Updated post-licensure surveillance of meningococcal C conjugate vaccine in England and Wales: effectiveness, validation of serological correlate of protection and modelling predictions of the duration of herd immunity
Bibliographic record
Abstract
Meningococcal serogroup C conjugate (MCC) vaccines were licensed in the UK more than 10 years ago based on correlates of protection that had previously been established for serogroup C containing polysaccharide vaccines using the serum bactericidal antibody (SBA) assay. These correlates of protection were subsequently validated against post licensure estimates of observed vaccine effectiveness up to 7-9 months after the administration of MCC vaccine. Vaccine effectiveness was however shown to fall significantly more than one 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 ever recorded incidence (0.02 per 100,000 population) in 2008/09, mainly due to the indirect herd immunity effect of the vaccine in reducing carriage. Updated estimates of vaccine effectiveness to 30 June 2009 confirmed high short term protection after vaccination in infancy at 97% (95% CI, 91% to 99%) falling to 68% (95% CI, -63 to 90%) more than a year after vaccination. Observed vaccine effectiveness more than 12 months post vaccination was consistent with measured declining SBA levels but confidence intervals were imprecise and vaccine effectiveness estimates were consistent with SBAs of 1:4 or 1:8 as correlates of long term protection after a primary course in infants. Modelling suggested protection against carriage persists for at least 3 years and predicted stabilisation of serogroup C disease levels at low levels (fewer than 50 cases per year) up to 2015/2016.
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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".