Keywords
COVID-19 - vaccine acceptance - vaccine hesitancy - India
Introduction
The coronavirus disease 2019 (COVID-19) infection is caused by severe acute respiratory
syndrome (SARS)-associated coronavirus, which was initially detected in Wuhan, China,
in the month of December 2019. This virus spread rapidly throughout the world and
on January 27, 2020, its first case was confirmed in India. Later, on March 11, 2020,
the World Health Organization (WHO) declared COVID-19 as a worldwide pandemic.[1] Further, in the absence of any highly effective therapeutic agent for COVID-19,
the development of vaccines that would provide protection from SARS-CoV-2—severe acute
respiratory syndrome coronavirus-2—infection, emerged as global imperative.
The Drug Controller General of India approved two Corona virus vaccines, Covishield (the Indian variant of the AZD1222 vaccine developed by Oxford University and AstraZeneca)
and Covaxin (made by Bharat Biotech International Ltd.), after the recommendations of Central
Drugs and Standards Committee, for restricted emergency use. Further, on January 16,
2021, massive countrywide COVID-19 vaccination drive was launched successfully.[2]
In the beginning, the priority groups included were health workers and frontline workers.
There was considerable enthusiasm and anticipation for the COVID-19 vaccine; however,
doubts about its safety and efficacy among the people in several states in India led
to the struggle with low turnouts. Moreover, vaccine hesitancy is not a novel phenomenon;
there are population subgroups around the world with high vaccine hesitancy, as reported
before the COVID-19 pandemic.[3]
[4]
[5] Vaccine hesitancy is defined as “delay in acceptance or rejection of vaccine, despite
the easy availability of vaccination services,” by the WHO Strategic Advisory Group
of Experts on immunization.[6]
[7] As little is known about vaccine hesitancy specifically for COVID-19 in the Indian
population, we planned to conduct a comprehensive assessment of COVID-19-related vaccine
acceptance in India and to identify population subgroups with higher probability of
vaccine hesitancy, and thus improving its acceptance among general people.
Materials and Methods
Study Design, Setting, and Participants
A cross-sectional survey-based study was conducted from January 1 to January 31, 2021.
A convenience sample approach was adopted in this study, where people aged 18 years
and above, living in various States and Union Territories of India, were invited to
participate.
Sample Size
Assuming prevalence of vaccine acceptance as 50%, Schwartz formula was applied. Using
90% power with 95% confidence level, the sample size came out to be 400.
Procedure
A bilingual (English/Hindi) semi-structured questionnaire was prepared. Sections 1
and 2 contained detailed information and consent about the survey. Section 3 had sociodemographic
details and information related to any chronic infection in family as well as COVID-19
infection in family. Section 4 contained questions related to awareness and perception
of the participants related to COVID-19 infection and its vaccination. Section 5 explored
about their attitude toward vaccination against COVID-19 as well as non-COVID-19 infections.
Sections 6 and 7 dealt with reasons for either accepting or rejecting COVID-19 vaccination.
The questions were validated based on comprehensive literature review[7]
[8] (to ensure face validity) and expert suggestions (to ensure content validity) as
well as repeated consultations followed by modifications. A pilot study (N = 26) was conducted to improve the wording and clarity of expression of the survey
items. Data from the pilot study were not used in any further analysis and the questionnaire
was remodified, which required an estimated time of 5 to 10 minutes to complete.
Google forms were shared by the researchers within their social media sites, networks
such as academic posts, community organizations, and in personal/family groups. Further,
the primary participants were requested to forward the survey among their friends
and relatives. Indian, 18 years and above, consenting, and willing to spare time to
fill the survey were asked to participate in the survey. After receiving and clicking
the survey link, participants got auto-directed to the informed consent page, followed
by the set of survey questionnaires.
Data Analysis
The questionnaires were checked for their completeness and consistency. Collected
data were exported from the MS Excel spreadsheet into SPSS—Statistical Package for
the Social Sciences—for Windows version 24.0 (2016), coded appropriately, and later
cleaned for any possible errors. For analysis, responses to the intention to get COVID-19
vaccination section were combined. For example, both responses “No” and “May be” were
combined in one category. Descriptive statistics like frequency and percentage (%)
to describe the demographic characteristics of the study participants were used in
the study. The main outcome variable of the survey was the public acceptance of COVID-19
vaccines. To determine this, categorical data were presented as percentage (%), and
Pearson's chi-squared test was used to evaluate differences between groups for categorized
variables. In case the expected cell count was found to be less than 5 in >20% cells,
the Fisher's exact test was used. All tests were performed at a 5% level significance,
and thus the value less than 0.05 (p-value < 0.05) was taken as significant association.
