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Systematic Review
Revised

The refusal of COVID-19 vaccination and its associated factors: a meta-analysis

[version 2; peer review: 3 approved with reservations]
Previously titled: The refusal of COVID-19 vaccination and its associated factors: a systematic review
PUBLISHED 29 Jan 2024
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OPEN PEER REVIEW
REVIEWER STATUS

This article is included in the Sociology of Health gateway.

This article is included in the Emerging Diseases and Outbreaks gateway.

This article is included in the Sociology of Vaccines collection.

Abstract

Background

To date, more than 10% of the global population is unvaccinated against the coronavirus disease 2019 (COVID-19), and the reasons why this population is not vaccinated are not well identified.

Objectives

We investigated the prevalence of COVID-19 vaccine refusal and to assess the factors associated with COVID-19 vaccine refusal.

Methods

A meta-analysis was conducted from August to November 2022 (PROSPERO: CRD42022384562). We searched for articles investigating the refusal of COVID-19 vaccination and its potential associated factors in PubMed, Scopus, and the Web of Sciences. The quality of the articles was assessed using the Newcastle–Ottawa scale, and data were collected using a pilot form. The cumulative prevalence of the refusal to vaccinate against COVID-19 was identified through a single-arm meta-analysis. Factors associated with COVID-19 vaccine refusals were determined using the Mantel-Haenszel method.

Results

A total of 24 articles were included in the analysis. Our findings showed that the global prevalence of COVID-19 vaccine refusal was 12%, with the highest prevalence observed in the general population and the lowest prevalence in the healthcare worker subgroup. Furthermore, individuals with a high socioeconomic status, history of previous vaccination, and a medical background had a lower rate of COVID-19 vaccination refusal. Subsequently, the following factors were associated with an increased risk of COVID-19 vaccine refusal: being female, educational attainment lower than an undergraduate degree, and living in a rural area.

Conclusion

Our study identified the prevalence of and factors associated with COVID-19 vaccine refusal. This study may serve as an initial reference to achieve global coverage of COVID-19 vaccination by influencing the population of COVID-19 vaccine refusal.

Keywords

COVID-19; vaccination; refusal; acceptance; risk factors.

Revised Amendments from Version 1

In the revised version of the article, we made several modifications based on the reviewer's suggestions, but these changes did not alter the final findings of our study. The revisions to our article encompassed adjustments to the title, abstract, introduction, methods, results, and discussion. In the title, we replaced the term "a systematic review" with "a meta-analysis." In the abstract, we conducted a reproofreading to enhance sentence clarity as directed by the reviewer. In the introduction, we revised by adding explanations about the differences between vaccine refusal and vaccine hesitancy, specifically incorporated into the second paragraph of the introduction. Furthermore, we conducted reproofreading in the introduction to clarify sentence meanings. In the methods section, we added I-squared analysis, in addition to p heterogeneity, to assess heterogeneity across studies. Moreover, in the search strategy, we included the keyword "intention not to get vaccinated" as an additional term related to vaccine refusal. In the results section, we modified Table 1 by adding columns detailing final findings and sample size methods. Additionally, in the results section, we removed the design of included studies from the Table 1 and included it in the text under the subheading “selection of studies." In the discussion section, we introduced discussions on the 3Cs model in the fourth discussion paragraph, emphasized socioeconomic factors (SES) on vaccine refusal in the third paragraph of the discussion, and explained the contextual differences between vaccine refusal and hesitancy in the first discussion paragraph. Regarding study limitations, in the last paragraph of the discussion section, we removed the limitation about the study design of included studies and added country-specific factors and the WHO BeSD framework as additional study limitations. Finally, in the discussion section, we conducted proofreading to clarify the meaning of the discussions.

See the authors' detailed response to the review by Amy Morrison
See the authors' detailed response to the review by Angelo Capodici

