Open Forum Infectious Diseases

MAJOR ARTICLE

Effectiveness of the Coronavirus Disease 2019 Bivalent

Vaccine
Nabin K. Shrestha,1, Patrick C. Burke,2 Amy S. Nowacki,3, James F. Simon,4 Amanda Hagen,5 and Steven M. Gordon1
1
Department of Infectious Diseases, Cleveland Clinic, Cleveland, Ohio, USA, 2Infection Prevention, Cleveland Clinic, Cleveland, Ohio, USA, 3Quantitative Health Sciences, Cleveland Clinic, Cleveland,
Ohio, USA, 4Enterprise Business Intelligence, Cleveland Clinic, Cleveland, Ohio, USA, and 5Occupational Health, Cleveland Clinic, Cleveland, Ohio, USA

Background. The purpose of this study was to evaluate whether a bivalent coronavirus disease 2019 (COVID-19) vaccine
protects against COVID-19.

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Methods. The study included employees of Cleveland Clinic in employment when the bivalent COVID-19 vaccine first became
available. Cumulative incidence of COVID-19 over the following 26 weeks was examined. Protection provided by vaccination
(analyzed as a time-dependent covariate) was evaluated using Cox proportional hazards regression, with change in dominant
circulating lineages over time accounted for by time-dependent coefficients. The analysis was adjusted for the pandemic phase
when the last prior COVID-19 episode occurred and the number of prior vaccine doses.
Results. Among 51 017 employees, COVID-19 occurred in 4424 (8.7%) during the study. In multivariable analysis, the bivalent-
vaccinated state was associated with lower risk of COVID-19 during the BA.4/5-dominant (hazard ratio, 0.71 [95% confidence
interval, .63–79]) and the BQ-dominant (0.80 [.69–.94]) phases, but decreased risk was not found during the XBB-dominant
phase (0.96 [.82–.1.12]). The estimated vaccine effectiveness was 29% (95% confidence interval, 21%–37%), 20% (6%–31%), and
4% (−12% to 18%), during the BA.4/5-, BQ-, and XBB-dominant phases, respectively. The risk of COVID-19 also increased
with time since the most recent prior COVID-19 episode and with the number of vaccine doses previously received.
Conclusions. The bivalent COVID-19 vaccine given to working-aged adults afforded modest protection overall against
COVID-19 while the BA.4/5 lineages were the dominant circulating strains, afforded less protection when the BQ lineages were
dominant, and effectiveness was not demonstrated when the XBB lineages were dominant.
Keywords. COVID-19; SARS-CoV-2; bivalent vaccine; effectiveness; vaccines.

