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ORIGINAL ARTICLE

Vaccine Hesitancy Against SARS-CoV-2 in Health Personnel of Northeastern Mexico and Its Determinants

Castañeda-Vasquez, David Emmanuel MD, MPH, ScD; Ruiz-Padilla, Juan Pablo MD; Botello-Hernandez, Edgar MD

Author Information
Journal of Occupational and Environmental Medicine: August 2021 - Volume 63 - Issue 8 - p 633-637
doi: 10.1097/JOM.0000000000002205
  • Open
  • CME Test

Abstract

Learning Objectives

  • Identify the percentage of health professionals in one Mexican state who say they would reject vaccination against SARS-CoV-2.
  • Summarize the findings on determinants of vaccine rejection.
  • Discuss the implications for developing effective public health strategies for COVID-19 control.

Highlights

  • Hope for an effective vaccine against the SARS-CoV-2 virus has been present since the beginning of the pandemic, with health personnel being the most directly exposed to infection by this disease.
  • A total of 543 responses were collected from health professionals, where 5.5% of the subjects stated that they would reject the SARS-CoV-2 vaccination.
  • How well informed the subjects were was the most determining factor, where misinformation related to vaccination and COVID-19 was the most important causes of vaccine rejection.

The global pandemic of the Coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome coronavirus (SARS-CoV-2) has been declared by the WHO1–3 for almost a year ago, having already claimed millions of deaths around the world.4,5 It is a disease with a high mortality rate among older people, and in those with coexisting conditions, such as hypertension, diabetes, and cardiovascular diseases.6,7

The only viable strategy for the prevention and control of this disease is vaccination. The scientific community has developed many vaccines for human use,8–11 now we need to achieve a successful distribution of the vaccine with the implementation of strategies to attain a herd immunity and for it, its acceptance is of the outmost importance.12–14

Vaccine hesitancy is a concern that would slow vaccine distribution among people15,16; it arises from safety concerns, disinformation, and mistrust of its effectiveness.17,18 Frontline health personnel play a role in vaccine acceptance because they influence people's decisions by sharing their personal experience with the vaccine.19–22

Vaccination of health personnel is imperative because they are crucial for the management of the large influx of COVID-19 patients, and they can persuade the general population to accept the vaccine. Knowing the determinants for health personnel to accept vaccination against SARS-CoV-2 will help create an effective public health strategy for COVID-19 control.

MATERIALS AND METHODS

A cross-sectional study was carried out through a survey applied by Google Forms, which was distributed among health personnel in the state of Nuevo León, Mexico, from October to December 2020. After providing informed consent, they were questioned about their intention to be vaccinated against SARS-CoV-2 if they had the opportunity, as well as their perception of the risks, benefits and efficacy of the vaccine. Socioeconomic position was also retrieved using a validated scale in the Mexican population.23 Our questionnaire was proposed based on the literature and was validated reaching a statistical value of Cronbach's alpha > 0.7. A Likert-type scale of 4 points was used to classify the grade of agreement between the statements; then they were divided into two groups for the statistical analysis.

For the analysis, the subjects were divided into two groups: the health personnel who were planning to be vaccinated and those who were not. A comparative analysis was performed using the chi-square test or Fisher's exact test for qualitative variables and the Mann–Whitney U for non-parametric quantitative variables. Subsequently, a univariate analysis was performed using a binary logistic regression to find the predictive factors of vaccination rejection, where their odds ratios (ORs) and confidence intervals (95% CI) were obtained. We did not adjust OR's with other predicting variables because we considered limited our cases of people refusing vaccine. Statistical analysis was performed using the SPSS v26 program.24 A value of P < 0.05 was interpreted as statistically significant.

RESULTS

A total of 543 responses were collected from health professionals, of which 455 (83.7%) belonged to the medical guild; the rest represented nursing, dental, psychology, and laboratory personnel. The majority were women (65%), and the median age was 21 years (range 18 to 69).

Only 5.5% of the participants stated that they would reject the SARS-CoV-2 vaccine. The characteristics of the groups that intended and did not intend to be vaccinated are shown in Table 1.

