ABSTRACT
Objectives
The coronavirus disease-2019 (COVID-19) pandemic continues to ravage the world. People living with HIV (PLHIV) are one of the most vulnerable groups. This study aims to identify the factors associated with the uptake and adverse reactions of COVID-19 vaccination.
Methods
We recruited PLHIV in China by convenience sampling between 7 and 23 February 2021. Participants were asked to complete an online questionnaire. Chi-squared test and multivariable logistic regression were used to assess factors associated with vaccine uptake.
Results
A total of 527 vaccinated and 1091 unvaccinated PLHIV were recruited. Individuals who had a higher education, engaged in occupations with a higher risk of COVID-19 infection, received influenza or pneumonia vaccine in the past 3 years (5.40, 3.36–8.77), believed in the effectiveness of vaccines (3.01, 2.20–4.12), and received media information regarding COVID-19 vaccine (2.23, 1.61–3.11), were more likely to be vaccinated. Concerning about adverse reactions (0.31, 0.22–0.44), negative impact on the progression of HIV/AIDS (0.36, 0.26–0.50) or antiretroviral therapy (ART) (0.61, 0.44–0.85), disclosure of HIV infection status (0.69, 0.49–0.96), comorbidities (0.33, 0.22–0.47), being unmarried (0.43, 0.28–0.66) and older age were negatively associated with vaccination. Of the 527 vaccinated PLHIV, 155 (29.4%) PLHIV reported adverse reactions, with pain at the injection site being the most common (18.2%).
Conclusions
PLHIV, who are concerned about adverse reactions, negative impact on ART outcome and disclosure of HIV infection status, were less likely to adopt COVID-19 vaccination. To increase vaccination coverage among PLHIV, health-care professionals should emphasize the benefits and necessity of vaccination and provide consultancy regarding adverse reactions.
KEYWORDS: PLHIV, COVID-19 vaccination, vaccine uptake, adverse reactions
Introduction
The world is in the midst of a COVID-19 pandemic. The COVID-19 pandemic has been profoundly impacting various aspects of our societies from economic growth1–3 to individuals’ health.4–7 COVID-19 vaccines are effective in preventing new infections. It is vital to understand whether people are willing to be vaccinated against COVID-19. Previous research in England found that only 47.5% of the general population reported a definite willingness to receive the COVID-19 vaccine.8 Another international survey found that the ratio of outright refusal of COVID-19 vaccination among the general population ranges from 2.6% in China to 44.0% in Turkey.9 The COVID-19 vaccine hesitancy or refusal will negatively impact the vaccination coverage. Given that COVID-19 vaccine is relatively new, it is understandable that the general population might be hesitant to be vaccinated. Vaccine hesitancy is prevalent and has many influencing factors.10–13 Existing studies found that vaccine efficacy, adverse reactions,14–17 proportion of vaccinated acquaintances,18 individual’s economic status, educational level,19 and race20 influence its acceptability.
Although global attention is attracted by COVID-19, the HIV/AIDS pandemic remains a major public health crisis. Data from the Joint United Nations Programme on HIV/AIDS show that there were 38.0 million PLWH worldwide, including 1.7 million new infections, and nearly 0.7 million people died of AIDS-related illnesses in 2019.21 PLHIV with compromised immune systems are at higher risk of COVID-19 infection.22 A significant proportion of PLHIV were at risk of antiretroviral therapy (ART) interruption. Some 35.1% (1782/5084) of PLHIV in China were at risk of ART interruption at the early stage of the COVID-19 outbreak.23 As for COVID-19 vaccination, PLHIV may have more concerns about adverse reactions, and the impact of COVID-19 vaccination on ART.
There is a lack of information on the current status of COVID-19 vaccination among PLHIV in China. Given the lack of evidence in this area, this present study was performed to explore factors associated with the uptake of COVID-19 vaccination and characterize the vaccine adverse reactions among Chinese PLHIV.