When the original messenger RNA (mRNA) coronavirus response among the human population, led to the emergence
disease 2019 (COVID-19) vaccines first became available in and spread of SARS-CoV-2 variants. Despite this, for almost 2
2020, there was ample evidence of efficacy from randomized years since the onset of the pandemic, those previously infected
clinical trials [1, 2].Vaccine effectiveness was subsequently con­ or vaccinated continued to have substantial protection against re­
firmed by clinical effectiveness data in the real world outside of infection by virtue of natural or vaccine-induced immunity [6].
clinical trials [3, 4], including an effectiveness estimate of 97% The arrival of the Omicron variant in December 2021 brought
among employees within our own healthcare system [5]. This a significant change to the immune protection landscape.
was when the human population had just encountered the Previously infected or vaccinated individuals were no longer pro­
novel severe acute respiratory syndrome coronavirus 2 tected from COVID-19 [6]. Vaccine boosting provided some
(SARS-CoV-2) virus, and the pathogen had exacted a high protection against the Omicron variant [7, 8], but the degree of
morbidity and mortality burden across the world. The vaccines protection was not near that of the original vaccine against the
were amazingly effective in preventing COVID-19, saved a pre-Omicron variants of SARS-CoV-2 [8]. After the emergence
large number of lives, and changed the impact of the pandemic. of the Omicron variant, prior infection with an earlier lineage
Continued acquisition of mutations in the virus, from natu­ of the Omicron variant protected against subsequent infection
ral evolution in response to interaction with the immune with a subsequent lineage [9], but such protection appeared to
wear off within a few months [10]. During the Omicron phase
Received 21 December 2022; editorial decision 12 April 2023; accepted 17 April 2023; pub­ of the pandemic, protection from vaccine-induced immunity de­
lished online 19 April 2023 creased within a few months after vaccine boosting [8].
Correspondence: Nabin K. Shrestha, MD, MPH, Department of Infectious Diseases,
Cleveland Clinic, 9500 Euclid Ave/G-21, Cleveland, OH 44195 ([email protected]); Steven
Recognition that the original COVID-19 vaccines provided
M. Gordon, MD, Department of Infectious Diseases, Cleveland Clinic, 9500 Euclid Ave/G-21, much less protection after the emergence of the Omicron var­
Cleveland, OH 44195 ([email protected]).
iant spurred efforts to produce newer vaccines that were more
Open Forum Infectious Diseases®
© Crown copyright 2023. This Open Access article contains public sector information licensed effective. These efforts culminated in the approval by the US
under the Open Government Licence v3.0 (http://www.nationalarchives.gov.uk/doc/open-
Food and Drug Administration, on 31 August 2022, of bivalent
government-licence/version/3/).
https://doi.org/10.1093/ofid/ofad209 COVID-19 mRNA vaccines, which encoded antigens

COVID-19 Bivalent Vaccine Effectiveness • OFID • 1

represented in the original vaccine as well as antigens repre­ COVID-19 testing became available in our institution, and
senting the BA.4/5 lineages of the Omicron variant. Given pandemic hires if hired on or after that date.
the demonstrated safety of the earlier mRNA vaccines and Prior COVID-19 was defined as a positive nucleic acid am­
the perceived urgency of need of a more effective preventive plification test (NAAT) result for SARS-CoV-2 any time before
tool, these vaccines were approved without demonstration of the study start date. The date of infection for a prior episode of
effectiveness in clinical studies. The purpose of this study was COVID-19 was the date of the first positive test for that episode
to evaluate whether the bivalent COVID-19 vaccine protects of illness. A positive test >90 days after the date of a previous
against COVID-19. infection was considered a new episode of infection. Since
the health system never had a requirement for systematic
METHODS asymptomatic employee test screening, most positive test re­
sults would have been from tests done to evaluate suspicious
Study Design
symptoms. Some would have been tests done to evaluate
This was a retrospective cohort study conducted at the
known exposures or for preoperative or preprocedural screen­

