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Article

COVID-19 Vaccine Booster Hesitancy (VBH) and Its Drivers in Algeria: National Cross-Sectional Survey-Based Study

by
Mohamed Lounis
1,*,
Djihad Bencherit
2,
Mohammed Amir Rais
3 and
Abanoub Riad
4
1
Department of Agro-Veterinary Science, Faculty of Natural and Life Sciences, University of Ziane Achour, Djelfa 17000, Algeria
2
Department of Biology, Faculty of Natural and Life Sciences, University of Ziane Achour, Djelfa 17000, Algeria
3
Department of Dentistry, Faculty of Medicine, University of Algiers Benyoucef Benkhedda, Algiers 16000, Algeria
4
Department of Public Health, Faculty of Medicine, Masaryk University, 625 00 Brno, Czech Republic
*
Author to whom correspondence should be addressed.
Vaccines 2022, 10(4), 621; https://doi.org/10.3390/vaccines10040621
Submission received: 1 April 2022 / Revised: 12 April 2022 / Accepted: 13 April 2022 / Published: 15 April 2022
(This article belongs to the Collection COVID-19 Vaccine Hesitancy: Correlates and Interventions)
Review Reports Versions Notes

Abstract

:
Due to the emergence of various highly contagious variants of SARS-CoV-2, vaccine boosters were adopted as a complementary strategy in different countries. This strategy has, however, posed another challenge for the national authorities to convince their population to receive the booster after the first challenge of COVID-19 primer dose vaccines. This study was conducted to determine COVID-19 vaccine booster acceptance and its associated factors in the general population in Algeria. Using social media platforms, an online self-administered questionnaire was distributed between 28 January and 5 March 2022 for all Algerian citizens who received COVID-19 vaccines. Overall, 787 respondents were included in this study. Among them, 51.6%, 25%, and 23.8% accepted, rejected, or were hesitant about the COVID-19 vaccine booster, respectively. However, only 13.2% declared receiving the booster dose. Additionally, while 58.2% of the respondents declared being relieved after primer vaccination, 11.4% among them declared that they regretted being vaccinated. The most common reasons for acceptance were experts’ recommendations (24.6%) and the belief that COVID-19 vaccine boosters were necessary and efficient, while rejection was mainly due to the belief that primer doses are sufficient (15.5%), or that vaccination in general is inefficient (8%). Males, older individuals, those with chronic comorbidities or a history of COVID-19 infection, non-healthcare workers, and those with low educational levels were associated with significantly higher odds for booster acceptance. Moreover, belief that booster doses were necessary and efficient, disagreeing with the notion that primer doses were not sufficient, experts’ recommendations, and the desire to travel abroad were significantly associated with higher odds of COVID-19 vaccine booster acceptance.

1. Introduction

The world is still in battle against the coronavirus disease (COVID-19) pandemic since its start two years ago, with a heavy balance of four hundred and seventy-six million cases and more than six million deaths [1].
After trying multiple non-pharmaceutical measures including border closure, social distancing measures and containments, which achieved a relative slowing of the SARS-CoV-2 dissemination, countries and international health authorities realized that these measures were not sufficient to completely control the disease [2,3]. Later, they opted for another strategy known as “herd immunity or population immunity” [4]. This approach refers to the indirect protection from an infectious disease occurring after immunization of a large portion of a community either through vaccination or immunity developed through previous infection. It will limit the spread of the disease, and consequently, the whole community becomes protected—not just those who are immune [5]. The best approach to achieve “herd immunity” recommended by the World Health Organization (WHO) is to protect people by vaccination [6].
The proportion of the population that must be vaccinated to achieve herd immunity with vaccination is not well-defined. It will vary according to multiple factors such as the community, the vaccine and the population prioritized for vaccination. A study by Anderson et al., 2020 showed that herd immunity could be achieved with 75–90% vaccination coverage for 100% vaccine efficacy with long-term protection and the entire population for lower efficacies [7].
Since the emergency authorization of some COVID-19 vaccines in December 2020, ten vaccines are currently approved by the WHO, and 33 COVID-19 vaccines are approved by at least one country [8].
Despite misinformation and conspiracy theories surrounding COVID-19 vaccines that have highly influenced vaccine uptake, more than 10.16 billion doses have been administered worldwide [9]. In addition, after high rates of vaccine hesitancy reported in the first months in different countries, results obtained in the last months demonstrated that people’s attitudes trended more frequently toward vaccine acceptance [10,11,12,13,14,15,16].
However, the emergence of different variants of SARS-CoV-2 and the relative decreases in vaccine efficacy against them have created a real dilemma. While many countries have opted for the administration of a vaccine booster to increase the protection of vaccinated people, this strategy did not gain a real consensus among scientists [17].
Consequently, this strategy is again faced with the challenge of vaccine booster hesitancy or rejection. For instance, results obtained in developed countries are encouraging, with rates of willingness to receive vaccine boosters varying from 61.8% to 95.5% in the USA, Poland, Czech Republic, Germany, Japan, China and Denmark [18,19,20,21,22,23,24,25,26].
Data from low- and lower-middle-income countries are, however, scarce. Algeria is one of these countries. It is the eleventh most affected African country with a total of 265,694 infections and 6419 deaths [1]. Based mainly on four COVID-19 vaccines including Sputnik V, AstraZeneca, Sinopharm and Sinovac vaccines, the vaccination campaign in the country was initiated in January 2021 [8]. However, this campaign was characterized by a high rate of vaccine hesitancy, as confirmed by either vaccination statistics (only 13.7% are fully vaccinated) [9] and published studies [27,28,29,30,31]. Regarding the COVID-19 vaccine booster, the current data show that 490,676 (1.1% of the vaccinated population) persons have received it since its start in November 2021 [32]. Therefore, the present work was conducted to evaluate vaccine booster hesitancy and acceptance in Algeria’s vaccinated population and to determine the associated demographic, anamnestic and psychosocial factors.

2. Materials and Methods

2.1. Design

A descriptive cross-sectional survey-based study was carried out between 28 January and 5 March 2022 in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cross-sectional studies [33]. To collect data from the target population, the study utilized a self-administered questionnaire (SAQ) that was developed and disseminated online through Google Forms (Google LLC, Menlo Park, CA, USA, 2021).

2.2. Population

The target population of this study was the adult population in Algeria, from which participants were recruited using a non-random sampling technique through snowballing recruitment. The eligibility criteria included: (i) being an Algerian national at least 18 years old, (ii) capacity to communicate in Arabic or French, and (iii) being previously vaccinated against SARS-CoV-2. Potential participants were invited to access the digital SAQ through either a uniform resource locator (URL) or a quick response (QR) code. Using social media platforms, participants were invited to complete the questionnaire voluntarily without any incentives.
The minimum sample size was computed using Epi-InfoTM version 7.2.4 (CDC. Atlanta, GA, USA, 2020), with the following assumptions: confidence level 95%, expected COVID-19 vaccine booster acceptance 50%, error margin 4%, and postulated proportion of invalid responses generated by careless/insufficient effort (C/IE) 10% [34]. The pragmatic sample size for this study was 660 responses.
Participation in this study was not incentivized by any means of reward, and participants’ interest in taking part was not coerced by any means or threat. Participants’ identities were kept anonymous to control for the Hawthorne effect and information bias.
A total of 790 responses were initially received, out of which three responses were excluded due to a lack of information about their attitudes towards COVID-19 vaccine booster doses.

