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Record W2982006085 · doi:10.1016/j.vaccine.2019.09.086

Exploring indirect protection associated with influenza immunization – A systematic review of the literature

2019· review· en· W2982006085 on OpenAlexaff
Lindsay Friedman, Ariane Renaud, Delaney Hines, A.-L. Winter, Shelly Bolotin, Jennie Johnstone, Jeffrey C. Kwong, Allison McGeer, Natasha S. Crowcroft, Bryna Warshawsky

Bibliographic record

VenueVaccine · 2019
Typereview
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsWestern UniversityToronto Western HospitalCanada Research ChairsMount Sinai HospitalUniversity of TorontoPublic Health Ontario
Fundersnot available
KeywordsMedicineInfluenza vaccineCritical appraisalMEDLINEImmunizationSystematic reviewFamily medicineVaccinationImmunologyAlternative medicineImmune systemPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Influenza causes significant annual morbidity and mortality, particularly in older adults, for whom influenza vaccine effectiveness (VE) is also lower. Immunizing one group (e.g., children) against influenza may indirectly protect another group (e.g., older adults) against influenza and its complications. METHODS: We updated previous systematic reviews on indirect protection against influenza by searching MEDLINE and EMBASE for relevant human studies published until January 4, 2017. We abstracted and critically appraised English language publications that reported or provided information to calculate indirect VE against influenza, as a percentage, in non-institutional settings. We developed a term called 'estimated actual protection' to explore the relationship between indirect protection and the product of direct VE and relative vaccine coverage. We calculated estimated actual protection for a subset of studies that reported coverage and indirect VE for: laboratory-confirmed influenza; outpatient care for respiratory illness; influenza-associated emergency visits; or influenza-associated hospitalizations. We ran linear mixed models to compare estimated actual protection against indirect VE for the four outcomes, and graphed the data. RESULTS: Of 2320 unique records identified, we abstracted and appraised 26 articles describing 24 studies. The majority of included studies reported at least one outcome suggesting that immunizing one group reduced influenza-related outcomes in another group. Critical appraisal of the abstracted studies identified recurring methodological weaknesses, such as lack of laboratory-confirmed influenza. Our exploratory analyses of 18 studies indicated a positive but not statistically significant relationship between estimated actual protection and indirect protection for each of the four outcomes. CONCLUSIONS: Our systematic review and exploratory analyses suggest influenza immunization provides some level of indirect protection. However, our critical appraisal highlights the need for a standardized and consistently applied approach to measuring indirect protection against influenza to fill existing knowledge gaps. Additionally, the concept of estimated actual protection requires validation.

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)0.016
metaresearch head score (Gemma)0.068
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.068
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0090.010
Bibliometrics0.0150.014
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.265
GPT teacher head0.389
Teacher spread0.124 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations12
Published2019
Admission routes1
Has abstractyes

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