BNT162b2 effectiveness against Delta & Omicron variants in teens by dosing interval and duration
Bibliographic record
Abstract
Abstract Background and Objectives Two- and three-dose BNT162b2 (Pfizer-BioNTech) mRNA vaccine effectiveness (VE) against SARS-CoV-2 infection, including Delta and Omicron variants, was assessed among adolescents in two Canadian provinces where first and second doses were spaced longer than the manufacturer-specified 3-week interval. Methods Test-negative design estimated VE against laboratory-confirmed SARS-CoV-2 infection among adolescents 12-17 years old in Quebec and British Columbia, Canada between September 5, 2021 (epi-week 36), and April 30, 2022 (epi-week 17). Delta-dominant and Omicron-dominant periods spanned epi-weeks 36-47 and 51-17, respectively. VE was assessed from 14 days and explored by interval between first and second doses, time since second dose, and with administration of a third dose. Results Median first-second dosing-interval was ∼8 weeks and second-third dosing-interval was ∼28-31 weeks. Median follow-up post-second-dose was ∼10-11 weeks for Delta-dominant and ∼21-22 weeks for Omicron-dominant periods, and ∼3-9 weeks post-third dose. VE against Delta was ≥90% to at least the 5th month post-second dose. VE against Omicron declined from ∼65-75% at weeks to ≤50% by the 3 rd month post-vaccination, restored to ∼60-65% shortly following a third dose. VE exceeded 90% against Delta regardless of dosing-interval but appeared improved against Omicron with ≥8 weeks between first and second doses. Conclusion In adolescents, two BNT162b2 doses provided strong and sustained protection against Delta but reduced and rapidly-waning VE against Omicron. Longer interval between first and second doses and a third dose improved Omicron protection. Updated vaccine antigens, increased doses and/or dosing-intervals may be needed to improve adolescent VE against immunological-escape variants.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".