2.3. Instrument

The SAQ used in this study was developed based on previous literature about COVID-19 vaccine booster hesitancy [18,19,20,21,22]. It had twenty-seven items that were predominantly close-ended and stratified into four sections: (i) demographic characteristics including sex, age group, profession, educational level, and region, (ii) medical anamnesis including chronic illnesses and influenza vaccine, (iii) COVID-19-related anamnesis including previous infection, onset, severity, vaccine type, and post-vaccination relief, regret, and preventive measures, and (iv) attitudes towards COVID-19 vaccine booster doses and promoters of and barriers to their acceptance.
The dependent variable was the willingness to receive COVID-19 vaccine booster doses stratified into three levels (rejection, hesitancy, acceptance). The independent variables included demographic and anamnestic characteristics and psychological perceptions. Content validity of the instrument was reviewed by a panel of experts who verified its content and provided guiding comments that helped develop the final version. The digital SAQ was provided in bilingual format (Arabic and French).

2.4. Ethics

The study protocol was reviewed and approved by the Scientific Committee of the Faculty of Natural and Life Sciences, the University of Djelfa, on 25 January 2022. All participants provided their informed consent digitally prior to their participation, and they were allowed to withdraw from the study at any moment without the need to justify their decision. The Declaration of Helsinki for research involving human subjects and the general data protection regulation (GDPR) were followed during the design and implementation of this study [35,36]. No identifying personal information was collected from the participants; therefore, retrospective identification of the participants was not possible.

2.5. Analyses

The Statistical Package for the Social Sciences (SPSS) version 28.0 (SPSS Inc. Chicago, IL, USA, 2021) and the R-based open software Jamovi were used to perform all statistical analyses [37,38]. Initially, descriptive statistics were performed to present the qualitative variables using frequencies (n) and percentages (%). Inferential statistics were performed using the Chi-squared test (χ2), Fisher’s exact test for <5 cases, and binary logistic regression to test the association between independent and dependent variables. Subsequently, multivariate logistic regression was performed to compute the adjusted odds ratio (AOR) of various psychosocial factors for COVID-19 vaccine booster dose acceptance. All analytical tests were performed following the assumptions of a confidence level of 95% and significance level of <0.05.

3. Results

3.1. Demographic Characteristics

Out of the 787 included participants, 61.6% were females, and 61.2% were non-healthcare professionals. Females were significantly (p < 0.001) more represented in the healthcare professionals’ group (70.2%) than in the non-healthcare professionals’ group (56.2%). The most represented age group was 31–40 years old (31.3%), followed by 18–30 years old (26.9%) and 41–50 years old (24.4%). Most participants were married (61.1%) without a statistically significant difference (p = 0.590) between healthcare professionals (62.3%) and non-healthcare professionals (60.4%). The vast majority were living in urban areas (91.2%) without a statistically significant difference (p = 0.478) between healthcare professionals (92.1%) and non-healthcare professionals (90.7%). Only 8.1% of the participants had a college or school level of education, which was more common among non-healthcare professionals (10.4%) than healthcare professionals (4.6%). Less than half (48.2%) of the sample reported having postgraduate degrees (Master’s or above), which were more common among healthcare professionals (55.7%) than non-healthcare professionals (43.4%) (Table 1).

3.2. Anamnestic Characteristics

On evaluating their medical anamnesis, 27.8% of the participants reported having at least one chronic illness without a statistically significant difference (p = 0.983) between healthcare professionals (27.9%) and non-healthcare professionals (27.8%). The most commonly reported disease was chronic hypertension (8.9%), followed by diabetes mellitus (8%) and respiratory diseases (5.6%). Less than one quarter (24.3%) of the participants reported receiving the influenza vaccine recently without a statistically significant difference (p = 0.089) between healthcare professionals (27.5%) and non-healthcare professionals (22.2%) (Table 2).
On evaluating their COVID-19-related anamnesis, less than two-thirds (65.3%) of the sample reported being previously infected by SARS-CoV-2, with healthcare professionals (75.1%) being significantly (p < 0.001) more frequently infected than non-healthcare professionals (59.1%). More than half (51.4%) of those previously infected were infected before receiving the first vaccine dose, followed by 39% infected after the second dose. Only 2.5% were infected after the third dose, and 4.5% reported hospitalization due to SARS-CoV-2 infection. While the vast majority (90.6%) reported having at least one COVID-19 infection among their family, 41.9% reported that one of their family members passed away due to COVID-19 (Table 3).
On evaluating their COVID-19 vaccine-related anamnesis, the most commonly administered vaccine type was Sinovac (66.1%), followed by AstraZeneca-Oxford (12.6%) and Sputnik V (10.2%). The least common vaccine was Pfizer-BioNTech, which was received by only 4 participants, representing 0.5% of the sample. While inactivated virus vaccines were more common among non-healthcare professionals (77.8%) than healthcare professionals (65.9%), adenoviral vector vaccines were significantly more common among healthcare professionals (33.4%) than non-healthcare professionals (21.8%) (p < 0.001). Most participants reported following preventive measures even after being vaccinated (88.8%).
While 58.2% of the participants felt relieved after vaccination, only 11.4% regretted being vaccinated. The most common reason for regretting vaccination was being infected after receiving the COVID-19 vaccine (breakthrough infection) (6.9%), followed by the belief that vaccines are inefficient (6.7%) and being burdened by post-vaccination side effects (3%). Only 13.2% of the participants reported receiving the third dose by the time they responded to the questionnaire, and the most commonly administered vaccine type for booster doses was Sinovac (48%), followed by Janssen (15.2%) and AstraZeneca-Oxford (12.8%) (Table 4).

3.3. COVID-19 Vaccine Booster-Related Attitudes

Overall, more than half (51.6%) of the participants indicated their acceptance to receive COVID-19 vaccine booster doses, while one quarter (25%) rejected booster doses, and 23.4% were hesitant. Healthcare professionals were significantly (p = 0.011) less inclined to accept (45.9%) booster doses than non-healthcare professionals (55.2%).
The most common reason for acceptance was experts’ recommendation (24.6%), which was more common for non-healthcare professionals (29.3%) than healthcare professionals (17%), followed by the belief that COVID-19 vaccine boosters were necessary and efficient (23.4%). The most preferred COVID-19 vaccine type was Sinovac (33.3%), followed by Janssen (12.6%), AstraZeneca-Oxford (11.8%), and Pfizer-BioNTech (9.6%). The most common reason for rejection was the belief that primer doses are sufficient (15.5%), followed by the belief that vaccination, in general, is inefficient (8%), the belief that vaccines could impact the immune system adversely (6.5%), and the fear of post-vaccination side effects (5%) (Table 5).

3.4. Promoters of and Barriers to COVID-19 Vaccine Booster Acceptance

Male participants had a significantly (p < 0.001) higher acceptance level (59.9%) than females (46.4%). Similarly, the older age groups, i.e., those aged >60 years and between 51–60 years, had significantly (p < 0.001 and = 0.002) higher acceptance levels (71.8% and 66.3%) than the group aged 18–30 years (43.9%), respectively. There were no statistically significant differences between single (49.3%) versus married (53%) participants and urban (51.3%) versus rural residents (55.1%) in terms of COVID-19 vaccine booster dose acceptance. Individuals with low educational levels (college or school) had the highest acceptance level (71.9%) compared with bachelor’s degree holders (47.1%) and postgraduate degree holders (52.2%) (Table 6).

