Cost-Effectiveness of Nirsevimab for the Prevention of Respiratory Syncytial Virus Infection in Infants
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
During CADTH’s search of the economic literature, 3 economic studies were identified that assessed the cost-effectiveness of a long-acting monoclonal antibody, nirsevimab, as an intervention to prevent respiratory syncytial virus in infants in high-income countries, including 1 study set in Nunavik. The 3 studies were conducted for different geographical locations: Canada, the US, and England and Wales. While each study conducted an economic evaluation, their approaches differed: 1 was a cost-consequence analysis and the other 2 were cost-utility analyses. The results from the 3 studies varied considerably, and the nirsevimab programs differed (e.g., in terms of patients eligible for immunization). In general, nirsevimab was generally more effective and associated with lower total costs than comparator programs. The results were sensitive to the modelled region, source of efficacy data, price of nirsevimab, and severity of the respiratory syncytial virus season. The generalizability of the identified studies to Canadian policy-making may be limited given the population compositions and cost parameters included in the models. To understand the potential cost-effectiveness of nirsevimab, a de novo economic evaluation would be required that compared nirsevimab with the existing preventive strategies employed in Canada (which may include monoclonal antibodies for infants) and is conducted in a Canadian setting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it