10–14) | 229 (19.4) | 111 (17.8) | 118 (21.1) | |
| Moderately severe (scores 15–19) | 125 (10.6) | 60 (9.6) | 65 (11.6) | |
| Severe (scores 20–27) | 133 (11.3) | 67 (10.7) | 66 (11.8) | |
| Level of anxiety severity, GAD-7 score | 0.046 | |||
| Minimal (scores 0–4) | 502 (42.5) | 287 (46.0) | 215 (38.5) | |
| Mild (scores 5–9) | 354 (29.9) | 169 (27.1) | 185 (33.2) | |
| Moderate (scores 10–14) | 164 (13.9) | 82 (13.1) | 82 (14.7) | |
| Severe (scores 15–21) | 162 (13.7) | 86 (13.8) | 76 (13.6) | |
| Viral load of HIV in recent year | 0.500 | |||
| Detectable | 133 (11.3) | 65 (10.4) | 68 (12.2) | |
| Undetectable | 903 (76.4) | 485 (77.7) | 418 (74.9) | |
| Not sure | 146 (12.4) | 74 (11.9) | 72 (12.9) | |
| HIV transmission route | 0.014 | |||
| Male-male sex | 1050 (88.8) | 570 (91.3) | 480 (86.0) | |
| Other | 36 (3.0) | 14 (2.2) | 22 (3.9) | |
| Not sure | 96 (8.1) | 40 (6.4) | 56 (10.0) | |
| Time since HIV diagnosise | 0.735 | |||
| <6 months | 64 (5.4) | 31 (5.0) | 33 (5.9) | |
| 6–12 months | 63 (5.3) | 31 (5.0) | 32 (5.7) | |
| 13–35 months | 453 (38.4) | 246 (39.5) | 207 (37.1) | |
| ≥36 months | 600 (50.8) | 314 (50.5) | 286 (51.3) | |
| ART adherence, MMAS-8 score | 0.002 | |||
| Low (scores < 6) | 221 (18.7) | 103 (16.5) | 118 (21.1) | |
| Medium (6 ≤ scores < 8) | 595 (50.3) | 301 (48.2) | 294 (52.7) | |
| High (scores = 8) | 366 (31.0) | 220 (35.3) | 146 (26.2) |
Degree of vaccine hesitancy was dichotomized into “lower” and “higher” by the median value of scores of the Vaccine Hesitancy Scale (VHS). USD 1 ≈ RMB 6.4. The bold values are statistically significant (P<.05) in Chi-squared tests. MSM, men who have sex with men; ART, antiretroviral therapy.
aOptions in sexual orientation of “bisexual,” “pansexual” and “not sure” were recategorized into “other and not sure.”
b11 missing.
c39 missing.
dThis was a multiple choice question and we deleted 46 logically contradicted answers (there are four types of social medical insurances in China and one citizen can only have reimbursement through one, if participants chose multiple then the answer was regarded invalid).
eDeleted 2 logically contradictory answers.
Knowledge of and attitudes toward COVID-19 pandemic and COVID-19 vaccine
Nearly one-third (32.2%) participants often paid attention to information about the COVID-19 vaccine. Among those who paid attention (including often, sometimes or seldom) to the vaccine, information was almost attained via the internet (96.1%), followed by TV programs (39.6%), communication with relatives and friends (14.7%), expert lectures (11.2%). A majority (88.3%) participants showed preference to domestic vaccines. Over half of the participants thought COVID-19 pandemic had moderately severe or severe impact on clinical attendance or ART collection (56.9%)/immunity (58.0%)/discrimination and inequity (58.4%)/other psychologic disruptions (52.7%). See Table 2.
Table 2.