3.5. Regression Analyses

Primarily, binary logistic regression was performed to evaluate the odds ratios (OR) of demographic and anamnestic factors for COVID-19 vaccine booster acceptance based on significant results from the previous analyses. Males (OR: 1.729; CI 95%: 1.292–2.313), the age group of >60 years old (OR: 3.257; CI 95%: 1.541–6.884), and those suffering from chronic illness (OR: 1.394; CI 95%: 1.018–1.908) had significantly higher odds for COVID-19 vaccine booster acceptance. The highest odds ratio for acceptance was among those who felt post-vaccination relief (OR: 8.120; CI 95%: 4.892–13.479). Contrarily, healthcare professionals (OR: 0.689; CI 95%: 0.517–0.919) and those with postgraduate degrees (OR: 0.428; CI 95%: 0.239–0.765) had lower odds of acceptance (Table 7).
Subsequently, multivariable logistic regression analysis adjusted for sex, age group, educational level, profession, chronic illness, previous COVID-19 infection, post-vaccination relief and regret was performed to estimate the adjusted odds ratio (AOR) of COVID-19 vaccine acceptance. The highest AOR was among those participants who believed that booster doses were necessary and efficient (AOR: 28.112; CI 95%: 13.235–59.709), followed by disagreement with the notion that primer doses were not sufficient (AOR: 23.641; CI 95%: 11.087–50.409), and having no breakthrough infections (AOR: 6.870; CI 95%: 0.783–60.248). Fear of side effects was not statistically significant, as well as breakthrough infections. Experts’ recommendations (AOR: 4.801; CI 95%: 3.116–7.398) and the desire to travel abroad (AOR: 1.804; CI 95%: 1.136–2.863) were significant promoters of COVID-19 vaccine booster acceptance (Table 8).

4. Discussion

The main objective of this study was to determine the attitudes and associated factors related to COVID-19 vaccine booster acceptance and hesitancy among the general public in Algeria. To the best of the authors’ knowledge, this is the first study regarding the COVID-19 vaccine booster in Algeria. In this way, after the challenge of convincing the Algerian public to receive the COVID-19 vaccine when vaccine acceptance did not exceed 51.1% [31], the new task for the Algerian health authorities has been to encourage vaccinated individuals to receive the vaccine booster after it became available in November 2021.
The results of our study revealed that 51.6% of all respondents were in favor of the COVID-19 vaccine booster, while 25% rejected it. Moreover, only 13.2% of all respondents declared that they had received the COVID-19 vaccine booster. However, this rate is higher than the current rate in Algeria, estimated at 1% (436,274 administered doses) [32]. The rate of acceptance identified in this study is not far from the reported rate of 55% in Saudi Arabia [39] but higher than the reported rate in Jordan (39%) [40]. Globally, vaccine booster acceptance is generally higher in developed countries. Some available data showed rates of 79.1% and 83.6% among adults and healthcare workers (HCWs) in the United States [18,19], 67.4% and 71% in Poland [20,41], 71.3% among HCWs in Czechia [21], 84.5% among medical students in Japan [23], 85.7% in the university community in Italy [42], 84.8% and 93.7% among the general population in China [25,43], 87.8% among university academics and students in Germany, and 95.5% among the adult Danish population [26].
The most common reasons for acceptance in this study were experts’ recommendations (24.6%), followed by the belief that COVID-19 vaccine boosters were necessary and efficient (23.4%), while the most common causes for rejection were the belief that primer doses were sufficient (15.5%), the belief that vaccination—in general—is inefficient (8%) or could impact immune system (6.5%), and the fear of post-vaccination side effects (5%). In this way, previous studies reported that one of the most common causes of vaccine booster rejection was the presence of side effects after the primer doses [41]. In the same direction, post-vaccination relief greatly increased the odds of acceptance of vaccine boosters (OR: 8.120; CI 95%: 4.892–13.479).
It is known that elderly people are one of the prioritized categories for COVID-19 vaccine boosters [44]. Fortunately, in our study, aged persons were more likely to accept vaccine boosters than younger ones (OR: 3.257; CI 95%: 1.541–6.884). The same results were also obtained for individuals with chronic diseases (OR: 1.394; CI 95%: 1.018–1.908) which is in accordance with the results of previous studies reporting that prioritized groups were more likely to accept vaccine boosters [20,43,45]. These results could be very helpful for health authorities, given the high risk of COVID-19 infection in these categories. Moreover, previous infection with COVID-19 was associated with higher odds of acceptance of a vaccine booster than among those who were not in contact with this disease in this study.
The surprising result for the prioritized groups is, however, in relation with healthcare workers’ attitudes. In fact, healthcare workers had lower odds of acceptance of a vaccine booster dose than the general population (OR: 0.689; CI 95%: 0.517–0.919). Hence, hesitancy among healthcare workers could have a negative effect for the general public, given their role as the main sources of medical information for the general population. This point should be explored to better understand the reasons for vaccine booster hesitancy among members of this category. Globally, the healthcare profession was generally associated with high acceptance of either primers or booster doses of COVID-19 vaccine [18,21,41,43]. In a previous study of COVID-9 vaccine acceptance (primer doses) in Algeria, healthcare workers were more likely to accept this vaccine than non-health workers [31].
Similarly, our results showed that the higher the educational level, the lower the acceptance rate. In fact, individuals with university level (OR: 0.348; CI 95%: 0.194–0.625) and postgraduate degrees (OR: 0.428; CI 95%: 0.239–0.765) had lower odds of acceptance than those with a college/school level education. These results did not agree with previously published studies in different countries.
For gender, the question seems to become increasingly clear with males being more in favor of vaccines in general than females. As in our results (OR: 1.729; CI 95%: 1.292–2.313), male acceptance was previously confirmed for COVID-19 vaccines primers [12,28,46] and booster doses [19,47,48]. The most reported explanations of these low rates of acceptance among females are related to their psychological and hormonal characteristics [20].
Apart from these socio-demographic and anamnestic factors, we also assessed the influence of behavioral and psychological factors on vaccine acceptance. Results showed that the belief that booster doses were necessary and efficient (AOR: 28.112; CI 95%: 13.235–59.709), and the disagreement with the notion that primer doses were not sufficient (AOR: 23.641; CI 95%: 11.087–50.409) were highly associated with booster acceptance. Other promoters of COVID-19 vaccine booster acceptance included experts and scientists’ recommendations (AOR: 4.801; CI 95%: 3.116–7.398) and the desire to travel (AOR: 1.804; CI 95%: 1.136–2.863), while fear of side effects and breakthrough infections were not statistically associated with COVID-19 booster acceptance. These findings join results of previous studies that suggested that confidence in vaccine safety and effectiveness and trust in pharmaceutical companies would enhance vaccine acceptance rates and thus help to increase the number of vaccinated people [47,48,49]. These observations indicate the important role of public health education in increasing public vaccine acceptance.
In the population study, the most commonly administered vaccine type was Sinovac (66.1%), followed by AstraZeneca (12.6%) and Sputnik V (10.2%). However, none of the vaccine types or technologies affected attitudes toward booster doses. Booster preference closely mirrored that for the Sinovac (33.3%), Janssen (12.6%), AstraZeneca (11.8%), Pfizer-BioNTech (9.6%) and Sputnik V (7.1%) vaccines. These findings showed that vaccinated people are more likely to prefer a booster dose from the same vaccine. However, as reported by Rzymski et al., 2021 [20] and Alhasan et al., 2021 [39], vaccinated individuals do not necessarily prefer the same vaccine that they received in the primer doses. In the same way, the last authors reported that persons who believe that combining different vaccines is effective against variants are significantly more likely to accept a vaccine booster. The preference for inactivated vaccines could be related to the conventional production method and their lower side effects compared to the other vaccines, as confirmed in previous studies. Additionally, preferences for the other vaccines, such as those from Janssen, AstraZeneca-Oxford, and Pfizer-BioNTech, could be mainly related to trust in the manufacturing company.

