Cost-Effectiveness of Prefusion F Protein-Based Vaccines Against Respiratory Syncytial Virus Disease for Older Adults in the United States
Bibliographic record
Abstract
Background: Two prefusion F protein-based vaccines, Arexvy and Abrysvo, have been authorized by the US Food and Drug Administration for protecting older adults against Respiratory Syncytial Virus (RSV)-associated lower respiratory tract illness. We evaluated the health benefits and cost-effectiveness of these vaccines. Methods: We developed a discrete-event simulation model, parameterized with the burden of RSV disease including outpatient care, hospitalization, and death for adults aged 60 years or older in the US. Taking into account the costs associated with these RSV-related outcomes, we calculated the net monetary benefit using quality-adjusted life-years (QALY) gained as a measure of effectiveness, and determined the range of price-per-dose (PPD) for Arexvy and Abrysvo vaccination programs to be cost-effective from a societal perspective. Results: Using a willingness-to-pay of $95,000 per QALY gained, we found that vaccination programs could be cost-effective for a PPD under $120 with Arexvy and $111 with Abrysvo over the first RSV season. Achieving an influenza-like vaccination coverage of 66% for the population of older adults in the US, the budget impact of these programs at the maximum PPD ranged from $5.74 to $6.10 billion. If the benefits of vaccination extend to a second RSV season as reported in clinical trials, we estimated a maximum PPD of $250 for Arexvy and $233 for Abrysvo, with two-year budget impacts of $11.59 and $10.89 billion, respectively. Conclusions: Vaccination of older adults would provide substantial direct health benefits by reducing outcomes associated with RSV-related illness in this population.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".