JMIR PUBLIC HEALTH AND SURVEILLANCE
Bachtiger et al
Original Paper
The Impact of the COVID-19 Pandemic on the Uptake of Influenza
Vaccine: UK-Wide Observational Study
Patrik Bachtiger, MBBS, BSc, MRCP, MSc, MPH; Alexander Adamson, MSc; Ji-Jian Chow, MBBS, MRCP, MA;
Rupa Sisodia, BSc; Jennifer K Quint, MBBS, FRCP, MSc, PhD; Nicholas S Peters, MD, FRCP
National Heart & Lung Institute, Imperial College London, London, United Kingdom
Corresponding Author:
Nicholas S Peters, MD, FRCP
National Heart & Lung Institute
Imperial College London
4th Floor ICTEM Building
Hammersmith Campus, Du Cane Road
London, W12 0NN
United Kingdom
Phone: 44 020 7589 5111
Email: n.peters@imperial.ac.uk
Abstract
Background: In the face of the COVID-19 pandemic, the UK National Health Service (NHS) extended eligibility for influenza
vaccination this season to approximately 32.4 million people (48.8% of the population). Knowing the intended uptake of the
vaccine will inform supply and public health messaging to maximize vaccination.
Objective: The objective of this study was to measure the impact of the COVID-19 pandemic on the acceptance of influenza
vaccination in the 2020-2021 season, specifically focusing on people who were previously eligible but routinely declined
vaccination and newly eligible people.
Methods: Intention to receive the influenza vaccine in 2020-2021 was asked of all registrants of the largest electronic personal
health record in the NHS by a web-based questionnaire on July 31, 2020. Of those who were either newly or previously eligible
but had not previously received an influenza vaccination, multivariable logistic regression and network diagrams were used to
examine their reasons to undergo or decline vaccination.
Results: Among 6641 respondents, 945 (14.2%) were previously eligible but were not vaccinated; of these, 536 (56.7%) intended
to receive an influenza vaccination in 2020-2021, as did 466 (68.6%) of the newly eligible respondents. Intention to receive the
influenza vaccine was associated with increased age, index of multiple deprivation quintile, and considering oneself to be at high
risk from COVID-19. Among those who were eligible but not intending to be vaccinated in 2020-2021, 164/543 (30.2%) gave
reasons based on misinformation. Of the previously unvaccinated health care workers, 47/96 (49%) stated they would decline
vaccination in 2020-2021.
Conclusions: In this sample, COVID-19 has increased acceptance of influenza vaccination in previously eligible but unvaccinated
people and has motivated substantial uptake in newly eligible people. This study is essential for informing resource planning and
the need for effective messaging campaigns to address negative misconceptions, which is also necessary for COVID-19 vaccination
programs.
(JMIR Public Health Surveill 2021;7(4):e26734) doi: 10.2196/26734
KEYWORDS
COVID-19; influenza; vaccination; COVID; Pandemic; National Health Service; Health Service; flu; virus; vaccine; impact;
uptake; observational; United Kingdom; public health; intention; electronic health record
Introduction
To date, the COVID-19 pandemic has led to over 100,000 deaths
in the United Kingdom alone. With increasing regional
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outbreaks [1], substantial concern has been raised about
preparedness for a nationwide escalation of cases throughout
winter pressures in 2020-2021 [2-4]. Seasonal influenza places
the UK National Health Service (NHS) under considerable
pressure each winter, with up to 18,000 additional daily
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emergency admissions [5] and >4000 hospital beds occupied
daily by patients with influenza in 2017-2018 [6,7].
For this reason, the NHS has extended its free seasonal influenza
vaccination program for the current season to all people aged
over 50 years (previously 65 years) and to include the 11-12
years age group (previously 2-10 years) [8]; thus, an estimated
32.4 million people (48.8% of the UK population) are now
eligible [9]. In England in 2019, uptake of the influenza vaccine
among those eligible was only 70.6% [10], below the critical
75% target for effectiveness recommended by the World Health
Organization [11]. Against a background of declining numbers
over the last decade (from a peak of 74.2% in 2008-2009), the
uptake this season is not only unknown but is also completely
unpredictable. The threat of COVID-19 and the associated
publicity educating the public about viruses and vaccine
development, coupled with recent evidence that coinfection
with influenza and SARS-CoV-2 doubles mortality compared
with infection with SARS-CoV-2 alone [12] and that the
influenza vaccination may reduce incidence of life-threatening
COVID-19 disease in people aged over 65 years [13], are likely
to affect attitudes and the public health imperative of mass
uptake. With substantial concerns that higher earlier uptake of
influenza vaccination in 2020-2021 will rapidly deplete stocks
(as already reported [14]), there is still a risk that a lack of
informed planning will result in failure to meet the requirements
of this public health initiative.
Therefore, the objective of this study was to measure the impact
of the COVID-19 pandemic on the acceptance of influenza
vaccination in the 2020-2021 season, specifically focusing on
people who were previously eligible (aged over 65 years or
having an eligible comorbidity) who routinely decline
vaccination and newly eligible people (aged 50-64 years)—two
groups in which the determinants of vaccine hesitancy may
differ. These groups include those at highest risk from
COVID-19; if the influenza vaccine confers a reduced risk of
COVID-19, understanding specific covariates that relate to
vaccine hesitancy can inform public health messaging to
maximize uptake and help contend with potential double winter
pandemics of influenza and COVID-19.