Results
Sociodemographic Factors of the Participants
Overall, 450 individuals completed the self-administered electronic questionnaire
from various States and Union Territories of India ([Fig. 1]), out of which more than half of the participants (54.4%) belonged to the age group
18 to 30 years while individuals of age >60 years constituted only 2.7% of the study
population. Majority of the participants were males (59.6%), Hindu (88.7%), residing
in urban localities (79.8%), and graduate and above (75.3%). Almost half (49.7%) of
them were health care workers and 39.3% were working in public sector ([Table 1]).
Table 1
Sociodemographic characteristics of the participants (n = 450)
|
Factors
|
Total sample: n (%)
|
|
Age (in completed years)
|
≤30 years
|
245 (54.4)
|
|
31–60 years
|
193 (42.9)
|
|
>60 years
|
12 (2.7)
|
|
Gender
|
Male
|
267 (59.3)
|
|
Female
|
183 (40.7)
|
|
Religion
|
Hindu
|
399 (88.7)
|
|
Muslim
|
36 (8.0)
|
|
Others
|
15 (3.3)
|
|
Locality
|
Rural
|
91 (20.2)
|
|
Urban
|
359 (79.8)
|
|
Occupation
|
Health care workers
|
224 (49.7)
|
|
Unemployed/housewives
|
44 (9.0)
|
|
Other professionals
|
182 (40.4)
|
|
Employee sector
|
Public
|
177 (39.3)
|
|
Private
|
145 (32.2)
|
|
Others
|
128 (28.4)
|
|
Education
|
Graduate and above
|
339 (75.3)
|
|
Below graduate
|
111 (24.7)
|
Note: n (%) indicates frequency and percentage of individuals who selected an option on the
variables.
Fig. 1 Participants (%) from various states/union territories of India.
Perception about COVID-19 Infection among the Participants
As per [Table 2], the study shows that around half (53.8%) of the participants believed that they
are at risk of contracting COVID-19 infection in next 1 year and think that it does
not cause severe infection (55.8%). However, this has no significant association with
their vaccine acceptance.
Table 2
Association of vaccine acceptance response and perception about COVID-19 infection
among participants (n = 450)
|
Associated variables
|
Acceptance of vaccination against COVID-19 infection
|
Total: n (%)
|
p-Value[a]
|
|
Yes: n (%)
|
No: n (%)
|
|
Do you think you are at risk of contracting COVID-19 infection in the next 1 year?
|
Very likely
|
169 (69.8)
|
73 (30.2)
|
242 (53.8)
|
0.096
|
|
Not at all
|
67 (66.3)
|
34 (33.7)
|
101 (22.4)
|
|
Cannot say
|
62 (57.9)
|
45 (42.1)
|
107 (23.8)
|
|
How severe do you think COVID-19 infection is?
|
Does not cause severe infection
|
155 (61.8)
|
96 (38.2)
|
251 (55.8)
|
0.082
|
|
Cannot say
|
44 (63.8)
|
25 (36.2)
|
69 (15.3)
|
|
It causes severe infection
|
99 (76.2)
|
31 (23.80)
|
130 (28.9)
|
Abbreviation: COVID-19, coronavirus disease 2019.
Note: n (%) indicates frequency and percentage of individuals who selected an option on the
variables.
a
p < 0.05, p-value indicates level of α for statistical significance.
Information about COVID-19 Vaccination among the Participants
Most common sources of information related to COVID-19 vaccine were television/radio
(45.3%) and social media (42.2%), followed by newspaper (29.1%) and medical literature
(22.7%; [Fig. 2]). But majority (62.7%) of them felt that they have received only “some information”
and trust their source (67.6%) for vaccine. Participants who were graduate and above,
and living in urban areas, were found to be more informed about vaccination as compared
to others (p < 0.05). Only half of the participants believed that vaccine can protect them from
COVID-19 infection (51.1%) and is safe (52.4%), whereas 40% were still found indecisive
about it.
Fig. 2 Source of information regarding coronavirus disease 19 vaccine (percentages may not
add to 100 due to multiple responses).
COVID-19 Vaccine-Related Preferences among Study Population
Out of total 450 participants, 66.8% felt that COVID-19 vaccine can save them and
their family from the COVID-19 infection. Further, 44.7% of them believed that benefit
of taking vaccine is more than the risk ([Fig. 3]). However, 26% of the participants were still indecisive and 7.8% showed their unwillingness
in accepting vaccination. Most common reason for not accepting was lack of enough
scientific evidence (40.8%) and “waiting for others to get vaccinated first” (34.8%;
[Fig. 4]).
Fig. 3 Reasons for “accepting” coronavirus disease 19 (COVID-19) vaccine (percentages may
not add to 100 due to multiple responses).
Fig. 4 Reasons for “not accepting” coronavirus disease 19 vaccine (percentages may not add
to 100 due to multiple responses).
