92 Trends in COVID-19 Vaccination Coverage among Children <5 Years of Age in Canada
Bibliographic record
Abstract
Abstract Introduction/Background COVID-19 vaccinations for those aged 6 months to 5 years were announced in the summer of 2022. Specifically, Moderna Spikevax and Pfizer-BioNTech Comirnaty were authorized on July 14, 2022, and September 9, 2022, respectively. Given that this was the last age group to become eligible for vaccination against COVID-19, promoting and measuring vaccination coverage in this vulnerable population is of public health significance. Objectives This analysis describes and compares the trend in vaccination coverage (VC) over the initial weeks of eligibility in those 0-17 years old. Design/Methods Data were obtained from the Canadian COVID-19 Vaccination Coverage Surveillance System and were analyzed to describe and compare VC of those <5, 5-11, and 12-17-year-olds over the first 16 weeks of eligibility. VC is defined as the percent of the population that have received at least 1 dose of a COVID-19 vaccine. Results Sixteen weeks after those <5 years became eligible for vaccination, coverage was 10.9% in those aged 2-4 and 6.3% in those aged <2. Compared to other paediatric age groups, VC in those <5 is markedly lower, where, after 16 weeks of eligibility, coverage in those aged 5–11 was 54.4% and 81.5% in those 12-17. There was an immediate spike in coverage for both 5–11-year-olds and 12–17-year-olds over the first 4 weeks following eligibility, where VC was 40.1% and 63.3%, respectively. A similar increase was not observed 4 weeks following eligibility in those aged <5, where VC was 7.4% in those aged 2-4 and 4.0% in those <2. The weekly increase in VC decreased more rapidly as age groups decreased; weekly increase in VC slowed to less than 1% in 28 weeks, 20 weeks, and 16 weeks after eligibility in those aged 12-17, 5-11, and <5, respectively. Conclusion These data suggest that VC over time in the <5 population has been slow and has not followed the trajectory of other paediatric populations, when compared to the 5-11 and 12-17 age groups. Reasons for this may include but are not limited to parents and guardians’ knowledge, attitudes, and beliefs toward getting their infant children vaccinated, as well as pandemic fatigue, as eligibility for the infant population occurred after the other paediatric age groups.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".