Epidemiology of varicella zoster virus infection in Canada and the United Kingdom
Bibliographic record
Abstract
Many countries are currently studying the possibility of mass vaccination against varicella. The objective of this study was to provide a comprehensive picture of the pre-vaccine epidemiology of the varicella zoster virus (VZV) to aid in the design of immunization programs and to adequately measure the impact of vaccination. Population-based data including physician visit claims, sentinel surveillance and hospitalization data from Canada and the United Kingdom were analysed. The key epidemiological characteristics of varicella and zoster (age specific consultation rates, seasonality, force of infection, hospitalization rates and inpatient days) were compared. Results show that the overall epidemiology of varicella and zoster is remarkably similar between the two countries. The major difference being that, contrary to Canada, the epidemiology of varicella seems to be changing in the United Kingdom with an important decrease in the average age at infection that coincides with a significant increase in children attending preschool. Furthermore, differences exist in the seasonality between the United Kingdom and Canada, which seem to be primarily due to the school calendar. These results illustrate that school and preschool contact patterns play an important role in the dynamics of varicella. Finally, our results provide baseline estimates of varicella and zoster incidence and morbidity for VZV vaccine effectiveness and cost-effectiveness studies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".