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Interim estimates of vaccine effectiveness against influenza A(H1N1)pdm09 and A(H3N2) during a delayed influenza season, Canada, 2024/25

2025· article· en· W4407040137 on OpenAlexafffundabout
Lea Separovic, Yuping Zhan, Samantha E Kaweski, Suzana Sabaiduc, Sara Carazo, Romy Olsha, Richard Mather, James A. Dickinson, Maan Hasso, Isabelle Meunier, Agatha N. Jassem, Nathan Zelyas, Ruimin Gao, Nathalie Bastien, Danuta M. Skowronski

Bibliographic record

VenueEurosurveillance · 2025
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsPublic Health Agency of CanadaAlberta Hospital EdmontonUniversity of CalgaryQueen's UniversityInstitut National de Santé Publique du QuébecUniversity of British ColumbiaPublic Health OntarioBC Centre for Disease Control
FundersCentre Hospitalier Universitaire de QuébecBritish Columbia Centre for Disease ControlInstitut National de Santé Publique du QuébecUniversité Laval
KeywordsInterimVirologyInfluenza A virusInfluenza vaccineMedicineInfluenza seasonHuman influenzaCoronavirus disease 2019 (COVID-19)Environmental scienceVirusInternal medicineGeographyInfectious disease (medical specialty)Disease

Abstract

fetched live from OpenAlex

The Canadian Sentinel Practitioner Surveillance Network (SPSN) reports interim 2024/25 vaccine effectiveness (VE) against acute respiratory illness due to laboratory-confirmed influenza during a delayed season of predominant A(H1N1)pdm09 and lower A(H3N2) co-circulation. Through mid-January, the risk of outpatient illness due to influenza A is reduced by about half among vaccinated vs unvaccinated individuals. Adjusted VE is 53% (95% CI: 36-65) against A(H1N1)pdm09, comprised of clades 5a.2a and 5a.2a.1, and 54% (95% CI: 29-70) against A(H3N2), virtually all clade 2a.3a.1.

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)0.005
metaresearch head score (Gemma)0.008
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: none
Teacher disagreement score0.347
Threshold uncertainty score0.698

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.025
GPT teacher head0.342
Teacher spread0.317 · 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

Citations16
Published2025
Admission routes3
Has abstractyes

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