Uptake of pertussis immunization in pregnancy and determinants of vaccination in Toronto, Canada
Bibliographic record
Abstract
INTRODUCTION: Pertussis causes significant morbidity and mortality in infants aged <6 months. Maternal pertussis vaccination during pregnancy has been recommended in Canada since 2018 to reduce these negative outcomes. In the absence of routine immunization coverage data, our objective was to evaluate uptake in Toronto, Canada. METHODS: We recruited mother-infant pairs at The Hospital for Sick Children, Toronto, between 2018 and 2020. We performed logistic regression to examine associations between demographics and self-reported pertussis vaccination. RESULTS: 76/243 mothers (31.3 %) reported receiving pertussis vaccination during their most recent pregnancy. Odds of receiving vaccination more than doubled with each 1-year increase in year of pregnancy (aOR: 2.2; 95 % CI: 1.3, 3.6; p < 0.01) and among those born in Canada as compared to those not (aOR: 2.0; 95 % CI: 1.1, 3.6; p = 0.02) CONCLUSION: Uptake of pertussis vaccination during pregnancy in Ontario has increased in recent years, however coverage remains lower than desirable.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".