# The COVID-19 vaccination acceptance/hesitancy rate and its determinants among healthcare workers of 91 Countries: A multicenter cross-sectional study

Mehrdad Askarian, Aleksandr Semenov, Ferran Llopis, Francesca Rubulotta, Gorana Dragovac, Natalia Pshenichnaya, Ojan Assadian, Yvon Ruch, Zahra Shayan, Cristobal Padilla Fortunatti, et al.

► To cite this version:

Mehrdad Askarian, Aleksandr Semenov, Ferran Llopis, Francesca Rubulotta, Gorana Dragovac, et al. The COVID-19 vaccination acceptance/hesitancy rate and its determinants among healthcare workers of 91 Countries: A multicenter cross-sectional study. EXCLI Journal, 2022, 21, pp.93-103. 10.17179/excli2021-4439. hal-04086803

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Original article:

THE COVID-19 VACCINATION ACCEPTANCE/HESITANCY RATE
AND ITS DETERMINANTS AMONG HEALTHCARE WORKERS OF
91 COUNTRIES: A MULTICENTER CROSS-SECTIONAL STUDY

Mehrdad Askarian<fnref n="1" /> ID, Aleksandr Semenov<fnref n="2" /> ID, Ferran Llopis<fnref n="3" /> ID, Francesca Rubulotta<fnref n="4" /> ID,
Gorana Dragovac<fnref n="5" /> ID, Natalia Pshenichnaya<fnref n="6" /> ID, Ojan Assadian<fnref n="7" /> ID, Yvon Ruch<fnref n="8" /> ID, Zahra
Shayan<fnref n="9" /> ID, Cristobal Padilla Fortunatti<fnref n="10" /> ID, Daniel Lucey<fnref n="11" /> ID, Abdullah Almohaizeie<fnref n="12" /> ID,
Abu Hena Mostafa Kamal<fnref n="13" /> ID, Adenike Ogunshe<fnref n="14" /> ID, Aidos Konkayev<fnref n="15" /> ID, Asim Beg<fnref n="16" /> ID,
Enzo Primerano<fnref n="17" /> ID, Fatma Amer<fnref n="18" /> ID, Hema Prakash Kumari Pilli<fnref n="19" /> ID, Ivan Hung<fnref n="20" /> ID,
Folusakin Ayoade<fnref n="21" /> ID, Jean Yves Lefrant<fnref n="22" /> ID, Joanna Zajkowska<fnref n="23" /> ID, Jordi Rello<fnref n="24" /> ID,
Momin Kazi<fnref n="25" /> ID, Mohammad Hossein Taghrir<fnref n="26" />,* ID, Stijn Blot²⁷ ID, Stephen Leib²⁸ ID,
Parisa Hosseinpour²⁹ ID, Hamidreza Hosseinpour³⁰ ID, Amirhossein Erfani³¹ ID,
Roham Borazjani<fnref n="26" /> ID, Hossein Akbarialiabad³² ID, Masoud Najafi³² ID, Ardalan Askarian³³ ID,
Hakan Erdem³⁴ ID

<footnote n="1">¹ Department of Community Medicine, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran; Health Behavior Science Research Center, Shiraz University of Medical Sciences, Shiraz</footnote>

<footnote n="2">² Ekaterinburg Research Institute of Viral Infections SRC VB Vector, Ekaterinburg, Russia</footnote>

<footnote n="3">³ Emergency Department, Bellvitge University Hospital, l'Hospitalet de Llobregat, Barcelona, Spain</footnote>

<footnote n="4">⁴ Department of Intensive Care Medicine, Charing Cross Hospital, Imperial College, NHS Trust London, UK</footnote>

<footnote n="5">⁵ Department of Epidemiology, Faculty of Medicine, University of Novi Sad, Serbia; Center of Disease Prevention and Control, Institute of Public Health of Vojvodina, Novi Sad, Serbia</footnote>

<footnote n="6">⁶ Clinical Department of Infectious Pathology, Central Research Institute of Epidemiology, Moscow, Russia</footnote>

<footnote n="7">⁷ Regional Hospital Wiener Neustadt, Austria; Institute of Skin Integrity and Infection Prevention, University of Huddersfield, UK</footnote>

<footnote n="8">⁸ Department of Infectious Diseases, Strasbourg University Hospital, Strasbourg, France</footnote>

<footnote n="9">⁹ Trauma Research Center, Department of Biostatistics, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran</footnote>

<footnote n="10">¹⁰ School of Nursing, Pontificia Universidad Catolica de Chile, Santiago, Chile</footnote>

<footnote n="11">¹¹ Department of Infectious Diseases, Georgetown University Medical Center, Washington, DC 20057, USA</footnote>

<footnote n="12">¹² King Faisal Specialist Hospital and Research Center, Riyadh, Alfaisal University Riyadh, Saudi Arabia</footnote>

<footnote n="13">¹³ Department of Anaesthesiology & ICU, Rajshahi Medical College Hospital, Rajshahi, Bangladesh</footnote>

<footnote n="14">¹⁴ Applied Microbiology and Infectious Diseases, Department of Microbiology, Faculty of Science, University of Ibadan, Oyo State, Nigeria</footnote>