Methods
Ethical Approval
The weekly questionnaire was a direct care tool for patients to
self-monitor their well-being during the COVID-19 pandemic.
Participants were not paid or otherwise compensated for
completing questionnaires. Upon review, the Imperial College
Healthcare NHS Trust Data Protection Office advised that
ethical approval for data analysis and publication was not
required. Participants gave informed consent within the CIE,
were free to opt out of receiving questionnaires at any time, and
were informed prior to completing their responses that these
would be fully anonymized and stored on secure servers before
analysis toward informing local and national health policy.
Study Participants
Participants were registrants of the Care Information Exchange
(CIE) of Imperial College Healthcare NHS Foundation Trust.
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Bachtiger et al
The CIE is the largest patient-facing electronic health record in
the United Kingdom; it is accessible by email registration for
any patient who has had an encounter at the Trust (UK-wide
population, Figure S1 in Multimedia Appendix 1). On June 5,
2020, the CIE held 57,056 registrants, of whom 34,502 were
active users, defined as having one or more logins in the
preceding month.
Participants in this study were CIE registrants receiving weekly
web-based questionnaires through the platform, starting April
9, 2020 (week 1), as a direct care tool for self-monitoring
physical, mental, and social well-being during the COVID-19
pandemic. This was the first ever such use of the CIE platform,
prompted by the immediate public health priorities to provide
patients with a tool to track their well-being and inform local
and national health policy through this exercise in participatory
epidemiology.
Questionnaire Design and Timing
A questionnaire including items on the government's expanded
influenza vaccination program was sent to participants on July
31, 2020 (week 16, Table S1 in Multimedia Appendix 1).
Applying recommendations for questionnaire design [15,16],
the question items were developed by a collaboration of experts
in qualitative research at Imperial College London,
encompassing public health, respiratory epidemiology, and
digital health, and were also informed by previous studies
[17,18]. Question items were externally peer-reviewed and
tested on lay persons (n=5) before being included. The focus
was on previous uptake of influenza vaccination, being for or
against vaccination in 2020-2021 and reasons why (unrestricted
free text responses), health worker status, and presence of
school-age children in the household. Responses from
participants regarding the presence of school-age children in
their household were also recorded. Specifically, they were
asked whether they would want any of these children to receive
the influenza vaccination if it were offered in 2020-2021. It
could not be assumed that people who were vaccinated in the
previous year would continue this habit. Subsequently, a specific
question was posed to also measure if any participants who
were vaccinated in 2019-2020 would not be vaccinated again
in 2020-2021.
Responses to items in prior questionnaires in the series were
used to complete information on participant ethnicity, additional
vaccine eligibility criteria (including chronic disease), index of
multiple deprivation (IMD) quintile (obtained from participant
postcode), health care utilization since the beginning of the
lockdown, whether the participant considered themselves at
high risk from COVID-19, experience of any COVID-19
symptoms, self-reported understanding of government advice,
anxiety related to a return to lockdown, and whether the
participant would agree to receive a COVID-19 vaccine if
available.
Inclusion and Exclusion Criteria
Participants were aged 18 years or above and were required to
have answered questionnaires capturing variables relevant to
the analysis (see the flow diagram in Figure 1) and to have
answered “no” to a question assessing whether they routinely
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received influenza vaccination. Respondents not eligible for
influenza vaccination (ie, aged <50 years) were excluded.
Participants who submitted incomplete or inconsistent responses
to the questions on influenza vaccination were excluded, as
were those who answered “prefer not to say” for ethnicity and
Bachtiger et al
who were missing responses for other variables required in the
analysis, with the exception of postcode. Responses submitted
later than 4 days from the time of the questionnaire launch were
excluded.
Figure 1. Participant inclusion flow diagram based on responses to questionnaires capturing variables required for analysis. CIE: Care Information
Exchange.
Definition of Study Groups
The analyses in this study were confined to participants who
were eligible for a free NHS influenza vaccination in 2020-2021
who indicated they had previously not routinely received it (this
group is the greatest unknown factor when planning resourcing
and targeting public health campaigns to maximize uptake).
Members of this previously unvaccinated group were either
previously eligible (main criteria up to 2019-2020 were age
over 65 years, eligible comorbidity, and working in the health
care sector) or newly eligible for the expanded 2020-2021
program (age over 50 years).
Further stratification according to whether or not the influenza
vaccine would be accepted in 2020-2021 generated four groups:
(1) Previously eligible, newly responding “yes,” (2) previously
eligible, still responding “no,” (3) newly eligible, responding
“yes,” and (4) newly eligible, responding “no.” Owing to
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inherent differences in age and comorbidity status of the
previously and newly eligible cohorts, their covariates for
willingness to receive the influenza vaccine may be different;
therefore, this stratification was maintained throughout our
analyses.
Data Analysis
Age was categorized into bands of 18-29, 30-39, 40-49, 50-59,
60-69, and 70+ years to enable easier interpretation of a potential
nonlinear relationship between age and responses to influenza
vaccination. The 10-point scale measurements of “anxiety
related to return to lockdown” and “understanding of
government messaging” were regrouped into categories of 1-2,
3-4, 5-6, 7-8, and 9-10, and ethnicity was categorized into five
groups due to low numbers in some categories. Descriptive
statistics reported for the data set are broken down according
to study group. Differences in categorical variables were
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assessed by chi-square test or by Fisher exact test where
chi-square test assumptions were violated, and differences in
continuous variables were assessed using t tests. P values <.05
were considered statistically significant.
