New open-source model guides smarter global TB spending

Tuberculosis remains a stubborn global health crisis, hitting low- and middle-income countries hardest and threatening progress toward the WHO End TB targets. Because resources are limited, deciding which programs, tests and treatments to fund is a matter of life and death. Existing tools for estimating TB costs have struggled to represent the full complexity of care and to support comparisons across diverse populations worldwide. In response, a team led by Carel Pretorius developed a new, open-source TB costing model designed specifically to fill those gaps. The model maps the full TB care cascade — screening, diagnosis, treatment and prevention — and builds those steps into a detailed financial picture for people eligible under WHO guidance. It does this across 20 distinct population groups, capturing differences in how people enter care and in their clinical and social profiles. By creating a flexible, transparent tool, the developers aimed to give policymakers and funders a clearer way to decide which combinations of interventions are most likely to cut TB cases and deaths given the money available.

The model simulates care pathways in depth, representing both patient-initiated and provider-initiated routes to care. It separates 20 groups into 10 patient-initiated and 10 provider-initiated categories and captures variation by pulmonary status, age, HIV/ART status, and drug sensitivity. It also includes the cost implications of deploying a large-scale vaccine. The team demonstrated the model in a real-world case study used to inform the Global Fund's Investment Case for its 8th replenishment (2027-2029). First, the model estimated the cost of implementing the TB Global Plan 2023 - 2030 under a scenario that combined intervention targets, normative standards of care, and the availability of new TB tools. Then an optimization routine was applied across 29 high-burden countries to estimate the maximal possible TB impact when funding is limited. Those results were used to assess the potential contribution of innovation and to guide priorities for the Global Fund's 8th replenishment (2027-2029).

This new TB costing model improves how the economics of TB programs are represented across diverse populations, offering greater transparency, flexibility and policy relevance than many previous tools. By modeling detailed cascades and multiple population subgroups, it helps decision makers compare the likely health returns of different investments and to focus limited funds where they will do the most good. Because the model is open-source, it can be adapted as new tools and evidence emerge and can be scrutinized by researchers and program planners. Its application to the Global Fund case shows how such a tool can inform large investment decisions and support prioritization of interventions that maximize impact under resource constraints. In short, the model is positioned to be a practical aid for countries, donors and global agencies trying to get the biggest TB gains from the dollars available and to accelerate progress toward WHO End TB targets.