Methods
Study population and procedures
First, we conducted a nationwide online survey among PLHIV who received COVID-19 vaccination. Then, the same survey was done among PLHIV who did not receive vaccination in China. The survey lasted for around 2 weeks from 7 February to 23 February 2021. Individuals were recruited by convenience sampling through Li Hui Shi Kong, an online WeChat official account with over 76,000 PLHIV subscribers from various regions of the country.
To be eligible, participants had to be at least 18 years of age and diagnosed with HIV. A web-based, self-administered anonymous questionnaire was developed using the online survey platform Wenjuanxing (https://www.wjx.cn), which can be accessed via smart phone, iPad, or laptop. 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 the survey, each participant received a reimbursement of RMB 20 (USD 3.1).
Ethics approval for the study was obtained from the Ethics Review Board of the Department of Preventive Medicine, Changzhi Medical College (RT2021003).
Measures
The questionnaire collected the following information: 1) sociodemographic information, including gender, age, body-mass index, marital status, highest level of education, and occupation. 2) HIV treatment, including age at HIV diagnosis, age at ART initiation, latest CD4+ T cell count (cells/ul), latest HIV viral load (copies/ml), and other comorbidities. 3) view on COVID-19 vaccination, including belief in effectiveness of COVID-19 vaccines (yes/no), concerning about the adverse reactions of COVID-19 vaccines (yes/no), concerning about negative impact of COVID-19 vaccine on the progression of HIV/AIDS (yes/no), concerning about negative impact of COVID-19 vaccine on the effectiveness of ART (yes/no), and concerning about disclosure of HIV infection status (yes/no), any consultation about COVID-19 vaccination from HIV specialists, outpatient doctors, community-based organizations (CBOs), sex partners, friends, family, other PLHIV, and any COVID-19 health education from the media. Vaccine receivers were defined as participants who had received at least one dose of any COVID-19 vaccine. Vaccine receivers were asked about their experience of adverse reactions.
Statistical analysis
Descriptive results of sample characteristics (sociodemographic characteristics, HIV treatment, view on COVID-19 vaccination) were presented in frequency and percentage. Pearson Chi-squared test was used to compare the difference between vaccine receivers and vaccine non-receivers. For vaccine receivers, we assessed potential correlates of adverse reactions.
Multivariable logistic regression analysis was conducted to assess the factors associated with COVID-19 vaccination and its adverse reactions. Variables with P ≤ 0.10 in the Pearson Chi-squared test were entered into the multivariable models. Given that gender and age were associated with adverse reactions in previous studies,24,25 they will be included in adverse reactions’ multivariable analysis regardless of their P values. Statistical significance was set at P< 0.05. All statistical analyses were performed using R version 4.0.3 (R Core Team, Vienna, Austria).
Results
Participant characteristics
A total of 527 (32.6%) vaccinated and 1091 (67.4%) unvaccinated PLHIV were recruited in our study. Most participants (95.2%) were men, and over two-thirds (70.9%) were unmarried. More than half (60.3%) of all PLHIV had a college degree. The majority (97.0%) received ART, most participants (69.3%) reported their latest HIV viral load was undetectable (<50 copies/ml), and just under half (48.0%) of PLHIV had a CD4+ T cell count >500 cells/ul. Sociodemographic characteristics and HIV records of participants are summarized in Table 1.
Table 1.