The effects of variables of interest on the inclination to receive
an influenza vaccination were calculated using univariate and
multivariable logistic regression models, with presentation of
both to identify if results in the univariate analysis were due to
confounding by other collected variables. The relationship
between age (the only continuous variable) and the log odds of
receipt of influenza vaccination were plotted and visually
inspected. If the effect appeared to be linear, age was included
as a linear variable; otherwise, it was included as a categorical
variable. All data were analyzed in R, version 3.6.2 (R Project).
Variables with low numbers in categories were not included in
the multivariable analyses. “Acceptance of COVID-19 vaccine
if available” was deemed likely to be highly correlated with
“accepting influenza vaccine in 2020-2021” and was not
included in multivariable models to enable greater interpretation
of other predictors. Multicollinearity was assessed by calculation
of the variance inflation factor (VIF), and variables with a VIF
>5 (indicating substantial multicollinearity) were removed from
the model.
Each participant not routinely receiving influenza vaccination,
whether previously or newly eligible, was asked to qualify their
yes/no response to whether they would accept vaccination in
2020-2021 using a free text response option. Three researchers,
blinded to the responses on vaccine acceptance, each
independently coded the content of 100 responses according to
multiple prospectively identified themes that could co-occur.
A consensus was then reached to define the main themes for
coding the remaining responses. For example, “I don’t see the
point because I’ve never had flu [influenza]” was coded as
“unnecessary” and “not had flu before.” A full list of the themes
with examples is available in Table S2 in Multimedia Appendix
1.
Using this codified qualitative data, a network diagram [19,20]
was generated for each of the four groups using the Networkx
package in Python, version 3.7. Dimensions of centrality and
overall topography of the nodes were not applicable; thus, the
network was laid out in a comprehensible circular “shell”
arrangement. Each diagram was limited to the 10 most
represented themes within each group’s responses. Nodes were
color-coded to reflect positive, negative, and neutral sentiments
of the themes. Separately, reasons for health care workers’
continued nonvaccination in 2020-2021 were reported
descriptively.
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Dissemination to Participants and Related Patient and
Public Communities
We plan to disseminate the findings of this study to participants
in the Imperial College Healthcare NHS Trust’s annual
web-based newsletter.
Results
Sample Characteristics
Among respondents aged ≥18 years, 6641 completed the week
16 questionnaire on influenza vaccination in the predefined time
period and the requisite previous questionnaires to complete
the baseline characteristics (Figure 1). Of these, 208 (3.1%)
were missing answers to one or more essential variables and
were removed, leaving 6433 complete responses. The total
number of previously eligible but unvaccinated (n=945) and
newly eligible but unvaccinated (n=679) participants was 1624
(see Figure 1 for details).
Of the vaccinated and unvaccinated previously eligible
participants, those who had previously declined vaccination
were more likely to be younger (median age 61 years, IQR
51-67, vs median age 67 years, IQR 58-73, P<.001), female
(520/945, 55.0%, vs 1727/3696, 46.7%, P<.001), have chronic
neurological disease (102/945, 10.8%, vs 241/3696, 6.5%,
P<.001), work in the health sector (96/945, 10.2%, vs 287/3696,
7.8%, P=.02), and be in a lower IMD quintile (P=.03), and they
were less likely to have chronic respiratory disease (137/945,
14.5%, vs 757/3696, 20.5%, P<.001) or chronic heart disease
(66/945, 7.0%, vs 757/3696, 12.2%, P<.001) compared to those
who were previously eligible and received the vaccine. Of the
newly eligible participants, when compared with those who had
received the vaccine despite being ineligible by NHS criteria,
those who had not received the vaccine were more likely to be
younger (mean age 57 years, IQR 54-61, vs median age 59
years, IQR 55-63) and in a lower IMD quintile (Table S3,
Multimedia Appendix 1). Among all respondents who indicated
having received the influenza vaccine in 2019-2020, 309/6867
(4.5%) responded that they did not intend to repeat this in
2020-2021.
Change in Acceptance and Uptake of Influenza Vaccine
in 2020-2021
Summary statistics for the groups broken down according to
vaccine eligibility and acceptance of the influenza vaccine in
2020-2021 are shown in Table 1. Of those previously eligible
but routinely not vaccinated, 536 (56.7%) intended to be
vaccinated in 2020-2021, increasing the vaccination rate in the
entire previously eligible cohort from 79.6% to 91.2%. Among
the newly eligible, 466 (68.6%) reported they would accept
vaccination in 2020-2021.
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Bachtiger et al
Table 1. Characteristics of the study participants (N=1624) based on UK-wide responses to web-based questionnaires administered through Care
Information Exchange (influenza-related questionnaire sent July 31, 2020). Baseline demographics and questionnaire responses of all participants
previously not routinely receiving influenza vaccination are grouped by previously eligible but nonvaccinated and newly eligible, further stratified by
acceptance (yes/no) of influenza vaccination in 2020-2021.