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Cleveland Clinic Health System (Cleveland, Ohio) in the
ing. The pandemic phase (pre-Omicron or Omicron) during
United States.
which a study participant had his or her last prior episode of
Patient Consent Statement
COVID-19 was also collected as a variable, based on which var­
The study was approved by the Cleveland Clinic Institutional iant/lineages accounted for >50% of infections in Ohio at the
Review Board as exempt research (IRB no. 22–917). Waivers time [11].
of informed consent and of HIPAA (Health Insurance
Outcome
Portability and Accountability Act) authorization were ap­
proved to allow the research team access to the required data. The study outcome was time to COVID-19, the latter defined as
a positive NAAT result for SARS-CoV-2 any time after the
Setting study start date. Outcomes were followed up until 14 March
Since the arrival of the COVID-19 pandemic at Cleveland 2023, allowing for evaluation of outcomes up to 26 weeks
Clinic in March 2020, employee access to testing has been a pri­ from the study start date.
ority. Voluntary vaccination for COVID-19 began on 16
December 2020, and the monovalent mRNA vaccine as a boos­ Statistical Analysis
ter became available to employees on 5 October 2021. The bi­ A Simon-Makuch hazard plot [12] was created to compare the
valent COVID-19 mRNA vaccine was first offered to cumulative incidence of COVID-19 in the bivalent-vaccinated
employees on 12 September 2022. This date was considered and nonvaccinated states, by treating bivalent vaccination as a
the study start date. The mix of circulating variants of time-dependent covariate. Study participants were considered
SARS-CoV-2 changed over the course of the study. The major­ bivalent vaccinated 7 days after receipt of a single dose of the
ity of infections in Ohio were initially caused by the BA.4 or bivalent COVID-19 vaccine. Those whose employment was
BA.5 lineages of the Omicron variant. By mid-December terminated during the study period before they had
2022 the BQ lineages, and by mid-January 2023 the XBB line­ COVID-19 were censored on the date of termination. Curves
ages of the Omicron variant were the dominant circulating for the nonvaccinated state were based on data while the biva­
strains [11]. lent vaccination status of participants remained “nonvacci­
nated.” Curves for the bivalent-vaccinated state were based
Study Participants on data from the date the bivalent vaccination status changed
The study included Cleveland Clinic Health System employees to “vaccinated.”
in employment at any Cleveland Clinic location in Ohio on 12 Multivariable Cox proportional hazards regression models
September 2022, the day the bivalent vaccine first became avail­ were fitted to examine the association of various variables
able to employees. Those for whom age and sex were not avail­ with time to COVID-19. Bivalent vaccination was included as
able were excluded. a time-dependent covariate [13]. The study period was divided
into BA.4/5-dominant, BQ-dominant, and XBB-dominant
Variables phases, depending on which group of lineages accounted for
The covariates collected were age, sex, job location, and job type >50% of all COVID-19 infections at the time (based on variant
categorized into clinical or nonclinical, as described in our ear­ proportion data from the Centers for Disease Control and
lier studies [5–7]. Institutional data governance rules related to Prevention [CDC]) [11] and which group of lineages was
employee data limited our ability to supplement our data set most abundant in our internal sequencing data.
with additional clinical variables. Employees were considered Time-dependent coefficients were used to separate out the ef­
prepandemic hires if hired before 16 March 2020, the day fects of the bivalent vaccine during the different phases.

2 • OFID • Shrestha et al
 The primary model included all study participants. The sec­ Table 1. Baseline Characteristics of 51 017 Employees of Cleveland
ondary model included only those with prior exposure to Clinic in Ohio

SARS-CoV-2 by infection or vaccination and evaluated the ef­

Employees, No.
fect of bivalent vaccination with inclusion of time since most Characteristic (%)a
recent exposure to SARS-CoV-2 by infection or vaccination, Age in years, mean (SD) 42.3 (13.4)
to adjust for the effect of waning immunity on susceptibility Sex
to COVID-19. The possibility of multicollinearity in the models Female 38 052 (74.6)
was evaluated using variance inflation factors. The proportion­ Male 12 965 (25.4)
Location
al hazards assumption was checked using log(−log[survival])
Cleveland Clinic Main Campus 20 495 (40.2)
versus time plots. Vaccine effectiveness was calculated from Cleveland area regional hospitals 12 039 (23.6)
the hazard ratios (HRs) for bivalent vaccination in the models. Ambulatory centers 8865 (17.4)
The analysis was performed by N. K. S. and A. S. N. using the Cleveland Clinic Akron 4301 (8.4)
survival package and R software, version 4.2.2 (R Foundation Administrative centers 4141 (8.1)

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for Statistical Computing) [13–15]. Cleveland Clinic Medina 1176 (2.3)
Hire cohort
Prepandemic 34 509 (67.6)
RESULTS Pandemic 16 508 (32.4)
Human resources job classification
Of 51 982 eligible study participants, 965 (1.9%) were excluded
Clinical 25 795 (50.6)
because of missing age or sex. Of the remaining 51 017 employ­
Nonclinical 25 222 (49.4)
ees included, 3294 (6.5%) were censored during the study be­ Pandemic phase when most recent infection occurred
cause of termination of employment. By the end of the study, Not previously infected 30 331 (59.4)
13 134 (26%) had received the bivalent vaccine, which was Pre-Omicron 6969 (13.7)