Introduction

At the beginning of 2021, the coronavirus disease 2019 (COVID-19) vaccination program involving several designs including protein subunit, vector, inactivated, and mRNA, was started.1 Currently, referring to data presented on Our World in Data, this vaccination program has included 84.6% of the global population, and the reason the rest of the population (15.4%) did not receive vaccination is still unknown.2 The high number of vaccinated country populations is the result of the hard work of various parties, and this may be associated with factors such as the seriousness of governments in promoting vaccination programs, equitable distributions of vaccines, hard work of healthcare workers, good public awareness about the importance of vaccination, and effective promotion of vaccines to populations who have the power to hesitate about vaccines.3 Contrarily, in the unvaccinated population, several factors may contribute to hesitation, including fear of harmful ingredients in vaccines, distrust of pharmaceutical companies, lack of knowledge about COVID-19, belief that a healthy lifestyle and a good diet are sufficient to fight against COVID-19, preference for natural immunity, lack of seriousness from the government in promoting vaccination programs, religious rules suggesting not to vaccinate, and limited information regarding the safety of vaccination. These factors have been reported to trigger hesitancy and refusal of the COVID-19 vaccination.47 Moreover, there is a distinction between vaccine hesitancy and vaccine refusal. Vaccine hesitancy involves a delay in accepting or refusing vaccines despite the availability of vaccination services, and it is a complex and context-specific phenomenon that varies across time, place, and vaccines. Influencing factors include complacency, convenience, and confidence.8 In contrast, vaccine refusal is characterized by a lack of vaccination and an explicit intention not to get vaccinated.9 Consequently, it can be inferred that the context of vaccine hesitancy has a more extensive scope and includes the population of refusal. In our previous study, we had explored the global prevalence of COVID-19 vaccination hesitancy and its potential associated factors.10 However, because the hesitancy population consists of both hesitancy and refusal populations, and the refusal population can influence individuals within their circle to become hesitant or refuse the COVID-19 vaccine, the prevalence of the COVID-19 vaccine refusal should also be investigated.

It is widely known that new vaccines or vaccine candidates are commonly met with hesitation or rejection by the public. Before the COVID-19 pandemic, this phenomenon has been widely reported in several cases, such as: dengue,11 malaria,12 Ebola,13 chikungunya,14 and monkeypox.15 This might be caused by poor public knowledge regarding the vaccine, including inadequate understanding of vaccine efficacy and side effects. In the case of COVID-19, this phenomenon might be affected by multiple factors, and theoretically, the factors had been contextualized into three major categories, including poor knowledge of vaccination programs, socioeconomic status, and social interaction.16 Moreover, recently, influencers in their podcasts discussed the rejection of the COVID-19 vaccine, which is a dilemma that can influence people in society to reject COVID-19 vaccinations, thereby threatening the success of the COVID-19 vaccination program.17 However, to date, there are no precise data on the prevalence of COVID-19 vaccination refusal and its potential associated factors. Several previous studies have investigated the refusal of COVID-19 vaccines; however, the results of these studies have been inconclusive. In the present study, we seek to explore the global prevalence of COVID-19 vaccination refusal and identify the associated factors using a meta-analysis approach.

Methods

Study design

A meta-analysis following the guidelines of the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) protocol was carried out from August to November 2022 (PROSPERO: CRD42022384562). The PRISMA checklist in our study is provided in Figshare.18 A systematic search was implemented in PubMed, Scopus, and Web of Science; and the information was collected from each relevant article to determine the prevalence and associated factors of COVID-19 vaccines refusal.

Eligibility criteria

Pre-defined eligibility criteria were assigned prior to performing the search strategy. The inclusion criteria were: (1) assessment of the prevalence of COVID-19 vaccination refusal, and (2) investigation of the factors associated with COVID-19 vaccination refusal. Articles with double publications, letters to the editor, commentaries, and reviews were excluded.

Search strategy and data extraction

PubMed, Scopus, and Web of Science were searched up to November 5th, 2022. Before conducting a search for the primary outcome, we identified the factors that might have an impact on the incidence of refusal of COVID-19 vaccines. The potential keywords adapted from medical subject headings were applied: “vaccine,” “vaccination,” or “immunization;” “COVID-19” or “coronavirus disease 2019;” “refusal” or “rejection” or “acceptance” or “intention not to get vaccinated.” The search strategy used only English words. In case of duplication, articles with a lower sample size used in the study were excluded. Moreover, to acquire additional references, a search on the reference list of related articles was also carried out. A pilot form was used to collect data from each study and consisted of the following items: (1) first author name, (2) time of publication, (3) design of study, (4) study period, (5) Newcastle–Ottawa scale (NOS), (6) the event rate of COVID-19 vaccination refusal or rejection or intention not to get vaccinated, and (7) factors associated with COVID-19 vaccination refusal. Data were collected by FT, JKF, APK, EAP, RPP, MR, TA, MN, SW, GP, AP, QA, MVPHM, RY, and YSP.

Assessment of the methodological quality

The NOS was used to assess the quality of potential articles. We included articles of moderate and high quality, and low quality articles were excluded. A score of 0–3, 4–6, and 7–9 indicated low, moderate, and high quality articles, respectively. The NOS assessment was performed by JKF, APK, and EAP using the NOS pilot form. Disagreements were resolved through discussion.

Outcome measures

The primary endpoints of our study were the global prevalence and factors associated with COVID-19 vaccination refusal. Potential factors associated with the refusal of COVID-19 vaccination were: age group, gender, marital status, educational attainment, employment status, healthcare-related job, socioeconomic status (SES), urbanity, presence of children and elderly people at home, individual with medical background, history of testing for COVID-19, family member/friend ever diagnosed with COVID-19, personal history of COVID-19 diagnosis, history of hospitalization due to COVID-19 among people in a social circle, and history of previous vaccination.