Factors Associated with COVID-19 Vaccine Acceptance
The observations, as recorded in [Table 3], show that factors significantly associated with COVID-19 vaccine acceptance were
gender (male), age group (31–60 years), religion (Hindu), and chronic disease status
of family (p < 0.05). Similarly, in [Table 4], it was seen that respondents who were aware about vaccine drive by the government,
who have received most of the information about it, who trusted their source of information,
and thus believed that COVID-19 vaccine was safe for them and their family members
were found more likely to accept COVID-19 (p < 0.05) than others.
Table 3
Association of vaccine acceptance response and sociodemographic factors (n = 450)
|
Factors
|
|
Acceptance of vaccination against COVID-19 infection
|
Total: n (%)
|
p-Value[a]
|
|
Yes: n (%)
|
No: n (%)
|
|
|
Age (in completed years)
|
≤30 years
|
142 (58.0)
|
103 (42.0)
|
245 (54.4)
|
<0.001
|
|
31–60 years
|
146 (75.6)
|
47 (24.4)
|
193 (42.9)
|
|
>60 years
|
10 (83.3)
|
2 (16.7)
|
12 (2.7)
|
|
Gender
|
Male
|
190 (71.2)
|
77 (28.8)
|
267 (59.3)
|
0.007
|
|
Female
|
108 (59.0)
|
75 (41.0)
|
183 (40.7)
|
|
Religion
|
Hindu
|
274 (68.7)
|
125 (31.3)
|
399 (88.7)
|
0.004
|
|
Muslim
|
19 (52.8)
|
17 (47.2)
|
36 (8.0)
|
|
Others
|
5 (33.3)
|
10 (66.7)
|
15 (3.3)
|
|
Locality
|
Rural
|
65 (71.4)
|
26 (28.6)
|
91 (20.2)
|
0.240
|
|
Urban
|
233 (64.9)
|
126 (35.1)
|
359 (79.8)
|
|
Education
|
Graduate and above
|
231 (68.1)
|
108 (31.9)
|
339 (75.3)
|
0.132
|
|
Intermediate and below
|
67 (60.4)
|
44 (39.6)
|
111 (24.7)
|
|
Occupation
|
Health workers
|
151 (67.4)
|
73 (32.6)
|
224 (49.7)
|
0.380
|
|
Unemployed/housewife
|
25 (56.8)
|
19 (43.2)
|
44 (9.0)
|
|
Other professionals
|
122 (67.0)
|
60 (33.0)
|
182 (40.4)
|
|
Are you or any family member suffering from any of the longstanding chronic diseases
(>2 months)?
|
No chronic disease
|
240 (64.0)
|
135 (36.0)
|
375 (83.3)
|
0.025
|
|
Chronic disease present
|
58 (77.3)
|
17 (22.7)
|
75 (16.7)
|
|
Have you or any of your family members been infected with COVID-19 infection?
|
No
|
252 (66.0)
|
130 (34.0)
|
382 (84.9)
|
0.787
|
|
Yes
|
46 (67.6)
|
22 (32.4)
|
68 (15.1)
|
Abbreviation: COVID-19, coronavirus disease 2019.
Note: n (%) indicates frequency and percentage of individuals who selected an option on the
variables.
a
p <0.05; p-value indicates level of α for statistical significance.
Table 4
Association of vaccine acceptance response and attitude and awareness toward COVID-19
vaccine among the participants (n = 450)
|
Associated variables
|
Acceptance of vaccination against COVID-19 infection
|
Total: n (%)
|
p-Value
|
|
Yes: n (%)
|
No: n (%)
|
|
In past, have you ever refused any vaccine for yourself or your children?
|
Yes
|
2 (33.3)
|
4 (66.7)
|
6 (1.3)
|
0.081
|
|
No
|
296 (66.7)
|
148 (33.3)
|
444 (98.7)
|
|
Do you believe that vaccine can protect you from COVID-19 infection?
|
Very likely
|
160 (69.3)
|
71 (30.7)
|
231 (51.3)
|
0.108
|
|
Not at all
|
4 (40.0)
|
6 (60.0)
|
10 (2.2)
|
|
May be
|
134 (64.1)
|
75 (35.9)
|
209 (46.4)
|
|
Do you believe that COVID-19 vaccine is safe for you and your family members?
|
Very likely
|
218 (92.4)
|
18 (7.6)
|
236 (52.4)
|
<0.001
|
|
Do not Know
|
78 (39.6)
|
119 (60.4)
|
197 (43.8)
|
|
Not at all
|
2 (11.8)
|
15 (88.2)
|
17 (3.8)
|
|
Are you aware that Government of India is starting vaccination drive?
|
Yes
|
296 (67.7)
|
141 (32.3)
|
437 (97.1)
|
<0.001
|
|
No
|
2 (15.4)
|
11 (84.6)
|
13 (2.9)
|
|
Do you feel you have got enough information about Coronavirus vaccine?
|
No information
|
24 (53.3)
|
21 (46.7)
|
45 (10.0)
|
0.002
|
|
Some information
|
178 (63.1)
|
104 (36.9)
|
282 (62.7)
|
|
Most information
|
96 (78.0)
|
27 (22.0)
|
123 (27.3)
|
|
Do you trust the source from where you received information regarding vaccination?
|
Very likely
|
235 (77.3)
|
69 (22.7)
|
304 (67.6)
|
<0.001
|
|
Not at all
|
7 (25.9)
|
20 (74.1)
|
27 (6.0)
|
|
May be
|
56 (47.1)
|
63 (52.9)
|
119 (26.4)
|
Abbreviation: COVID-19, coronavirus disease-2019.