<footnote n="15">¹⁵ Department of Anesthesiology and Intensive Care, Astana Medical University, Nur-Sultan, Kazakhstan; National Centre of Traumatology and Orthopedia named by Batpenov, Nur-Sultan, Kazakhstan</footnote>

<footnote n="16">¹⁶ Department of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan</footnote>

<footnote n="17">¹⁷ Department of Anesthesia and Intensive Care, Polyclinic of Monza, Monza, Italy</footnote>

<footnote n="18">¹⁸ Department of Medical Microbiology and Immunology, School of Medicine, Zagazig University, Zagazig, Egypt</footnote>

<footnote n="19">¹⁹ Department of Microbiology, GITAM Institute of Medical Sciences and Research, GITAM, Deemed to be University, Visakhapatnam, India</footnote>

<footnote n="20">²⁰ Department of Infectious Diseases; Gastroenterology & Hepatology, The University of Hong Kong</footnote>

<footnote n="21">²¹ Division of Infectious Diseases, Department of Medicine, University of Miami Miller School of Medicine, Miami, FL 33136, USA</footnote>

<footnote n="22">²² Department of Anaesthesia, Critical Care Emergency and Pain Medicine, University Hospital of Nimes, Montpellier University, Nimes, France</footnote>

<footnote n="23">²³ Department of Infectious Diseases and Neuroinfections, Medical University in Białystok, Poland</footnote>

<footnote n="24">²⁴ CRIPS, Vall Hebron Institute of Research (VHIR) & CHRU Nimes, Nimes, France</footnote>

<footnote n="25">²⁵ Research Department of Paediatrics and Child Health, Aga Khan University, Karachi, Pakistan</footnote>

<footnote n="26">²⁶ Trauma Research Center, Shahid Rajaee (Emtiaz) Trauma Hospital, Shiraz University of Medical Sciences, Shiraz, Iran</footnote>
27 Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium

28 Institute for Infectious Diseases, University of Bern, Bern, Switzerland

29 School of Medicine, Islamic Azad University, Kazeroun branch, Kazeroun, Iran

30 Department of Surgery, Shiraz Laparoscopic Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

31 Thoracic and Vascular Surgery Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

32 Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran

33 Student, College of Arts & Science, University of Saskatchewan, Saskatoon, Canada

34 ID-IRI Lead Coordinator, Ankara, Turkey

* Corresponding author: Mohammad Hossein Taghrir, MD, Trauma Research Center, Shahid Rajaee (Emtiaz) Trauma Hospital, Shiraz University of Medical Sciences, Shiraz, Iran, Postal code: 7143838167, Phone: +989107031235, E-mail: Mhtaghrir@gmail.com

https://dx.doi.org/10.17179/excli2021-4439

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/).

## ABSTRACT

The aim of this study was to investigate the COVID-19 vaccination acceptance rate and its determinants among healthcare workers in a multicenter study. This was a cross-sectional multi-center survey conducted from February 5 to April 29, 2021. The questionnaire consisted of 26 items in 6 subscales. The English version of the questionnaire was translated into seven languages and distributed through Google Forms using snowball sampling; a col- league in each country was responsible for the forward and backward translation, and also the distribution of the questionnaire. A forward stepwise logistic regression was utilized to explore the variables and questionnaire fac- tors tied to the intention to COVID-19 vaccination. 4630 participants from 91 countries completed the question- naire. According to the United Nations Development Program 2020, 43.6 % of participants were from low Human Development Index (HDI) regions, 48.3 % high and very high, and 8.1 % from medium. The overall vaccination hesitancy rate was 37 %. Three out of six factors of the questionnaire were significantly related to intention to the vaccination. While ‘Perceived benefits of the COVID-19 vaccination’ (OR: 3.82, p-value<0.001) and ‘Prosocial norms’ (OR: 5.18, p-value<0.001) were associated with vaccination acceptance, ‘The vaccine safety/cost con- cerns’ with OR: 3.52, p-value<0.001 was tied to vaccination hesitancy. Medical doctors and pharmacists were more willing to take the vaccine in comparison to others. Importantly, HDI with OR: 12.28, 95 % CI: 6.10-24.72 was a strong positive determinant of COVID-19 vaccination acceptance. This study highlighted the vaccination hesitancy rate of 37 % in our sample among HCWs. Increasing awareness regarding vaccination benefits, con- fronting the misinformation, and strengthening the prosocial norms would be the primary domains for maximizing the vaccination coverage. The study also showed that the HDI is strongly associated with the vaccination ac- ceptance/hesitancy, in a way that those living in low HDI contexts are more hesitant to receive the vaccine.

**Keywords:** COVID-19, COVID-19 vaccines, Human Development Index, HDI, health personnel, vaccination coverage

## INTRODUCTION

The severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2), widely known as COVID-19, was first reported in December 2019 in Wuhan, China. The disease spread rapidly, infected the entire world and created a pandemic. As of the September 23, 2021 more than 230 million people in 223 coun- tries/areas were affected by COVID-19 and caused more than 4.7 million deaths

(Worldometer, 2021). In addition to the ef- fects on public health through morbidity and mortality, its detrimental impact on the econ- omy has also been severe in many countries (Al-Mohaithef and Padhi, 2020; McKibbin and Fernando, 2020). Thus, taking necessary action to reduce the pandemic's consequences is a priority of health authorities.

