Economic Evaluation of Transitioning to the 20-Valent Pneumococcal Conjugate Vaccine in the Dutch Paediatric National Immunisation Programme
Bibliographic record
Abstract
INTRODUCTION: In 2024, the vaccination strategy against pneumococcal disease in the Dutch paediatric population was changed from the 10-valent pneumococcal conjugate vaccine (PCV) (PCV10) to a 15-valent PCV (PCV15) under a 2 + 1 schedule. We aimed to assess whether switching from PCV15 under a 2 + 1 schedule to 20-valent PCV (PCV20) under a 3 + 1 schedule in the Dutch paediatric national immunisation programme (NIP) would yield economic savings and health benefits. METHODS: A multiple-cohort population model with an annual cycle and 10-year time horizon was adapted for the Dutch population from a societal perspective. Discounting was set at 3.0% and 1.5% for costs and benefits, respectively. Medical and societal costs were calculated, along with cases of invasive and non-invasive pneumococcal disease, and quality-adjusted life years (QALY) for PCV15 and PCV20, from which, the incremental cost-effectiveness ratio (ICER) per QALY was calculated for PCV20 versus PCV15 to determine the economic benefits of PCV20. The model assumptions were tested in probabilistic and deterministic sensitivity analyses, as well as a series of scenario analyses. RESULTS: Both medical and societal cost of disease were substantially lower with PCV20 versus PCV15 (incremental cost-savings of €130,113,010 and €61,593,168, respectively), with total incremental cost-savings of €29,365,696 when considering the cost of the vaccination programme. With an overall QALY gain of 33,232, the ICER per QALY placed PCV20 as the dominant strategy, as it was both more effective and less costly than PCV15. PCV20 was estimated to result in 57,657 fewer pneumococcal disease cases across invasive and non-invasive disease and 1561 fewer disease-related deaths. The sensitivity and scenario analyses demonstrated the robustness of the model results. CONCLUSION: This cost-effectiveness analysis demonstrated that switching from PCV15 2 + 1 to PCV20 3 + 1 in the Dutch paediatric NIP would reduce both the clinical burden and projected costs of pneumococcal disease over 10 years.
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.
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 | 0.015 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".