Updated Postlicensure Surveillance of the Meningococcal C Conjugate Vaccine in England and Wales: Effectiveness, Validation of Serological Correlates of Protection, and Modeling Predictions of the Duration of Herd Immunity
Bibliographic record
Abstract
Meningococcal serogroup C conjugate (MCC) vaccines were licensed in the United Kingdom more than 10 years ago based on correlates of protection that had previously been established for serogroup C-containing polysaccharide vaccines by using the serum bactericidal antibody (SBA) assay. These correlates of protection were subsequently validated against postlicensure estimates of observed vaccine effectiveness up to 7 to 9 months after the administration of the MCC vaccine. Vaccine effectiveness was, however, shown to fall significantly more than 1 year after the administration of a 3-dose course in infancy. Despite this finding, the marked impact on serogroup C disease has been sustained, with the lowest recorded incidence (0.02 case per 100,000 population) in the 2008-2009 epidemiological year, mainly due to the indirect herd immunity effect of the vaccine in reducing carriage. Updated estimates of vaccine effectiveness through 30 June 2009 confirmed high short-term protection after vaccination in infancy, at 97% (95% confidence interval [CI], 91% to 99%), falling to 68% (95% CI, -63% to 90%) more than a year after vaccination. The observed vaccine effectiveness more than 12 months postvaccination was consistent with measured declining SBA levels, but confidence intervals were imprecise; vaccine effectiveness estimates were consistent with SBA titers of 1:4 or 1:8 as correlates of long-term protection after a primary course in infants. Modeling suggested that protection against carriage persists for at least 3 years and predicted the stabilization of serogroup C disease at low levels (fewer than 50 cases per year) up to 2015-2016.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".