Since the commencement of the pan- pandemic, several approaches for preventing the spread of the novel coronavirus have been
practiced, including mass quarantine, social
distancing, wearing face masks, travel bans,
and closure of schools and businesses. These
mitigation strategies reduced the spread of the
virus, however, were not always successful in
flattening the epidemic curve and were not al-
ways a definitive solution (World Health
Organization, 2020). Moreover, despite all
these efforts, the morbidity and mortality
caused by COVID-19 often persist, and a
heavy burden has been imposed on govern-
ments societies, businesses, and healthcare
workers (Worldometer, 2021). Thus, effec-
tive vaccination to provide active immunity
is needed to help put an end to the pandemic
(Lurie et al., 2020).

Developing a safe and effective COVID-
19 vaccine is a crucial challenge for scientists.
Numerous researchers from both private and
governmental sectors are working intensely to
develop multiple reliable and effective vac-
cines (Callaway, 2020a). This process of test-
ing and marketing new vaccines can take up
to 15 years, however with the current critical
pandemic situation, it has been reduced to
around 12-18 months or even less (Krammer,
2020, Lurie et al., 2020). Currently, around
200 types of vaccines are in different pre-clin-
ical and clinical phases of development,
which over 30 of them in clinical trials. For
instance, Pfizer-BioNTech, Moderna's
mRNA-1273 AstraZeneca/Oxford's
AZD1222, China's Sinopharm and Sinovac,
and Johnson and Johnson's one-dose adeno-
virus-vectored vaccine have received Emer-
gency Use Listing (EUL) from the World
Health Organization and are being adminis-
tered throughout the world (Callaway, 2020b;
Knoll and Wonodi, 2020). Clearly, a success-
ful vaccine's critical parameter is its efficacy,
although the question is how much efficacy is
essential to slow the pandemic. A minimum
vaccine efficacy was set by the World Health
Organization (WHO) as 50 %. When a suita-
ble vaccine is available, it is essential to pri-
oritize high-risk groups, including health care
providers, those with comorbidities, immuno-
compromised, and the elderly (Askarian et al.,
2021; Sharma et al., 2020).

Although vaccination can control the
COVID-19 pandemic, low levels of trust with
regard to COVID-19 vaccines can lead to vac-
cine hesitancy. The definition of vaccine hes-
itancy is "delay in acceptance or refusal of
vaccination despite availability of vaccination
services." The World Health Organization
mentioned reluctance to receive vaccine de-
spite of vaccine availability as one of the top
ten health threats of 2019 (Dubé and
MacDonald, 2020; Pekmezci, 2019). Many
countries are dealing with anti-vaccine move-
ments, lack of access to vaccines, as well as
fighting the COVID-19 infodemic and the
disease itself (Wilson and Wiysonge, 2020).

Health care workers (HCWs) play an im-
portant role both on the frontlines of COVID-
19 and also providing routine non-COVID-19
health services. Clearly, HCWs who have re-
ceived vaccine, are better able to influence
other person's willingness to take the
COVID-19 vaccine (Nzaji et al., 2020). A sur-
vey in China reported higher acceptance of
COVID-19 vaccination among medical staff
in comparison to general population. While
another study in the United States showed
only 20 % vaccine hesitancy among HCWs
(Al-Mohaithef and Padhi, 2020). Moreover, a
survey in the Democratic Republic of the
Congo (DRC) reported that nurses are more
vaccine-hesitant than physicians and this hes-
itancy can negatively impact the rolling out of
the COVID-19 vaccination (Nzaji et al.,
2020). Another study demonstrated several
negative and positive predictors for vaccine
inoculation, positive predictors include occu-
pation as a physician, unemployment during
quarantine period, working in health care ser-
vice giving care to SARS-CoV2 positive pa-
tients, and negative predictors were working
as a nurse and parenthood (Dror et al., 2020).

Since the HCWs have a crucial role in this
pandemic and have direct exposure to
COVID-19, this multi-center survey was con-
ducted to evaluate the acceptance of COVID-
19 vaccine and its refusal rate among HCWs.
The findings will help local and global health
authorities in designing programs to maxim-
ize the vaccination coverage.
# METHODS AND MATERIALS

This cross-sectional multi-center survey was conducted on an international scale between February 5 to April 29, 2021, to evaluate the COVID-19 vaccination acceptance/ hesitancy among HCWs and the factors that may contribute to it. The English version of the questionnaire was translated into seven languages including Persian, Russian, Italian, Spanish, German, French, and Serbian. The questionnaire was distributed through Google Forms using snowball sampling; a colleague in each country or context was responsible for the forward and backward translation, and also the distribution of the questionnaire.

After participants entered the survey homepage, the aim of the survey and an online consent form were displayed. If the participants had an agreement to the survey objectives, they could officially start the survey by clicking the “Next” button below the form, or they could choose to cease the survey. Participation was entirely voluntary, non-commercial, and anonymous. Moreover, all investigators had signed confidentiality agreements before starting the study. The study was approved by the institutional board review of Shiraz University of Medical Sciences.