Characteristics of PLHIV stratified by COVID-19 vaccination status (N = 1618)
| Variables | |
COVID-19 vaccination |
Univariable |
Multivariable |
||
|---|---|---|---|---|---|---|
| Overall | Received | Did not receive | P-value | aOR (95% CI) | P-value | |
| Total | 1618(100.0%) | 527(32.6%) | 1091(67.4%) | |||
| Sociodemographic information | ||||||
| Gender | 0.788 | |||||
| Male | 1541(95.2%) | 503(95.4%) | 1038(95.1%) | - | ||
| Female | 77(4.8%) | 24(4.6%) | 53(4.9%) | - | ||
| Age (years) | 0.043 | |||||
| 18–29 | 511(31.6%) | 186(35.3%) | 325(29.8%) | Ref | ||
| 30–39 | 742(45.9%) | 240(45.5%) | 502(46.0%) | 0.69(0.48–0.99) | 0.044 | |
| 40–49 | 262(16.2%) | 76(14.4%) | 186(17.0%) | 0.55(0.33–0.92) | 0.023 | |
| ≥50 | 103(6.4%) | 25(4.7%) | 78(7.1%) | 0.36(0.17–0.76) | 0.009 | |
| BMI | 0.238 | |||||
| <18.5 | 129(8.0%) | 39(7.4%) | 90(8.2%) | - | ||
| 18.5–24 | 1038(64.2%) | 327(62.0%) | 711(65.2%) | - | ||
| ≥24 | 451(27.9%) | 161(30.6%) | 290(26.6%) | - | ||
| Marital status | <0.001 | |||||
| Married | 288(17.8%) | 108(20.5%) | 180(16.5%) | Ref | ||
| Unmarried | 1147(70.9%) | 352(66.8%) | 795(72.9%) | 0.43(0.28–0.66) | <0.001 | |
| Divorced or widowed | 171(10.6%) | 57(10.8%) | 114(10.4%) | 1.25(0.72–2.15) | 0.430 | |
| Other | 12(0.7%) | 10(1.9%) | 2(0.2%) | 1.68(0.38–11.93) | 0.536 | |
| Educational level | <0.001 | |||||
| Junior high school or primary school | 217(13.4%) | 37(7.0%) | 180(16.5%) | Ref | ||
| High school | 319(19.7%) | 82(15.6%) | 237(21.7%) | 1.51(0.86–2.68) | 0.151 | |
| College | 975(60.3%) | 338(64.1%) | 637(58.4%) | 2.16(1.30–3.67) | 0.004 | |
| Postgraduate | 107(6.6%) | 70(13.3%) | 37(3.4%) | 8.38(3.89–18.48) | <0.001 | |
| Occupation | <0.001 | |||||
| Other | 897(55.4%) | 140(26.6%) | 757(69.4%) | Ref | ||
| Urban functional security workers | 349(21.6%) | 193(36.6%) | 156(14.3%) | 6.21(4.35–8.92) | <0.001 | |
| Medical workers | 126(7.8%) | 88(16.7%) | 38(3.5%) | 8.50(5.05–15.52) | <0.001 | |
| Unemployed | 95(5.9%) | 15(2.8%) | 80(7.3%) | 1.57(0.76–3.07) | 0.203 | |
| International transportation workers | 75(4.6%) | 30(5.7%) | 45(4.1%) | 3.63(1.93–6.74) | <0.001 | |
| Entry quarantine site workers | 52(3.2%) | 40(7.6%) | 12(1.1%) | 13.58(6.30–31.15) | <0.001 | |
| Cold chain workers | 24(1.5%) | 21(4.0%) | 3(0.3%) | 30.41(8.89–145.70) | <0.001 | |
| Received influenza or pneumonia vaccine in the past 3 years | <0.001 | |||||
| Yes | 167(10.3%) | 101(19.2%) | 66(6.0%) | 5.40(3.36–8.77) | <0.001 | |
| No | 1451(89.7%) | 426(80.8%) | 1025(94.0%) | Ref | ||
| HIV treatment | ||||||
| Time of HIV diagnosis | 0.628 | |||||
| ≤5 years | 1045(64.6%) | 336(63.8%) | 709(65.0%) | - | ||
| >5 years | 573(35.4%) | 191(36.2%) | 382(35.0%) | - | ||
| On ART | 0.293 | |||||
| Yes | 1570(97.0%) | 508(96.4%) | 1062(97.3%) | - | ||
| No | 48(3.0%) | 19(3.6%) | 29(2.7%) | - | ||
| ART duration | 0.245 | |||||
| ≤5 years | 1112(70.8%) | 350(68.9%) | 762(71.8%) | - | ||
| >5 years | 458(29.2%) | 158(31.1%) | 300(28.2%) | - | ||