Statistical analysis

Data are presented as n (%). The statistical analysis consisted of the following parameters: publication bias among studies, heterogeneity among studies, event rate, and odds ratio with a 95% confidence interval (OR95%CI). Publication bias was assessed using Egger’s test. A p-value of less than 0.05 indicated that publication bias existed among studies. The heterogeneity in our study was determined using the Q test. Evidence of heterogeneity was considered if the p-value was less than 0.10 and I-squared was more than 50%. If we found heterogeneity among studies, we applied the random effects model, and in cases where no heterogeneity was found, we used a fixed effects model. The cumulative event rate of COVID-19 vaccine refusal was calculated using a single-arm meta-analysis with a dichotomous model, and the pooled OR95%CIs of factors associated with the refusal of COVID-19 vaccination were calculated using the Mantel-Haenszel method. The analysis was performed using the R package (RStudio version 4.1.1, R Studio, California, MA, USA).

Results

Selection of studies

A total of 3,422 papers and 4 papers were assessed from the databases and reference lists of related articles, respectively. In the initial evaluation, we excluded 33 papers due to duplication and 3,318 papers due to irrelevant topics. Subsequently, 75 articles were included in further review. We further excluded 17 articles as they were reviews and 34 articles due to insufficient data. Finally, the data retrieved from 24 articles were analyzed to estimate the cumulative prevalence and factors associated with COVID-19 vaccination refusal.1942 The flow diagram of article selection in our study is outlined in Figure 1, and the characteristics of the articles included in our study are listed in Table 1. The design employed for all articles in our study was cross-sectional.

18975000-3cc2-434b-8e85-d3642ecbb4ec_figure1.gif

Figure 1. A flowchart of article selection in our study.

Table 1. Baseline characteristics of articles included in our study.

Author & yearCountrySample selection methodSample sizeStudy periodPopulationNOSStudy findings
Al- Sanaf et al. 2021KuwaitConvenience1019March 2021HCW5Females, nurses, and private sector healthcare workers had higher vaccine refusal rates.
Aurilio et al. 2021ItalyNA531December 2020HCW6Female gender and belief in vaccine efficacy strongly predict vaccine intention.
Baniak et al. 2021USAConvenience275February 2021HCW6Vaccine uptake was higher with confidence in safety and over 10 years of experience.
Fakonti et al. 2021CyprusStratified435December 2020HCW6Cyprus nurses and midwives showed vaccine reluctance due to concerns.
Fares et al. 2021EgyptProbability385December 2020–January 2021HCW7Vaccine acceptance depended on COVID-19 concerns and confidence in safety and effectiveness, while refusal was linked to limited trials and fear of side effects; accurate information was seen as crucial for increased acceptance.
Fisher et al. 2020USAConvenience991April 2020GP6Vaccine refusal was associated with younger age, Black race, lower education, and not receiving the prior year's influenza vaccine, while refusal reasons included vaccine-specific concerns, a need for more information, anti-vaccine attitudes, and lack of trust.
Grochowska et al. 2021PolandPurposive419September–November 2020HCW5For 86.3% of those hesitant and refusing COVID-19 vaccination, assurance of safety and efficacy would be convincing.
Handam et al. 2021LebanonProbability758May–June 2021Students6Vaccine refusal was linked to nationality, residency, and university rank, with less refusal among those confident in vaccine safety. Non-receipt of the flu vaccine, endorsement of conspiracies, and lower COVID-19 knowledge were associated with higher refusal.
İkiışık et al. 2021TurkeyProbability384December 2020GP5Vaccine acceptance was influenced by individual perceptions of risk and age.
Janssen et al. 2021FranceConvenience4349December 2020–March 2021HCW5The primary concern among professionals who declined was the fear of adverse events.
Kose et al. 2020TurkeyConvenience1138September 2020HCW7Men, students, and those with a prior flu shot were willing to get the COVID-19 vaccine.
Kozak et al. 2021GermanyConvenience and snowball3368March–April 2021HCW6There was a high vaccination rate and strong willingness to receive the vaccine (over 80%) among all professional groups and fields of work
Manning et al. 2021USAStratified and convenience1205August 2020–September 2020Students7The primary factors for not receiving vaccination were concerns related to vaccine safety and potential side effects.
Mena et al. 2021SpainNA865December 2020–January 2021HCW7Addressing doubts and fears about vaccination is crucial, especially among less inclined groups like females, younger individuals, and those without recent influenza vaccinations.
Ousseine et al. 2021FranceNon-probability15426February–April 2021GP6Lower education level, low health literacy, financial hardship, being under 30 years old, and residing in a rural area were independently associated with uncertainty and unwillingness to get vaccinated.
Paris et al. 2021FranceConvenience1965February–February 2021HCW7COVID-19 vaccine intention was independently associated with age, occupation, flu vaccine history, and concerns about AstraZeneca vaccine tolerability.
Pataka et al. 2021GreeceProbability656December 2020HCW6Most responders intending to accept vaccination were male physicians, older, married with children, and treated COVID-19 patients, with predictors for healthcare professionals' willingness being parenthood, physician status, and treating confirmed/suspected COVID-19 cases.
Rodriguez-Blanco et al. 2021SpainConvenience and probability2494November–December 2020GP7Acceptance of the COVID-19 vaccine might be more likely among males, individuals aged over 60, married, retired, highly educated, or with a leftist political inclination.
Saied et al. 2021EgyptConvenience and probability2133January 2021Students7The primary barriers to COVID-19 vaccination were insufficient data on vaccine side effects and a lack of information about the vaccine itself.
Schwarzinger et al. 2021FranceStratified random1942July 2020GP6Refusing vaccines and vaccine hesitancy were significantly associated with being female, age, lower education, poor compliance with past vaccinations, and the absence of specified chronic conditions or having only hypertension.
Shaw et al. 2021USANA5287November–December 2020HCW6Older, male, White, or Asian respondents showed higher vaccination likelihood, while predominant concerns among participants included vaccine safety, potential adverse events, efficacy, and speed of development.
Spinewine et al. 2021BelgiumConvenience1132January 2021HCW6A positive outlook on COVID-19 vaccination was associated with older age, physician status, seasonal flu vaccination, and various Health Belief Model factors.
Vignier et al. 2021French GuianaConvenience and snowball579January–March 2021HCW8Older and concerned healthcare workers were more willing to get vaccinated, while nurses or those in non-medical professions, especially those born in French Guiana, were less likely due to fears of adverse effects or lack of trust in pharmaceutical companies and authorities' epidemic management.
Wang et al. 2020Hong KongStratified and convenience806February–March 2020HCW6Individuals in the private sector, those with chronic conditions, those in contact with suspected or confirmed COVID-19 patients, and those who accepted influenza vaccination in 2019 were more inclined to accept COVID-19 vaccination.