Knowledge of and attitudes toward COVID-19 pandemic and COVID-19 vaccine among HIV-infected MSM in China, stratified by degree of vaccine hesitancy
| Variables | Total (N = 1182) n (%) |
Lower vaccine hesitancy (N = 624) n (%) |
Higher vaccine hesitancy (N = 558) n (%) |
P |
|---|---|---|---|---|
| Perception of the severity of SARS-CoV-2 | <0.001 | |||
| Severe | 596 (50.4) | 340 (54.5) | 256 (45.9) | |
| Moderate | 456 (38.6) | 236 (37.8) | 220 (39.4) | |
| Mild | 68 (5.8) | 22 (3.5) | 46 (8.2) | |
| No idea | 62 (5.2) | 26 (4.2) | 36 (6.5) | |
| Frequency of following information about the COVID-19 vaccine | <0.001 | |||
| Often | 381 (32.2) | 253 (40.5) | 128 (22.9) | |
| Sometimes | 594 (50.3) | 300 (48.1) | 294 (52.7) | |
| Seldom or nevera | 207 (17.5) | 71 (11.4) | 136 (24.4) | |
| Source of COVID-19 informationb | ||||
| Internet | 1094 (96.1) | 592 (96.6) | 502 (95.6) | 0.405 |
| TV programs | 451 (39.6) | 255 (41.6) | 196 (37.3) | 0.143 |
| Communication with friends and family | 167 (14.7) | 85 (13.9) | 82 (15.6) | 0.405 |
| Expert lectures | 127 (11.2) | 82 (13.4) | 45 (8.6) | 0.010 |
| Other | 3 (0.3) | 2 (0.3) | 1 (0.2) | 1.000* |
| Vaccine preference | <0.001 | |||
| Domestic vaccines | 1044 (88.3) | 584 (93.6) | 460 (82.4) | |
| Imported vaccines | 138 (11.7) | 40 (6.4) | 98 (17.6) | |
| Can ART prevent COVID-19 | 0.007 | |||
| Yes | 211 (17.9) | 112 (17.9) | 99 (17.7) | |
| No | 424 (35.9) | 248 (39.7) | 176 (31.5) | |
| Not sure | 547 (46.3) | 264 (42.3) | 283 (50.7) | |
| COVID-19 impact on clinical attendance or ART collection | 0.098 | |||
| Moderately severe or severe | 672 (56.9) | 373 (59.8) | 299 (53.6) | |
| Moderate | 287 (24.3) | 140 (22.4) | 147 (26.3) | |
| Mild or none | 223 (18.9) | 111 (17.8) | 112 (20.1) | |
| COVID-19 impact on immunity | 0.023 | |||
| Moderately severe or severe | 685 (58.0) | 372 (59.6) | 313 (56.1) | |
| Moderate | 265 (22.4) | 148 (23.7) | 117 (21.0) | |
| Mild or none | 232 (19.6) | 104 (16.7) | 128 (22.9) | |
| COVID-19 impact on discrimination and inequity | 0.480 | |||
| Moderately severe or severe | 690 (58.4) | 359 (57.5) | 331 (59.3) | |
| Moderate | 265 (22.4) | 137 (22.0) | 128 (22.9) | |
| Mild or none | 227 (19.2) | 128 (20.5) | 99 (17.7) | |
| COVID-19 impact on other psychologic disruptions | 0.124 | |||
| Moderately severe or severe | 623 (52.7) | 329 (52.7) | 294 (52.7) | |
| Moderate | 290 (24.5) | 141 (22.6) | 149 (26.7) | |
| Mild or none | 269 (22.8) | 154 (24.7) | 115 (20.6) | |
| Reasons not to initiate the COVID-19 vaccinationc | ||||
| Concern about personal financial situation | 99 (8.4) | 44 (7.1) | 55 (9.9) | 0.082 |
| Concern about the efficacy | 205 (17.3) | 60 (9.6) | 145 (26.0) | <0.001 |
| Concern about side effects | 549 (46.4) | 204 (32.7) | 345 (61.8) | <0.001 |
| Concern about disclosure of HIV infection | 456 (38.6) | 202 (32.4) | 254 (45.5) | <0.001 |
| Waiting for vaccination programs organized at workplaced | 384 (36.0) | 246 (44.6) | 138 (26.7) | <0.001 |
| Unawareness of where to get COVID-19 vaccine | 387 (32.7) | 245 (39.3) | 142 (25.4) | <0.001 |
| Regarded vaccination as unnecessary | 21 (1.8) | 9 (1.4) | 12 (2.2) | 0.357 |
| Doctors told me not to take COVID-19 vaccines | 15 (1.3) | 8 (1.3) | 7 (1.3) | 0.966 |
| Other | 29 (2.5) | 16 (2.6) | 13 (2.3) | 0.795 |
Degree of vaccine hesitancy was dichotomized into “lower” and “higher” by the median value of scores of the Vaccine Hesitancy Scale (VHS). The bold values are statistically significant (P<.05) in Chi-squared tests. “*” was used if P value was calculated by continuity correction. MSM, men who have sex with men; ART, antiretroviral therapy.