4.1. Limitations

This study had some limitations related essentially to the sampling method. We used a non-random sampling technique through snowballing recruitment on a generated selection basis, which could affect the generalization of the results to the entire Algerian population. The online survey method used in this study could have excluded people with no access to the internet and those who could not read or write. Younger persons who spend more time with social media were more likely to be covered than other groups. The cross-sectional nature of this study could only provide a snapshot of acceptance and/or hesitancy, which could change through time. Additionally, booster dose acceptance and hesitancy were assessed by self-reporting, and we did not use a scale standard of acceptance and hesitancy. Furthermore, the survey did not include information about side effects of primer doses of COVID-19 vaccines. Finally, the response rate could not be calculated due to the impossibility of determining the total number of people reached by the survey.

4.2. Strengths

This is the first study of the general population’s attitudes toward the COVID-19 vaccine booster and factors associated with its acceptance in Algeria. Limited data are available in developing countries on this question. The study was conducted using an online survey that allowed the respondents to complete the questionnaire in a private environment, thus reducing some social and interviewer biases. In addition, though not representative, the sample covered almost all Algerian sectors and categories related to the socio-demographic and anamnestic characteristics of the population (age, sex, marital status, residence, chronic illnesses, COVID-19 infection, etc.).
The results of this study could be helpful for health authorities in their campaign to promote COVID-19 booster awareness and uptake. These results could be of great importance for African and other developing countries where vaccine hesitancy was generally reported at high levels. They could be a key in understanding this phenomenon and contribute to its mapping around the world.

5. Conclusions

In conclusion, this study reported for the first time the attitudes of the Algerian public toward the COVID-19 vaccine booster. A medium rate of booster acceptance was obtained, which remains lower than those reported in developed countries.
The study identified specific groups with the highest rates of booster acceptance (males, persons over the age of 60 years, and those suffering from chronic diseases) and hesitancy (healthcare professionals and postgraduate students). It also described that vaccine booster acceptance is mainly related to certain psychological factors related to vaccine effectiveness and safety. Taking these factors into consideration could be helpful for the national authorities in their effort to convince the general population of the importance of the COVID-19 vaccine booster in the battle against COVID-19.