Characteristic
Value
Previously eligible and
Previously eligible and
Newly eligible and plans
plans to receive the influen- does not plan to receive the to receive the influenza
za vaccine (n=536, 56.7%) influenza vaccine (n=409, vaccine (n=466, 68.6%)
43.3%)
Newly eligible and does not
plan to receive the influenza
vaccine (n=213, 31.4%)
62.0 (51.0-67.0)
60.0 (49.0-68.0)
58.0 (55.0-61.8)
56.0 (53.0-60.0)
Male
248 (46.3)
177 (43.3)
214 (45.9)
69 (32.4)
Female
288 (53.7)
232 (56.7)
252 (54.1)
144 (67.6)
White
453 (84.5)
320 (78.2)
415 (89.1)
181 (85.0)
Asian
36 (6.7)
39 (9.5)
19 (4.1)
13 (6.1)
Black
15 (2.8)
20 (4.9)
13 (2.8)
9 (4.2)
Mixed
8 (1.5)
6 (1.5)
6 (1.3)
2 (.9)
Other
24 (4.5)
24 (5.9)
13 (2.8)
8 (3.8)
Eligible disease, n (%)
368 (68.7)
282 (68.9)
N/Aa
N/A
Chronic respiratory disease, n
(%)
71 (13.2)
66 (16.1)
N/A
N/A
Chronic heart disease, n (%)
40 (7.5)
26 (6.4)
N/A
N/A
Chronic kidney disease, n (%)
25 (4.7)
23 (5.6)
N/A
N/A
Chronic liver disease, n (%)
15 (2.8)
11 (2.7)
N/A
N/A
Chronic neurological disease, n
(%)
48 (9.0)
54 (13.2)
N/A
N/A
Immunocompromised, n (%)
196 (36.6)
137 (33.5)
N/A
N/A
Other eligible comorbidity, n (%) 103 (19.2)
93 (22.7)
N/A
N/A
Health sector employee, n (%)
49 (12.0)
N/A
N/A
Age, median (IQR)
Sex, n (%)
Ethnicity, n (%)
47 (8.8)
Index of multiple deprivation, n (%)
1
34 (6.3)
31 (7.6)
17 (3.6)
14 (6.6)
2
78 (14.6)
64 (15.6)
69 (14.8)
36 (16.9)
3
107 (20.0)
59 (14.4)
94 (20.2)
29 (13.6)
4
85 (15.9)
55 (13.4)
87 (18.7)
28 (13.1)
5
79 (14.7)
44 (10.8)
57 (12.2)
15 (7.0)
Missing
153 (28.5)
156 (38.1)
142 (30.5)
91 (42.7)
None
91 (17.0)
89 (21.8)
145 (31.1)
80 (37.6)
Any
445 (83.0)
320 (78.2)
321 (68.9)
133 (62.4)
346 (64.6)
267 (65.3)
140 (30.0)
41 (19.2)
Health care utilization, n (%)
Considers self at high risk from
COVID-19, n (%)
Understanding of government messaging (score from 1-10) , n (%)
1-2
31 (5.8)
34 (8.3)
48 (10.3)
16 (7.5)
3-4
69 (12.9)
48 (11.7)
65 (13.9)
24 (11.3)
5-6
138 (25.7)
93 (22.7)
107 (23.0)
53 (24.9)
7-8
190 (35.4)
133 (32.5)
159 (34.1)
72 (33.8)
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Characteristic
9-10
Bachtiger et al
Value
Previously eligible and
Previously eligible and
Newly eligible and plans
plans to receive the influen- does not plan to receive the to receive the influenza
za vaccine (n=536, 56.7%) influenza vaccine (n=409, vaccine (n=466, 68.6%)
43.3%)
Newly eligible and does not
plan to receive the influenza
vaccine (n=213, 31.4%)
108 (20.1)
87 (18.7)
48 (22.5)
101 (24.7)
Anxiety related to return to lockdown (score from 1-10) , n (%)
1-2
87 (16.2)
85 (20.8)
76 (16.3)
50 (23.5)
3-4
90 (16.8)
59 (14.4)
85 (18.2)
35 (16.4)
5-6
149 (27.8)
111 (27.1)
127 (27.3)
48 (22.5)
7-8
150 (28.0)
105 (25.7)
130 (27.9)
50 (23.5)
9-10
60 (11.2)
49 (12.0)
48 (10.3)
30 (14.1)
Acceptance of COVID-19 vaccine if available , n (%)
a
Not sure
100 (18.7)
159 (38.9)
72 (15.5)
85 (39.9)
No
35 (6.5)
117 (28.6)
25 (5.4)
38 (17.8)
Yes
401 (74.8)
133 (32.5)
369 (79.2)
90 (42.3)
N/A: not applicable.
Predictors of Willingness to Receive Influenza
Vaccination
In the univariate analysis (Tables 2 and 3), willingness to receive
a COVID-19 vaccine was associated with willingness to receive
an influenza vaccination in 2020-2021 in both groups compared
to those who were unsure (odds ratio [OR] 4.79, 95% CI
3.50-6.61, vs OR 4.84, 95% CI 3.29-7.17). Among respondents
who would newly accept influenza vaccination, of those who
were previously eligible and newly eligible, 401/536 (74.8%)
and 369/466 (79.2%), respectively, responded they would accept
a COVID-19 vaccination, compared to 133/409 (32.5%) and
90/213 (42.3%) of those declining the influenza vaccine.
