Evaluation of serogroup C and ACWY meningococcal vaccine programs: Projected impact on disease burden according to a stochastic two-strain dynamic model
Bibliographic record
Abstract
OBJECTIVE: Advisory committees in Canada and the United States have updated recommendations for quadrivalent meningococcal conjugate vaccines against serogroups A, C, W135, and Y. Our objective was to evaluate optimally effective meningococcal vaccination policies using a stochastic dynamic model. Canada was used as an example. METHODS: Our stochastic dynamic model of Neisseria meningitidis (Nm) transmission in an age-structured population assumed partial cross-immunity among two aggregated serogroup categories: 'AWY' containing A, W135, and Y; and 'Other' containing B, C, and ungroupable types. We compared the impact of monovalent C versus quadrivalent ACWY vaccination on Nm carriage and invasive meningococcal disease (IMD). Our model was parameterized with Canadian epidemiological and demographic data and employed probabilistic sensitivity analysis. RESULTS: Routine infant immunization at 12 months and boosting at 15 years with a quadrivalent vaccine is projected to have the largest impact on total IMD incidence: a 74% reduction over 40 years. Routine infant immunization with a monovalent vaccine at 12 months only has much less impact and also generates strain replacement appearing after approximately ten years of continuous use. CONCLUSIONS: Immunizing infants at 12 months and boosting adolescents at 15 years with an ACWY vaccine is predicted to be most effective at reducing IMD incidence.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 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 | 0.002 | 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".