The cumulative prevalence of the refusal to COVID-19 vaccination

Our analysis identified that the cumulative prevalence of the refusal to COVID-19 vaccination was 12% (event rate: 0.12; 95%CI: 0.10, 0.15; p Egger: 0.5290; p Heterogeneity<0.0001; p<0.0001) (Figure 2A). Subsequently, sub – group analysis found that the prevalence of the refusal to COVID-19 in general population was 20% (Figure 2B), healthcare workers 10% (Figure 2C), and students 11% (Figure 2D).

18975000-3cc2-434b-8e85-d3642ecbb4ec_figure2.gif

Figure 2. The prevalence of COVID-19 vaccines refusal.

A). All prevalence of COVID-19 refusal (Event rate: 0.12; 95%CI: 0.10, 0.15; p Egger: 0.5290; p Heterogeneity<0.0001; p<0.0001).

B). The prevalence in general population subgroup (Event rate: 0.20; 95%CI: 0.15, 0.26; p Egger: 0.4100; p Heterogeneity<0.0001; p<0.0001).

C). The prevalence in healthcare workers subgroup (Event rate: 0.10; 95%CI: 0.07, 0.14; p Egger: 0.6760; p Heterogeneity<0.0001; p<0.0001).

D). The prevalence in student subgroup (Event rate: 0.11; 95%CI: 0.06, 0.20; p Egger: 0.5830; p Heterogeneity<0.0001; p<0.0001).

Factors associated with COVID-19 vaccination refusal

Table 2 and Figures 35 summarize the factors associated with the refusal of COVID-19 vaccination. Our calculation revealed that six of the 15 factors had a significant impact on COVID-19 vaccine refusal. We found that an increased risk of COVID-19 vaccine refusal was observed in the following covariates: female (Figure 3A), educational attainment lower than an undergraduate degree (Figure 4A) and living in rural areas (Figure 5B).

Table 2. Factors associated with refusal to COVID-19 vaccination.

