Respiratory syncytial virus vaccination strategies for older Canadian adults: a cost-utility analysis
Bibliographic record
Abstract
ABSTRACT Background Vaccines against respiratory syncytial virus (RSV) have the potential to reduce disease burden and costs in Canadians, but the cost-effectiveness of RSV vaccination programs for older adults is unknown. We evaluated the cost-effectiveness of different adult age cutoffs for RSV vaccination programs, with or without a focus on people with higher disease risk due to chronic medical conditions (CMCs). Methods We developed a static individual-based model of medically-attended RSV disease to evaluate the cost-utility of alternate age-, medical risk-, and age-plus medical risk-based vaccination policies. The model followed a multi-age cohort of 100,000 people aged 50 years and older over a three-year period. Vaccine characteristics were based on RSV vaccines authorized in Canada as of March 2024. We calculated incremental cost-effectiveness ratios (ICERs) in 2023 Canadian dollars per quality-adjust life year (QALY) from the health system and societal perspectives, discounted at 1.5%. Results Although all vaccination strategies averted medically-attended RSV disease, strategies focused on adults with CMCs were more likely to be cost-effective than age-based strategies. A program focused on vaccinating adults aged 70 years and older with one or more CMCs was optimal for a cost-effectiveness threshold of $50,000 per QALY. Results were sensitive to assumptions about vaccine price, but approaches based on medical risk remained optimal compared to age-based strategies even when vaccine prices were low. Findings were robust to a range of alternate assumptions. Interpretation Based on available data, RSV vaccination programs in some groups of older Canadians with underlying medical conditions are expected to be cost-effective.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".