The : a tool for projecting the epidemiological impact of TB policy options.

Background: Tuberculosis (TB) remains one of the deadliest infectious diseases globally. Despite the World Health Organization's (WHO) End TB Strategy targets for 2035, progress has been hindered by structural, financial, and implementation barriers, including recent cuts in global funding. Strategic use of mathematical modelling is useful for prioritizing high-impact interventions and optimizing limited resources. A new global TB infection transmission model was developed to address limitations in existing tools with respect to these applications.

Methods: The model includes enhanced features such as age-specific mixing, explicit representation of asymptomatic TB, stratification by drug resistance, HIV status, and new vaccine status, and inclusion of both public and private care pathways. It was calibrated to country-specific data using Bayesian adaptive Markov Chain Monte Carlo (MCMC) methods. The model was used to assess the impact of national strategic plans and the Global Plan to End TB, using a Target Population (TP) component to map interventions to WHO guidelines.

Results: Model calibration showed good agreement with historical TB data from 29 high-burden countries, with case studies for Indonesia and Nigeria presented here. In Indonesia, comprehensive implementation of Global Plan interventions - including public-private mix efforts, modern diagnostics, improved treatment for drug-resistant TB, and a post-exposure vaccine - could enable the country to achieve End TB targets by 2035. In Nigeria, implementing its National Strategic Plan could reduce TB incidence by 27% and mortality by 37% by 2030, even without a vaccine. The model highlighted the additional efforts that are needed to meet the End-TB goals.

Conclusions: The enhanced TB model provides a flexible, policy-relevant framework for assessing the epidemiological impact of TB interventions at both national and global levels. Its open-source design and alignment with WHO recommendations make it a valuable tool for guiding evidence-based investments amid tightening global health budgets.