Protective effect of single‐dose adjuvanted pandemic influenza vaccine in children
Bibliographic record
Abstract
BACKGROUND: During the first wave of A/California/7/2009(H1N1) influenza, high rates of hospitalization in children under 5 years were seen in many countries. Subsequent policies for vaccinating children varied in both type of vaccine and number of doses. In Canada, children 36 months to <10 years received a single dose of 0.25 ml of the GSK adjuvanted vaccine (Arepanrix) equivalent to 1.9 microg HA. Children 6 months to 35 months received two doses as did those 36-119 months with chronic medical conditions. METHOD: We conducted a community-based case-control vaccine effectiveness (VE) review of children under 10 years with influenza like illness who were tested for H1N1 infection at the central provincial laboratory. Laboratory-confirmed influenza was the primary outcome, and vaccination status the primary exposure to assess VE after a single 0.25-ml dose. RESULTS: If vaccination was designated to be effective after 14 days, no vaccinated child had laboratory-confirmed influenza compared to 38% of controls. The VE of 100% was statistically significant for children <10 years of age and <5 years considered separately. If vaccination was considered effective after 10 days, VE dropped to 96% overall but was statistically significant and over 90% in all age subgroups, including those under 36 months. CONCLUSIONS: A single 0.25-ml dose of the GSK adjuvanted vaccine (Arepanrix) protects children against laboratory-confirmed pandemic influenza potentially avoiding any increased reactogenicity associated with second doses. Adjuvanted vaccines offer hope for improved seasonal vaccines in the future.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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".