Why the Anti-Meningococcal B Vaccination during Adolescence Should Be Implemented in Italy: An Overview of Available Evidence
Bibliographic record
Abstract
Although meningococcal disease has a low incidence in Italy, it is a public health concern owing to its high lethality rate and high frequency of transitory and/or permanent sequelae among survivors. The highest incidence rates are recorded in infants, children and adolescents, and most of the cases are due to Neisseria meningitidis B. In Italy, anti-meningococcal B (anti-MenB) vaccination is free for infants but, despite the considerable disease burden in adolescents, no national recommendation to vaccinate in this age-group is currently available. The aim of this study was to assess the main available scientific evidence to support the Italian health authorities in implementing a program of free anti-MenB vaccination for adolescents. We conducted an overview of the scientific literature on epidemiology, disease burden, immunogenicity and safety of available vaccines, and economic evaluations of vaccination strategies. Each case of invasive meningococcal disease generates a considerable health burden (lethality rate: 9%; up to 60% of patients experience at least one sequela) in terms of impaired quality of life for survivors and high direct and indirect costs (the mean overall cost of acute phase for a single case amounts to about EUR 13,952; the costs for post-acute and the long-term phases may vary widely depending of the type of sequela, reaching an annual cost of about EUR 100,000 in cases of severe neurological damage). Furthermore, vaccination against meningococcus B in adolescence proved cost-effective. The study highlights the need to actively offer the anti-MenB vaccination during adolescence at a national level. This would make it possible to avoid premature deaths and reduce the high costs borne by the National Health Service and by society of supporting survivors who suffer temporary and/or permanent sequelae.
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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 | 0.011 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".