CovariatesRefusal/Total (n [%])NSp Eggerp HetOR95% CIp
Age group (years)
<301827/9397 (19.44%)90.2570<0.00011.200.96-1.500.1090
30-501575/9579 (16.44%)90.16000.02000.960.82-1.130.6210
>50639/5344 (11.96%)90.5240<0.00010.910.60-1.360.6300
Sex
Male1194/8499 (14.05%)220.2550<0.00010.710.61-0.82<0.0001
Female3659/19842 (18.44%)220.2550<0.00011.421.22-1.65<0.0001
Marital status
Married1702/9960 (17.09%)6<0.0001<0.00010.770.71-0.82<0.0001
Single1954/9693 (20.16%)6<0.00010.96201.311.21-1.41<0.0001
Educational attainment
<BSc2892/12199 (23.71%)100.3620<0.00011.741.34-2.26<0.0001
≥BSc2397/16931 (14.16%)100.3620<0.00010.580.44-0.75<0.0001
Employment
Not Working1751/8770 (19.97%)70.12400.05501.110.96-1.280.1670
Working2666/14218 (18.75%)70.14500.02400.930.79-1.090.3850
Socioeconomic status
Low712/2947 (24.16%)60.6470<0.00011.050.59-1.840.8770
Medium1947/8561 (22.74%)61.0000<0.00011.860.81-4.280.1450
High1238/10286 (12.04%)60.9900<0.00010.420.18-0.990.0480
Having children at home421/1775 (23.72%)40.5940<0.00010.650.35-1.210.1730
Hospitalization due to COVID-19 among people in the same social circle16/668 (2.40%)20.58900.02500.620.05-7.130.7030
Health literacy about COVID-19 vaccine1795/11153 (16.09%)40.56300.00100.600.31-1.170.1330
History of previous vaccination2456/18868 (13.02%)140.9710<0.00010.280.17-0.48<0.0001
History of chronic disease(s)275/2317 (11.87%)90.5130<0.00010.940.64-1.380.7510
Personal history of COVID-19 diagnosis494/3498 (14.12%)80.19700.02800.940.77-1.150.5560
Family member/friend ever diagnosed with COVID-19932/6739 (13.83%)80.2800<0.00010.940.72-1.210.6120
Ever tested for COVID-1926/582 (4.47%)2<0.00010.69300.800.48-1.340.3950
Medical background200/3642 (5.49%)110.9170<0.00010.320.17-0.58<0.0001
Residential
Urban2629/16172 (16.26%)40.3030<0.00010.620.44-0.880.007
Rural859/3324 (25.84%)40.3030<0.00011.611.14-2.280.007
18975000-3cc2-434b-8e85-d3642ecbb4ec_figure3.gif

Figure 3. Females had higher risk of refusal to COVID-19 vaccination than males (A), and individual history of previous vaccination had lower risk of refusal to COVID-19 vaccination (B).

18975000-3cc2-434b-8e85-d3642ecbb4ec_figure4.gif

Figure 4. Individual with educational attainment <BSc had higher risk of refusal to COVID-19 vaccination than ≥BSc (A), and individual with medical background had lower risk of refusal to COVID-19 vaccination compared to general population (B).

18975000-3cc2-434b-8e85-d3642ecbb4ec_figure5.gif

Figure 5. Individual with high SES had lower risk of refusal to COVID-19 vaccination than low SES (A), and rural residential living was associated with increased risk of refusal to COVID-19 vaccination than urban population (B).

In contrast, the decreased risk of refusal of COVID-19 vaccination was affected by the following factors: high socioeconomic status (Figure 5A), history of previous vaccination (Figure 3B), and individuals with a medical background (Figure 4B).

Source of heterogeneity and potential publication bias

Our analysis using the Q test revealed that two variables (single marital status and history of testing for COVID-19) had no evidence of heterogeneity; thereafter, we applied a fixed-effects model. In contrast, a random-effects model was applied to the other covariates (Table 2). Subsequently, our analysis using Egger’s test revealed that the marital status and ever tested for COVID-19 covariates exhibited a risk of publication bias (Table 2).

Discussion

Our meta-analysis revealed that the prevalence of refusal to undergo the COVID-19 vaccination was 12%. Our findings were lower than those reported by Cenat et al. and Robinson et al.43,44 In our study, we had a larger sample size than those reported by in these studies. Moreover, studies by Cenat et al. and Robinson et al. also involved articles that reported COVID-19 vaccination hesitancy.43,44 It is well known that the terminologies of refusal and hesitancy to vaccinate are different, and not everyone is hesitant to vaccinate. Vaccine hesitancy is when individuals delay or decline vaccination despite vaccine availability.8 On the other hand, vaccine refusal is the complete avoidance of vaccination with a clear intention not to get vaccinated. Vaccine hesitancy encompasses a wider range, including those who outright refuse vaccination.9 Thus, it can be assumed that the context of previous studies has a gap in the definition of vaccine refusal. Therefore, our study may provide better data on the prevalence rate of COVID-19 vaccination refusal. Moreover, we also reported the prevalence of COVID-19 vaccination refusal in some subgroup populations: the general population, healthcare workers, and students. We found that healthcare workers had the lowest prevalence of COVID-19 vaccination refusal, followed by students, and the general population. Our current findings indicate that vaccination knowledge might affect our findings. We assumed that healthcare workers and students may have a better knowledge of vaccination programs than the general population. This assumption is supported by the results of previous studies, which found that healthcare workers and students had better knowledge of COVID-19 vaccination than the general population,45,46 and this factor was also shown to contribute to the acceptance of vaccination programs.47

