Cost-effectiveness of alternative strategies for vaccination of adolescents against serogroup B IMD with the MenB-FHbp vaccine in Canada
Bibliographic record
Abstract
OBJECTIVE: Serogroup B meningococci (MnB) are now the largest cause of invasive meningococcal disease (IMD) in Canada. We assessed the clinical and economic impact of 3 adolescent MenB-FHbp immunization strategies. METHODS: A population-based dynamic transmission model was developed to simulate the transmission of MnB among the entire Canadian population over a 30-year time horizon. Age group-based IMD incidence, bacterial carriage and transmission, disease outcomes, costs, and impact on quality of life were obtained from Canadian surveillance data and published literature. The vaccine was assumed to provide 85% protection against IMD and 26.6% against carriage acquisition. The model estimated the impact of routine vaccination with MenB-FHbp in 3 strategies: (1) age 14, along with existing school-based programs, with 75% uptake; (2) age 17 with 75% uptake, assuming school vaccination; and (3) age 17 with 30% uptake, assuming vaccination outside of school. Costs were calculated from the Canadian societal perspective. RESULTS: With no vaccination, an estimated 3974 MnB cases would be expected over 30 years. Vaccination with strategies 1-3 were estimated to avert 688, 1033, and 575 cases, respectively. These outcomes were associated with incremental costs per quality-adjusted life-year of $976,000, $685,000, and $490,000. CONCLUSIONS: Our model indicated that if the vaccine reduces risk of carriage acquisition, vaccination of older adolescents, even at lower uptake, could have a significant public health impact. Due to low disease incidence, MnB vaccination is unlikely to meet widely accepted cost-effectiveness thresholds, but evaluations of new programs should consider the overall benefits of the vaccination.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".