| Latest HIV viral load (copies/ml) | 0.042 | |||||
| <50 | 1121(69.3%) | 387(73.4%) | 734(67.3%) | Ref | ||
| ≥50 | 189(11.7%) | 54(10.2%) | 135(12.4%) | 1.30(0.81–2.07) | 0.268 | |
| Not sure | 308(19.0%) | 86(16.3%) | 222(20.3%) | 1.60(1.03–2.47) | 0.034 | |
| Latest CD4+ T cell count (cells/μl) | <0.001 | |||||
| <200 | 59(3.6%) | 15(2.8%) | 44(4.0%) | Ref | ||
| 200–500 | 481(29.7%) | 172(32.6%) | 309(28.3%) | 1.40(0.57–3.60) | 0.474 | |
| >500 | 776(48.0%) | 291(55.2%) | 485(44.5%) | 1.85(0.76–4.73) | 0.189 | |
| Not sure | 302(18.7%) | 49(9.3%) | 253(23.2%) | 0.55(0.21–1.48) | 0.225 | |
| Comorbidities | <0.001 | |||||
| Yes | 469(29.0%) | 68(12.9%) | 401(36.8%) | 0.33(0.22–0.47) | <0.001 | |
| No | 1149(71.0%) | 459(87.1%) | 690(63.2%) | Ref | ||
| View on COVID-19 vaccination | <0.001 | |||||
| Believing in effectiveness of vaccines | ||||||
| Yes | 568(35.1%) | 258(49.0%) | 310(28.4%) | 3.01(2.20–4.12) | <0.001 | |
| No | 1050(64.9%) | 269(51.0%) | 781(71.6%) | Ref | ||
| Concerning about adverse reactions of vaccines | <0.001 | |||||
| Yes | 672(41.5%) | 107(20.3%) | 565(51.8%) | 0.31(0.22–0.44) | <0.001 | |
| No | 946(58.5%) | 420(79.7%) | 526(48.2%) | Ref | ||
| Concerning about negative impact of vaccine on the progression of HIV/AIDS | <0.001 | |||||
| Yes | 758(46.8%) | 112(21.3%) | 646(59.2%) | 0.36(0.26–0.50) | <0.001 | |
| No | 860(53.2%) | 415(78.7%) | 445(40.8%) | Ref | ||
| Concerning about negative impact of vaccine on effectiveness of ART | <0.001 | |||||
| Yes | 891(55.1%) | 199(37.8%) | 692(63.4%) | 0.61(0.44–0.85) | 0.003 | |
| No | 727(44.9%) | 328(62.2%) | 399(36.6%) | Ref | ||
| Concerning about disclosure of HIV infection status | <0.001 | |||||
| Yes | 635(39.2%) | 121(23.0%) | 514(47.1%) | 0.69(0.49–0.96) | 0.030 | |
| No | 983(60.8%) | 406(77.0%) | 577(52.9%) | Ref | ||
| Consultation | ||||||
| Consulted HIV specialists | 0.113 | |||||
| Yes | 531(32.8%) | 187(35.5%) | 344(31.5%) | - | ||
| No | 1087(67.2%) | 340(64.5%) | 747(68.5%) | - | ||
| Consulted outpatient doctors | 0.318 | |||||
| Yes | 139(8.6%) | 40(7.6%) | 99(9.1%) | - | ||
| No | 1479(91.4%) | 487(92.4%) | 992(90.9%) | - | ||
| Consulted CBOs | 0.593 | |||||
| Yes | 366(22.6%) | 115(21.8%) | 251(23.0%) | - | ||
| No | 1252(77.4%) | 412(78.2%) | 840(77.0%) | - | ||
| Consulted sex partners/friends/family | 0.088 | |||||
| Yes | 113(7.0%) | 45(8.5%) | 68(6.2%) | 1.71(0.98–2.95) | 0.058 | |
| No | 1505(93.0%) | 482(91.5%) | 1023(93.8%) | Ref | ||
| Discussed with other PLHIV | 0.245 | |||||
| Yes | 335(20.7%) | 118(22.4%) | 217(19.9%) | - | ||
| No | 1283(79.3%) | 409(77.6%) | 874(80.1%) | - | ||
| Receiving media information regarding COVID-19 vaccine | <0.001 | |||||
| Yes | 471(29.1%) | 207(39.3%) | 264(24.2%) | 2.23(1.61–3.11) | <0.001 | |
| No | 1147(70.9%) | 320(60.7%) | 827(75.8%) | Ref | ||
PLHIV, people living with HIV; aOR, adjusted odds ratio; CI, confidence interval; BMI, body-mass index.