Our study found that the increased risk of COVID-19 vaccination refusal was higher in females and individuals with educational levels below an undergraduate degree (BSc). In contrast, lower risk of COVID-19 vaccination refusal was found in individuals with a history of previous vaccination and a medical background. Our current findings suggest that the factors related to knowledge of COVID-19 vaccination had the potential to affect the refusal to vaccinate against COVID-19. As previously reported, a study revealed that females lacked literacy regarding COVID-19 vaccination than males.48 This may be attributed to the fact that the majority of females are housewives, and therefore, may have less social interaction than males, as they are based at home rather than going out to work.49 This possibility might contribute to the lack of knowledge on COVID-19 vaccination in the female population. Furthermore, one study found that the majority of the side effects of COVID-19 vaccination were reported among female individuals.50 Taken together, those factors may affect the decision to accept or refuse the vaccines. Moreover, individuals with educational level below the undergraduate (BSc) degree might have an inadequate source of literature regarding COVID-19 vaccination compared to those with an educational level higher than an undergraduate (BSc) degree. In the context of vaccination knowledge, a study found that educational attainment was one of the predictors of vaccination knowledge, where lower educational attainment was associated with poorer knowledge of vaccination.51 Therefore, the population with an educational level below the undergraduate (BSc) degree might have insufficient consideration for COVID-19 vaccination compared to those with an educational level higher than the undergraduate (BSc) degree. Further, individuals with a history of previous vaccination and a medical background may have adequate information regarding the importance of COVID-19 vaccination, therefore, may have sufficient awareness regarding COVID-19 vaccination. Previous studies found that individuals with a medical background had better knowledge of COVID-19 vaccination than the general population.45,46 Likewise, another study revealed that individuals with a history of previous annual vaccination demonstrated good awareness and knowledge of the importance of vaccination programs.52 Prior to the COVID-19 pandemic, studies have extensively reported that knowledge of disease prevention and the adoption of good health behavior practices had a significant impact on the acceptance rate of vaccination, as observed in cases such as Monkeypox, Ebola, and Dengue.5355 Thus, this might imply that this population (individuals with a history of previous vaccination and medical background) has a low rate of refusal to vaccinate against COVID-19, as reported in our meta-analysis.

Our study also identified a higher risk of COVID-19 vaccination refusal in rural compared to urban populations, and a lower risk of COVID-19 vaccination refusal in individuals with high SES compared to those with low SES. Currently, providing precise explanations for the reasons underlying our findings might be challenging and could vary between different regions. However, we can propose the following reasons: social privileges, administrative requirements, and social circles. First, in the aspect of social privilege, individuals with high SES might take pride in being vaccinated, while this sense of pride might not be as prevalent in rural population. Studies found that COVID-19 vaccination was considered a socioeconomic privilege and political ideology,56 while the rural population may not view the COVID-19 vaccine as a privilege and tended to have poorer perception toward vaccine safety.57 The second reason is administrative requirements. Individuals with high SES might need COVID-19 vaccination for various activities, such as business, travelling, and career requirements, as the World Health Organization (WHO) has implemented a COVID-19 vaccine certificate as an administrative requirement for travel or business.58 However, these administrative requirements were not necessary for rural individuals, as the majority of rural individual jobs are in private and traditional sectors, such as farmers, fishermen, and manual laborers.59,60 The third factor is social circle. Individuals with high SES might have social circles that engage in high intellectual content, whereas in rural populations, their social circle might be limited to neighbors with similar intellectual contents. This factor might also indirectly contribute to the understanding of COVID-19 vaccinations, and consequently, affect their decision to accept or refuse the COVID-19 vaccine. This is supported by previous studies that revealed that SES was associated with the level of knowledge of vaccination programs and physical health status.61,62 Additionally, earlier studies had shown that vaccine refusal in Italy, Ghana, and Pakistan was influenced by SES, highlighting its importance as a determining factor.6365 Moreover, our previous study on dengue also revealed that SES was one of the predictive indicators for the acceptance of vaccination.55

