Gaps in childhood immunizations and preventive care visits during the COVID-19 pandemic: a population-based cohort study of children in Ontario and Manitoba, Canada, 2016–2021
Bibliographic record
Abstract
OBJECTIVE: We aimed to estimate the changes to the delivery of routine immunizations and well-child visits through the pandemic. METHODS: Using linked administrative health data in Ontario and Manitoba, Canada (1 September 2016 to 30 September 2021), infants <12 months old (N=291,917 Ontario, N=33,994 Manitoba) and children between 12 and 24 months old (N=293,523 Ontario, N=33,001 Manitoba) exposed and unexposed to the COVID-19 pandemic were compared on rates of receipt of recommended a) vaccinations and b) well-child visits after adjusting for sociodemographic measures. In Ontario, vaccinations were captured using physician billings database, and in Manitoba they were captured in a centralized vaccination registry. RESULTS: Exposed Ontario infants were slightly more likely to receive all vaccinations according to billing data (62.5% exposed vs. 61.6% unexposed; adjusted Relative Rate (aRR) 1.01 [95% confidence interval (CI) 1.00-1.02]) whereas exposed Manitoba infants were less likely to receive all vaccines (73.5% exposed vs. 79.2% unexposed; aRR 0.93 [95% CI 0.92-0.94]). Among children exposed to the pandemic, total vaccination receipt was modestly decreased compared to unexposed (Ontario aRR 0.98 [95% CI 0.97-0.99]; Manitoba aRR 0.93 [95% CI 0.91-0.94]). Pandemic-exposed infants were less likely to complete all recommended well-child visits in Ontario (33.0% exposed, 48.8% unexposed; aRR 0.67 [95% CI 0.68-0.69]) and Manitoba (55.0% exposed, 70.7% unexposed; aRR 0.78 [95% CI 0.77-0.79]). A similar relationship was observed for rates of completed well-child visits among children in Ontario (aRR 0.78 [95% CI 0.77-0.79]) and Manitoba (aRR 0.79 [95% CI 0.77-0.80]). CONCLUSION: Through the first 18 months of the pandemic, routine vaccines were delivered to children < 2 years old at close to pre-pandemic rates. There was a high proportion of incomplete well-child visits, indicating that developmental surveillance catch-up is crucial.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 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".