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In respondents who were previously eligible, answering “no”
in response to whether they would receive a COVID-19
vaccination if offered was associated with a lower likelihood
of wanting to receive the influenza vaccination in 2020-2021
(OR 0.48, 95% CI 0.30-0.74), as was having a chronic
neurological disease (OR 0.65, 95% CI 0.43-0.98). Although
people aged 60-69 years were more likely to respond “yes” than
those aged ≥70 years (OR 1.48, 95% CI 1.02-2.14), no clear
effect of age was found in people below the age of 60 years.
The multivariable analysis (Tables 2 and 3) resulted in few
substantial changes to effect estimates, with the exception of
age, for which all estimates shifted upward (showing a stronger
association with an increased likelihood of answering “yes”
after adjustment for other variables).
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Table 2. Unadjusted and adjusted logistic regressions to predict a “yes” response for participants who would accept an influenza vaccine in 2020-2021
and who were previously eligible but did not routinely receive influenza vaccination.
Unadjusted odds ratio (95% CI)
Adjusteda odds ratio (95% CI)
18-29
1.99 (0.85-5.06)
2.53 (1.00-6.89)
30-39
0.83 (0.46-1.49)
1.20 (0.62-2.31)
40-49
0.86 (0.54-1.35)
1.17 (0.70-1.95)
50-59
1.11 (0.75-1.66)
1.42 (0.90-2.25)
60-69
1.48 (1.02-2.14)
1.61 (1.09-2.37)
0.89 (0.68-1.15)
0.93 (0.70-1.23)
Asian
0.65 (0.40-1.05)
0.71 (0.43-1.18)
Black
0.53 (0.26-1.05)
0.58 (0.27-1.18)
Mixed
0.94 (0.32-2.89)
1.09 (0.36-3.50)
Other
0.71 (0.39-1.27)
0.71 (0.39-1.31)
Chronic respiratory disease
0.79 (0.55-1.14)
0.78 (0.52-1.18)
Chronic heart disease
1.19 (0.72-2.00)
1.03 (0.60-1.79)
Chronic kidney disease
0.82 (0.46-1.48)
0.71 (0.38-1.33)
Chronic liver disease
1.04 (0.48-2.35)
0.94 (0.41-2.22)
Chronic neurological disease
0.65 (0.43-0.98)
0.62 (0.38-0.99)
Immunocompromised
1.14 (0.87-1.50)
0.95 (0.69-1.32)
Other comorbidity
0.81 (0.59-1.11)
0.79 (0.56-1.10)
Health sector employee
0.71 (0.46-1.08)
0.76 (0.46-1.24)
2
1.11 (0.62-2.00)
1.09 (0.59-2.01)
3
1.65 (0.92-2.96)
1.54 (0.84-2.82)
4
1.41 (0.78-2.55)
1.29 (0.70 to 2.40)
5
1.64 (0.89 to 3.02)
1.59 (0.84-3.00)
Missing
0.89 (0.52-1.53)
0.91 (0.52-1.59)
Health care utilization
1.36 (0.98-1.88)
1.41 (0.99-2.01)
Considering self at high risk from COVID-19
0.97 (0.74-1.27)
1.03 (0.76-1.39)
Characteristic
Age (years; reference category: ≥70)
Female sex
Ethnicity (reference category: White)
Comorbidity
Index of multiple deprivation quintile (reference category: 1)
Understanding of government messaging (score from 1-10; reference category: 5-6)
1-2
0.61 (0.35-1.07)
0.59 (0.33-1.05)
3-4
0.97 (0.62-1.53)
0.89 (0.56-1.43)
7-8
0.96 (0.68-1.36)
0.92 (0.64-1.31)
9-10
0.72 (0.49-1.05)
0.75 (0.50-1.11)
Anxiety related to return to lockdown (score from 1-10; reference category: 5-6)
1-2
0.76 (0.52-1.12)
0.90 (0.60-1.37)
3-4
1.14 (0.76-1.72)
1.14 (0.74-1.75)
7-8
1.06 (0.75-1.51)
1.07 (0.74-1.54)
9-10
0.91 (0.58-1.43)
1.06 (0.66-1.71)
Acceptance of COVID-19 vaccine if available (reference category: “unsure”)
No
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0.48 (0.30-0.74)
N/Ab
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Characteristic
Yes
Bachtiger et al
Unadjusted odds ratio (95% CI)
Adjusteda odds ratio (95% CI)
4.79 (3.50-6.61)
N/A
a
Adjusted odds ratios were adjusted for every other variable in the model (age, sex, ethnicity, disease, index of multiple deprivation quintile, health care
utilization, considering oneself at high risk for COVID-19, undertaking any COVID-19 test, believing oneself to have had COVID-19, understanding
of government advice, anxiety related to a return to lockdown).
b
N/A: not applicable.
Table 3. Unadjusted and adjusted logistic regressions to predict a “yes” response for participants who would accept an influenza vaccine in 2020-2021
and who were newly eligible and not routinely vaccinated.
