The impact of varicella vaccination on paediatric herpes zoster epidemiology: a Canadian population-based retrospective cohort study
Bibliographic record
Abstract
The impact of universal varicella vaccination on herpes zoster (HZ) risk in unvaccinated and vaccinated children, and its long-term influence on HZ epidemiology, remains unknown. We conducted a retrospective cohort study using population-based administrative health data for children born between 1993 and 2018 (n = 924,124). We calculated age-specific cumulative HZ incidence rates by vaccination status for cohorts born before (1993-1999) and after (2000-2018) programme implementation; results were used to calculate relative risk of HZ by age group, vaccination status and vaccine availability period. Annual HZ incidence rates were calculated for 1993-2018. HZ risk was higher among unvaccinated children compared to vaccinated children across age groups; 64% higher before universal vaccination (RR: 0.36, 95% CI: 0.33, 0.39), and 32% higher after universal vaccination (RR: 0.68, 95% CI: 0.64, 0.73). Among unvaccinated children, HZ risk was 60% lower after vaccine programme implementation (RR: 0.40, 95% CI: 0.38, 0.43). Two-dose receipt corresponded with a 41% lower risk of HZ compared to one-dose receipt (RR: 0.59, 95% CI: 0.53, 0.65). Crude annual HZ incidence rates declined 64% after programme implementation, with decreases observed across age groups. Universal varicella vaccination programme implementation corresponds to decreased paediatric HZ incidence across age groups, in both vaccinated and unvaccinated individuals. Results from this study can be used to help inform varicella vaccination programme decision-making in other countries.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".