Cost-effectiveness of respiratory syncytial virus vaccination strategies for older Canadian adults: a multi-model comparison
Bibliographic record
Abstract
ABSTRACT Background Two respiratory syncytial virus (RSV) vaccines are currently approved for use in adults aged 60 years and older in Canada. Economic analyses have shown that adult RSV vaccination programs may be cost-effective, particularly when focused on people at increased risk of RSV disease due to increased age or presence of chronic medical conditions (CMCs). We conducted a multi-model comparison to explore the impact of alternate model structural and methodological assumptions on the cost-effectiveness of RSV vaccination programs. Methods We compared three static cost-utility models developed by the Public Health Agency of Canada, GSK, and Pfizer using a common set of input parameters. Each model evaluated sequential incremental cost-effectiveness ratios (ICERs) in 2023 Canadian dollars per quality-adjusted life year (QALY) for a set of policy alternatives, with vaccine eligibility determined by combinations of age and CMC status. Results were calculated for each vaccine separately for scenarios assuming two or three years of vaccine protection using the health system perspective and a 1.5% annual discount rate. Results The three cost-utility models were broadly concordant across the scenarios modeled. In all scenarios, focusing on vaccination of people with CMCs was preferred over broader age-based policies. RSV vaccination for people with CMCs over the age of 70 years was most commonly identified as the optimal policy when using a cost-effectiveness threshold of $50,000/QALY. When only considering policies based on age criteria, vaccinating people over 80 years was cost-effective at this threshold. Discussion A multi-model comparison of Canadian cost-utility models shows that RSV vaccination programs for RSV are likely cost-effective for some groups of older adults in Canada. These findings were consistent across models, despite differences in model structure.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.010 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".