Characteristic
Unadjusted odds ratio (95% CI)
Adjusteda odds ratio (95% CI)
Age
1.07 (1.03-1.12)
1.06 (1.01-1.10)
Female
0.56 (0.40-0.79)
0.54 (0.37-0.77)
Asian
0.64 (0.31-1.35)
0.57 (0.26-1.29)
Black
0.63 (0.27-1.55)
0.76 (0.30-2.01)
Mixed
1.31 (0.30-8.99)
0.89 (0.17-6.63)
Other
0.71 (0.29-1.82)
0.77 (0.29-2.17)
Other comorbidity
1.17 (0.79-1.76)
1.01 (0.66-1.59)
2
1.58 (0.69-3.57)
1.60 (0.66-3.85)
3
2.67 (1.17-6.08)
2.51 (1.02-6.13)
4
2.56 (1.11-5.86)
2.63 (1.07-6.45)
5
3.13 (1.26-7.86)
2.83 (1.07-7.59)
Missing
1.29 (0.60-2.73)
1.16 (0.51-2.63)
Health care utilization
1.33 (0.95-1.87)
1.45 (1.00-2.11)
Considering self at high risk for COVID-19
1.80 (1.22-2.70)
2.00 (1.29-3.16)
1-2
1.49 (0.78-2.92)
1.46 (0.73-3.02)
3-4
1.34 (0.76-2.40)
1.24 (0.68-2.30)
7-8
1.09 (0.71-1.68)
0.98 (0.62-1.56)
9-10
0.90 (0.55-1.46)
1.00 (0.59-1.68)
1-2
0.57 (0.35-0.93)
0.53 (0.31-0.90)
3-4
0.92 (0.55-1.54)
0.95 (0.55-1.65)
7-8
0.98 (0.62-1.57)
0.93 (0.57-1.53)
9-10
0.60 (0.34-1.07)
0.56 (0.30-1.05)
No
0.78 (0.43-1.40)
N/A
Yes
4.84 (3.29-7.17)
N/A
Index of multiple deprivation quintile
Understanding government messaging (score from 1-10)
Anxiety related to return to lockdown (score from 1-10)
Acceptance of COVID-19 vaccine if available
a
Adjusted odds ratios were adjusted for every other variable in the model (age, sex, ethnicity, disease, index of multiple deprivation quintile, health care
utilization, considering oneself at high risk for COVID-19, undertaking any COVID-19 test, believing oneself to have had COVID-19, understanding
of government advice, anxiety related to a return to lockdown).
b
N/A: not applicable.
In respondents who became newly eligible to receive the
influenza vaccine, there was an association between increased
age (OR for 1-year increase in age 1.07, 95% CI 1.03-1.12),
IMD quintile, and considering oneself at high risk from
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COVID-19 (OR 1.80, 95% CI 1.22-2.70) and answering “yes”
to receiving the influenza vaccine if offered. Female respondents
were less likely to answer “yes” (OR 0.56, 95% CI 0.40-0.79),
as were those who rated their anxiety about the lifting of
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lockdown as 1-2 (low anxiety) (OR 0.57, 95% CI 0.35-0.93),
compared to those who rated it 5-6. Multivariable analysis
resulted in minimal changes to the estimates, demonstrating
that the univariate associations found were not due to
confounding by the other variables included in the model.
Subgroup Analyses of Health Care Workers and
Households with School-Age Children
In the cohort of previously unvaccinated health care workers
(n=96), 49 (51.0%) stated they would accept the influenza
vaccine in 2020-2021, compared to 47 (49.9%) who would
continue to decline it. The question items pertaining to influenza
vaccination of school-age children was answered by 1419/1624
participants (87.4%). Among these, 150/1419 (10.6%) responded
that they had school-age children in their household and
answered “yes” or “no” to whether they would want any children
to be vaccinated in 2020-2021 if offered. Among the 71
participants who were previously eligible but not routinely
vaccinated, 33/40 (83%) of those who would accept vaccination
in 2020-2021 would also vaccinate their children, compared to
8/31 (26%) of those who would not accept the influenza vaccine
for themselves (Fisher exact test, P<.001). Among the 79
participants who were previously unvaccinated and newly
eligible in 2020-2021, 46/56 (82%) of those who would receive
an influenza vaccine this year would want their child to have it
also, compared to 10/23 (44%) of those who would not get the
influenza vaccine for themselves (Fisher exact test, P=.001).
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Bachtiger et al
Network Diagram of Reasons For or Against
Vaccination
A free text response qualifying why participants would or would
not accept influenza vaccination in 2020-2021 was submitted
by 834/945 (88.3%) from the previously eligible, unvaccinated
group and 619/679 (91.2%) of the newly eligible group. These
were coded according to 45 themes (the full list is provided in
Table S2 in Multimedia Appendix 1). Figure 2 displays network
diagrams for the 10 most common themes for each group.
Among the previously eligible respondents, the three most
frequent themes among those newly accepting influenza
vaccination in 2020-2021 were “precaution for myself”
(197/478, 41.2%), “COVID-19” (131/478, 27.4%), and “health
reasons” (76/478, 15.9%); among the newly eligible
respondents, the three most frequent themes were “precaution
for myself” (199/432, 46.1%), “COVID-19” (117/432, 27.1%)
and “age” (103/432, 23.9). “Precaution for myself” was qualified
by “COVID-19” in 71/197 (36.0%) and 58/199 (29.1%)
participants.
