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Record W4410983025 · doi:10.1371/journal.pone.0325269

Monovalent mRNA XBB.1.5 vaccine effectiveness against COVID-19 hospitalization in Quebec, Canada: Impact of variant replacement and waning protection during 10-month follow-up

2025· article· en· W4410983025 on OpenAlexafffundabout
Sara Carazo, Danuta M. Skowronski, Nicholas Brousseau, Charles-Antoine Guay, Chantal Sauvageau, Étienne Racine, Denis Talbot, Iulia Gabriela Ionescu, Judith Fafard, Rodica Gilca, Jonathan Phimmasone, Philippe De Wals, Gaston De Serres

Bibliographic record

VenuePLoS ONE · 2025
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de QuébecUniversité de SherbrookeBC Centre for Disease ControlCentre hospitalier de l'Université LavalUniversité LavalInstitut National de Santé Publique du Québec
FundersMinistère de la Santé et des Services sociaux
KeywordsCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakVirologyMedicineBetacoronavirusCoronavirus InfectionsBiologyOutbreakInternal medicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

BACKGROUND: Vaccine formulations targeting contemporaneous subvariants have been developed to respond to SARS-CoV-2 virus evolution. Updated monovalent COVID-19 vaccines targeting the Omicron XBB.1.5 variant (XBB-vaccines) were administered in the province of Quebec, Canada, during 2023 autumn and 2024 spring vaccination campaigns. Our objective was to evaluate mRNA XBB-vaccine effectiveness (VE) against COVID-19 hospitalizations among adults aged ≥60 years overall during a ten-month follow-up period, by subvariant predominant period, and by time since vaccination. METHODS: We conducted a test-negative case-control study using Quebec population-based administrative data. Specimens collected from individuals aged ≥60 years tested at an acute-care hospital from October 2023 to August 2024 were considered test-positive cases if hospitalized for COVID-19, or controls if test-negative for SARS-CoV-2. Vaccination was defined by receipt of at least one mRNA XBB-vaccine (autumn or spring) dose. Subvariant predominant periods were defined according to whole-genome sequencing data from provincial laboratories: XBB or EG.5 and subvariants (XBB period), BA.2.86, JN.1 or subvariants (JN period), and KP.2 or KP.3 and subvariants (KP period). Multivariable logistic regression analyses estimated VE relative to several comparator groups, primarily those last-vaccinated in 2022, by subvariant period, by time since XBB-vaccination and by number of XBB-vaccine doses (KP period). RESULTS: Participants overall and by XBB, JN and KP periods included: 5532 (4.9%) test-positive cases (1321, 1838 and 1372, respectively) and 108473 (95.1%) test-negative controls (12881, 53414 and 28595, respectively); 14584 specimens were collected during periods of subvariant cocirculation. By subvariant period, 3322 (25.8%), 27041 (50.6%) and 15401 (53.9%) controls, respectively, were considered XBB-vaccinated. Overall VE was 30% (95%CI:24-35) and by XBB, JN or KP period: 54% (95%CI:46-62), 23% (95%CI:13-32) and 0% (95%CI:-18-15), respectively. During each subvariant period, the hospitalization risk was reduced only during the first four months post-vaccination. CONCLUSIONS: Among individuals aged 60 years or older, mRNA XBB-vaccination provided meaningful, albeit limited to first four months post-vaccination, protection against COVID-19 hospitalization due to XBB, JN and KP subvariants. Better vaccines are needed to effectively protect older adults against COVID-19 hospitalizations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.299
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2025
Admission routes3
Has abstractyes

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