The everchanging epidemiology of meningococcal disease worldwide and the potential for prevention through vaccination
Bibliographic record
Abstract
Neisseria meningitidis is a major cause of bacterial meningitis and septicaemia worldwide and is associated with high case fatality rates and serious life-long complications among survivors. Twelve serogroups are recognised, of which six (A, B, C, W, X and Y) are responsible for nearly all cases of invasive meningococcal disease (IMD). The incidence of IMD and responsible serogroups vary widely both geographically and over time. For the first time, effective vaccines against all these serogroups are available or nearing licensure. Over the past two decades, IMD incidence has been declining across most parts of the world through a combination of successful meningococcal immunisation programmes and secular trends. The introduction of meningococcal C conjugate vaccines in the early 2000s was associated with rapid declines in meningococcal C disease, whilst implementation of a meningococcal A conjugate vaccine across the African meningitis belt led to near-elimination of meningococcal A disease. Consequently, other serogroups have become more important causes of IMD. In particular, the emergence of a hypervirulent meningococcal group W clone has led many countries to shift from monovalent meningococcal C to quadrivalent ACWY conjugate vaccines in their national immunisation programmes. Additionally, the recent licensure of two protein-based, broad-spectrum meningococcal B vaccines finally provides protection against the most common group responsible for childhood IMD across Europe and Australia. This review describes global IMD epidemiology across each continent and trends over time, the serogroups responsible for IMD, the impact of meningococcal immunisation programmes and future needs to eliminate this devastating disease.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".