Discussion
There are limited studies to explore the intention for uptake of COVID-19 vaccine
in the current pandemic crisis. In a cross-sectional study conducted in October 2020
of 351 Indian adults, it was found that 86.3% were planning to get COVID-19 vaccination
whereas 13.7% admitted hesitancy.[9] Further, during July–October 2020, another study of 513 residents of Delhi recorded
that 79.5% participants showed their willingness to take the vaccine while 8.8% were
not of the opinion to take the vaccine and remaining 11.7% had not yet decided about
the vaccine.[10] Similarly, in the current study, it was observed that most of the participants (97.1)
were quite aware about the COVID-19 vaccination. However, only 66.2% showed their
willingness to accept vaccination and 26.0% were still indecisive whereas 7.8% did
not want to accept it.
Moreover, these differences in acceptance of vaccine could also be in part due to
the different timing of studies conducted in COVID-19 pandemic. Besides this, in the
current study it was also recorded that people's occupation, locality, and education
played significant roles.
Various studies reported the perceived risk of becoming infected as predictor toward
intention behind vaccination.[11]
[12]
[13]
[14] Further, high trust in the source of information and level of information about
the vaccine were associated with the acceptance of COVID-19 vaccination.[15]
[16]
[17] Similarly, in the current study, participants having high trust in the information
system and having awareness and enough information were found more willing to accept
COVID-19 vaccination. Men perceived more risk of infection than women as they thought
they were more exposed and informed. Thus, significant gender gap was identified.
Locality (urban/rural) and religion also seemed to affect their behavior, which highlighted
them as target groups. Health workers were found willing to accept vaccination as
they were more informed, exposed, and perceived COVID-19 as very severe infection
while working during pandemic as compared with other professionals.
The present study revealed that only half of the participants believed that vaccine
could protect them from COVID-19 infection (51.1%) and was safe (52.4%) whereas more
than 40% were indecisive. Thus, we must acknowledge this uncertainty, combating misinformation,
myths, misperceptions, and conspiracy theories that can influence vaccine acceptance
behavior. Further, people living in rural areas believed COVID-19 infection was a
disease of urban areas, and thus showed unwillingness to vaccination. They had more
belief in their local cultural practices and had several myths concerning social and
religious values. Interestingly, many people preferred yoga practices, regular disciplined
lifestyle, immunity boosters, and Ayurvedic medicines, above the vaccine.
The findings emphasized that there is need for clear and consistent communication
by public health experts to build public confidence in vaccination campaign. This
includes targeting women, rural people, and professionals other than health workers,
and explaining them about the severity and risk of infection and its prevention through
vaccination. All information about how vaccines work as well as how they are developed,
from recruitment to regulatory approval based on safety and efficacy, should be clearly
conveyed. Credible and culturally informed health communication is vital in influencing
positive health behaviors[15]
[18] and has been observed with respect to encouraging people to cooperate with COVID-19
control measures. Thus, involvement of the public and leaders of civic, religious,
and fraternal organizations, who are respected within various sectors of society and
local communities, as well as its supplementation with accurate information and technological
support will promote mass vaccination program.
Limitation of the Study
As the current study was conducted majorly in Uttar Pradesh, mainly (around 75%) among
educated (graduate and above) and young adults (≤30 years) using an online self-administered
questionnaire, therefore it did not have equal representatives from various economic
and occupational strata of society, which could result in bias. Thus, large-scale
studies from whole of India are needed to understand the knowledge, expectation, and
apprehension related to COVID-19 vaccine.
Conclusion
India needs to immediately rethink its strategy regarding mass vaccination rollout.
However, effective campaigns have already been initiated to explain about a vaccine's
level of effectiveness, the time needed for protection (with multiple doses, if required),
and the importance of population-wide coverage to achieve community immunity. But,
such communication strategies and techniques to be used during the ongoing pandemic
should be transparent, accurate, socially acceptable, and must focus the target groups.
It must have partnerships with community members and healthcare professionals. Regarding
this, extensive studies from the entire parts of India are needed, to understand the
knowledge, expectation, and apprehension, covering various economic and occupational
strata of society.