Author Contributions

Conceptualization, M.L.; methodology, M.L.; software, A.R.; validation, M.L.; formal analysis, A.R.; investigation, M.L.; resources, M.L.; data curation, M.L., D.B. and M.A.R.; writing—original draft preparation, M.L. and A.R.; writing—review and editing, M.L. and A.R.; visualization, M.L. and A.R.; supervision, A.R.; project administration, M.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Scientific Committee of the Faculty of Natural and Life Sciences, University Ziane Achour, Djelfa (Ref: 73/25/01/2022).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. World Health Organization (WHO). Coronavirus (COVID-19) Dashboard. Available online: https://covid19.who.int/ (accessed on 23 March 2022).
  2. Lazarus, J.V.; Ratzan, S.; Palayew, A.; Billari, F.C.; Binagwaho, A.; Kimball, S.; Larson, H.J.; Melegaro, A.; Rabin, K.; White, T.M.; et al. COVID-SCORE: A global survey to assess public perceptions of government responses to COVID-19 (COVID-SCORE-10). PLoS ONE 2020, 15, e0240011. [Google Scholar] [CrossRef] [PubMed]
  3. Alqudeimat, Y.; Alenezi, D.; AlHajri, B.; Alfouzan, H.; Almokhaizeem, Z.; Altamimi, S.; Almansouri, W.; Alzalzalah, S.; Ziyab, A.H. Acceptance of a COVID-19 Vaccine and Its Related Determinants among the General Adult Population in Kuwait. Med. Princ. Pr. 2021, 30, 262–271. [Google Scholar] [CrossRef] [PubMed]
  4. Burki, T.K. Herd immunity for COVID-19. Lancet Respir. Med. 2021, 9, 135–136. [Google Scholar] [CrossRef]
  5. Randolph, H.E.; Barreiro, L.B. Herd Immunity: Understanding COVID-19. Immunity 2020, 52, 737–741. [Google Scholar] [CrossRef]
  6. World Health Organization (WHO). Coronavirus Disease (COVID-19): Herd Immunity, Lockdowns and COVID-19. 2020. Available online: https://www.who.int/news-room/questions-and-answers/item/herd-immunity-lockdowns-and-covid-19 (accessed on 26 March 2022).
  7. Anderson, R.M.; Vegvari, C.; Truscott, J.; Collyer, B.S. Challenges in creating herd immunity to SARS-CoV-2 infection by mass vaccination. Lancet 2020, 396, 1614–1616. [Google Scholar] [CrossRef]
  8. World Health Organization. COVID-19 Vaccine Tracker. Available online: https://covid19.trackvaccines.org/agency/who/ (accessed on 21 November 2021).
  9. Ourworlindata. 2022. Available online: https://ourworldindata.org/covid-vaccinations (accessed on 23 March 2022).
  10. Riad, A.; Pokorná, A.; Antalová, N.; Krobot, M.; Zviadadze, N.; Serdiuk, I.; Koščík, M.; Klugar, M. Prevalence and drivers of COVID-19 vaccine hesitancy among Czech university students: National cross-sectional study. Vaccines 2021, 9, 948. [Google Scholar] [CrossRef]
  11. Riad, A.; Jouzová, A.; Üstün, B.; Lagová, E.; Hruban, L.; Janků, P.; Pokorná, A.; Klugarová, J.; Koščík, M.; Klugar, M. COVID-19 Vaccine Acceptance of Pregnant and Lactating Women (PLW) in Czechia: An Analytical Cross-Sectional Study. Int. J. Environ. Res. Public Health 2021, 18, 13373. [Google Scholar] [CrossRef]
  12. Kateeb, E.; Danadneh, M.; Pokorná, A.; Klugarová, J.; Abdulqader, H.; Klugar, M.; Riad, A. Predictors of Willingness to Receive COVID-19 Vaccine: Cross-Sectional Study of Palestinian Dental Students. Vaccines 2021, 9, 954. [Google Scholar] [CrossRef]
  13. Nguyen, L.H.; Joshi, A.D.; Drew, D.A.; Merino, J.; Ma, W.; Lo, C.-H.; Kwon, S.; Wang, K.; Graham, M.S.; Polidori, L.; et al. Self-reported COVID-19 vaccine hesitancy and uptake among participants from different racial and ethnic groups in the United States and United Kingdom. Nat. Commun. 2022, 13, 636. [Google Scholar] [CrossRef]
  14. Wagner, A.L.; Huang, Z.; Ren, J.; Laffoon, M.; Ji, M.; Pinckney, L.C.; Sun, X.; Prosser, L.A.; Boulton, M.L.; Zikmund-Fisher, B.J. Vaccine hesitancy and concerns about vaccine safety and effectiveness in Shanghai, China. Am. J. Prev. Med. 2021, 60, S77–S86. [Google Scholar] [CrossRef]
  15. Hulen, E.; Rynerson, A.L.; Dobscha, S.K. Vaccine hesitancy among Veterans Affairs Health Care System employees. Prev. Med. Rep. 2022, 26, 101702. [Google Scholar] [CrossRef]
  16. Strupat, C.; Shigute, Z.; Bedi, A.S.; Rieger, M. Willingness to take COVID-19 vaccination in low-income countries: Evidence from Ethiopia. PLoS ONE 2022, 17, e0264633. [Google Scholar] [CrossRef]
  17. Dolgin, E. Omicron is supercharging the COVID vaccine booster debate. Nature 2021, 10. [Google Scholar] [CrossRef]
  18. Pal, S.; Shekhar, R.; Kottewar, S.; Upadhyay, S.; Singh, M.; Pathak, D.; Kapuria, D.; Barrett, E.; Sheikh, A.B. COVID-19 Vaccine Hesitancy and Attitude toward Booster Doses among US Healthcare Workers. Vaccines 2021, 9, 1358. [Google Scholar] [CrossRef]
  19. Yadete, T.; Batra, K.; Netski, D.M.; Antonio, S.; Patros, M.J.; Bester, J.C. Assessing acceptability of COVID-19 vaccine booster dose among adult Americans: A cross-sectional study. Vaccines 2021, 9, 1424. [Google Scholar] [CrossRef]
  20. Rzymski, P.; Poniedziałek, B.; Fal, A. Willingness to receive the booster COVID-19 vaccine dose in Poland. Vaccines 2021, 9, 1286. [Google Scholar] [CrossRef]
  21. Klugar, M.; Riad, A.; Mohanan, L.; Pokorná, A. COVID-19 vaccine booster hesitancy (VBH) of healthcare workers in Czechia: National cross-sectional study. Vaccines 2021, 9, 1437. [Google Scholar] [CrossRef]
  22. Attia, S.; Mausbach, K.; Klugar, M.; Howaldt, H.-P.; Riad, A. Prevalence and Drivers of COVID-19 Vaccine Booster Hesitancy Among German University Students and Employees. Front. Public Health 2022, 10, 706. [Google Scholar] [CrossRef]
  23. Sugawara, N.; Yasui-Furukori, N.; Fukushima, A.; Shimoda, K. Attitudes of Medical Students toward COVID-19 Vaccination: Who Is Willing to Receive a Third Dose of the Vaccine? Vaccines 2021, 9, 1295. [Google Scholar] [CrossRef]
  24. Tung, T.-H.; Lin, X.-Q.; Chen, Y.; Zhang, M.-X.; Zhu, J.-S. Willingness to receive a booster dose of inactivated coronavirus disease 2019 vaccine in Taizhou, China. Expert Rev. Vaccines 2021, 21, 261–267. [Google Scholar] [CrossRef]
  25. Qin, C.; Wang, R.; Tao, L.; Liu, M.; Liu, J. Acceptance of a Third Dose of COVID-19 Vaccine and Associated Factors in China Based on Health Belief Model: A National Cross-Sectional Study. Vaccines 2022, 10, 89. [Google Scholar] [CrossRef] [PubMed]
  26. Jørgensen, F.J.; Nielsen, L.H.; Petersen, M.B. Willingness to Take the Booster Vaccine in a Nationally Representative Sample of Danes. Vaccines 2022, 10, 425. [Google Scholar] [CrossRef] [PubMed]
  27. Kacimi, S.E.O.; Klouche-Djedid, S.N.; Riffi, O.; Belaouni, H.A.; Yasmine, F.; Taouza, F.A.; Belakhdar, Y.; Fellah, S.C.; Benmelouka, A.Y.; Ahmed, S.; et al. Determinants of SARS-CoV-2 Vaccine Engagement in Algeria: A Population-based Study with Systematic Review of Studies from Arab Countries of the MENA Region. medRxiv 2021. [Google Scholar] [CrossRef]