the Pfizer vaccine in 11 397 (87%) and the Moderna vaccine Omicron 13 717 (26.9)
Time since most recent infection, mean (SD), d 287 (220)
in the remaining 1700. In all, 4424 employees (8.7%) acquired
No. of prior vaccine doses
COVID-19 during the 26 weeks of the study. 0 5953 (11.7)
1 2514 (4.9)
Baseline Characteristics 2 14 985 (29.4)
Table 1 shows the characteristics of participants included in the 3 23 607 (46.3)
study. Notably, this was a relatively young population, with a 4 3850 (7.5)
5 91 (<1)
mean age of 42 years. Among these individuals, 20 686 (41%)
6 17 (<1)
had previously had a documented episode of COVID-19, and
Time since most recent vaccine, mean (SD), 3 319 (135)
13 717 (27%) had previously had an Omicron variant infection; Time since proximate SARS-CoV-2 exposure, mean 263 (142)
45 064 (88%) had previously received ≥1 dose of vaccine, 42 550 (SD)b

(83%) had received ≥2 doses, and 46 761 (92%) had been previ­ Abbreviations: SARS-Cov-2, severe acute respiratory syndrome; SD, standard deviation.
a
Data represented no. (%) of employees unless otherwise indicated.
ously exposed to SARS-CoV-2 by infection or vaccination. b
Exposure by infection or vaccination.

Risk of COVID-19 Based on Prior Infection and Vaccination History

The risk of COVID-19 varied by the phase of the epidemic in study start, and epidemic phase when the last prior COVID-19
which the study participant’s last prior COVID-19 episode oc­ episode occurred, bivalent vaccination provided some protec­
curred. In decreasing order of risk were those never previously tion against COVID-19 while the BA.4/5 lineages were the
infected, those last infected during the pre-Omicron phase, and dominant circulating strains (HR, 0.71 [95% confidence inter­
those last infected during the Omicron phase (Figure 1). The val (CI)], .63–.79; P <.001), and less protection while the BQ
risk of COVID-19 also varied by the number of COVID-19 vac­ lineages were dominant (0.80 [.69–.94]; P= .005).
cine doses previously received. The higher the number of vac­ A protective effect of bivalent vaccination could not be dem­
cines previously received, the higher the risk of contracting onstrated while the XBB strains were dominant (HR, 0.96 [95%
COVID-19 (Figure 2). CI, .82–.1.12]; P = .59). Point estimates and 95% CIs for HRs
for the variables included in the unadjusted and adjusted Cox
Bivalent Vaccine Effectiveness proportional hazards regression models are shown in Table 2.
The cumulative incidence of COVID-19 was similar for the The calculated overall bivalent vaccine effectiveness from the
bivalent-vaccinated and non–bivalent-vaccinated states in an model was 29% (95% CI, 21%–37%) during the BA.4/
unadjusted analysis (Figure 3). In a multivariable Cox propor­ 5-dominant phase, 20% (6%–31%) during the BQ-dominant
tional hazards regression model, adjusted for age, sex, hire co­ phase, and 4% (−12% to 18%) during the XBB-dominant phase.
hort, job category, number of COVID-19 vaccine doses before The multivariable analysis also found that, the more recent the

COVID-19 Bivalent Vaccine Effectiveness • OFID • 3

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Figure 1. Cumulative incidence of coronavirus disease 2019 (COVID-19) for study participants stratified by the pandemic phase when the participant’s last prior COVID-19
episode occurred. Day 0 was 12 September 2022, the date the bivalent vaccine was first offered to employees. Point estimates and 95% confidence intervals are jittered
along the x-axis to improve visibility.

