Maintaining the value of influenza vaccination – the shift from quadrivalent to trivalent vaccines: an expert review
Bibliographic record
Abstract
INTRODUCTION: This review provides an expert perspective on the sustained value of seasonal influenza vaccines as they transition from quadrivalent to trivalent formulations, based on apparent elimination of the B/Yamagata strain from circulation and subsequent advice from the World Health Organization (WHO) to remove the B/Yamagata antigen from influenza vaccines. Influenza has a high clinical and economic burden globally. However, coronavirus disease 2019 has created new challenges for managing seasonal influenza by amplifying vaccine hesitancy. Understanding why influenza virus circulation is monitored and vaccines subsequently updated is important for all relevant stakeholders to maintain confidence in the value of seasonal influenza vaccination. AREAS COVERED: Discussion is provided on the dynamic nature of communicable diseases, influenza virus monitoring and WHO vaccine composition guidance, and maintaining the value of influenza vaccination to individuals, society, and healthcare systems. EXPERT OPINION: The move from quadrivalent to trivalent influenza vaccines is a result of findings from strain surveillance. Continued surveillance and targeting of vaccines against strains most commonly in circulation to keep effectiveness high, and ensure the highest value of vaccination is vital to prevent influenza infection and severe illness, thus reducing pressure on healthcare systems and reducing the economic impact of influenza outbreaks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".