Trends and characteristics of Tdap vaccination during pregnancy in Ontario, Canada: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: In February 2018, Canada's National Advisory Committee on Immunization (NACI) recommended tetanus toxoid, reduced diphtheria toxoid and acellular pertussis (Tdap) vaccination during pregnancy to protect newborns against pertussis infection. We sought to describe pre- and postrecommendation trends in Tdap vaccination coverage among pregnant Ontario residents. METHODS: Using linked health administrative databases, we conducted a population-based retrospective cohort study of all pregnant individuals who gave birth in Ontario hospitals between April 2012 and March 2020. We described Tdap vaccination patterns in pregnancy for the entire study period and before and after the NACI recommendation. We used log-binomial regression to identify characteristics associated with Tdap vaccination during pregnancy. RESULTS: Among the 991 850 deliveries included, 7.0% of pregnant individuals received the Tdap vaccination during pregnancy. Vaccine coverage increased from 0.4% in 2011/12 to 29.2% in 2019/20. Coverage was highest among individuals who were older, had no previous live births, had adequate prenatal care and received maternity care primarily from a family physician. After adjustment, characteristics associated with lower coverage included younger maternal age, having a multiple birth, residing in a rural location and higher area material deprivation. In 2019/20, 71.0% of vaccinated individuals received the Tdap vaccination during the recommended gestational window (27-32 wk). Stratified analyses of the pre- and postrecommendation cohorts yielded similar findings to the main analyses with a few gradient differences after adjustment. INTERPRETATION: During pregnancy, Tdap vaccination coverage increased substantially in Ontario between 2011/12 and 2019/20, most notably after recommendations for universal Tdap vaccination during pregnancy began in Canada. To further improve vaccine coverage in the obstetric setting, public health strategies should consider tailoring their programs to reach subpopulations with lower vaccine coverage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.003 | 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 teacher head, 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".