aOptions in attention frequency of “seldom” and “never” were integrated into “seldom and never.”
bThis was a multiple choice question and 44 participants chose “never pay attention to progress of recent COVID-19 vaccine research” so they did not need to answer this question.
cA multiple choice question.
dDeleted 114 logically contradicted answers.
Reasons to initiate COVID-19 vaccination or not
One hundred and thirteen (8.7%) had at least one dose of any COVID-19 vaccine. A total of 1182 participants did not initiate the COVID-19 vaccination, Figure 1A shows the reasons to initiate the COVID-19 vaccination. Over two-thirds (67.3%) participants regarded vaccination as self-health protection, the same percentage with participants regarded vaccination as trust in domestic medical technology. Just under half (49.6%) of participants had been vaccinated because they thought SARS‑CoV‑2 may exacerbate preexisting diseases. Seven (6.2%) participants had participated in vaccination programs organized at workplace. Moreover, 18 (15.9%) participants had no special reasons.
Figure 1.
Reasons to initiate (A) and not to initiate (B) COVID-19 vaccination among HIV-infected MSM in China.
MSM: Men who have sex with men.
Reasons not to initiate the vaccination are depicted in Figure 1B. The top two reasons were concern about side effects (46.4%) and disclosure of HIV infection (38.6%), then the efficacy (17.3%) and personal financial situation (8.4%). Exception from all reasonable concerns above, waiting for vaccination programs organized at workplace and unawareness of where to get COVID-19 vaccine were also hinders, chosen by 384 (36.0%) and 378 (32.7%) participants. Besides, very few regarded vaccination as unnecessary (1.8%) or were told by doctors not to take COVID-19 vaccines (1.3%).
Vaccine hesitancy
The median value of VHS scoring was 2.4. Proportion of degree of vaccine hesitancy (lower or higher) was 52.8% vs 47.2%. The distribution of each item of VHS is depicted in Figure 2. At least one-tenth of participants agreed or strongly agreed with the statement that it is unnecessary to be vaccinated because self was in good health (item 2, 10.0%) and alleviated pandemic (item 3, 13.1%). Of note, over three-fifths of participants believed in the efficacy of COVID-19 vaccines (item 4, 60.8%) and the vaccine can protect people around them from infection (item 5, 75.7%). More than two-thirds had belief in government’s vaccination recommendation (item 8, 67.2%). Over half believed suggestions made by health care professionals had an influence on their decision-making (item 9, 55.7%).
Figure 2.
View on each item of the Vaccine Hesitancy Scale among HIV-infected MSM in China (N = 1182).
MSM: Men who have sex with men. The Scale was revised from the ten-item Vaccine Hesitancy Scale developed by the WHO Strategic Advisory Group on Experts (SAGE) Working Group. Scores of each item are 1 = Strongly disagree, 2 = Disagree, 3 = Neither agree nor disagree, 4 = Agree, 5 = Strongly agree. Item 2,3,6,7 were wording reversing to ensure the reliability of the scale. However, scores of the rest items were flipped so that emotional direction of all items can be the same. Higher total scores reflected more hesitant attitude toward the COVID-19 vaccine.
Correlates of COVID-19 vaccine hesitancy
In multivariable logistic regression analysis (Y: degree of vaccine hesitancy, 0 = lower hesitancy and 1 = higher hesitancy), lower COVID-19 hesitancy was associated with high ART adherence (aOR 0.53, 95% CI 0.35–0.80), often (0.26, 0.17–0.40) or sometimes (0.46, 0.31–0.67) paying attention to information about the COVID-19 vaccine, preference toward domestic vaccines (0.37, 0.24–0.59), perceived moderate (0.58, 0.38–0.90) and moderately severe or severe impact (0.54, 0.38–0.78) of SARS-CoV-2 on immunity, waiting for vaccination programs organized at workplace (0.60, 0.44–0.81) and unawareness of where to get COVID-19 vaccine (0.61, 0.45–0.82). Degree of vaccine hesitancy were positively correlated with concern about the efficacy (1.72, 1.16–2.54) and side effects (2.44, 1.78–3.35) of the COVID-19 vaccine. See Table 3.
