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.

The authors have declared no competing interest.

This study was funded by the Canadian Institute for Health Research (CIHR) Catalyst Grant: Impacts of financial and organizational restructuring of public health (Grant Number: 435188). CIHR had no role in the design or conduct of the study.

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The optimization model is available on request, and there is a publicly available version available online.

https://eshiny.ihe.ca/cvop/.