last prior COVID-19 episode was the lower the risk of afforded by bivalent vaccination while the BA.4/5 lineages
COVID-19, and the greater the number of vaccine doses previ­ were dominant was similar to that estimated in another study
ously received the higher the risk of COVID-19. using data from the Increasing Community Access to Testing
national SARS-CoV-2 testing program [16].
Bivalent Vaccine Effectiveness Among Those With Prior SARS-CoV-2 The strengths of our study include its large sample size and
Infection or Vaccination
its conduct in a healthcare system where very early recognition
Among persons with prior exposure to SARS-CoV-2 by infec­
of the critical importance of maintaining an effective workforce
tion or vaccination, HRs for bivalent vaccination for individu­
during the pandemic led to devotion of resources to provide an
als, after adjusting for time since proximate SARS-CoV-2
accurate accounting of who had COVID-19, when COVID-19
exposure, are shown in Table 3. Bivalent vaccination protected
was diagnosed, who received a COVID-19 vaccine, and when.
against COVID-19 during the BA.4/5-dominant phase (HR,
The study method, treating bivalent vaccination as a time-
0.78 [95% CI, .70–.88; P <.001), but a significant protective ef­
dependent covariate, allowed vaccine effectiveness to be deter­
fect could not be demonstrated during the BQ-dominant phase
mined in real time.
(0.91 [.78–.1.07]; P = .25) or the XBB-dominant phase (1.05
The study has several limitations. Individuals with unrecog­
[.85–.1.29]; P= .66).
nized prior infection would have been misclassified as previ­
ously uninfected. Since prior infection protects against
DISCUSSION
subsequent infection, such misclassification would have result­
This study found that the current bivalent vaccines were about ed in underestimating the protective effect of the vaccine.
29% effective overall in protecting against infection with However, there is little reason to suppose that prior infections
SARS-CoV-2 when the Omicron BA.4/5 lineages were the pre­ would have been missing in the bivalent-vaccinated and non­
dominant circulating strains, and effectiveness was lower when vaccinated states at disproportionate rates. There might be con­
the circulating strains were no longer represented in the vac­ cern that those who chose to receive the bivalent vaccine may
cine. A protective effect could not be demonstrated when the have been more worried about infection and more likely to
XBB lineages were dominant. The magnitude of protection be tested when they had symptoms, thereby disproportionately

4 • OFID • Shrestha et al
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Figure 2. Cumulative incidence of coronavirus disease 2019 (COVID-19) for study participants stratified by the number of COVID-19 vaccine doses previously received. Day
0 was 12 September 2022, the date the bivalent vaccine was first offered to employees. Point estimates and 95% confidence intervals are jittered along the x-axis to improve
visibility.

detecting more incident infections among those who received We were unable to distinguish between symptomatic and
the bivalent vaccine. We did not find an association between asymptomatic infections and had to limit our analyses to all de­
the number of COVID-19 tests done and the number of prior tected infections. Variables that were not considered might
vaccine doses, however, suggesting that this was not a con­ have influenced the findings substantially. Time since last prior
founding factor. Those who chose to get the bivalent vaccine exposure to SARS-CoV-2 could not be included in the primary
could have been those who were more likely to have lower risk- model owing to multicollinearity. It is possible that the associ­
taking behavior with respect to COVID-19. This would have ation of number of prior vaccine doses with increased risk of
the effect of finding a higher risk of COVID-19 in the nonvac­ infection may have been confounded by time since last prior
cinated state, thereby potentially overestimating vaccine effec­ exposure to SARS-CoV-2. There were too few severe illnesses
tiveness, because the lower risk of COVID-19 in the for the study to determine whether the vaccine decreased se­
bivalent-vaccinated state could have been due to lower risk- verity of illness. Finally, our study was done in a healthcare
taking behavior rather than the vaccine. population, and included no children and few elderly persons,
The widespread availability of home testing kits might and the majority of study participants would not have been
have reduced detection of incident infections. This potential immunocompromised.
effect should be somewhat mitigated in our healthcare cohort A possible explanation for a lower-than-expected vaccine ef­
because one needs a NAAT to get paid time off, providing a fectiveness is that a substantial proportion of the population
strong incentive to get a NAAT if one tests positive at home. may have had prior asymptomatic Omicron variant infection.
Even if one assumes that some individuals chose not to follow About a third of SARS-CoV-2 infections have been estimated
up on a positive home test result with a NAAT, it is very un­ to be asymptomatic in studies performed in different places
likely that individuals would have chosen to pursue NAAT at different times [17–19]. If so, protection from the bivalent
after receiving the bivalent vaccine more than before receiv­ vaccine may have been masked because those with prior
ing it, at rates disproportionate enough to affect the study’s Omicron variant infection may have already been somewhat
findings. protected against COVID-19 by virtue of natural immunity.

