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Influenza vaccine effectiveness against A(H3N2) during the delayed 2021/22 epidemic in Canada

2022· article· en· W4296810441 on OpenAlexafffundabout
Shin Hye Kim, Erica Chuang, Suzana Sabaiduc, Romy Olsha, Samantha E Kaweski, Nathan Zelyas, Jonathan B. Gubbay, Agatha N. Jassem, Hugues Charest, Gaston De Serres, James A. Dickinson, Danuta M. Skowronski

Bibliographic record

VenueEurosurveillance · 2022
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsUniversity of CalgaryUniversité LavalCentre hospitalier universitaire de QuébecInstitut National de Santé Publique du QuébecBC Centre for Disease ControlPublic Health OntarioUniversity of British ColumbiaAlberta Hospital EdmontonUniversity of Toronto
FundersBritish Columbia Centre for Disease Control
KeywordsPandemicVirologyCladeStrain (injury)Coronavirus disease 2019 (COVID-19)Influenza vaccineVirusInfluenza seasonHuman mortality from H5N1Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakMedicineBiologyOutbreakInternal medicineInfectious disease (medical specialty)Phylogenetics

Abstract

fetched live from OpenAlex

Influenza virus circulation virtually ceased in Canada during the COVID-19 pandemic, re-emerging with the relaxation of restrictions in spring 2022. Using a test-negative design, the Canadian Sentinel Practitioner Surveillance Network reports 2021/22 vaccine effectiveness of 36% (95% CI: -38 to 71) against late-season illness due to influenza A(H3N2) clade 3C.2a1b.2a.2 viruses, considered antigenically distinct from the 3C.2a1b.2a.1 vaccine strain. Findings reinforce the World Health Organization's decision to update the 2022/23 northern hemisphere vaccine to a more representative A(H3N2) clade 3C.2a1b.2a.2 strain.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.030
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.308
Teacher spread0.282 · 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

Citations23
Published2022
Admission routes3
Has abstractyes

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