## Assessment and measures

The questionnaire consisted of three main sections. In the first section, participants were asked for some demographic information. This information included: age, gender, pregnancy status, current location, marital status, the highest level of education, history of chronic disease related to the severity of the COVID-19 (including diabetes mellitus, hypertension, lung diseases, renal diseases, cardiovascular diseases, and corticosteroids consumption), history of COVID-19 infection family history of COVID-19 infection, history of influenza vaccination, being a frontline HCW, current occupation, working in a public or private facility, and whether their health care facility admits COVID-19 patients or not.

As for the participants’ location, we categorized them according to the World Bank classification of countries in the 2021 fiscal year for ‘area’ and ‘level of income’ (World Bank, 2020), and ‘Human Development Index (HDI)’ based on the United Nations Development Program (UNDP) 2020 classification (United Nations Development Programme, 2020). The human development index is a composite measure developed by the UNDP that aims at assessing the level of development of countries. The cutoff points were set as follows: HDI <0.550 for low human development, 0.550–0.699 for medium human development, 0.700–0.799 for high human development, and 0.800 or greater for very high human development.

The second section consisted of 26 items which were validated previously through factor analysis (questionnaire soon to be published in Int J Prev Med. 2022). These 26 Items were categorized into six factors encompassing: perceptions of the COVID-19 pandemic (three items), perceived benefits of the COVID-19 vaccination (four items), the vaccine safety/cost concerns (four items), preferences for alternatives (four items), social norms (eight items), and risk reduction habits (three items). All items were answered in a 5-point Likert scale from ‘Strongly agree’ to ‘Strongly disagree’. Items were scored from one for ‘Strongly disagree’ to five for ‘Strongly agree’ for all factors. A higher score indicates the higher willingness to take the vaccination except the items of vaccine safety/cost concerns and preferences for alternatives, where the higher score indicates higher hesitancy toward vaccination.

The third section was the primary outcome measure, willingness to receive COVID-19 vaccination. This section had one major item, "I will get the COVID-19 vaccine as soon as it is accessible". The answer was a 5-point Likert scale ranging from one ("strongly disagree") to five ("strongly agree"). For the analysis, we transform this 5-point scale to the binary view. ‘Strongly agree’ and ‘Agree’ were set as ‘Yes’ and the others as ‘No/I don’t know’. In addition, there
was another item in this section that asked for
the kind of vaccine they prefer (domestic, im-
ported, or it makes no differences).

Notably, the reliability of the whole ques-
tionnaire was calculated, and the Cronbach al-
pha was 0.89.

Data analysis

Data were analyzed using SPSS version
16.0 (IBM, Armonk, NY, USA). Categorical
variables were reported in number and per-
centage, and the Pearson Chi-square test was
computed to detect the statistically significant
differences between the demographics and
the primary outcome; and the independent-
sample t test was calculated for the continu-
ous variables. A forward stepwise logistic re-
gression was utilized to explore the variables
and questionnaire factors that tied to the in-
tention to COVID-19 vaccination. The two-
tailed P-value<0.05 was set for the signifi-
cance level.

Ethical approval

Ethics approval of the study was obtained
from the institutional review board of Shiraz
University of Medical Sciences and Research
Ethics Committee with the following numbers
of 22654 and IR.sums.med.rec.1399.549, re-
spectively.

RESULTS

Demographic information

Taken together, 4630 participants from 91
countries completed the questionnaire. The
majority of participants were from Iran, fol-
lowed by France, Kazakhstan, Italy, Spain,
Saudi Arabia and another eighty-five coun-
tries. As far as the level of income is con-
cerned, 2642 of participants (57.1 %) were
from upper-middle-income countries, 39.6 %
from high income, and only 3.3 % of the
study population were from low and lower-
middle countries. As for the region of partici-
pants, the main parts of participants were
from the Middle East and North Africa
(48.5 %), and Europe and Central Asia
(41.8 %). Other regions are as follow: Latin

America & the Caribbean (3 %), East Asia and Pacific (2.6 %), South Asia (1.5 %), Sub-Saharan Africa (1.2 %), and North America (1.4 %). According to UNDP, 43.6 % of participants were categorized into low HDI, 48.3 % high and very high, and 8.1 % medium.

In sum, the vaccination acceptance rate
was 63 %, and 37 % of participants were hes-
itant to the COVID-19 vaccination. The mean
age was 41.63 years; comparing the mean age
between the outcome groups, it was signifi-
cantly lower among those hesitant to receive
the vaccine (P-value<0.001). Almost 66.8 %
(3095) of participants were female; among
them, 3 % were pregnant. Males were more
willing to receive the vaccination.

Considering other demographics, roughly
70 % of participants were married, and 4 %
considered their marital status as 'other' such
as in-relationship (this concept might be dif-
ferent in different contexts). Those who were
single were more hesitant to receive the vac-
cination. Doctorate or above and master's de-
gree were the most self-reported highest level
of education. Among the reported highest
level of education, those with high school di-
ploma the diploma and master's degree were
less likely to accept the vaccination. Of all,
16.4 % mentioned that they have a chronic
disease that would be related to the severity of
COVID-19; and 28.3 % reported that they
have had COVID-19 disease already. In addi-
tion, 81.9 % of participants had family history
of the COVID-19 infection. Those who were
not infected by SARS-CoV-2/COVID-19 had
a higher willingness to receive the vaccina-
tion; parallel with those with negative family
history of the COVID-19 infection. Almost
two-thirds of participants had the influenza
vaccine, which was strongly tied to their will-
ingness to receive the COVID-19 vaccine.

