Temporal trends and determinants of COVID-19 vaccine series initiation after recent pregnancy
Bibliographic record
Abstract
During the rapid deployment of COVID-19 vaccines in 2021, safety concerns may have led some pregnant individuals to postpone vaccination until after giving birth. This study aimed to describe temporal patterns and factors associated with COVID-19 vaccine series initiation after recent pregnancy in Ontario, Canada. Using the provincial birth registry linked with the COVID-19 vaccine database, we identified all individuals who gave birth between January 1 and December 31, 2021, and had not yet been vaccinated by the end of pregnancy, and followed them to June 30, 2022 (follow-up ranged from 6 to 18 months). We used cumulative incidence curves to describe COVID-19 vaccine initiation after pregnancy and assessed associations with sociodemographic, pregnancy-related, and health behavioral factors using Cox proportional hazards regression to estimate adjusted hazard ratios (aHR) and 95% confidence intervals (CI). Among 137,198 individuals who gave birth in 2021, 87,376 (63.7%) remained unvaccinated at the end of pregnancy; of these, 65.0% initiated COVID-19 vaccination by June 30, 2022. Lower maternal age (<25 vs. 30-34 y aHR: 0.73, 95%CI: 0.70-0.77), smoking during pregnancy (vs. nonsmoking aHR: 0.68, 95%CI: 0.65-0.72), lower neighborhood income (lowest quintile vs. highest aHR: 0.79, 95%CI: 0.76-0.83), higher material deprivation (highest quintile vs. lowest aHR: 0.74, 95%CI: 0.70-0.79), and exclusive breastfeeding (vs. other feeding aHR: 0.81, 95%CI: 0.79-0.84) were associated with lower likelihood of vaccine initiation. Among unvaccinated individuals who gave birth in 2021, COVID-19 vaccine initiation after pregnancy reached 65% by June 30, 2022, suggesting persistent issues with vaccine hesitancy and/or access to vaccination in this population.
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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 | 0.001 | 0.001 |
| 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 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".