The Role of Economic Modelling Studies in Vaccine Decision Making: Focus on Meningococcal C Vaccination
Bibliographic record
Abstract
In recent years, several countries have experienced increases in the incidence of serogroup C meningococcal disease. It can be controlled with older polysaccharide vaccines and particularly the recently developed conjugate vaccines. For 21 developed countries, we investigated the role that economic evaluation played in the decision to introduce the conjugate vaccine into either the routine childhood vaccination schedule, as a mass vaccination 'catch-up' campaign or not at all. A literature review was performed and experts from these countries were contacted. For six countries, we identified published economic evaluations for meningococcal C conjugate vaccination. In four of them (Australia, Canada [Quebec], The Netherlands and the UK) the analyses were performed before a decision about the use of the conjugate vaccine was made. In all of these countries, the economic evaluation offered guidance as to the most efficient way to add the conjugate vaccine to the routine infant immunisation schedule and, in three countries, this advice was adopted by decision makers. In Portugal and Switzerland, initial vaccination decisions were made without the economic evaluations that are influencing current decision making. Of the countries without economic evaluations, six implemented vaccination programmes. Overall, there was a positive correlation between the reported incidence of meningococcal C disease and (a) the decision to vaccinate and (b) performing an economic evaluation. All economic evaluations were modelling studies. The reported cost-effectiveness ratios were sensitive to the age of vaccination, the future meningococcal incidence, vaccine price and some methodological characteristics that varied widely between studies making direct comparisons difficult. In conclusion, in almost all countries where economic evaluations for meningococcal C conjugate vaccinations have been conducted, their results had an important role in the decision-making process. However, in most countries with strongly increasing meningococcal incidence, public health considerations took precedence. In order to improve the international comparability of such studies, firmer national and international modelling guidelines and better adherence to such guidelines seem necessary.
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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 | 0.155 | 0.398 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.008 |
| 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".