Our meta-analysis is one of the first to report the prevalence of COVID-19 vaccination refusal and the potential factors associated with the refusal of COVID-19 vaccination. Our study also had a larger sample size compared to previous meta-analyses in a similar context.43,44 The findings of our study might serve as the initial step to prevent the failure of COVID-19 vaccination programs. By identifying the potential factors associated with refusal to vaccinate against COVID-19, we expect that governments may provide advanced interventions to those populations. Furthermore, concerning vaccine refusal, it is important to take into account the 3C concept: confidence, complacency, and convenience. Confidence involves a lack of trust in either the vaccine or the provider. Complacency is the absence of recognition for the need or value of the vaccine. Convenience pertains to the unavailability of easy access to vaccination services.66 As previously reported, the main concern in obtaining public trust regarding COVID-19 vaccines was the lack of adequate evidence from long-term and large-scale studies on the effectiveness and safety of COVID-19 vaccination.67 However, several studies have suggested interventions for the refusal population, including providing reliable information regarding the COVID-19 pandemic and the COVID-19 vaccination. Effective, ethical, and evidence-based communication, preferably delivered by community leaders and healthcare practitioners, is also recommended.6870

Our meta-analysis has several limitations. First, several potential confounding factors, such as the level of knowledge about COVID-19 vaccination, attitude toward COVID-19 prevention, government regulation, types of vaccine, environmental factors, and the source of literature regarding COVID-19 vaccination, were not included in the analysis due to the lack of available data. Second, the sample size in our present study was limited; therefore, further studies involving larger sample sizes are needed. Third, our meta-analysis could not reflect the prevalence of the global numbers because the proportion of sample sizes in each region was unequal. Fourth, as the earlier investigation indicated the efficacy of the WHO BeSD framework in forecasting COVID-19 vaccination acceptance, and our present study faced constraints in gathering covariates associated with the WHO BeSD framework, additional study that encompasses all elements of the WHO BeSD framework might be warranted.71 Fifth, it is highlighted that vaccine refusal is an intricate issue, and the extent to which populations reject vaccines may differ from one country to another. Unfortunately, due to data constraints, we could not analyze subgroups based on the country in which the study was conducted. Hence, it is important to recognize these limitations in future study.

Conclusion

In conclusion, we revealed that the cumulative prevalence of refusal to COVID-19 vaccination was 12%, with the highest prevalence observed in the general population and the lowest in the healthcare worker subgroup. The individuals with the following characteristics are at an increased risk of refusing COVID-19 vaccination: being female, having an educational attainment lower than an undergraduate degree, and living in a rural area. Conversely, reduced risk of refusing COVID-19 vaccination is associated with high socioeconomic status, a history of previous vaccination, and individuals with a medical background.

Author contribution

Conceptualization: FT, JKF, GS; Data Curation: FT, JKF, GS, APK, EAP, RPP, MR, TA, MN, SW, GP, AP, QA, MVPHM, RY, YSP; Formal Analysis: JKF, APK, EAP, RPP, MR, TA, MN, SW, GP, AP, QA, MVPHM, RY, YSP; Investigation: FT, JKF, GS, LW, APK, EAP, RPP, MR, TA, MN, SW, GP, AP, QA, MVPHM, RY, YSP; Project Administration: APK, EAP, RPP, MR, TA, MN, SW, GP, AP, QA, MVPHM, RY, YSP; Resources: APK, EAP, RPP, MR, TA, MN, SW, GP, AP, QA, MVPHM, RY, YSP; Methodology: FT, JKF, GS, LW, EAP, RPP, MR, TA, MN, SW, GP, AP, QA, MVPHM, RY, YSP; Software: FT, JKF, APK, EAP, RPP, MR, TA, MN, SW, GP, AP, QA, MVPHM, RY, YSP; Visualization: APK, EAP, RPP, MR, TA, MN, SW, GP, AP, QA, MVPHM, RY, YSP, CC, KD, HH; Supervision: FT, JKF, GS, LW, CC, KD, HH; Validation: FT, JKF, LW, CC, KD, HH; Writing – Original Draft Preparation: FT, JKF, LW, APK, EAP, RPP, MR, TA, MN, SW, GP, AP, QA, MVPHM, RY, YSP; Writing – Review & Editing: FT, JKF, GS, LW, CC, KD, HH. All authors have critically reviewed and approved the final draft and are responsible for the content and similarity index of the manuscript.