Other, other occupations at low risk for COVID-19 transmission.
Urban functional security workers include government personnel, public security officers, armed police, firefighters, community workers, media staff, guarantee urban water, electricity, heating, coal, gas, logistics, elderly care, sanitation, funeral, and communication personnel.
ART, antiretroviral therapy.
Comorbidities include hyperlipidemia, liver disease, kidney disease, hypertension, allergic rhinitis, allergic dermatitis, respiratory diseases, diabetes, cardiovascular diseases.
CBOs, community-based organizations.
Factors associated with receiving COVID-19 vaccination
Among all PLHIV, 527 received at least one dose of any COVID-19 vaccine (Table 1). In the multivariable logistic regression analysis (Table 1), we found that individuals who had a higher education [college: adjusted odds ratio (aOR) 2.16, 95% confidence interval (CI) 1.30–3.67; postgraduate: 8.38, 3.89–18.48], engaged in occupations with a higher risk of COVID-19 infection [urban functional security workers: 6.21, 4.35–8.92; medical workers: 8.50, 5.05–15.52; international transportation workers: 3.63, 1.93–6.74; entry quarantine site workers: 13.58, 6.30–31.15; cold chain workers: 30.41, 8.89–145.70], received influenza or pneumonia vaccine in the past 3 years (5.40, 3.36–8.77), believed in effectiveness of vaccines (3.01, 2.20–4.12), and received media information regarding COVID-19 vaccine (2.23, 1.61–3.11), were more likely to be vaccinated. Concerning about adverse reactions (0.31, 0.22–0.44), negative impact on the progression of HIV/AIDS (0.36, 0.26–0.50) or antiretroviral therapy (ART) (0.61, 0.44–0.85), disclosure of HIV infection status (0.69, 0.49–0.96), comorbidities (0.33, 0.22–0.47), being unmarried (0.43, 0.28–0.66) and older age [30–39 years: 0.69, 0.48–0.99; 40–49 years: 0.55, 0.33–0.92; ≥50 years: 0.36, 0.17–0.76] were negatively associated with vaccination.
Factors associated with having adverse reactions after COVID-19 vaccination
Of the 527 vaccine receivers, 155 (29.4%) experienced adverse reactions. Pain at the injection site was the most common (18.2%) adverse reaction, followed by fatigue, headache, dizziness or drowsiness (14.8%), muscle pain or joint pain (7.4%), fever (4.2%), red, swollen, pruritus, callous or rash at the injection site (2.8%), nausea, vomitive, ventosity or diarrhea (2.5%), loss of appetite (1.3%), pruritus at non-injection site (0.9%), and elevation of blood pressure (0.4%) (Figure 1). No factors are associated with a higher proportion of adverse reactions (Table 2).
Figure 1.
Adverse reactions among PLHIV after vaccination. The X-axis is the proportion of adverse reactions. The Y-axis is the specific adverse reactions. PLHIV, people living with HIV. Color shaded regions indicate whether participants have adverse reactions (dark blue = yes, light blue = no).
Table 2.
