Respiratory syncytial virus vaccination strategies for older Canadian adults: a cost–utility analysis
Bibliographic record
Abstract
BACKGROUND: Respiratory syncytial virus (RSV) vaccines could reduce disease burden and costs in older Canadian adults, but vaccination program cost-effectiveness is unknown. We evaluated the cost-effectiveness of different age cut-offs for RSV adult vaccination programs, with or without a focus on people with higher disease risk due to chronic medical conditions. METHODS: We developed a static individual-based model of medically attended RSV disease to compare alternative age-, medical risk-, and age-plus medical risk-based vaccination policies. The model followed a multiage population of 100 000 people aged 50 years and older. Vaccine characteristics were based on RSV vaccines authorized in Canada as of May 2024, with vaccine protection assumed to last 2 years (or 3 years in scenario analyses). We calculated sequential incremental cost-effectiveness ratios in 2023 Canadian dollars per quality-adjusted life year (QALY) from the health-system and societal perspectives, discounted at 1.5%. RESULTS: Although all vaccination strategies averted medically attended RSV disease, universal age-based strategies were not an efficient use of resources compared with medical risk-based strategies. Vaccinating adults aged 70 years and older with 1 or more chronic medical condition was the optimal strategy for a cost-effectiveness threshold of $50 000 per QALY. Results were sensitive to assumptions about vaccine price, but medical risk-based approaches remained optimal compared with age-based strategies, even when vaccine prices were low. Findings were robust to a range of alternative assumptions. INTERPRETATION: Vaccination programs for RSV in some groups of older Canadians with underlying medical conditions are likely cost-effective. These findings can inform the design of vaccination programs.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".