TABLE 1 - Characteristics of the Population and Predictive Factors for Not Considering Getting Vaccinated
Considers Getting Vaccinated Does not Consider Getting Vaccinated
N = 513 (%) N = 30 (%) P of X 2 Odds Ratio P a
Age (Q1–Q3) 21 (19–23) 23 (20.5–36.5) 0.011 1.071 (1.037–1.107) <0.0001
Male gender 178 (35.1) 9 (30) 0.568 0.746 (0.343–1.620) 0.459
≥40 years old 24 (4.7) 5 (16.7) 0.005 4.075 (1.435–11.575) 0.008
<40 years old 489 (95.3) 25 (83.3) 0.005 0.245 (0.086–0.697) 0.008
Non-medical guild 75 (14.6) 13 (43.3) <0.0001 4.466 (2–083–9.67) <0.0001
Does not have social security 94 (18.3) 11 (36.7) 0.013 2.581 (1.188–5.604) 0.017
Socioeconomic status upper class/middle-upper class 313 (61) 26 (86.7) 0.009 4.153 (1.428–12.079) 0.009
Refers having children 48 (9.4) 8 (26.7) 0.002 3.523 (1.488–8.342) 0.004
Considers COVID-19 as severe 452 (88.1) 18 (60) <0.0001 0.202 (0.093–0.441) <0.0001
Refers being afraid of COVID-19 426 (83) 16 (53.3) <0.0001 0.233 (0.110–0.496) <0.0001
Considers that the vaccine will help prevent Covid-19 502 (97.9) 23 (76.7) <0.0001 0.072 (0.026–0.203) <0.0001
Considers that the vaccine will help prevent complications 502 (97.9) 24 (80) <0.0001 0.088 (0.030–0.257) <0.0001
Considers that the vaccine will lessen his concern about the disease 475 (92.6) 17 (56.7) <0.0001 0.105 (0.047–0.232) <0.0001
Considers the vaccine dangerous 59 (11.5) 22 (73.3) <0.0001 21.161 (9.013–49.680) <0.0001
Considers that the vaccine will cause allergic reactions 159 (31) 19 (63.3) <0.0001 3.846 (1.788–8.271) 0.001
Considers that the vaccine is worse than the disease 23 (4.5) 8 (26.7) <0.0001 7.747 (3.116–19.263) <0.0001
The vaccine causes them anxiety and/or fear 44 (8.6) 16 (53.3) <0.0001 12.182 (5.579–26.601) <0.0001
Considers that the vaccine will help end the pandemic 499 (97.3) 21 (70) <0.0001 0.065 (0.025–0.168) <0.0001
Considers that the vaccine is needed only in people with comorbidities 55 (10.7) 15 (50) <0.0001 8.327 (3.862–17.956) <0.0001
Considers that the government is controlling the pandemic 20 (3.9) 10 (33.3) <0.0001 12.325 (5.107–29.743) <0.0001
Considers that the vaccine is not entirely necessary since God protects them 23 (4.5) 5 (16.7) 0.015 4.261 (1.495–12.143) 0.007
Considers that the vaccine is part of a worldwide conspiracy 22 (4.3) 12 (40) <0.0001 14.879 (6.384–34.677) <0.0001
Considers that the government should not intervene through vaccination 148 (28.8) 14 (46.7) 0.038 2.158 (1.027–4.533) 0.042
Considers that doctors should not intervene through vaccination 167 (32.6) 15 (50) 0.049 2.072 (0.989–4.339) 0.053
They are not willing to get vaccinated if …
 Vaccination results painful/uncomfortable 13 (2.5) 15 (50) <0.0001 38.462 (15.591–94.883) <0.0001
 The vaccine has adverse effects 91 (17.7) 26 (86.7) <0.0001 30.143 (10.270–88.475) <0.0001
 There are comments that it is little useful 18 (3.5) 15 (50) <0.0001 27.500 (11.679–64.751) <0.0001
 The vaccine has a monetary cost 42 (8.2) 14 (46.7) <0.0001 9.812 (4.482–21.484) <0.0001
 The vaccination is far from home 31 (6) 13 (43.3) <0.0001 11.890 (5.298–26.682) <0.0001
 Their relatives and/or friends are against vaccination 22 (4.3) 14 (46.7) <0.0001 19.528 (8.474–45.001) <0.0001
They agree with the following statements…
 The vaccine is unnecessary, they prefer to generate “natural immunity” 16 (3.1) 14 (46.7) <0.0001 27.180 (11.352–65.077) <0.0001
 Prefers homeopathic medicine over vaccination 11 (2.1) 10 (33.3) <0.0001 22.818 (8.685–59.951) <0.0001
 Vaccination is “unnatural” 16 (3.1) 8 (26.7) <0.0001 11.295 (4.368–29.209) <0.0001
 Medications such as Ivermectin, Hydroxychloroquine, or Dexamethasone are better than the vaccine to prevent disease 8 (1.6) 7 (23.3) <0.0001 19.212 (6.414–57.548) <0.0001
95%CI, 95% confidence interval; OR, odds ratio; Q1–Q3, quartile 1 to quartile 3.
Odds ratio for not contemplating getting vaccinated.
aP value from binary logistic regression.