  28. Kaadan, M.I.; Abdulkarim, J.; Chaar, M.; Zayegh, O.; Keblawi, M.A. Determinants of COVID-19 vaccine acceptance in the Arab world: A cross-sectional study. Glob. Health Res. Policy 2021, 6, 23. [Google Scholar] [CrossRef] [PubMed]
  29. Qunaibi, E.; Basheti, I.; Soudy, M.; Sultan, I. Hesitancy of Arab Healthcare Workers towards COVID-19 Vaccination: A Large-Scale Multinational Study. Vaccines 2021, 9, 446. [Google Scholar] [CrossRef] [PubMed]
  30. Kerdoun, M.A.; Henni, A.H.; Yamoun, A.; Rahmani, A.; Kerdoun, R.M.; Elouar, N. COVID-19 vaccine hesitancy among Algerian medical students: A cross-sectional study in five universities. medRxiv 2021. [Google Scholar] [CrossRef]
  31. Lounis, M.; Abdehadi, S.; Rais, M.A.; Bencherit, D.; Sallam, M. Intention to get COVID-19 vaccination and its associated predictors: A cross-sectional study among the general public in Algeria. Vacunas (accepted). 2022. [Google Scholar]
  32. Ourworlindata. Coronavirus (COVID-19) Vaccinations. 2022. Available online: https://ourworldindata.org/grapher/cumulative-covid-vaccine-booster-doses?country=~DZA (accessed on 23 March 2022).
  33. von Elm, E.; Altman, D.G.; Egger, M.; Pocock, S.J.; Gotzsche, P.C.; Vandenbroucke, J.P. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for reporting observational studies. BMJ 2007, 335, 806–808. [Google Scholar] [CrossRef] [Green Version]
  34. Centers for Disease Control and Prevention (CDC). Epi InfoTM for Windows. 2020. Available online: https://www.cdc.gov/epiinfo/pc.html (accessed on 25 December 2020).
  35. World Medical Association. World Medical Association declaration of Helsinki: Ethical principles for medical research involving human subjects. JAMA J. Am. Med. Assoc. 2013, 310, 2191–2194. [Google Scholar] [CrossRef] [Green Version]
  36. Proton Technologies AG; General Data Protection Regulation (GDPR) Compliance Guidelines. HORIZON 2020-Project REP-791727-1. 2020. Available online: https://gdpr.eu/ (accessed on 1 May 2020).
  37. SPSS Inc. IBM SPSS Statistics 28. 2021. Available online: https://www.ibm.com/support/pages/ibm-spss-statistics-28-documentation (accessed on 14 March 2021).
  38. The Jamovi Project. Jamovi (Version 1.6) [Computer Software]. 2021. Available online: https://www.jamovi.org (accessed on 11 February 2022).
  39. Alhasan, K.; Aljamaan, F.; Temsah, M.-H.; Alshahrani, F.; Bassrawi, R.; Alhaboob, A.; Assiri, R.; Alenezi, S.; Alaraj, A.; Alhomoudi, R.I.; et al. COVID-19 Delta Variant: Perceptions, Worries, and Vaccine-Booster Acceptability among Healthcare Workers. Healthcare 2021, 9, 1566. [Google Scholar] [CrossRef]
  40. Al-Qerem, W.; Al Bawab, A.Q.; Hammad, A.; Ling, J.; Alasmari, F. Willingness of the Jordanian Population to Receive a COVID-19 Booster Dose: A Cross-Sectional Study. Vaccines 2022, 10, 410. [Google Scholar] [CrossRef]
  41. Babicki, M.; Mastalerz-Migas, A. Attitudes of Poles towards the COVID-19 Vaccine Booster Dose: An Online Survey in Poland. Vaccines 2022, 10, 68. [Google Scholar] [CrossRef]
  42. Folcarelli, L.; del Giudice, G.M.; Corea, F.; Angelillo, I.F. Intention to Receive the COVID-19 Vaccine Booster Dose in a University Community in Italy. Vaccines 2022, 10, 146. [Google Scholar] [CrossRef]
  43. Lai, X.; Zhu, H.; Wang, J.; Huang, Y.; Jing, R.; Lyu, Y.; Zhang, H.; Feng, H.; Guo, J.; Fang, H. Public Perceptions and Acceptance of COVID-19 Booster Vaccination in China: A Cross-Sectional Study. Vaccines 2021, 9, 1461. [Google Scholar] [CrossRef]
  44. World Health Organization. Strategic Advisory Group of Experts on Immunization SAGE. Available online: https://www.who.int/news/item/04-10-2021-interim-statement-on-booster-doses-for-covid-19-vaccination (accessed on 23 March 2022).
  45. Sønderskov, K.M.; Vistisen, H.T.; Dinesen, P.T.; Østergaard, S.D. A positive update on COVID-19 booster vaccine willingness among Danes. Dan. Med. J. 2022, 69, A01220047. [Google Scholar]
  46. Sallam, M.; Dababseh, D.; Eid, H.; Al-Mahzoum, K.; Al-Haidar, A.; Taim, D.; Yaseen, A.; Ababneh, N.A.; Bakri, F.G.; Mahafzah, A. High Rates of COVID-19 Vaccine Hesitancy and Its Association with Conspiracy Beliefs: A Study in Jordan and Kuwait among Other Arab Countries. Vaccines 2021, 9, 42. [Google Scholar] [CrossRef]
  47. Wang, X.; Liu, L.; Pei, M.; Li, X.; Li, N. Willingness of the General Public to Receive A COVID-19 Vaccine Booster—China, April–May 2021. China CDC Wkly. 2022, 4, 66–70. [Google Scholar] [CrossRef]
  48. Hu, T.; Li, L.; Lin, C.; Yang, Z.; Chow, C.; Lu, Z.; You, C. An Analysis of the Willingness to the COVID-19 Vaccine Booster Shots among Urban Employees: Evidence from a Megacity H in Eastern China. Int. J. Environ. Res. Public Health 2022, 19, 2300. [Google Scholar] [CrossRef]
  49. Al Janabi, T.; Pino, M. Predictors for Actual COVID-19 Vaccine Uptake and Intended Booster Dosage among Medical Students of an Osteopathic Medical School in New York. Epidemiologia 2021, 2, 553–563. [Google Scholar] [CrossRef]
Table
Table 1. Demographic Characteristics of Algerian Adults Participating in COVID-19 VBH Survey (n = 787).
Table 1. Demographic Characteristics of Algerian Adults Participating in COVID-19 VBH Survey (n = 787).
VariableOutcomeNon-Healthcare Professionals (n = 482)Healthcare Professionals (n = 305)Total
(n = 787)		Sig.
SexFemale271 (56.2%)214 (70.2%)485 (61.6%)<0.001
Male211 (43.8%)91 (29.8%)302 (38.4%)
Age Group18–30 years old127 (26.3%)85 (27.9%)212 (26.9%)0.640
31–40 years old139 (28.8%)107 (35.1%)246 (31.3%)0.066
41–50 years old125 (25.9%)67 (22.0%)192 (24.4%)0.207
51–60 years old65 (13.5%)33 (10.8%)98 (12.5%)0.270
>60 years old26 (5.4%)13 (4.3%)39 (5%)0.476
Marital StatusSingle191 (39.6%)115 (37.7%)306 (38.9%)0.590
Married291 (60.4%)190 (62.3%)481 (61.1%)
ResidenceUrban437 (90.7%)281 (92.1%)718 (91.2%)0.478
Rural45 (9.3%)24 (7.9%)69 (8.8%)
Educational LevelCollege/School50 (10.4%)14 (4.6%)64 (8.1%)0.004
Bachelor’s Degree223 (46.3%)121 (39.7%)344 (43.7%)0.069
Masters’ Degree or above209 (43.4%)170 (55.7%)379 (48.2%)<0.001
Chi-squared test (χ2) was used with a significance level Sig. < 0.05. Statistically significant differences are indicated with bold character.
Table
Table 2. Medical Anamnesis of Algerian Adults Participating in COVID-19 VBH Survey (n = 787).
Table 2. Medical Anamnesis of Algerian Adults Participating in COVID-19 VBH Survey (n = 787).
VariableOutcomeNon-Healthcare Professionals (n = 482)Healthcare Professionals (n = 305)Total
(n = 787)		Sig.
Chronic IllnessDiabetes Mellitus35 (7.3%)28 (9.2%)63 (8%)0.334
