Optimization of an adult immunization program in Canada
Bibliographic record
Abstract
Abstract Background Provincial decisions to fund a new immunization program are generally made on a case-by-case basis, without systematic consideration of how the new immunization program may fit within the larger provincial immunization portfolio. Aim The goal of this study was to develop evidence and tools to guide policy-makers in making fiscally and ethically responsible decisions on which adult immunization programs to include in their portfolio under various constrained budgetary scenarios. Methods Using previously published infectious disease models, cost-utility data was estimated for adult pneumococcal, influenza, pertussis, and shingles immunization programs. This data was then inputted into a newly developed constrained optimization model to determine portfolios of immunization programs that maximize either population health or incremental net monetary benefit, subject to a budget constraint. Sensitivity analyses were conducted on model parameters such as vaccine costs, cost-effectiveness thresholds, and the budget constraint. Results Optimized solutions changed dramatically based on the number of immunization programs included, total budget, what was optimized for (i.e., population health or incremental net monetary benefit), the cost-effectiveness threshold and the assumed vaccine prices. Maximal health gains and budget spending was achieved when optimizing based on population health. Reductions in health gains and budget spending were observed at a CAN$50,000 cost-effectiveness threshold, and at a CAN$30,000 threshold, the budget was significantly underutilized and health gains were noticeably reduced. Conclusion If budgets for the adult immunization portfolio are fixed, then shifting to more expensive programs that offer large health benefits may be preferable. However, if budgets can be spread across various public health programs (i.e., childhood immunization, well-baby programs), it may make more sense to optimize based on cost-effectiveness. Constrained optimization tools could improve goals-based decision-making and allow for transparent and effective methods to make allocation decisions. Highlights Optimized solutions changed dramatically based on the number of immunization programs available, total budget, and the cost-effectiveness threshold. If budgets for the adult immunization portfolio are fixed, then shifting to more expensive programs that offer large health benefits may be preferable. If budgets can be spread across various public health programs, it may make more sense to optimize based on cost-effectiveness. Constrained optimization tools could improve goals-based decision-making and allow for transparent and effective methods to make allocation decisions.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".