Effectiveness of Pandemic H1N1 Vaccine Against Influenza-Related Hospitalization in Children
Bibliographic record
Abstract
OBJECTIVE: Young children are generally considered immunologically naive with respect to influenza exposure opportunities; thus, a 2-dose schedule is recommended when a child is first immunized with conventional influenza vaccine lacking adjuvant. We estimated the effectiveness of a single pediatric dose of AS03-adjuvanted vaccine against hospitalization for confirmed pandemic influenza A/H1N1 (pH1N1) infection in children aged 6 months to 9 years during the fall 2009 vaccination campaign. METHODS: In a matched case-control design, case subjects were children hospitalized for pH1N1 infection in the Fall of 2009, in Quebec, Canada. Controls were nonhospitalized children, matched by age and region of residence. Vaccination status in case subjects and controls was ascertained in relation to the case subject's date of illness onset. Vaccine effectiveness was estimated through conditional logistic regression. RESULTS: The overall effectiveness of a single pediatric dose of vaccine administered ≥14 days before illness onset was 85% (95% confidence interval [CI]: 61% to 94%), varying according to age category but with wide and overlapping CIs: 92% (95% CI: 51% to 99%) in 6-23 month-old children, 89% (95% CI: 34% to 98%) in 2-4 year-olds, and 79% (95% CI: -31% to 96%) in 5-9 year-olds. Overall vaccine effectiveness for immunization ≥10 days before illness onset was slightly lower at 80% (95% CI: 60% to 90%), with similar variation according to age. CONCLUSION: In children aged 6 months to 9 years, a single pediatric dose of the AS03-adjuvanted pH1N1 vaccine was highly protective against hospitalization beginning at 10 and 14 days after vaccination.
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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) | 0.000 | 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".