COVID-19 Bivalent Vaccine Effectiveness • OFID • 5

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Figure 3. Simon-Makuch plot comparing the cumulative incidence of coronavirus disease 2019 (COVID-19) for the bivalent-vaccinated and non–bivalent-vaccinated states.
Day 0 was 12 September 2022, the date the bivalent vaccine was first offered to employees. Point estimates and 95% confidence intervals are jittered along the x-axis to
improve visibility.

Table 2. Unadjusted and Adjusted Associations With Time to Coronavirus Disease 2019

Variable Unadjusted HR (95% CI) P Value Adjusted HR (95% CI)a P Value

b
Bivalent-vaccinated state
BA.4/5-dominant phase .85 (.76–.95) .005 .71 (.63–.79) <.001
BQ-dominant phase .98 (.85–1.14) .81 .80 (.69–.94) .005
XBB-dominant phase 1.17 (1.01–1.36) .04 .96 (.82–1.12) .59
Age 1.003 (1.000–1.005) .02 .997 (.995–1.000) .046
Male sexc .78 (.72–.84) <.001 .75 (.70–.80) <.001
Pandemic hired .92 (.86–.98) .01 .96 (.89–1.03) .24
Clinical jobe 1.12 (1.05–1.18) <.001 1.15 (1.09–1.23) <.001
Last prior infection phasef
Pre-Omicron 2.06 (1.85–2.31) <.001 2.20 (1.97–2.46) <.001
No known prior infection 2.35 (2.15–2.56) <.001 2.55 (2.34–2.79) <.001
No. of prior vaccine dosesg
1 1.91 (1.57–2.32) <.001 2.07 (1.70–2.52) <.001
2 2.22 (1.92–2.56) <.001 2.50 (2.17–2.89) <.001
3 2.69 (2.35–3.09) <.001 3.10 (2.69–3.56) <.001
>3 2.94 (2.50–3.45) <.001 3.53 (2.97–4.20) <.001
Abbreviations: CI, confidence interval; HR, hazard ratio.
a
From a multivariable Cox-proportional hazards regression model, with bivalent-vaccinated state treated as a time-dependent covariate and time-dependent coefficients used to separate
effects during the period of dominance of the Omicron BA.4/5, BQ, and XBB lineages.
b
Time-dependent covariate.
c
Reference: female sex.
d
Reference: prepandemic hire.
e
Reference: nonclinical job.
f
Reference: Omicron.
g
Reference: 0 doses.

6 • OFID • Shrestha et al
Table 3. Associations With Time to Coronavirus Disease 2019 Among behavior. Despite this, their risk of acquiring COVID-19 was
Study Participants With Prior Severe Acute Respiratory Syndrome lower than that that of participants those who received more
(SARS-CoV-2) Exposure, Adjusted for Time Since Proximate SARS-CoV-2
Exposure by Prior Infection or Vaccination prior vaccine doses.
Ours is not the only study to find a possible association with
Variablea Adjusted HR (95% CI) P Value more prior vaccine doses and higher risk of COVID-19. During
Bivalent-vaccinated state b an Omicron wave in Iceland, individuals who had previously
BA.4/5-dominant phase .78 (.69–.87) <.001 received ≥2 doses were found to have a higher odds of reinfec­
BQ-dominant phase .90 (.78–1.05) .19 tion than those who had received <2 doses, in an unadjusted
XBB-dominant phase 1.06 (.91–1.24) .43
analysis [21]. A large study found, in an adjusted analysis,
Age 1.004 (1.001–1.006) .005
Male sexc .78 (.73–.84) <.001
that those who had an Omicron variant infection after previ­
Pandemic hired 1.07 (.99–1.15) .08 ously receiving 3 doses of vaccine had a higher risk of reinfec­
Clinical jobe 1.11 (1.05–1.18) <.001 tion than those who had an Omicron variant infection after
Time since proximate SARS-CoV-2 previously receiving 2 doses [22]. Another study found, in mul­