Chronic Hypertension39 (8.1%)31 (10.2%)70 (8.9%)0.320
Cardiovascular Disease8 (1.7%)7 (2.3%)15 (1.9%)0.525
Respiratory Disease29 (6%)15 (4.9%)44 (5.6%)0.513
Renal Disease2 (0.4%)2 (0.7%)4 (0.5%)0.643 *
Other62 (12.9%)34 (11.1%)96 (12.2%)0.474
Total134 (27.8%)85 (27.9%)219 (27.8%)0.983
Influenza
Vaccine		No375 (77.8%)221 (72.5%)596 (75.7%)0.089
Yes107 (22.2%)84 (27.5%)191 (24.3%)
Chi-squared test (χ2) and Fisher’s exact test (*) were used with a significance level Sig. < 0.05.
Table
Table 3. COVID-19 Infection-related Anamnesis of Algerian Adults Participating in COVID-19 VBH Survey (n = 787).
Table 3. COVID-19 Infection-related Anamnesis of Algerian Adults Participating in COVID-19 VBH Survey (n = 787).
VariableOutcomeNon-Healthcare Professionals (n = 482)Healthcare Professionals (n = 305)Total
(n = 787)		Sig.
COVID-19
Infection		No197 (40.9%)76 (24.9%)273 (34.7%)<0.001
Yes +285 (59.1%)229 (75.1%)514 (65.3%)
+ OnsetBefore 1st Dose142 (50%)120 (53.1%)262 (51.4%)0.487
Between 1st and 2nd Dose20 (7%)16 (7.1%)36 (7.1%)0.987
After 2nd Dose116 (40.8%)83 (36.7%)199 (39%)0.343
After 3rd Dose6 (2.1%)7 (3.1%)133(2.5%)0.483
+ HospitalizationNo271 (95.8%)216 (95.2%)487 (95.5%)0.743
Yes12 (4.2%)11 (4.8%)23 (4.5%)
Infection in FamilyNo53 (11%)21 (6.9%)74 (9.4%)0.054
Yes429 (89%)284 (93.1%)713 (90.6%)
Mortality in FamilyNo273 (56.6%)184 (60.3%)457 (58.1%)0.307
Yes209 (43.4%)121 (39.7%)330 (41.9%)
Chi-squared test (χ2) was used with a significance level Sig. < 0.05. Statistically significant differences are indicated with bold character. + Respondents being COVID-19 infected (Yes).
Table
Table 4. COVID-19 Vaccine-related Anamnesis of Algerian Adults Participating in COVID-19 VBH Survey (n = 787).
Table 4. COVID-19 Vaccine-related Anamnesis of Algerian Adults Participating in COVID-19 VBH Survey (n = 787).
VariableOutcomeNon-Healthcare Professionals (n = 482)Healthcare Professionals
(n = 305)		Total
(n = 787)		Sig.
Vaccine TypeSinovac334 (69.3%)186 (61%)520 (66.1%)0.016
Sinopharm27 (5.6%)15 (4.9%)42 (5.3%)0.678
AstraZeneca-Oxford66 (13.7%)33 (10.8%)99 (12.6%)0.236
Janssen8 (1.7%)16 (5.2%)24 (3%)0.004
Sputnik V27 (5.6%)53 (17.4%)80 (10.2%)<0.001
Pfizer-BioNTech2 (0.4%)2 (0.7%)4 (0.5%)0.643 *
I do not know18 (3.7%)0 (0%)18 (2.3%)<0.001
Vaccine TechnologyInactivated Virus361 (77.8%)201 (65.9%)562 (73.1%)<0.001
Adenoviral Vector101 (21.8%)102 (33.4%)203 (26.4%)<0.001
mRNA-based2 (0.4%)2 (0.7%)4 (0.5%)0.672
Relief after VaccinationAgree287 (59.5%)171 (56.1%)458 (58.2%)0.335
Unsure133 (27.6%)87 (28.5%)220 (28%)0.777
Disagree62 (12.9%)47 (15.4%)109 (13.9%)0.314
Prevention after VaccinationNo55 (11.5%)33 (10.8%)88 (11.2%)0.798
Yes427 (88.6%)272 (89.2%)699 (88.8%)
Regret after VaccinationDisagree385 (79.9%)232 (76.1%)617 (78.4%)0.206
Unsure47 (9.8%)33 (10.8%)80 (10.2%)0.629
Agree π50 (10.4%)40 (13.1%)90 (11.4%)0.239
π Reasons for RegretVaccines are not efficient27 (5.6%)26 (8.5%)53 (6.7%)0.111
Post-vaccination infection30 (6.2%)24 (7.9%)54 (6.9%)0.374
Post-vaccination side effects10 (2.1%)14 (4.6%)24 (3%)0.046
Did not choose best vaccine3 (0.6%)3 (1%)6 (0.8%)0.682 *
Disease became milder1 (0.2%)1 (0.3%)2 (0.3%)1.000 *
COVID-19 Vaccine BoosterNo420 (87.1%)263 (86.2%)683 (86.8%)0.714
Yes Ψ62 (12.9%)42 (13.8%)104 (13.2%)
Ψ Booster Dose TypeSinovac39 (50%)21 (44.7%)60 (48%)0.564
Sinopharm3 (3.8%)6 (12.8%)9 (7.2%)0.062
AstraZeneca-Oxford12 (15.4%)4 (8.5%)16 (12.8%)0.265
Janssen7 (9%)12 (25.5%)19 (15.2%)0.013
Sputnik V5 (6.4%)1 (2.1%)6 (4.8%)0.278
Pfizer-BioNTech2 (2.6%)3 (6.4%)5 (4%)0.291
I do not know10 (12.8%)0 (0%)10 (8%)0.010
Chi-squared test (χ2) and Fisher’s exact test (*) were used with a significance level Sig. < 0.05. Statistically significant differences are indicated with bold character. π Respondents who are willing to receive COVID-19 vaccine booster dose. Ψ Respondents who received COVID-19 vaccine booster dose.
Table
Table 5. COVID-19 Vaccine Booster-related Attitudes of Algerian Adults Participating in COVID-19 VBH Survey (n = 787).
Table 5. COVID-19 Vaccine Booster-related Attitudes of Algerian Adults Participating in COVID-19 VBH Survey (n = 787).
VariableOutcomeNon-Healthcare Professionals (n = 482)Healthcare Professionals (n = 305)Total
(n = 787)		Sig.
WillingnessRejection ‡95 (19.7%)102 (33.4%)197 (25%)<0.001
Hesitancy121 (25.1%)63 (20.7%)184 (23.4%)0.151
Acceptance +266 (55.2%)140 (45.9%)406 (51.6%)0.011
+ Reasons for AcceptanceThere is no alternative72 (15%)37 (12.1%)109 (13.9%)0.262
I want to travel abroad64 (13.3%)44 (14.4%)108 (13.7%)0.657
Experts recommend it141 (29.3%)52 (17%)193 (24.6%)<0.001
It is necessary and efficient119 (24.7%)65 (21.3%)184 (23.4%)0.269
+ Preferred Vaccine TypeSinovac93 (35%)42 (30%)135 (33.3%)0.313
Sinopharm5 (1.9%)3 (2.1%)8 (2%)1.000 *
AstraZeneca-Oxford31 (11.7%)17 (12.1%)48 (11.8%)0.885
Janssen21 (7.9%)30 (21.4%)51 (12.6%)<0.001
Sputnik V18 (6.8%)11 (7.9%)29 (7.1%)0.685
Pfizer-BioNTech28 (10.5%)11 (7.9%)39 (9.6%)0.386
Moderna6 (2.3%)3 (2.1%)9 (2.2%)1.000 *
No Preference23 (8.6%)7 (5%)30 (7.4%)0.182
‡ Reasons for RejectionPrimer doses are sufficient72 (14.9%)50 (16.4%)122 (15.5%)0.583
Fear of side effects18 (3.7%)21 (6.9%)39 (5%)0.047
Vaccination is inefficient36 (7.5%)27 (8.9%)63 (8%)0.486
It can harm immune system31 (6.4%)20 (6.6%)51 (6.5%)0.944
I had breakthrough infection2 (0.4%)4 (1.3%)6 (0.8%)0.214 *
Chi-squared test (χ2) and Fisher’s exact test (*) were used with a significance level Sig. < 0.05. Statistically significant differences are indicated with bold character. + Respondents who regret being vaccinated. ‡ Respondents who rejected the COVID-19 vaccine booster dose.
Table
Table 6. Demographic and Anamnestic Determinants of Vaccine Booster-related Attitudes among Algerian Adults Participating in COVID-19 VBH Survey (n = 787).
Table 6. Demographic and Anamnestic Determinants of Vaccine Booster-related Attitudes among Algerian Adults Participating in COVID-19 VBH Survey (n = 787).
VariableOutcomeRejection
(n = 197)		Sig.Hesitancy
(n = 184)		Sig.Acceptance
(n = 406)		Sig.
SexFemale138 (28.5%)0.005122 (25.2%)0.136225 (46.4%)<0.001
Male59 (19.5%)62 (20.5%)181 (59.9%)
Age Group18–30 years old64 (30.2%)0.04355 (25.9%)0.30293 (43.9%)0.008
31–40 years old66 (26.8%)0.43256 (22.8%)0.783124 (50.4%)0.655
41–50 years old45 (23.4%)0.55851 (26.6%)0.23196 (50%)0.613
51–60 years old19 (19.4%)0.16814 (14.3%)0.02365 (66.3%)0.002
>60 years old3 (7.7%)0.0108 (20.5%)0.66428 (71.8%)0.010
Marital StatusSingle76 (24.8%)0.92079 (25.8%)0.198151 (49.3%)0.315
Married121 (25.2%)105 (21.8%)255 (53%)
ResidenceUrban181 (25.2%)0.711169 (23.5%)0.736368 (51.3%)0.544
