Patterns in COVID-19 vaccination among children aged 5–11 years in Alberta, Canada: Lessons for future vaccination campaigns
Bibliographic record
Abstract
Objectives: In Alberta, Canada, the COVID-19 vaccination program for children aged 5-11 years was launched on November 26, 2021. Our objectives were to determine the cumulative vaccine coverage, stratified by age, during the first thirteen months of vaccine availability, and investigate factors associated with vaccine uptake. Study design: This retrospective cohort study used population-based administrative health data. Methods: We determined cumulative vaccine coverage among 5-11 year olds, stratified by year of age, during the first thirteen months of vaccine availability and used a modified Poisson regression to evaluate factors associated with vaccine uptake. Results: Of 377,103 eligible children, 44.8 % (n = 168,761) received one or more doses of COVID-19 vaccine during the study period (9.7 % received only one dose, while 35.1 % received 2 doses). Almost 90 % of initial doses were received within the first two months of vaccine availability. We found a step-wise relationship between increasing child age and higher vaccine coverage. Conclusions: Plateaued vaccine uptake indicates a need to adapt programmatic efforts to encourage parents to act on positive vaccination intentions, and reach the large contingent of parents who have reported that they remain undecided. In order to promote vaccine uptake, messaging around vaccine safety and need should be tailored to child age, rather than uniformly applied across the 5-11 year age range.
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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 | 0.005 | 0.006 |
| 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 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".