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Tamara F, Fajar JK, Soegiarto G et al. The refusal of COVID-19 vaccination and its associated factors: a meta-analysis [version 2; peer review: 3 approved with reservations]. F1000Research 2024, 12:54 (https://doi.org/10.12688/f1000research.128912.2)
NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.
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ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions
Version 2
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PUBLISHED 29 Jan 2024
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Reviewer Report 25 Oct 2024
Amy Morrison, Department of Pathology, Microbiology and Immunology, School of Veterinary Medicine, University of California, Davis (UC Davis), Davis, CA, USA 
Approved with Reservations
VIEWS 4
Review: The refusal of COVID-19 vaccination and its associated factors: a meta-analysis [version 2; peer review: 2 approved with reservations]

Overall, the manuscript is significantly improved over the previous version and many of my concerns were addressed, ... Continue reading
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HOW TO CITE THIS REPORT
Morrison A. Reviewer Report For: The refusal of COVID-19 vaccination and its associated factors: a meta-analysis [version 2; peer review: 3 approved with reservations]. F1000Research 2024, 12:54 (https://doi.org/10.5256/f1000research.161802.r241859)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
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Reviewer Report 05 Apr 2024
Hassan Hadi Al-kazzaz, Medical and Health Technology College, Al- Zahra University for Women, Karbala, Iraq 
Approved with Reservations
VIEWS 4
Intention not to get vaccinated; its not clearly stated whether this refusal or hesitation, please explain. What is the accepted sample size according to your statement “articles with a lower sample size used in the study were excluded”? It's important ... Continue reading
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Al-kazzaz HH. Reviewer Report For: The refusal of COVID-19 vaccination and its associated factors: a meta-analysis [version 2; peer review: 3 approved with reservations]. F1000Research 2024, 12:54 (https://doi.org/10.5256/f1000research.161802.r255307)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
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PUBLISHED 13 Jan 2023
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Reviewer Report 30 Aug 2023
Angelo Capodici, University of Bologna, Bologna, Italy 
Approved with Reservations
VIEWS 8
Regarding the question of whether ample methodological and analytical details are furnished to facilitate replication by fellow researchers, my response leans toward the negative. The omission of the search string and the absence of a reported PRISMA checklist, despite claims ... Continue reading
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CITE
HOW TO CITE THIS REPORT
Capodici A. Reviewer Report For: The refusal of COVID-19 vaccination and its associated factors: a meta-analysis [version 2; peer review: 3 approved with reservations]. F1000Research 2024, 12:54 (https://doi.org/10.5256/f1000research.141551.r201174)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
  • Author Response 20 Mar 2024
    Jonny Fajar, Brawijaya Internal Medicine Research Center, Department of Internal Medicine, Faculty of Medicine, Universitas Brawijaya, Malang, 65145, Indonesia
    20 Mar 2024
    Author Response
    1. Regarding the question of whether ample methodological and analytical details are furnished to facilitate replication by fellow researchers, my response leans toward the negative. The omission of the
    ... Continue reading
COMMENTS ON THIS REPORT
  • Author Response 20 Mar 2024
    Jonny Fajar, Brawijaya Internal Medicine Research Center, Department of Internal Medicine, Faculty of Medicine, Universitas Brawijaya, Malang, 65145, Indonesia
    20 Mar 2024
    Author Response
    1. Regarding the question of whether ample methodological and analytical details are furnished to facilitate replication by fellow researchers, my response leans toward the negative. The omission of the
    ... Continue reading
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18
Cite
Reviewer Report 09 Aug 2023
Amy Morrison, Department of Pathology, Microbiology and Immunology, School of Veterinary Medicine, University of California, Davis (UC Davis), Davis, CA, USA 
Approved with Reservations
VIEWS 18
This manuscript presents results from a systematic review and meta-analysis on the global prevalence of COVID-19 vaccine refusal factors that increase or decrease the risk of refusal. This manuscript follows the publication from the same group titled “Global Prevalence and ... Continue reading
CITE
CITE
HOW TO CITE THIS REPORT
Morrison A. Reviewer Report For: The refusal of COVID-19 vaccination and its associated factors: a meta-analysis [version 2; peer review: 3 approved with reservations]. F1000Research 2024, 12:54 (https://doi.org/10.5256/f1000research.141551.r190442)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
  • Author Response 20 Mar 2024
    Jonny Fajar, Brawijaya Internal Medicine Research Center, Department of Internal Medicine, Faculty of Medicine, Universitas Brawijaya, Malang, 65145, Indonesia
    20 Mar 2024
    Author Response
    This manuscript presents results from a systematic review and meta-analysis on the global prevalence of COVID-19 vaccine refusal factors that increase or decrease the risk of refusal. This manuscript follows ... Continue reading
COMMENTS ON THIS REPORT
  • Author Response 20 Mar 2024
    Jonny Fajar, Brawijaya Internal Medicine Research Center, Department of Internal Medicine, Faculty of Medicine, Universitas Brawijaya, Malang, 65145, Indonesia
    20 Mar 2024
    Author Response
    This manuscript presents results from a systematic review and meta-analysis on the global prevalence of COVID-19 vaccine refusal factors that increase or decrease the risk of refusal. This manuscript follows ... Continue reading

Comments on this article Comments (0)

Version 2
VERSION 2 PUBLISHED 13 Jan 2023
Comment
Alongside their report, reviewers assign a status to the article:
Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions
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