As for occupation, medical doctors and
nurses comprised the majority of the study
population. Among them, medical doctors
and pharmacists had significantly higher will-
ingness to accept the vaccination. Notably,
85.6 % stated that their setting accepts and ad-
mits COVID-19 patients; and those caring for
COVID-19 patients had a higher willingness to receive the vaccine. The participants also were asked their preference regarding the type of vaccine. Although 54.9 % stated that there is no difference between domestic or imported ones, 16.4 % responded that they only

prefer domestic vaccines. Those who stated that there is no difference between the types of vaccine had a higher rate of vaccination acceptance. Other demographic characteristics are listed in Table 1.

<table><caption>**Table 1:** Demographic variables and their association with the primary outcome</caption><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th rowspan="2">Total frequency</th><th colspan="3">Intention to receive COVID-19 vaccine</th></tr><tr><th>N (Column %) =4630 (100)</th><th>Yes N (Row %) = 2918 (63)</th><th>No/I don't know N (Row %) = 1712 (37)</th><th>P-value*</th></tr></thead><tbody><tr><td rowspan="2">Gender</td><td>Female</td><td>3095 (66.8)</td><td>1850 (59.8)</td><td>1245 (40.2)</td><td rowspan="2">&lt;0.001</td></tr><tr><td>Male</td><td>1535 (33.2)</td><td>1068 (69.6)</td><td>467 (30.4)</td></tr><tr><td rowspan="3">Marital status</td><td>Married</td><td>3249 (70.2)</td><td>2075 (63.9)</td><td>1174 (36.1)</td><td rowspan="3">&lt;0.001</td></tr><tr><td>Single</td><td>1196 (25.8)</td><td>702 (58.7)</td><td>494 (41.3)</td></tr><tr><td>Other</td><td>185 (4)</td><td>141 (76.3)</td><td>44 (23.8)</td></tr><tr><td rowspan="6">Highest level of education</td><td>Lower than diploma</td><td>107 (2.3)</td><td>70 (65.4)</td><td>37 (34.6)</td><td rowspan="6">&lt;0.001</td></tr><tr><td>Diploma</td><td>494 (10.7)</td><td>225 (45.5)</td><td>269 (54.5)</td></tr><tr><td>Associate degree</td><td>89 (1.9)</td><td>65 (73)</td><td>24 (27)</td></tr><tr><td>Bachelor's degree</td><td>680 (14.7)</td><td>547 (80.4)</td><td>133 (19.6)</td></tr><tr><td>Master's degree</td><td>1673 (36.1)</td><td>916 (54.8)</td><td>757 (45.2)</td></tr><tr><td>Doctorate or above</td><td>1587 (34.3)</td><td>1095 (69)</td><td>492 (31)</td></tr><tr><td rowspan="2">History of chronic disease</td><td>Yes</td><td>760 (16.4)</td><td>487 (64.1)</td><td>273 (35.9)</td><td rowspan="2">0.51</td></tr><tr><td>No</td><td>3870 (83.6)</td><td>2431 (62.8)</td><td>1439 (37.2)</td></tr><tr><td rowspan="2">History of COVID-19 disease</td><td>Yes</td><td>1311 (28.3)</td><td>715 (54.5)</td><td>596 (45.5)</td><td rowspan="2">&lt;0.001</td></tr><tr><td>No</td><td>3319 (71.7)</td><td>2203 (66.4)</td><td>1116 (33.6)</td></tr><tr><td rowspan="2">Family history of COVID-19 disease</td><td>Yes</td><td>3794 (81.9)</td><td>2301 (60.6)</td><td>1493 (39.4)</td><td rowspan="2">&lt;0.001</td></tr><tr><td>No</td><td>836 (18.1)</td><td>617 (73.8)</td><td>219 (26.2)</td></tr><tr><td rowspan="2">History of Flu vaccine</td><td>Yes</td><td>3069 (66.3)</td><td>2224 (72.5)</td><td>845 (27.5)</td><td rowspan="2">&lt;0.001</td></tr><tr><td>No</td><td>1561 (33.7)</td><td>694 (44.5)</td><td>867 (55.5)</td></tr><tr><td rowspan="2">Working as a frontline HCW</td><td>Yes</td><td>3486 (75.3)</td><td>2211 (63.4)</td><td>1275 (36.6)</td><td rowspan="2">0.32</td></tr><tr><td>No</td><td>1144 (24.7)</td><td>707 (61.8)</td><td>437 (38.2)</td></tr></tbody></table>
<table><caption>**Table 1 (cont.):** Demographic variables and their association with the primary outcome</caption><thead><tr><th></th><th></th><th>Total frequency</th><th colspan="2">Intention to receive COVID-19 vaccine</th><th></th></tr></thead><tbody><tr><td rowspan="8">Occupation</td><td>Medical doctor</td><td>2154 (46.5)</td><td>1519 (70.5)</td><td>635 (29.5)</td><td rowspan="8">&lt;0.001</td></tr><tr><td>Nurse</td><td>1477 (31.9)</td><td>825 (55.9)</td><td>652 (44.1)</td></tr><tr><td>Laboratory staff</td><td>118 (2.5)</td><td>62 (52.5)</td><td>56 (47.5)</td></tr><tr><td>Pharmacist</td><td>69 (1.5)</td><td>51 (73.9)</td><td>18 (26.1)</td></tr><tr><td>Cleaning staff</td><td>9 (0.2)</td><td>6 (66.7)</td><td>3 (33.3)</td></tr><tr><td>Technician</td><td>128 (2.8)</td><td>83 (64.8)</td><td>45 (35.2)</td></tr><tr><td>Office job</td><td>377 (8.1)</td><td>229 (60.7)</td><td>148 (39.3)</td></tr><tr><td>Other</td><td>298 (6.5)</td><td>143 (47.9)</td><td>155 (52.1)</td></tr><tr><td rowspan="2">Health care sector</td><td>Public</td><td>3621 (78.2)</td><td>2302 (63.6)</td><td>1319 (36.4)</td><td rowspan="2">0.14</td></tr><tr><td>Private</td><td>1009 (21.8)</td><td>616 (61.1)</td><td>393 (38.9)</td></tr><tr><td rowspan="2">Admitting COVID-19 patients</td><td>Yes</td><td>3962 (85.6)</td><td>2532 (63.9)</td><td>1430 (36.1)</td><td rowspan="2">0.002</td></tr><tr><td>No</td><td>668 (14.4)</td><td>386 (57.8)</td><td>282 (42.2)</td></tr><tr><td rowspan="3">Vaccine preference</td><td>Domestic</td><td>761 (16.4)</td><td>410 (53.9)</td><td>351 (46.1)</td><td rowspan="3">&lt;0.001</td></tr><tr><td>Imported</td><td>1329 (28.7)</td><td>743 (55.9)</td><td>586 (44.1)</td></tr><tr><td>No difference</td><td>2540 (54.9)</td><td>1765 (69.5)</td><td>775 (30.5)</td></tr></tbody></table>