Rural16 (23.2%)15 (21.7%)38 (55.1%)
Educational LevelHigh School5 (7.8%)<0.00113 (20.3%)0.54546 (71.9%)<0.001
Bachelor’s Degree98 (28.5%)0.04984 (24.4%)0.544162 (47.1%)0.026
Masters’ Degree or above94 (24.8%)0.88687 (23%)0.786198 (52.2%)0.723
Chronic IllnessDiabetes Mellitus9 (14.3%)0.04014 (22.2%)0.82140 (63.5%)0.049
Chronic Hypertension19 (27.1%)0.6699 (12.9%)0.02942 (60%)0.140
Cardiovascular Disease6 (40%)0.225 *2 (13.3%)0.540 *7 (46.7%)0.700
Respiratory Disease10 (22.7%)0.7166 (13.6%)0.11628 (63.6%)0.100
Renal Disease1 (25%)1.000 *0 (0%)0.578 *3 (75%)0.625 *
Other28 (29.2%)0.31824 (25%)0.68944 (45.8%)0.229
Total49 (22.4%)0.28544 (20.1%)0.176126 (57.5%)0.038
Influenza
Vaccine		No153 (25.7%)0.465146 (24.5%)0.191297 (49.8%)0.082
Yes44 (23%)38 (19.9%)109 (57.1%)
COVID-19
Infection		No50 (18.3%)0.00269 (25.3%)0.360154 (56.4%)0.049
Yes +147 (28.6%)115 (22.4%)252 (49%)
+ OnsetBefore 1st Dose76 (29%)0.69062 (23.7%)0.536124 (47.3%)0.381
Between 1st and2nd Dose10 (27.8%)0.95012 (33.3%)0.10814 (38.9%)0.199
After 2nd Dose58 (29.1%)0.71541 (20.6%)0.400100 (50.3%)0.708
After 3rd Dose0 (0%)0.0220 (0%)0.047 *13 (100%)<0.001
+ HospitalizationNo141 (29%)0.767113 (23.2%)0.104233(47.8%)0.103
Yes6 (26.1%)2 (8.7%)15 (65.2%)
Infection in FamilyNo12 (16.2%)0.06613 (17.6%)0.21549 (66.2%)0.008
Yes185 (25.9%)171 (24%)357 (50.1%)
Mortality in FamilyNo115 (25.2%)0.920104 (22.8%)0.627238 (52.1%)0.746
Yes82 (24.8%)80 (24.2%)168 (50.9%)
Vaccine TypeSinovac137 (26.3%)0.235125 (24%)0.542258 (49.6%)0.122
Sinopharm9 (21.4%)0.5809 (21.4%)0.75924 (57.1%)0.459
AstraZeneca-Oxford22 (22.2%)0.49020 (20.2%)0.42457 (57.6%)0.202
Janssen10 (41.7%)0.0567 (29.2%)0.4967 (29.2%)0.026
Sputnik V15 (18.8%)0.17118 (22.5%)0.84447 (58.8%)0.176
Pfizer-BioNTech0 (0%)0.2470 (0%)0.578 *4 (100%)0.125
I do not know4 (22.2%)0.7815 (27.8%)0.585 *9 (50%)0.891
Vaccine TechnologyInactivated Virus146 (26%)0.353134 (23.8%)0.540282 (50.2%)0.186
Adenoviral Vector47 (23.2%)0.45645 (22.2%)0.663111 (54.7%)0.310
mRNA-based0 (0%)0.2460 (0%)0.578 *4 (100%)0.052
Relief after VaccinationAgree59 (12.9%)<0.00191 (19.9%)0.006308 (67.2%)<0.001
Unsure70 (31.8%)0.00674 (33.6%)<0.00176 (34.5%)<0.001
Disagree68 (62.4%)<0.00119 (17.4%)0.11422 (20.2%)<0.001
Prevention after VaccinationNo26 (29.5%)0.30021 (23.9%)0.90941 (46.6%)0.320
Yes171 (24.5%)163 (23.3%)365 (52.2%)
Regret after VaccinationDisagree105 (17%)<0.001143 (23.2%)0.797369 (59.8%)<0.001
Unsure28 (35%)0.03029 (36.3%)0.00423 (28.7%)<0.001
Agree ‡64 (71.1%)<0.00112 (13.3%)0.01714 (15.6%)<0.001
‡ Reasons for RegretVaccines are not efficient36 (67.9%)<0.0016 (11.3%)0.03211 (20.8%)<0.001
Post-vaccination infection34 (63%)<0.00110 (18.5%)0.38210 (18.5%)<0.001
Post-vaccination side effects15 (62.5%)<0.0012 (8.3%)0.0777 (29.2%)0.026
Did not choose best vaccine5 (83.3%)0.005 *0 (0%)0.345 *1 (16.7%)0.113 *
Disease became milder2 (100%)0.062 *0 (0%)1.000 *0 (0%)0.234 *
Chi-squared test (χ2) and Fisher’s exact test (*) were used with a significance level Sig. < 0.05. Statistically significant differences are indicated with bold character. + Respondents being COVID-19 infected (Yes). ‡ Respondents who regret being vaccinated.
Table
Table 7. Regression Analysis of Demographic and Anamnestic Factors for COVID-19 VB Acceptance.
Table 7. Regression Analysis of Demographic and Anamnestic Factors for COVID-19 VB Acceptance.
PredictorB (SE)WaldORCI 95%Sig.
Sex: Male (vs. Female)0.547 (0.149)13.5651.7291.292–2.313<0.001
Age Group: 31–40 yo (vs. 18–30 yo)0.263 (0.188)1.9501.3010.899–1.8810.163
Age Group: 41–50 yo (vs. 18–30 yo)0.247 (0.200)1.5201.2800.865–1.8940.218
Age Group: 51–60 yo (vs. 18–30 yo)0.924 (0.255)13.1782.5201.530–4.152<0.001
Age Group: >60 yo (vs. 18–30 yo)1.181 (0.382)9.5653.2571.541–6.8840.002
Education: BA./BSc. (vs. College/School)−1.055 (0.298)12.5040.3480.194–0.625<0.001
Education: MSc. or above (vs. College/School)−0.848 (0.296)8.1930.4280.239–0.7650.004
Profession: Healthcare (vs. Non-healthcare)−0.373 (0.147)6.4270.6890.517–0.9190.011
Chronic Illness: Yes (vs. No)0.332 (0.160)4.2801.3941.018–1.9080.039
COVID-19 Infection: No (vs. Yes)0.297 (0.151)3.8821.3451.002–1.8070.049
Post-vaccination Relief: Agree (vs. Disagree)2.094 (0.259)65.6018.1204.892–13.479<0.001
Post-vaccination Regret: Disagree (vs. Agree)2.089 (0.302)47.7858.0774.467–14.605<0.001
Binary logistic regression was used with a significance level Sig. < 0.05. Statistically significant differences are indicated with bold character.
Table
Table 8. Regression Analysis of Psychological Promoters of and Barriers to COVID-19 VB Acceptance.
Table 8. Regression Analysis of Psychological Promoters of and Barriers to COVID-19 VB Acceptance.
PredictorB (SE)WaldAORCI 95%Sig.
There is no alternative: Agree (vs. Disagree)1.180 (0.253)21.8243.2561.984–5.342<0.001
I want to travel abroad: Agree (vs. Disagree)0.590 (0.236)6.2611.8041.136–2.8630.012
Experts recommend it: Agree (vs. Disagree)1.569 (0.221)50.5704.8013.116–7.398<0.001
It is necessary and efficient: Agree (vs. Disagree)3.336 (0.384)75.34828.11213.235–59.709<0.001
Primer doses are sufficient: Disagree (vs. Agree)3.163 (0.386)67.02923.64111.087–50.409<0.001
Fear of side effects: Disagree (vs. Agree)0.391 (0.500)0.6121.4790.555–3.9430.434
Vaccination is inefficient: Disagree (vs. Agree)1.641 (0.471)12.1515.1592.051–12.979<0.001
It can harm immune system: Disagree (vs. Agree)1.612 (0.516)9.7765.0131.825–13.7700.002
I had breakthrough infection: Disagree (vs. Agree)1.927 (1.108)3.0266.8700.783–60.2480.082
Multivariable logistic regression was adjusted for sex, age group, educational level, profession, chronic illness, previous COVID-19 infection, post-vaccination relief and regret. Statistically significant differences are indicated with bold character.
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Lounis, M.; Bencherit, D.; Rais, M.A.; Riad, A. COVID-19 Vaccine Booster Hesitancy (VBH) and Its Drivers in Algeria: National Cross-Sectional Survey-Based Study. Vaccines 2022, 10, 621. https://doi.org/10.3390/vaccines10040621

AMA Style

Lounis M, Bencherit D, Rais MA, Riad A. COVID-19 Vaccine Booster Hesitancy (VBH) and Its Drivers in Algeria: National Cross-Sectional Survey-Based Study. Vaccines. 2022; 10(4):621. https://doi.org/10.3390/vaccines10040621

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Lounis, Mohamed, Djihad Bencherit, Mohammed Amir Rais, and Abanoub Riad. 2022. "COVID-19 Vaccine Booster Hesitancy (VBH) and Its Drivers in Algeria: National Cross-Sectional Survey-Based Study" Vaccines 10, no. 4: 621. https://doi.org/10.3390/vaccines10040621

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