For the previously and newly eligible groups declining
vaccination, the three most frequent themes were “unnecessary”
(88/356, 24.7%), “vaccine doesn’t work” (53/356, 14.9%), and
“makes me unwell” (54/356, 15.2%), and “unnecessary”
(87/187, 46.5%), “not had flu before” (30/188, 16.0%) and
“vaccine doesn’t work” (19/186, 10.2%), respectively.
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Bachtiger et al
Figure 2. Study participants (N=1624) from UK-wide responses to web-based questionnaires administered through Care Information Exchange
(influenza-related questionnaire sent July 31, 2020); network diagram of free-text responses (n=1453, 89.5%). Responses from previously eligible
respondents who had previously not accepted the influenza vaccine but would (A) accept it in 2020-2021 (n=478) or (B) continue to decline it (n=356);
responses from newly eligible participants who would (C) accept vaccination (n=432) or (D) decline it (n=187). A connecting line (edge) between nodes
implies at least one response in which themes of connected nodes co-occurred; the thickness of the line corresponds to the frequency of co-occurrence.
Flu: influenza; NHS: National Health Service.
Reasons for Continued Nonvaccination Among Health
Care Workers
Of the health care workers reporting previous nonvaccination,
89/104 (85.6%) submitted qualifying responses, among whom
47 were from those newly accepting and 42 continuing to
decline vaccination in 2020-2021. For the former, “precaution
for myself” (17/47, 36.2%), “COVID-19” (16/47, 34.0%) and
“health reasons” (8/47, 17.0%) were the most cited reasons. In
those continuing to decline, most frequent reasons were “gives
me flu” (10/42, 23.8%), “vaccine doesn’t work” (8/42, 19.0%)
and “unnecessary” (6/42, 14.3%).
Discussion
Principal Findings
Due to the threat of COVID-19 and the associated publicity
educating the public about viruses and vaccine development,
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following a decade of declining numbers, uptake of the influenza
vaccine this year is both unknown and unpredictable. With early
reports that higher uptake of influenza vaccination will rapidly
deplete stocks [14], there is yet again a threat of a lack of
informed planning resulting in failure to meet the demands of
a public health initiative. Our findings, including that >90% of
previously and 70% of newly eligible participants want
vaccination, provide strong evidence to inform planning and
public health messaging to maximize vaccination.
The finding that coinfection doubles the risk of death [12] was
published after collection of the data described in this study;
however, our results indicate that specific avoidance of
“synchronous influenza and COVID-19” and “differentiating
influenza from COVID-19” were already motivators for new
influenza vaccine uptake for the 2020-2021 season. This
suggests that the UK public already perceived the risk from a
convergence of both viruses. Indeed, in this study, increasing
age, IMD quartile, and higher levels of anxiety were associated
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with increased likelihood of accepting vaccination among the
newly eligible; however, the strongest association was
considering oneself at high risk from COVID-19, which was
associated with an 80% increase in uptake. This relates to our
observation in the network diagram that the common reason of
“precaution for myself” was frequently qualified by
“COVID-19” in both of the groups accepting vaccination.
Among those not accepting vaccination, the newly eligible
appear to be predominantly motivated by a belief that
vaccination is “unnecessary,” contrasting with previously
eligible respondents, who gave substantially more misinformed
reasons (eg, “gives me flu”), presumably by virtue of having
more experience and exposure to vaccination and therefore
having more time to develop misinformed beliefs.
Our finding that previously eligible but unvaccinated
respondents in the 60-69 years age group were 50% more likely
to respond “yes” to vaccination in 2021 than those aged ≥70
years is perhaps unsurprising, given that the latter are at highest
risk if exposed—as in, by leaving home to receive an influenza
vaccine—to COVID-19. The observation that chronic
neurological disease was associated with more vaccine hesitancy
may be explained by patients receiving specific therapy (such
as for multiple sclerosis) contraindicating influenza vaccination.
Childhood influenza vaccination in the United Kingdom has
never reached its 65% uptake target (60.8% in 2018-2019) [21],
and our study suggests part of the narrative around unvaccinated
children is that adults in their household may also be hesitant
to receive an influenza vaccine themselves. Perhaps more
concerning is that children may assume their parents’ attitudes
to vaccination in later life [19]. Public trust is critical for
confidence in vaccination programs [20,22], which must be
underpinned by clear messaging campaigns; this is particularly
relevant for newly eligible people who, as shown in our study,
express fewer misinformed views around the influenza vaccine.
Media coverage during the current global health crisis has led
to an unprecedented level of education of the general public on
respiratory viruses and vaccine development and associated
trust in scientific reporting [23,24]. However, social media can
potentially be damaging by proliferating misinformation [25].
Collectively, misinformed themes of “makes me unwell,” “gives
me flu,” and “vaccine doesn’t work” were present across 35.1%
and 20.9% of responses in previously unvaccinated and newly
eligible respondents, respectively. Governmental messaging
campaigns to address misconceptions such as these are doubly
important because they have the potential not only to increase
uptake of the influenza vaccine but also to prevent these same
misconceptions from undermining the uptake of a future
COVID-19 vaccine. Transparency in how a vaccine is being
developed must be accompanied by assurances that safety and
efficacy are critical and that problematic vaccines will be
avoided, which might otherwise diminish public trust [26].
