The potential cost-effectiveness of vaccination against herpes zoster and post-herpetic neuralgia
Bibliographic record
Abstract
A clinical trial has shown that a live-attenuated varicella-zoster virus vaccine is effective against herpes zoster (HZ) and post-herpetic neuralgia (PHN). The aim of this study was to examine the cost-effectiveness of vaccination against HZ and PHN in Canada. A cohort model was developed to estimate the burden of HZ and the cost-effectiveness of HZ vaccination, using Canadian population-based data. Different ages at vaccination were examined and probabilistic sensitivity analysis was performed. The economic evaluation was conducted from the ministry of health perspective and 5% discounting was used for costs and benefits. In Canada (population = 30 million), we estimate that each year there are 130,000 new cases of HZ, 17,000 cases of PHN and 20 deaths. Most of the pain and suffering is borne by adults over the age of 60 years and is due to PHN. Vaccinating 65-year-olds (HZ efficacy = 63%, PHN efficacy = 67%, no waning, cost/course = $150) is estimated to cost $33,000 per QALY-gained (90% CrI: 19,000-63,000). Assuming the cost per course of HZ vaccination is $150, probabilistic sensitivity analysis suggest that vaccinating between 65 and 75 years of age will likely yield cost-effectiveness ratios below $40,000 per Quality-Adjusted Life-Year (QALY) gained, while vaccinating adults older than 75 years will yield ratios less than $70,000 per QALY-gained. These results are most sensitive to the duration of vaccine protection and the cost of vaccination. In conclusion, results suggest that vaccinating adults between the ages of 65 and 75 years is likely to be cost-effective and thus to be a judicious use of scarce health care resources.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".