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exposuref
tivariable analysis, that receipt of 2 or 3 doses of am mRNA vac­
91–180 d 1.70 (1.45–1.99) <.001
181–270 d 1.88 (1.63–2.16) <.001
cine following prior COVID-19 was associated with a higher
271–365 d 2.81 (2.45–3.21) <.001 risk of reinfection than receipt of a single dose [7]. Immune im­
>365 d 2.15 (1.86–2.50) <.001 printing from prior exposure to different antigens in a prior
Abbreviations: CI, confidence interval; HR, hazard ratio; SARS-CoV-2, severe acute vaccine [22, 23] and class switch toward noninflammatory
respiratory syndrome coronavirus 2.
a
The number of prior vaccine doses was not included as a variable because its inclusion
spike-specific immunoglobulin G4 antibodies after repeated
would have introduced significant multicollinearity into the model. SARS-CoV-2 mRNA vaccination [24] have been suggested as
b
Time-dependent covariate.
c
possible mechanisms whereby prior vaccine may provide less
Reference: female sex.
d
Reference: prepandemic hire.
protection than expected. We still have a lot to learn about pro­
e
Reference: nonclinical job. tection from COVID-19 vaccination, and in addition to vaccine
f
Reference: ≤90 days; this includes those previously vaccinated within 90 days but not effectiveness, it is important to examine whether multiple vac­
those previously infected within 90 days, as the latter would not have qualified for
inclusion until 90 days after their most recent infection. cine doses given over time may not be having the beneficial ef­
fect that is generally assumed.
In conclusion, this study found an overall modest protective
A seroprevalence study conducted by the CDC found that by effect of the bivalent vaccine against COVID-19 while the cir­
February 2022, 64% of the 18–64-year age-group population culating strains were represented in the vaccine and lower pro­
and 75% of children and adolescents had serologic evidence tection when the circulating strains were no longer represented.
of prior SARS-CoV-2 infection [20], with almost half of the A significant protective effect was not found when the XBB lin­
positive serologic results attributed to infections occurring be­ eages were dominant. The unexpected finding of increasing
tween December 2021 and February 2022, which would have risk with increasing number of prior COVID-19 vaccine doses
predominantly been Omicron BA.1/BA.2-lineage infections. needs further study.
With such a large proportion of the population expected to
have already been previously exposed to the Omicron variant Acknowledgments
of SARS-CoV-2, it is possible that a substantial proportion of Author contributions. N. K. S.: Conceptualization, methodology, valida­
tion, investigation, data curation, software, formal analysis, visualization,
individuals may be unlikely to derive any meaningful benefit
writing (original draft preparation; reviewing and editing), supervision,
from a bivalent vaccine. and project administration. P. C. B.: Resources, investigation, validation,
The association of increased risk of COVID-19 with more and writing (reviewing and editing). A. S. N.: Methodology, formal analy­
prior vaccine doses was unexpected. A simplistic explanation sis, visualization, validation, and writing (reviewing and editing). J. F. S.
and A. H.: Resources and writing (reviewing and editing). S. M. G.:
might be that those who received more doses were more likely Project administration, resources, and writing (reviewing and editing).
to be individuals at higher risk of COVID-19. A small propor­ Potential conflicts of interest. All authors: No reported conflicts.
tion of individuals may have fit this description. However, the
majority of participants in this study were young, and all were References
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