School immunization coverage in adolescents during the COVID-19 pandemic: A retrospective cohort study
Bibliographic record
Abstract
INTRODUCTION: Few studies have assessed the impact of the coronavirus disease 2019 (COVID-19) pandemic on immunization coverage for adolescents, and little is known about how coverage has changed throughout the pandemic. We aimed to: (1) assess the change in coverage for school-based vaccines in Alberta, Canada resulting from the pandemic; (2) determine whether coverage differed by geographic health zone and school type; and (3) ascertain whether coverage has returned to pre-pandemic levels. METHODS: Using a retrospective cohort design, we used administrative health data to compare coverage for human papillomavirus (HPV) and meningococcal conjugate A, C, Y, W-135 (MenC-ACYW) vaccines between pre-pandemic (2017-2018 school year) and pandemic (2019-2020 and 2020-2021 school years) cohorts (N = 289,420). Coverage was also compared by health zone and authority type. The 2019-2020 cohort was followed over one year to assess catch-up. RESULTS: Compared to 2017-2018, immunization coverage for HPV was significantly lower in the 2019-2020 (absolute difference: 60.8%; 95% CI: 60.4-61.3%) and 2020-2021 cohorts (absolute difference: 59.9%; 95% CI: 59.4-60.3%). There was a smaller, significant decline in MenC-ACYW coverage comparing 2017-2018 to 2019-2020 (absolute difference: 6.1%; 95% CI: 5.6-6.5%) and 2020-2021 (absolute difference: 32.2%; 95% CI: 31.6-32.7%). Private schools had low coverage overall, while coverage fluctuated by zone. During follow-up of the 2019-2020 cohort, coverage for HPV and MenC-ACYW increased from 5.6% to 50.2%, and 80.7% to 83.0%, respectively. CONCLUSION: There was a substantial decrease in school-based immunization coverage during the COVID-19 pandemic, and coverage has not returned to pre-pandemic levels, suggesting further catch-up is needed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".