In the binary logistic regression analysis, the variables that had a greater association as a risk factor for not considering vaccination were: not wanting to be vaccinated because it could be uncomfortable (OR = 38,462, 95% CI 15,591 to 94,883), that the vaccine could produce adverse effects (OR = 30,143, 95% CI 10,270 to 88,475), that people around them say that the vaccine is not very useful (OR = 27.5, 95% CI 11,679 to 64,751), prefer to generate a “natural immunity” (OR = 27.18, 95% CI 11.352 to 65.077), prefer homeopathic medicine before vaccination (OR = 22.818, 95% CI 8.685 to 59.951), consider that the vaccine is dangerous (OR = 21.161, 95% CI 9.013 to 49.68), among others. Likewise, this rejection increased significantly among older adults (over 40 years of age, OR = 4.075, 95% CI 1.435 to 11.575), among those from the upper-middle/upper economic class (OR = 4.15, 95% CI 1.42 to 12.07), among those with children (OR = 3.52, 95% CI 1.488 to 8.342), and among people not belonging to the medical guild (OR = 4.46, 95% CI 2.083 to 9.673). There were no significant differences related to sex, or religious beliefs.

The most important protective factors for not contemplating getting vaccinated were: considering that the vaccine will help end the pandemic (OR = 0.065, 95% CI 0.025 to 0.168), considering that the vaccine will help prevent COVID-19 (OR = 0.072, 95% CI 0.026 to 0.203), considering that the vaccine will help prevent complications (OR = 0.088, 95% CI 0.030 to 0.257), considering that vaccination will reduce their concern about the disease (OR = 0.105, 95% CI 0.047 to 0.232), believing that COVID-19 is a serious disease (OR = 0.202, 95% CI 0.093 to 0.441), considering that they know enough about COVID-19 (OR = 0.206, 95% CI 0.095 to 0.449), being afraid of getting sick of COVID-19 (OR = 0.233, 95% CI 0.110 to 0.496), among others. The other ORs are shown in (Table 1) and the most significant in (Fig. 1).

FIGURE 1
FIGURE 1:
Forest plot of the major predictive variables for not considering vaccination among health personnel. (A) Major risk factors. (B) Protective factors. It is possible to conclude that the major risk factors are directly related to the correct knowledge about vaccination and SARS-CoV-2, while the protective factors are related precisely to the opposite. SARS-CoV-2, severe acute respiratory syndrome coronavirus.

DISCUSSION

Our results show that the health sector is widely receptive to SARS-CoV-2 vaccination, as only 5.5% said they did not intend to be vaccinated. This percentage was higher within the upper-middle economic classes, those over 40 years of age, and those not belonging to the medical guild.