This study suggests that the UK population continues to feel a
sense of duty to the NHS; 8.5% of those newly accepting
vaccination cited “protect the NHS” as their reason. This
messaging, which was used to encourage adherence to the
government’s stay-at-home policy during the height of the first
wave of the pandemic [27], could also be leveraged to increase
uptake of influenza and COVID-19 vaccines. It is noteworthy
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Bachtiger et al
in the context of the general public’s motivation to protect the
NHS that 50% of health care professionals in this sample who
previously refused the influenza vaccine still do not intend to
receive it. Confirmation of this finding requires further study
of larger cohorts of such professionals.
Limitations
This study has several limitations. These results are only
indicative; whether the participants would maintain their
responses when faced with influenza vaccination is uncertain.
Intentionality may not always translate to actual vaccine uptake.
Although one study of US adults aged over 18 years suggested
that just over half of respondents who declared intending to
receive an influenza vaccine followed through [28],
follow-through in the population aged over 50 years in our study
is likely to be significantly higher [29]. The advantage of this
study using the CIE of the NHS to collect responses is an
inherent ability to link to both primary and secondary care data,
thereby enabling us to further progress this work at the end of
the 2020-2021 influenza season by measuring how intentionality
translated to actual uptake.
Use of the CIE, to which all participants were registered, implies
both a higher disease burden and better agency over one’s health,
and notably, the previously eligible population had a higher
baseline uptake (79.6%) than last year’s national average
(70.6%). This is more broadly indicative of a sample that is not
fully representative of the general population, although our data
do suggest that some of the lower IMD quintiles were adequately
captured. Despite a representative distribution of questionnaires,
ethnic minority groups were underrepresented among the
respondents, limiting the generalizability of the acceptance rates
and their reasons for and against new uptake. Our study could
not fully consider potential mismatches between those eligible
for influenza vaccination and those at highest risk of severe
COVID-19. By also examining changes in vaccine hesitancy
in those ineligible for influenza vaccination but nonetheless at
higher risk of COVID-19, such as people who are nonmorbidly
obese [30], we could inform policy for further extension of the
influenza vaccine criteria to include such individuals. The
time-sensitive need to accumulate these data prohibited the
generation of question items using, for example, in-depth Delphi
methods and full psychometric evaluation of validity; however,
an expert team including patient representation designed the
questionnaire.
Conclusion
In the sample in this study, the COVID-19 pandemic has
influenced increased acceptance of influenza vaccination in
2020-2021 in people who were previously eligible for the
vaccine but routinely unvaccinated, and it is also a major driver
of acceptance among people who are newly eligible for the
vaccine. This high anticipated demand requires appropriate
planning but can be further increased with effective messaging
campaigns to address negative misconceptions about influenza
vaccination, which may also help prepare for future COVID-19
vaccination. Maximizing vaccination requires informed planning
of vaccine supply and public health messaging if we are to avoid
failure once again of an essential public health response to the
COVID-19 pandemic this winter.
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Data Availability
Imperial College Healthcare NHS Trust is the data controller.
Bachtiger et al
The data sets analyzed in this study are not publicly available
but can be shared for scientific collaboration subject to meeting
requirements of the institution’s data protection policy.
Acknowledgments
We are grateful to colleagues from Faculty of Medicine, School of Public Health, and Institute of Global Health Innovation at
Imperial College London for help with the questionnaires, and to the project team for Imperial NHS Care Information Exchange,
including Felicia Opoku and John Kelly. Funding was received from Imperial Health Charity, Imperial Biomedical Research
Centre of the National Institute of Health Research, British Heart Foundation, Pfizer Independent Grants, NHSX, and Rosetrees
Foundation.
Authors' Contributions
PB contributed to the study design, data collection, literature review, data analysis, figures, and writing of the paper. AA contributed
to the study design, literature review, figures, data analysis, and writing. JJC contributed to the figures, data analysis, and writing.
RS contributed to the figures, data analysis, and writing. JKQ contributed to the study design, literature review, data analysis,
figures, and writing. NSP contributed to the study design, data collection, literature review, data analysis, figures, and writing.
NSP is the guarantor. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting
the criteria have been omitted. The lead author affirms that this manuscript is an honest, accurate, and transparent account of the
study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as
planned (and, if relevant, registered) have been explained.
Conflicts of Interest
None declared.
Multimedia Appendix 1
Supplementary materials.
[DOCX File , 170 KB-Multimedia Appendix 1]
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Abbreviations
CIE: Care Information Exchange
IMD: index of multiple deprivation
NHS: National Health Service
OR: odds ratio
VIF: variance inflation factor
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Bachtiger et al
Edited by T Sanchez; submitted 23.12.20; peer-reviewed by A Grow, M Das, Y Cai; comments to author 20.01.21; revised version
received 07.02.21; accepted 18.02.21; published 14.04.21
Please cite as:
Bachtiger P, Adamson A, Chow JJ, Sisodia R, Quint JK, Peters NS
The Impact of the COVID-19 Pandemic on the Uptake of Influenza Vaccine: UK-Wide Observational Study
JMIR Public Health Surveill 2021;7(4):e26734
URL: https://publichealth.jmir.org/2021/4/e26734
doi: 10.2196/26734
PMID: 33651708
©Patrik Bachtiger, Alexander Adamson, Ji-Jian Chow, Rupa Sisodia, Jennifer K Quint, Nicholas S Peters. Originally published
in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 14.04.2021. This is an open-access article distributed under
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