Table 3.
Correlates of COVID-19 vaccine hesitancy among HIV-infected MSM in China
| Variables | aOR (95% CI) | P |
|---|---|---|
| Age, year | ||
| ≤25 | 0.71 (0.34–1.47) | 0.359 |
| 26–44 | 0.91 (0.45–1.84) | 0.799 |
| ≥45 | Ref | |
| Level of depression severity, PHQ-9 score | ||
| Minimal (scores 0–4) | Ref | |
| Mild (scores 5–9) | 0.99 (0.66–1.47) | 0.947 |
| Moderate (scores 10–14) | 1.29 (0.78–2.13) | 0.321 |
| Moderately severe (scores 15–19) | 1.19 (0.62–2.29) | 0.597 |
| Severe (scores 20–27) | 1.07 (0.50–2.31) | 0.854 |
| Level of anxiety severity, GAD-7 score | ||
| Minimal (scores 0–4) | Ref | |
| Mild (scores 5–9) | 1.25 (0.85–1.85) | 0.264 |
| Moderate (scores 10–14) | 1.02 (0.59–1.78) | 0.944 |
| Severe (scores 15–21) | 0.90 (0.44–1.81) | 0.760 |
| HIV transmission route | ||
| Male-male sex | Ref | |
| Other | 2.10 (0.93–4.73) | 0.072 |
| Not sure | 1.39 (0.83–2.33) | 0.210 |
| ART adherence, MMAS-8 score | ||
| Low (scores < 6) | Ref | |
| Medium (6 ≤ scores < 8) | 0.91 (0.63–1.33) | 0.635 |
| High (scores = 8) | 0.53 (0.35–0.80) | 0.003 |
| Perception of the severity of SARS-CoV-2 | ||
| Severe | 0.65 (0.34–1.24) | 0.192 |
| Moderate | 0.78 (0.41–1.49) | 0.451 |
| Mild | 1.56 (0.66–3.65) | 0.311 |
| No idea | Ref | |
| Frequency of following information about the COVID-19 vaccine | ||
| Often | 0.26 (0.17–0.40) | <0.001 |
| Sometimes | 0.46 (0.31–0.67) | <0.001 |
| Seldom or never | Ref | |
| Vaccine preference | ||
| Domestic vaccines | 0.37 (0.24–0.59) | <0.001 |
| Imported vaccines | Ref | |
| Can ART prevent COVID-19 | ||
| Yes | Ref | |
| No | 0.97 (0.65–1.45) | 0.891 |
| Not sure | 1.37 (0.93–2.00) | 0.110 |
| COVID-19 impact on immunity | ||
| Moderately severe or severe | 0.54 (0.38–0.78) | 0.001 |
| Moderate | 0.58 (0.38–0.90) | 0.014 |
| Mild or none | Ref | |
| Reasons not to initiate the COVID-19 vaccination | ||
| Concern about the efficacy | ||
| Yes | 1.72 (1.16–2.54) | 0.007 |
| No | Ref | |
| Concern about side effects | ||
| Yes | 2.44 (1.78–3.35) | <0.001 |
| No | Ref | |
| Concern about disclosure of HIV infection | ||
| Yes | 1.06 (0.78–1.43) | 0.707 |
| No | Ref | |
| Waiting for vaccination programs organized at workplace | ||
| Yes | 0.60 (0.44–0.81) | 0.001 |
| No | Ref | |
| Did not know where to where to get COVID-19 vaccine | ||
| Yes | 0.61 (0.45–0.82) | 0.001 |
| No | Ref |
The bold values are statistically significant (P < .05). aOR, adjusted odds ratio; CI, confidence interval; MSM, men who have sex with men; ART, antiretroviral therapy.