Characteristics of PLHIV stratified by adverse reactions after COVID-19 vaccination (N = 527)
| Variables | |
Adverse reactions |
Univariable |
Multivariable |
||
|---|---|---|---|---|---|---|
| Overall | Yes | No | P-value | aOR (95% CI) | P-value | |
| Total | 527(100.0%) | 155(29.4%) | 372(70.6%) | |||
| Gender | 0.177 | |||||
| Male | 503(95.4%) | 145(93.5%) | 358(96.2%) | Ref | ||
| Female | 24(4.6%) | 10(6.5%) | 14(3.8%) | 1.81(0.76–4.17) | 0.168 | |
| Age | 0.353 | |||||
| 18–29 | 186(35.3%) | 46(29.7%) | 140(37.6%) | Ref | ||
| 30–39 | 240(45.5%) | 78(50.3%) | 162(43.5%) | 1.49(0.97–2.30) | 0.071 | |
| 40–49 | 76(14.4%) | 24(15.5%) | 52(14.0%) | 1.37(0.75–2.46) | 0.299 | |
| ≥50 | 25(4.7%) | 7(4.5%) | 18(4.8%) | 1.19(0.44–2.93) | 0.715 | |
| BMI | 0.245 | |||||
| <18.5 | 39(7.4%) | 7(4.5%) | 32(8.6%) | - | ||
| 18.5–24 | 327(62.0%) | 101(65.2%) | 226(60.8%) | - | ||
| ≥24 | 161(30.6%) | 47(30.3%) | 114(30.6%) | - | ||
| Received influenza or pneumonia vaccine inthe past 3 years | 0.511 | |||||
| Yes | 426(80.8%) | 128(82.6%) | 298(80.1%) | - | ||
| No | 101(19.2%) | 27(17.4%) | 74(19.9%) | - | ||
| Time of HIV diagnosis | 0.120 | |||||
| ≤5 year | 336(63.8%) | 91(58.7%) | 245(65.9%) | - | ||
| >5 year | 191(36.2%) | 64(41.3%) | 127(34.1%) | - | ||
| On ART | 0.216 | |||||
| Yes | 508(96.4%) | 147(94.8%) | 361(97.0%) | - | ||
| No | 19(3.6%) | 8(5.2%) | 11(3.0%) | - | ||
| ART duration | 0.184 | |||||
| ≤5 years | 350(68.9%) | 95(64.6%) | 255(70.6%) | - | ||
| >5 years | 158(31.1%) | 52(35.4%) | 106(29.4%) | - | ||
| Latest HIV viral load (copies/ml) | 0.661 | |||||
| <50 | 387(73.4%) | 118(76.1%) | 269(72.3%) | - | ||
| ≥50 | 54(10.2%) | 14(9.0%) | 40(10.8%) | - | ||
| Not sure | 86(16.3%) | 23(14.8%) | 63(16.9%) | |||
| Latest CD4+ T cell count (cells/μl) | 0.309 | |||||
| <200 | 15(2.8%) | 3(1.9%) | 12(3.2%) | |||
| 200–500 | 172(32.6%) | 43(27.7%) | 129(34.7%) | - | ||
| >500 | 291(55.2%) | 92(59.4%) | 199(53.5%) | - | ||
| Not sure | 49(9.3%) | 17(11.0%) | 32(8.6%) | - | ||
| Comorbidities | 0.392 | |||||
| Yes | 68(12.9%) | 23(14.8%) | 45(12.1%) | - | ||
| No | 459(87.1%) | 132(85.2%) | 327(87.9%) | - | ||
PLHIV, people living with HIV; aOR, adjusted odds ratio; CI, confidence interval; BMI, body-mass index.
ART, antiretroviral therapy.
Comorbidities include hyperlipidemia, liver disease, kidney disease, hypertension, allergic rhinitis, allergic dermatitis, respiratory diseases, diabetes, cardiovascular diseases.
Discussion
To the best of our knowledge, this is one of the first studies to explore factors associated with the uptake and adverse reactions of COVID-19 vaccination among PLHIV. Older age, unmarried status, having other comorbidities, concerning about adverse reactions, concerning about the negative impact of the vaccine on the progression of HIV/AIDS or on the effectiveness of ART, and concerning about the disclosure of HIV infection status were negatively associated with the willingness to initiate COVID-19 vaccination. Individuals who had a higher educational level, engaged in occupations with a higher risk of COVID-19 infection, received influenza or pneumonia vaccine in the past 3 years, trusted the effectiveness of vaccines, and received media information regarding COVID-19 vaccine, displayed higher willingness to initiate vaccination. Most adverse reactions were mild. There are no factors associated with having adverse reactions.
