Effectiveness of BNT162b2 Vaccine Against Omicron-SARS-CoV-2 Subvariants in Children 5–11 Years of Age in Quebec, Canada, January 2022 to January 2023
Bibliographic record
Abstract
BACKGROUND: In premarketing clinical trials conducted before Omicron emergence, BNT162b2 vaccine efficacy against COVID-19 was 90% in children. We conducted postmarketing evaluation of 1- and 2-dose vaccine effectiveness (VE) against Omicron BA.1, BA.2 and BA.4/5 subvariants in 5- to 11-year olds. METHODS: We estimated VE against SARS-CoV-2 infection using a test-negative design. Specimens collected between January 9, 2022, and January 7, 2023, from children 5-11 years old in Quebec, Canada, and tested by nucleic acid amplification test were eligible. We estimated VE by time since last vaccine dose, interval between doses and by period of Omicron subvariant predominance. RESULTS: A total of 48,826 NAATs were included in overall analysis. From 14-55 to 56-385 days postvaccination, 2-dose VE against symptomatic infection decreased from 68% (95% CI, 62-74) to 25% (95% CI, 11-36). Two-dose VE with restriction to specimens collected from acute care hospitals (emergency rooms or wards) did not decline but was stable at ~40%. VE against symptomatic infection remained comparable at any interval between doses but increased with longer interval among children tested in acute care settings, from 18% (95% CI, -17 to 44) with 21- to 55-day interval to 69% (95% CI, 43-86) with ≥84-day interval. Two-dose VE against symptomatic infection dropped from 70% (95% CI, 63-76) during BA.1, to 32% (95% CI, 13-47) with BA.2 and to nonprotective during BA.4/5 dominance. CONCLUSIONS: In children 5-11 years of age, VE against symptomatic infection was stable at any interval between doses but decreased with time since the last dose and against more divergent omicron subvariants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".