Vaccine effectiveness of the 7-valent and 13-valent pneumococcal conjugate vaccines in Canada: An IMPACT study
Bibliographic record
Abstract
We used an indirect cohort analysis in children under 5 years-old from 2002 to 2018 to examine vaccine effectiveness (VE) of the 7-valent pneumococcal conjugate vaccine (PCV) (3 + 1 doses in most regions) and the 13-valent PCV (2 + 1 doses in all regions) against invasive pneumococcal disease (IPD) caused by vaccine serotypes in children in Canada. Cases were identified from the Canadian Immunization Monitoring Program ACTive (IMPACT), a national active surveillance network of 12 tertiary care pediatric hospitals that represent about 90% of tertiary care hospital beds in Canada. There were 1477 children evaluated for PCV7 VE and 489 for PCV13 VE. PCV7 VE in children with vaccination up to date for their age was 96% (95% CI: 67-99%) after a single dose and 95% (95% CI: 92-97%) after ≥2 doses. The VE was 91% (95% CI: 85-94%) in children who had received doses but were not up to date for their age. PCV13 VE in children with vaccinations up to date for their age was 55% (95% CI: 28-72%) after ≥2 doses. The PCV13-vaccine serotypes causing breakthrough IPD in children up to date for their age with 2+ doses of PCV13 were 3 (13/27, 48.2%),19A (11/27, 40.7%), and 19F (3/27, 11.1%). When serotype 3 and 19A were excluded, the VE of PCV13 against the remaining vaccine serotypes was 89% (95% CI: 64-97%) in children with ≥2 doses. The lower VE of PCV13 may be due to lower effectiveness against serotypes 3 and 19A, which could be influenced by the change in dosing schedule from 4 to 3 total doses with the introduction of PCV13, combined with vaccine uptake of 80%. However, PCV13 still provides the benefit of protection against more serotypes than PCV7, and good VE against all serotypes except 3 and 19A.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".