Vaccine effectiveness and impact of meningococcal vaccines against gonococcal infections: A systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: To systematically review and synthesis the evidence of vaccine effectiveness (VE) and impact (VI) of meningococcal vaccines in preventing gonorrhoea. METHODS: We systematically evaluated studies. Literature searches were conducted in PubMed, Embase, Cochrane Library, CINAHL, Google Scholar, clinical trial registries, and major health and immunisation conferences. Meta-analysis was performed with the DerSimonian-Laird random-effects model to estimate the pooled VE. RESULTS: Twelve studies met the criteria for inclusion. VE of meningococcal B (MenB) outer membrane vesicle (OMV) vaccines was evaluated in nine studies, with one study evaluating a non-OMV vaccine, MenB-FHbp. The majority of studies targeted individuals aged 15-30 years. Adjusted VE for OMV vaccines against gonorrhoea ranged from 22% to 46%. MenB-FHbp did not show protection against gonorrhoea. The pooled VE estimates of OMV vaccines against any gonorrhoea infection following the full vaccine series were 33-34%. VI was assessed for 4CMenB in Canada and Australia, for VA-MENGOC-BC in Cuba; and for MenBvac in Norway. VI ranged from a 30% to 59% reduction in gonorrhoea incidence. CONCLUSIONS: 4CMenB and other MenB-OMV vaccines show moderate effectiveness against gonorrhoea. Further research is required to explore the factors associated with vaccine protection, informing more effective vaccination strategies for the management of gonococcal infections.
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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 | 0.025 | 0.074 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.039 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".