Coverage for pertussis vaccination during pregnancy with 4 models of vaccine delivery: a quasiexperimental, multicentre observational study
Bibliographic record
Abstract
BACKGROUND: Vaccination of pregnant people with a vaccine containing acellular pertussis (tetanus-diphtheria-acellular pertussis [Tdap]) has been recommended in Canada since 2018, and the evaluation of delivery models for efficient maternal Tdap administration is a priority for the Quebec Ministry of Health. We implemented 3 vaccine delivery models, in addition to the existing standard of practice model, and compared the vaccine coverage achieved by the 4 models in Quebec. METHODS: In this quasiexperimental, multicentre observational study, we recruited pregnant people at less than 21 weeks' gestation in 4 Quebec regions from April to October 2019. We compared 4 vaccine delivery models: local community service centres (centre local de services communautaires [CLSCs], baseline), family medicine groups (FMGs), obstetrics clinic and the oral glucose challenge test (OGCT). In addition to the CLSCs, 3 FMGs, 1 obstetric clinic and a hospital-based OGCT screening program participated. We determined vaccination status from a self-reported questionnaire, the Quebec Immunization Registry or medical charts. We compared model-specific (for participants recruited to a model and subsequently vaccinated within that model) and overall vaccine coverage (considering all vaccine delivery pathways) and used logistic regression to adjust for sociodemographic variables. RESULTS: Overall, 946 of 1000 recruited pregnant people were eligible for analyses. Vaccination via the FMGs achieved the highest model-specific vaccine coverage (67.8%, 95% confidence interval [CI] 60.5%-74.4%), but coverage was not significantly different from the CLSCs (63.8%, 95% CI 57.6%-69.6%). For overall vaccine coverage, the FMG (86.5%, 95% CI 80.6%-90.9%) and obstetrics models (85.9%, 95% CI 80.9%-89.7%) achieved significantly higher vaccine coverage than the CLSCs (66.3%, 95% CI 60.1%-71.9%). The OGCT model did not improve overall vaccine coverage (61.8%, 95% CI 56.1%-67.2%). INTERPRETATION: Compared with CLSCs, overall vaccine coverage was higher when Tdap was offered in FMGs or an obstetrics clinic providing prenatal care. Health professionals involved in pregnancy follow-up recommending and offering the vaccine may be a key factor in optimizing 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) | 0.002 | 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".