Our study found that most factors that lead to vaccine rejection are related to misinformation about the benefits and risks of vaccination, as well as COVID-19, as previously shown by S. Loomba.25

Those who are not willing to be vaccinated tend to fear of the possibility of adverse effects or pain when applying it, or simply doubt their ability to prevent the disease. It will then be necessary to plan evidence-based information strategies where the potential benefits and risks of vaccination are explained in order to improve its acceptance and distribution. The attitude of health personnel influences the patient decision to accept immunization, so ensuring that all health care professionals know immunization practices is an effective strategy to address vaccine hesitancy.25

To February 2021, Mexico's regulatory body “COFEPRIS” has approved three COVID-19 vaccines: Pfizer-BioNTech COVID-19 (BNT162b2) vaccine, Oxford-AstraZeneca COVID-19 vaccine, and Gam-COVID-Vac (Sputnik V). All of them show a high efficacy in preventing COVID-19, and an acceptable incidence of side effects, being flu-like illness, injection site reactions, muscle pain, and joint pain the most frequents.26–28 It would be useful to share this information with health personnel so that they can better understand this risk-benefit ratio, and they can also share it with their patients. This strategy has worked in improve influenza vaccine acceptance.25

Numerous previous studies have evaluated the determinants for the vaccination acceptance among health professionals.29–31 The work presented by Esteves-Jaramillo et al,32 evaluated the acceptance of the influenza A (H1N1) vaccine among health personnel in Mexico. It was found that the most common reasons for rejection were concerns that the vaccine was risky, or that it was not effective; in addition, the least receptive were less influenced by health agencies, or health personnel. We also found these concerns as part of the reasons for not wanting to be vaccinated against COVID-19, but we saw no differences in the sources of information of the participants, such as social networks, friends, family, scientific articles, or health professionals. Both false and veritable information are present in all the mentioned sources, which may explain our findings.

Health personnel over 40 years old showed less acceptance in our study, while in others studies, this was not the case.19,20 Old people are more likely to think that the vaccine is dangerous or ineffective after receiving misinformation from social media or television,25 and this is probably a more determinant factor than fearing COVID-19. This disturbs us because the mortality rate is the highest among older patients, so it is necessary to inform this group about the benefits that they can have with the vaccine.

Economic class may play a role in vaccine acceptance. We found that those health personnel belonging to the upper-middle/upper economic class were more likely to refuse to vaccinate. This finding is difficult to interpret because the refusal was present only between those of the upper-middle class and not in the upper economic class, and because our survey did not register any response among people with the lowest incomes, where previous studies19 have shown a high refusal rate.

Gender was not a determinant factor in our population to accept COVID-19 vaccination. A previous study in health personnel found that being male was a protective factor against COVID-19 vaccine hesitancy,19 while others found gender to be irrelevant.20 Women show a stronger hesitancy to COVID-19 vaccine in the general population,33 but this effect seems to weaken among health personnel, and this may be due to better information about vaccines.

Religion in health personnel shows no effect on vaccine acceptance. In a previous study on health personnel just 5% considered religion as a reason to not getting vaccinated,19 so its effect may be weak.

Our main limitation is age bias, since most participants were less than 30 years old. Selection bias could also be a limitation, since people with negative perceptions of the vaccine may be less likely to answer the survey.

CONCLUSION

Our study takes place within an important historical context in which the Mexican population has been hard-hit by COVID-19. The health sector is expected to be the first to receive the vaccine, and therefore, to evaluate its acceptance and the factors that influence are essential. Factors related to misinformation and a misperception of the risks and benefits of the vaccine were found to be important causes of its rejection. This study is the first to evaluate these factors in Mexico, and it is hoped that their better understanding can help to develop information plans among health personnel, especially in subgroups that were at high risk of refusing the vaccine. Additional studies are needed to understand the determinants of vaccination in different geographic regions.

Acknowledgments

We appreciate the support and assistance provided by Dr Med. Raúl Gabino Salazar Montalvo and Dr Med. Rodrigo Enrique Elizondo Omaña, it was of great importance for the culmination of this paper.

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Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American College of Occupational and Environmental Medicine.