Discussion
Overall, the COVID-19 vaccine uptake among HIV-infected MSM in mainland China was 8.7%. A total of 1182 participants did not vaccinate in this survey. Proportion of participants with lower and higher vaccine hesitancy were 52.8% vs 47.2%. Our findings demonstrated that primary correlates of COVID-19 vaccine hesitancy were vaccine-attribute factors (i.e., preference for domestic vaccines, concern about the efficacy and side effects of vaccine) and factors relevant to HIV infection (i.e., ART adherence and COVID-19 impact on immunity). Thus, this study suggests that there is an urgent need to make tailored strategies to alleviate vaccine hesitancy.
Health awareness is an essential motivation. Individuals who thought the pandemic had at least moderate impact on immunity were less hesitant about the vaccine. Moreover, some ART-related topics are associated with vaccine hesitancy. In this survey, high ART adherence was negatively associated with degree of vaccine hesitancy. View on “can ART prevent COVID-19” may also influence vaccine hesitancy, although this variable did not show statistical significance while entering into logistic regression model. Advice about the role of ART in preventing or treating COVID-19 has not reached a consensus.28 If unvaccinated HIV-infected individuals regard antivirals as a useful prophylactic or regard COVID-19 vaccines as interference in previous antiretroviral medications, it may influence decision on COVID-19 vaccination. Also, health awareness can be influenced by a personal threat, which can be explained by the term “complacency” caused by low self-perceived risk of vaccine-preventable diseases.11 Due to timely action and united effort to contain the epidemic, China has entered the stage of “regular epidemic prevention and control” where work, study and life of civils has been orderly resumed. They regarded this condition as a symbol of safety consequently became vaccine non-adaptors. Hence, immunization work from public health institutions should shed light on altruism and the benefit of herd immunity.29 Then COVID-19 vaccination can be facilitated as a social responsibility.30
The phenomenon of vaccine hesitancy is common. The WHO declared vaccine hesitancy was one of the top 10 global health threats in 2019.31 Regarding the COVID-19 vaccine, concerns about the efficacy and side effects hindered the expansion of vaccination in this survey. This is understandable because vaccine-specific issues were most frequent cited determinants in vaccine hesitancy.13 Besides COVID-19 vaccines, vaccine hesitancy also appeared with other types of vaccines applied among HIV-infected individuals. Common reasons not to initiate the vaccination including concerns about side effects32 and lack of expected efficacy.33 In addition, for HIV-infected individuals, they may worry that the vaccine would further worsen their immune system.32 Even if taking ART, some parameters such as increased CD8 T cells and lymphocytic exhaustion cannot be fully normalized and long-term antibody production and decreased responses to neoantigens or recall antigens may develop a potential threat to COVID-19 vaccine response.34 Considering insufficient data on HIV-infected individuals included in approved phase 2 and 3 COVID-19 vaccine trials,34 it is vital to carry out rigorous vaccine testing and offer efficacious evidence in a transport way to maintain public trust and relieve vaccine hesitancy.
We started this online survey on 13 February 2021, which was 1 month later than the initiation of national free vaccination policy.6 Of note, before implementing such a policy, priority of vaccination had been given to high-risk populations,4 but there was no guidance on COVID-19 vaccination for people with immunodeficiency or immune disorders.35 In our study, nearly one-tenth participants (8.7%) were vaccinated under such circumstances. According to an interview with Dr. Nanshan Zhong 30 March 2021, only about 4.0% of people in China received at least one dose against COVID-19.36 Primary reasons for vaccination were self-health protection (67.3%) and trust in domestic medical technology (67.3%). China disseminated COVID-19 related knowledge in a timely manner, and as a result public awareness reached a high level.37 In addition, followers of Li Hui Shi Kong (an HIV-themed WeChat official account) are likely to have higher health literacy. The frequency of following information about the COVID-19 vaccine was a predictor of degree of vaccine hesitancy and the Internet was the most common media where they attained information about vaccine progress (96.1%). Information from social media is an important source of healthcare information,38,39 and those who at least sometimes paid attention to information about the COVID-19 vaccine may care more about preventive measures for health protection. There were also two phenomena worth considering. Participants who were waiting for organized vaccination at workplace or did not know where to get COVID-19 vaccine were less likely to have hesitancy. A possible explanation for the former group is that under the management of street committee staff, members in one company or organization are viewed as a unit to be vaccinated. Nevertheless, vaccination service was not widely available at the time of survey. Thus, waiting was more convenient. For the latter group, insufficient dissemination in their communities may be the main reason. Hence, optimal publicity of vaccine through social media may contribute to the COVID-19 vaccination program.