COVID-19, Corona Virus Disease 2019; HCW, Health Care worker

*Chi-square Test

Since the vaccination acceptance was significantly different among male and female, and highest level of education, we did a sub-group analysis considering these two variables. Using Chi-square test, males with highest education level of Bachelor's, Master's,

and Doctorate or above degree had higher vaccination acceptance rate compared to female. It might indicate that the significant difference among male and female in vaccination acceptance rate could be rooted in the highest level of education (Table 2).

<table><caption>**Table 2:** Sub-group analysis considering Gender and Highest level of education</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Gender</th><th colspan="2">Intention to receive COVID-19 vaccine</th><th rowspan="2">P-value*</th></tr><tr><th>Yes<br>N (Row %)</th><th>No/I don't know<br>N (Row %)</th></tr></thead><tbody><tr><td rowspan="2">Lower than diploma</td><td>Female</td><td>58 (65.9 %)</td><td>30 (34.1 %)</td><td rowspan="2">0.81</td></tr><tr><td>Male</td><td>12 (63.2 %)</td><td>7 (36.8 %)</td></tr><tr><td rowspan="2">Diploma</td><td>Female</td><td>162 (47.4 %)</td><td>180 (52.6 %)</td><td rowspan="2">0.22</td></tr><tr><td>Male</td><td>63 (41.7 %)</td><td>89 (58.6 %)</td></tr><tr><td rowspan="2">Associate degree</td><td>Female</td><td>55 (74.3 %)</td><td>19 (25.7 %)</td><td rowspan="2">0.54</td></tr><tr><td>Male</td><td>10 (66.7 %)</td><td>5 (33.3 %)</td></tr><tr><td rowspan="2">Bachelor's degree</td><td>Female</td><td>403 (78.4 %)</td><td>111 (21.6 %)</td><td rowspan="2">0.018</td></tr><tr><td>Male</td><td>144 (86.7 %)</td><td>22 (13.3 %)</td></tr><tr><td rowspan="2">Master's degree</td><td>Female</td><td>634 (50.8 %)</td><td>614 (49.2 %)</td><td rowspan="2">&lt;0.001</td></tr><tr><td>Male</td><td>282 (66.4 %)</td><td>143 (33.6 %)</td></tr><tr><td rowspan="2">Doctorate or above</td><td>Female</td><td>538 (64.9 %)</td><td>291 (35.1 %)</td><td rowspan="2">&lt;0.001</td></tr><tr><td>Male</td><td>557 (73.5 %)</td><td>201 (26.5 %)</td></tr></tbody></table>

*Chi-square Test
Table 3 outlined the mean scores of our six recruited factors of the questionnaire. Mean scores are shown separately between the outcome groups. All factors were significantly higher among those with more intention to receive the vaccine.

