Economic evaluation of vaccines in Canada: A systematic review
Bibliographic record
Abstract
BACKGROUND: Economic evaluations should form part of the basis for public health decision making on new vaccine programs. While Canada's national immunization advisory committee does not systematically include economic evaluations in immunization decision making, there is increasing interest in adopting them. We therefore sought to examine the extent and quality of economic evaluations of vaccines in Canada. OBJECTIVE: We conducted a systematic review of economic evaluations of vaccines in Canada to determine and summarize: comprehensiveness across jurisdictions, studied vaccines, funding sources, study designs, research quality, and changes over time. METHODS: Searches in multiple databases were conducted using the terms "vaccine," "economics" and "Canada." Descriptive data from eligible manuscripts was abstracted and three authors independently evaluated manuscript quality using a 7-point Likert-type scale scoring tool based on criteria from the International Society for Pharmacoeconomics and Outcomes Research (ISPOR). RESULTS: 42/175 articles met the search criteria. Of these, Canada-wide studies were most common (25/42), while provincial studies largely focused on the three populous provinces of Ontario, Quebec and British Columbia. The most common funding source was industry (17/42), followed by government (7/42). 38 studies used mathematical models estimating expected economic benefit while 4 studies examined post-hoc data on established programs. Studies covered 10 diseases, with 28/42 addressing pediatric vaccines. Many studies considered cost-utility (22/42) and the majority of these studies reported favorable economic results (16/22). The mean quality score was 5.9/7 and was consistent over publication date, funding sources, and disease areas. CONCLUSIONS: We observed diverse approaches to evaluate vaccine economics in Canada. Given the increased complexity of economic studies evaluating vaccines and the impact of results on public health practice, Canada needs improved, transparent and consistent processes to review and assess the findings of the economic evaluations of vaccines.
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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 | 0.032 | 0.171 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.019 | 0.025 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".