A Cost-Effectiveness Analysis of the Switch to 20-Valent Pneumococcal Conjugate Vaccine from Lower-Valent Pneumococcal Conjugate Vaccines in the French Pediatric Population
Bibliographic record
Abstract
INTRODUCTION: The pneumococcal conjugate vaccine (PCV) with valency of 20 (PCV20) was approved for pediatric use by the European Commission in 2024. However, PCV20 is not yet implemented into the French infant National Immunization Program (NIP). In this cost-effectiveness analysis, we compared PCV20 under a 3 + 1 schedule to the current standard of care (13-valent PCV [PCV13]) or 15-valent PCV (PCV15), both under a 2 + 1 schedule, for infant vaccination in France. METHODS: The study adopted a multiple-cohort population-level model under the French Collective perspective over a 10-year time horizon. Inputs were sourced from published and unpublished studies conducted in the French population, where available. Clinical outcomes included disease cases (i.e., invasive pneumococcal disease [IPD], inpatient pneumonia, and otitis media [OM]) and deaths. Incremental cost-effectiveness ratios were calculated on the basis of estimated costs and quality-adjusted life years (QALY) for PCV20 3 + 1 versus PCV15 2 + 1 and PCV13 2 + 1 in separate pairwise comparisons. RESULTS: Compared with PCV13 2 + 1 and PCV15 2 + 1, PCV20 3 + 1 was estimated to be dominant, resulting in improved public health and economic outcomes. PCV20 was predicted to prevent more disease cases versus PCV13 (IPD: 13,510; hospitalized pneumonia: 317,136; hospitalized OM: 66,579) and PCV15 (IPD: 11,187; hospitalized pneumonia: 255,790; hospitalized OM: 53,733) and provide cost-savings of €1,567,052,379 and €1,134,653,266 versus PCV13 and PCV15, respectively. CONCLUSIONS: This study predicted that infant immunization with PCV20 was the most cost-effective option compared with PCV13 and PCV15. These results could help decision-makers implement the optimal PCV strategy in the French pediatric NIP.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".