Logistic regression

A forward stepwise logistic regression was performed to identify the significant factors related to the intention to receive the COVID-19 vaccine; the Nagelkerke R2 was 0.67. As shown in Table 4, regarding the main questions, the following factors were significantly tied to higher intention to receive the vaccine: perceived benefits (Odds Ratio (OR): 3.82, 95 % Confidence Interval (CI): 3.23-4.51), safety/cost concerns, and prosocial norms (OR: 5.18, 95 % CI: 4.46-6.02).

The factor of vaccine safety/cost concerns was also significantly related to our primary outcome (OR: 3.52, 95 % CI: 3.07-4.03), and because its items were scored inversely, the higher OR means higher hesitancy to the vaccination. As for demographic characteristics, the history of getting the COVID-19 was associated with vaccination hesitancy, and the history of receiving the influenza vaccine was also significantly related to the intention to receive the vaccine. Interestingly, HDI with OR: 12.28 (95 % CI: 6.10-24.72) was strongly associated with our participants' higher willingness to receive the COVID-19 vaccine. Other factors and demographics were not significantly related to vaccination intention.

<table><caption>Table 3: The details of continuous variables and their association with the primary outcome</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Range</th><th colspan="2">Intention to receive the vaccine</th><th rowspan="2">P-value*</th></tr><tr><th>Yes, Mean (SD)</th><th>No/I don't know, Mean (SD)</th></tr></thead><tbody><tr><td>Age</td><td>19-89</td><td>42.69 (11.10)</td><td>39.81 (11.03)</td><td>&lt;0.001</td></tr><tr><td>Perceptions of the COVID-19</td><td>1-5</td><td>4.40 (0.52)</td><td>4.19 (0.67)</td><td>&lt;0.001</td></tr><tr><td>Perceived benefits of the COVID-19 vaccination</td><td>1-5</td><td>4.82 (0.38)</td><td>3.97 (1.04)</td><td>&lt;0.001</td></tr><tr><td>The vaccine safety/cost concerns</td><td>1-5</td><td>3.42 (0.89)</td><td>2.2 (0.7)</td><td>&lt;0.001</td></tr><tr><td>Preferences for alternatives</td><td>1-5</td><td>4.13 (0.63)</td><td>3.80 (0.72)</td><td>&lt;0.001</td></tr><tr><td>Prosocial norms</td><td>1-5</td><td>3.67 (0.69)</td><td>2.61 (0.75)</td><td>&lt;0.001</td></tr><tr><td>Risk reduction habits</td><td>1-5</td><td>4.75 (0.44)</td><td>4.55 (0.66)</td><td>&lt;0.001</td></tr></tbody></table>

SD, Standard Deviation; COVID-19, Corona Virus Disease 2019

*Independent sample t Test

<table><caption>Table 4: The results of the forward stepwise logistic regression</caption><thead><tr><th>Variables</th><th>Odds ratio</th><th>95 % Confidence interval</th><th>P-value</th></tr></thead><tbody><tr><td>Perceived benefits of the COVID-19 vaccination <sup>a</sup></td><td>3.82</td><td>3.23-4.51</td><td>&lt;0.001</td></tr><tr><td>The vaccine safety/cost concerns<sup># b</sup></td><td>3.52</td><td>3.07-4.03</td><td>&lt;0.001</td></tr><tr><td>Prosocial norms <sup>a</sup></td><td>5.18</td><td>4.46-6.02</td><td>&lt;0.001</td></tr><tr><td>History of getting the COVID-19 <sup>b</sup></td><td>0.76</td><td>0.62-0.93</td><td>0.01</td></tr><tr><td>History of the Flu vaccination <sup>a</sup></td><td>1.35</td><td>1.11-1.63</td><td>&lt;0.001</td></tr><tr><td>HDI <sup>a</sup></td><td>12.28</td><td>6.10-24.72</td><td>&lt;0.001</td></tr></tbody></table>

COVID-19, Corona Virus Disease 2019; HDI, Human Development Index

#Reverse coding

<footnote><sup>a</sup>Tied to vaccination acceptance, <sup>b</sup>Tied to vaccination hesitancy</footnote>
DISCUSSION

Since the development of vaccines against SARS-CoV-2, several studies have been conducted concerning the vaccination acceptance among different populations. Here, we studied vaccination acceptance among healthcare providers in an international and multi-center survey. Our results demonstrated that doctors and pharmacist had higher rate of vaccination acceptance. Moreover, those who have never been infected with COVID-19 nor any of their family members, were more willing to receive the vaccine. Importantly, those who live in countries with higher HDI score had more willingness to be vaccinated than others.

HDI is defined as a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living (United Nations Development Programme, 2020). In a study by de Oliveira et al., HDI was shown to be a positive factor for vaccine dose per thousand persons, and countries with higher HDI received more doses of vaccine per thousand citizens (de Oliveira et al., 2021). In our study, we sought to evaluate whether vaccine acceptance is also associated with higher HDI. The odds ratio was calculated to be 12.28, which means a high strong positive association of HDI with vaccine acceptance. This odds ratio was the highest rate we had in our study, showing its very important impact on vaccine acceptance. These findings were what we expected from countries with higher HDI. Since one of the primary aspects of calculating HDI is considering the knowledge domain, it is reasonable for countries with higher HDIs to have higher willingness to receive the vaccine. In a multinational study done in March 2020, it was found that those who live in countries with higher HDI and those who live in Europe were most aware of the importance of COVID-19 vaccination and its measure to implement receiving the vaccine (García-Toledano et al., 2021).