Factors associated with receiving COVID-19 vaccination among PLHIV in this study were similar to those reported in previous studies conducted among the general population.26–29 Concerning about the fast track of vaccine development might compromise the efficacy and safety of vaccine was the most common reason. Considering that a substantial gap will exist in the number needed to be vaccinated to achieve herd protection, any effective measure promoting information about the safety of COVID-19 vaccines is needed, such as improving the transparency of vaccine’s clinical data. The National Health Commission issued the first edition of COVID-19 vaccination guideline on 29 March, 2021. The guideline emphasizes that inactivated vaccine and recombinant subunit vaccine are recommended for immune impaired people based on the safety characteristics of previous same type of vaccines. For adenovirus vector vaccines, there is no safety data for the same type of vaccines in the past. It is necessary to balance the benefits and risks before inoculating adenovirus vector vaccines for immune impaired individuals.30
COVID-19 vaccine uptake varied among different groups of PLHIV. For example, individuals who were younger, had occupations at higher risk of exposure to COVID-19, and had a higher educational level were more willing to receive COVID-19 vaccines. This finding is consistent with previous research.19,31 It could be argued that these people are more aware of the benefits of vaccination and it is even more in their self-interest to take the vaccine. Another important result in our study was that participants who received influenza or pneumonia vaccine were more willing to get COVID-19 vaccines, suggesting that individuals who received influenza or pneumonia vaccine may have stronger awareness of disease prevention and more confidence in vaccines.
The last but equally important factor associated with receiving COVID-19 vaccination was concerning about the negative impact of the vaccine on the progression of HIV or the effectiveness of ART. Given that COVID-19 vaccines are quite new, this concern is understandable, and the long-term adverse reactions aside from those identified from the clinical trials are unknown. Our study showed that experiencing adverse reactions was not associated with current ART use, lower CD4+ T cell count, and higher HIV viral load. This finding suggests that there were no serious interactions between COVID-19 vaccine and ART in people with compromised immune system. However, it is unknown whether ART and compromised immune system would impact the effectiveness of COVID-19 vaccine. We find that the proportion of adverse reactions reported by PLHIV in our study (29.4%) is similar to that reported by healthy adults in another study (25.0%).32 PLHIV also expressed their concerns about the disclosure of their HIV infection status. Therefore, interventions are needed to strengthen their privacy protections, such as do not ask if you have immunodeficiency disease in public.
The present study has some limitations. First, as this study was a web-based survey, selection bias may exist, which may impact the generalizability of results. Second, due to the short time frame, we were unable to assess the potential long-term adverse reactions of COVID-19 vaccination on ART. It is not certain whether PLHIV can produce the same protective antibody levels as general people. Third, the sample size might be smaller when compared to similar studies using online questionnaires.33 Future research based on larger PLHIV populations and longer periods of time is needed to further understand the differences in protective antibody levels between PLHIV and the general population.
In conclusion, PLHIV are mainly concerned about the safety of the vaccine, disclosure of HIV infection status, and the impact of the vaccine on the progression of HIV/AIDS and on the effectiveness of ART. In order to ensure the coverage of COVID-19 vaccination among PLHIV, politicians, health-care professionals, and media should emphasize the benefit and necessity of vaccine and provide consultancy regarding adverse reactions. Additionally, measures on protecting privacy are needed in this group to decrease their concerns about exposure to HIV infection.
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 Centrol Research Institute Fund of Chinese Academy of Medical Sciences [2020]. The Science and Technology Innovation Committee of Shenzhen Municipality [JCYJ20170412151650600 to H.W.]. Academic technology leader project of Changzhi Medical College [Grant No. XSQ201902]. 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 Junjie Xu, Hui Wang, and Huachun Zou in consultation with the other authors. Hui Li and Jianzhou Yang were responsible for the field study. Heping Zhao and Weiran Zheng were responsible for data compilation and data analysis. All authors have contributed to the interpretation of the data and study findings. Heping Zhao, Jianzhou Yang, Weiran Zheng, and Yuqing Hu drafted the manuscript with all authors critically reviewing the paper.
Disclosure statement
No potential conflict of interest was reported by the author(s).
References
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