As of 29 March 2021, National Health Commission of the People’s Republic of China officially announced technical guideline for the inoculation of COVID-19 vaccines (1st version), offering vaccination advice for people with impaired immunity. Inactivated vaccines and the recombinant subunit vaccine are recommended; for the adenovirus vector vaccine, it is recommended that individuals are fully informed and fully consider the benefits and the risks before vaccination.40 Expert recommendation on COVID-19 vaccination for HIV-infected adults, drafted by professionals from AIDS and Hepatitis C Professional Group, Chinese Society of Infectious Diseases has been published recently,41 may also provide reliable suggestions for HIV-infected individuals. The vaccination should be delayed if there are clinical contraindications such as allergy to vaccine components and an HIV-infected individual does not start ART with diagnosed opportunistic infection/uncontrolled malignant rumor. The WHO and NIH both advise HIV-infected individuals should receive COVID-19 vaccines regardless of their CD4 or viral load status because the potential benefits outweigh potential risks.42,43 Policies or guidelines relevant to vaccination can provide reliable suggestions about COVID-19 vaccination and relieve possible concerns among HIV-infected individuals to some extent. Albeit the Chinese government set high vaccination coverage target, the Joint Prevention and Control Mechanism of the State Council of the People’s Republic of China emphasized that COVID-19 vaccination is not compulsory and should be implemented based on consent and voluntariness.44 The majority of vaccine receivers were likely to take the vaccine based on their own decision.
Vaccines are considered as the only method to provide long-term immunity and prevent viral diseases.45 Only by achieving an uptake rate of 70–80% of the entire population, can herd immunity be better realized and benefit everyone in the society. China’s goal was to achieve 60% uptake rate by the end of June 2021.36 As of 18 Sep 2021, share of people fully vaccinated against COVID-19 in China was 78%.46 Despite of such progress, we cannot lose attention about vaccination with the spread of new variants47 and the looming of resurgence.48–51 Understanding factors associated with COVID-19 vaccine hesitancy among HIV-infected individuals from personal aspect (health awareness), vaccine aspect and national aspect (information dissemination and guidance making), making tailored measures would benefit the coverage of COVID-19 vaccination in this population.
There are several limitations in this study. First, a cross-sectional study design confines a causal conclusion so that we can only describe associations between degree of vaccine hesitancy and related factors. Second, this web-based survey was only conducted in mainland China, which may limit the generalizability of results. Third, information bias is unavoidable due to the self-reported information. However, data examination was set to exclude ineligible participants and ensure data quality.
Supplementary Material
Funding Statement
This study was supported by the Natural Science Foundation of China Excellent Young Scientists Fund [82022064]; Natural Science Foundation of China International/Regional Research Collaboration Project [72061137001]; Natural Science Foundation of China Young Scientist Fund [81703278]; the National Science and Technology Major Project of China [2018ZX10721102]; the Sanming Project of Medicine in Shenzhen [SZSM201811071]; the High Level Project of Medicine in Longhua, Shenzhen [HLPM201907020105]; the National Key Research and Development Program of China [2020YFC0840900], the Shenzhen Science and Technology Innovation Commission Basic Research Program [JCYJ20190807155409373]; Special Support Plan for High-Level Talents of Guangdong Province [2019TQ05Y230]; the Fundamental Research Funds for the Central Universities [58000-31620005]; Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences [2020]. All funding parties did not have any role in the design of the study or in the explanation of the data.
Author contributions
This study was conceived and designed by Huachun Zou and Yong Cai in consultation with the other authors. Weiran Zheng and Hui Li were responsible for field study. Yinghui Sun and Heping Zhao were responsible for data compilation and data analysis. All authors have contributed to interpretation of data and study findings. Weiran Zheng, Yinghui Sun, Hui Li and Heping Zhao drafted the manuscript with all authors critically reviewing the paper.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Supplementary material
Supplemental data for this article can be accessed on the publisher’s website at https://doi.org/10.1080/21645515.2021.1996152
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