Keywords
COVID-19; vaccination; refusal; acceptance; risk factors.
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.
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.
We investigated the prevalence of COVID-19 vaccine refusal and to assess the factors associated with COVID-19 vaccine refusal.
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.
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.
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.
COVID-19; vaccination; refusal; acceptance; risk factors.
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
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.4–7 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.
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.
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.
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.
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.
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.
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).
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.19–42 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.
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).
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).
Table 2 and Figures 3–5 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).
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).
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).
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.53–55 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.63–65 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.68–70
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.
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.
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.
All data underlying the results are available as part of the article and no additional sources of data are required.
Figshare: PRISMA checklist for ‘The refusal of COVID-19 vaccination and its associated factors: A meta-analysis’. https://doi.org/10.6084/m9.figshare.21617979.v1. 18
Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).
We thank Lembaga Pengelola Dana Pendidikan (LPDP) and Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi (Kemendikbudristek) Republic of Indonesia for supporting this project.
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References
1. Fajar JK, Sallam M, Soegiarto G, Sugiri YJ, et al.: Global Prevalence and Potential Influencing Factors of COVID-19 Vaccination Hesitancy: A Meta-Analysis.Vaccines (Basel). 2022; 10 (8). PubMed Abstract | Publisher Full TextCompeting Interests: No competing interests were disclosed.
Reviewer Expertise: Dengue epidemiology; arbovirus epidemiology; systematic review
Are the rationale for, and objectives of, the Systematic Review clearly stated?
Yes
Are sufficient details of the methods and analysis provided to allow replication by others?
Yes
Is the statistical analysis and its interpretation appropriate?
Yes
Are the conclusions drawn adequately supported by the results presented in the review?
Yes
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: public health and family medicine
Are the rationale for, and objectives of, the Systematic Review clearly stated?
Yes
Are sufficient details of the methods and analysis provided to allow replication by others?
No
Is the statistical analysis and its interpretation appropriate?
Yes
Are the conclusions drawn adequately supported by the results presented in the review?
Yes
References
1. Gori D, Capodici A, La Fauci G, Montalti M, et al.: COVID-19 Vaccine Refusal and Delay among Adults in Italy: Evidence from the OBVIOUS Project, a National Survey in Italy.Vaccines (Basel). 2023; 11 (4). PubMed Abstract | Publisher Full TextCompeting Interests: No competing interests were disclosed.
Reviewer Expertise: Epidemiology
Are the rationale for, and objectives of, the Systematic Review clearly stated?
Partly
Are sufficient details of the methods and analysis provided to allow replication by others?
Partly
Is the statistical analysis and its interpretation appropriate?
Yes
Are the conclusions drawn adequately supported by the results presented in the review?
Partly
References
1. Larson H, Jarrett C, Eckersberger E, Smith D, et al.: Understanding vaccine hesitancy around vaccines and vaccination from a global perspective: A systematic review of published literature, 2007–2012. Vaccine. 2014; 32 (19): 2150-2159 Publisher Full TextCompeting Interests: Currently have funding to study vaccine hesitancy for dengue vaccines in Peru, where our research touched on hesitancy for COVID-19 vaccination as well.
Reviewer Expertise: Dengue epidemiology; arbovirus epidemiology; systematic review
Alongside their report, reviewers assign a status to the article:
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