Influenza vaccine effectiveness against influenza-associated hospitalizations in children, Hong Kong, November 2023 to June 2024
Bibliographic record
Abstract
ABSTRACT We conducted a test negative study from November 2023 to June 2024, enrolling 4,367 children hospitalized with acute respiratory illness in Hong Kong. Among the children who tested negative for influenza virus and SARS-CoV-2, 56.8% had received influenza vaccination. Between November 2023 and March 2024, influenza A(H3N2) predominated and the VE against influenza A(H3N2) was estimated as 55% (95% CI: 29.6%, 71.8%). VE point estimates were higher for younger children than older children. In February to June 2024 influenza A(H1N1) predominated and VE against influenza A(H1N1) was 54% (95% CI: 33%, 69%) during this period. Influenza B circulated at low intensity throughout the 2023/24 season and VE against influenza B was 66% (95% CI: 42%, 80%). Since its introduction in 2018/19 the school-based influenza vaccination program has substantially increased vaccine uptake in children in Hong Kong and prevented influenza-associated hospitalizations.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".