Meningococcal Disease Outbreaks: A Moving Target and a Case for Routine Preventative Vaccination
Bibliographic record
Abstract
Outbreaks of invasive meningococcal disease (IMD) are unpredictable, can be sudden and have devastating consequences. We conducted a non-systematic review of the literature in PubMed (1997-2020) to assess outbreak response strategies and the impact of vaccine interventions. Since 1997, IMD outbreaks due to serogroups A, B, C, W, Y and X have occurred globally. Reactive emergency mass vaccination campaigns have encompassed single institutions (schools, universities) through to whole sections of the population at regional/national levels (e.g. serogroup B outbreaks in Saguenay-Lac-Saint-Jean region, Canada and New Zealand). Emergency vaccination responses to IMD outbreaks consistently incurred substantial costs (expenditure on vaccine supplies, personnel costs and interruption of other programmes). Impediments included the limited pace of transmission of information to parents/communities/healthcare workers; issues around collection of informed consents; poor vaccine uptake by older adolescents/young adults, often a target age group; issues of reimbursement, particularly in the USA; and difficulties in swift supply of large quantities of vaccines. For serogroup B outbreaks, the need for two doses was a significant issue that contributed substantially to costs, delayed onset of protection and non-compliance with dose 2. Real-world descriptions of outbreak control strategies and the associated challenges systematically show that reactive outbreak management is administratively, logistically and financially costly, and that its impact can be difficult to measure. In view of the unpredictability, fast pace and potential lethality of outbreak-associated IMD, prevention through routine vaccination appears the most effective mitigation tool. Highly effective vaccines covering five of six disease-causing serogroups are available. Preparedness through routine vaccination programmes will enhance the speed and effectiveness of outbreak responses, should they be needed (ready access to vaccines and need for a single booster dose rather than a primary series).
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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 | 0.107 | 0.193 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.011 | 0.038 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.020 | 0.015 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".