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Record W2745379188 · doi:10.1186/s12916-018-1239-8

The impact of repeated vaccination on influenza vaccine effectiveness: a systematic review and meta-analysis

2019· review· en· W2745379188 on OpenAlex
Lauren Ramsay, Sarah A. Buchan, Rob G. Stirling, Benjamin J. Cowling, Shuo Feng, Jeffrey C. Kwong, Bryna Warshawsky

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMC Medicine · 2019
Typereview
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsWestern UniversityUniversity of TorontoUniversity Health NetworkInstitute for Clinical Evaluative SciencesPublic Health Agency of CanadaPublic Health Ontario
Fundersnot available
KeywordsMedicineVaccinationMeta-analysisInfluenza vaccineVirologyImmunologyIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Conflicting results regarding the impact of repeated vaccination on influenza vaccine effectiveness (VE) may cause confusion regarding the benefits of receiving the current season's vaccine. METHODS: We systematically searched MEDLINE, Embase, PubMed, and Cumulative Index to Nursing and Allied Health Literature from database inception to August 17, 2016, for observational studies published in English that reported VE against laboratory-confirmed influenza for the following four vaccination groups: current season only, prior season only, both seasons, and neither season. We pooled differences in VE (∆VE) between vaccination groups by influenza season and type/subtype using a random-effects model. The study protocol is registered with PROSPERO (registration number: CRD42016037241). RESULTS: We identified 3435 unique articles, reviewed the full text of 634, and included 20 for meta-analysis. Compared to prior season vaccination only, vaccination in both seasons was associated with greater protection against influenza H1N1 (∆VE = 25%; 95% CI 14%, 35%) and B (∆VE = 18%; 95% CI 3%, 33%), but not H3N2 (∆VE = 7%; 95% CI - 7%, 21%). Compared to no vaccination for either season, individuals who received the current season's vaccine had greater protection against H1N1 (∆VE = 62%; 95% CI 51%, 70%), H3N2 (∆VE = 45%; 95% CI 35%, 53%), and B (∆VE = 64%; 95% CI 57%, 71%). We observed no differences in VE between vaccination in both seasons and the current season only for H1N1 (∆VE = 3%; 95% CI - 8%, 13%), but less protection against influenza H3N2 (∆VE = - 20%; 95% CI - 36%, - 4%), and B (∆VE = - 11%; 95% CI - 20%, - 2%). CONCLUSIONS: Our results support current season vaccination regardless of prior season vaccination because VE for vaccination in the current season only is higher compared to no vaccination in either season for all types/subtypes, and for H1N1 and influenza B, vaccination in both seasons provides better VE than vaccination in the prior season only. Although VE was lower against H3N2 and B for individuals vaccinated in both seasons compared to those vaccinated in the current season only, it should be noted that past vaccination history cannot be altered and this comparison disregards susceptibility to influenza during the prior season among those vaccinated in the current season only. In addition, our results for H3N2 were particularly influenced by the 2014-2015 influenza season and the impact of repeated vaccination for all types/subtypes may vary from season to season. It is important that future VE studies include vaccination history over multiple seasons to evaluate repeated vaccination in more detail.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.573
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0200.004
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.332
GPT teacher head0.531
Teacher spread0.198 · 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