Among healthcare workers, medical doctors and pharmacists were more willing to receive the vaccine. However, working as a

frontline healthcare worker was not statistically associated with vaccine acceptance. Since medical doctors and pharmacists usually work as the head of the teams in healthcare settings, they can increase awareness about beneficial effects of the vaccine administrations for their staff. In a study by Shekhar et al., vaccine acceptance was studied among healthcare workers in the United States (Shekhar et al., 2021). They reported higher acceptance in healthcare workers involved in direct patient care and also workers with chronic medical conditions. In our study, those working as the frontline and those with history of chronic disease had higher vaccination acceptance rate, but the differences were not statistically significant. Furthermore, similar to our study, Dror and colleagues reported the highest level of vaccine hesitancy in nurses (Dror et al., 2020).

Men were more likely to accept the COVID-19 vaccine. This was in line with previous studies (Solís Arce et al., 2021; Wouters et al., 2021). In addition, unmarried individuals were less willing to take the vaccine. This can be attributed to the fact that married people are more concerned about transmitting the disease to their family members, which is why they are more likely to receive the vaccine.

Regarding the main factors of our questionnaire, three of them have reached the level of statistical significance. In the factor of 'Perceived benefits of the COVID-19 vaccination' the participants were asked about the beneficial aspects of the COVID-19 vaccination. It contained four items including: 'If I know COVID-19 vaccination can protect me I'll do it', 'If I know COVID-19 vaccination can protect my family and my friends, I'll do it', 'If I know COVID-19 vaccination can protect other community members, I'll do it, and 'If I know COVID-19 vaccination can help return society to normal public to normalcy, I'll do it'. According to the logistic regression model, its odds ratio was 3.82, signifying a positive association with vaccine acceptance.

The odds ratio of 'The vaccine safety/cost concerns' was 3.52. Since its items were scored inversely, this odds ratio means that
this factor was positively associated with vac-
cine hesitancy. The items were as follow: ‘I’m
concerned about potential side effects of
COVID-19 vaccine’, ‘I think COVID-19 vac-
cine may not be safe’, ‘I have concerns about
getting COVID-19 from the vaccine’, and
‘Vaccination may have some cost for me’.
Previous studies reported similar results; they
reported that the fear of potential side effects
was the most common reason for vaccine re-
fusal (Elharake et al., 2021). However, as
more people get vaccinated, more accurate in-
formation becomes available about the effec-
tiveness and possible side effects of vaccines
which may lead to more vaccine acceptance
over time.

In the factor of ‘Prosocial norms’, the
HCWs were assessed through eight items.
The domain of items consisted of the role of
national TV programs, social media, trusted
physician, parents, and friends in convincing
them to receive the vaccine. The odds ratio
was 5.18 which was strongly tied to vaccina-
tion acceptance.

The history of contracting COVID-19 dis-
ease, and also infection in family members,
were positively associated with vaccine hesi-
tancy. Also, the odds ratio for the history of
COVID-19 disease was 0.76, which is tied to
vaccine hesitancy. Maybe this was because
these individuals thought they were immune
against COVID-19 after contracting it or be-
cause they thought that they once defeated
COVID-19, they could still do it. Besides, in-
dividuals with a positive history of flu vac-
cination were more willing to receive the
COVID-19 vaccine, similar to previous stud-
ies (Shekhar et al., 2021). Also, the odds ratio
of the history of flu vaccination was 1.35. As
expected, it shows that people who accept the
concept of vaccination and also, people who
care more about their health were willing to
take COVID-19 vaccines.

In regard to educational level, bachelor’s
degree and associate degree were more eager
to receive the vaccine, in contrast to individu-
als with diplomas and master’s degrees who
were vaccine-hesitant. So, we did not observe
an increase in the desire to receive the vaccine

from the lowest to the highest educations
level in our study. A multinational survey
study done by Lazarus et al. demonstrated
various result based on countries and educa-
tional level in acceptance of COVID-19 vac-
cine. Higher educated people in the United
States, Ecuador, France, Germany and India
were more likely to be vaccinated while
higher educated ones in Spain, Canada and
United Kingdom were more vaccine hesitant
(Lazarus et al., 2020).

CONCLUSION

This study highlighted the vaccination
hesitancy rate of 37 % in our sample among
HCWs. Increasing awareness regarding bene-
fits of the vaccination, confronting the misin-
formation, and strengthening the prosocial
norms would be the primary domains for
maximizing the vaccination coverage. The
study also showed that the HDI is strongly as-
sociated with the vaccination acceptance/hes-
itancy, in a way that those living in low HDI
contexts are more hesitant to receive the vac-
cine.

Acknowledgment

We would like to thank Prof. Daniel R.
Lucey for his great contributions in reviewing
and editing the paper.

Conflict of interest

The authors declare that they have no
known competing financial interests or per-
sonal relationships that could have appeared
to influence the work reported in this paper.

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