Assessing the economics of vaccination for<i>Neisseria meningitidis</i>in industrialized nations: A review and recommendations for further research
Bibliographic record
Abstract
OBJECTIVES: To review the existing health economic literature on meningococcal disease vaccination. METHODS: A Medline search for economic evaluations of vaccination programs for meningococcal disease in developed countries was conducted. All identified studies were reviewed. RESULTS: Nine published studies were identified examining either mass vaccination during outbreaks or routine vaccination. Although net expenses were estimated in almost all studies, the resulting cost-effectiveness ratios varied widely. Vaccination of college-age students was found to be potentially cost-effective in Australia but not in the United States. With one exception, routine vaccination of children and adolescents in Europe was predicted to be cost-effective. Many simplifying assumptions were made, and important elements were often left out, in particular the potential for reduced transmission of disease. CONCLUSIONS: The methods used and the vaccination strategies vary widely, and results do not provide strong grounds for making conclusions as to whether vaccination is cost-effective. Furthermore, in all instances, transmission of disease, changes in population carriage rates, and outbreaks are either ignored, dealt with using very broad simplifying assumptions, or are not necessarily generalizable to other settings. The analyses provide some insight into the potential cost-effectiveness of vaccination, but more importantly, they highlight areas requiring further study. Economic evaluations based on observed outcomes from recently implemented strategies would be helpful, as would more sophisticated health economic models. The choice of vaccination strategies cannot be based on the results of existing economic analyses.
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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 | 0.010 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".