Epidemiology and prevention of meningococcal disease: a critical appraisal of vaccine policies
Bibliographic record
Abstract
Meningococcal disease is characterized by a marked variation in incidence and serogroup distribution by region and over time. In several European countries, Canada and Australia, immunization programs, including universal vaccination of infants or toddlers with catch-up campaigns in children and adolescents, aimed at controlling disease caused by meningococcal serogroup C have been successful in reducing disease incidence through direct and indirect protection. More recently, meningococcal conjugate vaccines targeting disease caused by serogroups A, C, W-135 and Y have been licensed and are being used in adolescent programs in the USA and Canada while a mass immunization campaign against serogroup A disease has been implemented in Africa. Positive results from clinical trials using vaccines against serogroup B disease in various age groups suggest the possibility of providing broader protection against serogroup B disease than is provided by the currently used outer membrane vesicle vaccines. The purpose of our review of meningococcal epidemiology and assessment of existing policies is to set the stage for future policy decisions. Vaccination policies to prevent meningococcal disease in different regions of the world should be based on quality information from enhanced surveillance systems.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".