Tuberculosis remains one of the most consequential infectious disease crises in modern public health, and the prospect of shrinking global health budgets arriving precisely as WHO's 2035 elimination targets approach makes this analysis unusually high-stakes. Understanding where the burden truly sits — stratified by HIV co-infection, drug resistance, and modifiable risk factors — is essential for allocating what may become increasingly scarce resources.
Drawing on the Global Burden of Disease 2023 framework, this systematic analysis quantified TB mortality, morbidity, and disability-adjusted life-years across 204 countries and territories from 1990 through 2023. The researchers deployed a multi-model approach: the Cause of Death Ensemble model integrated vital registration, surveillance, verbal autopsy, and minimally invasive tissue sampling data, while DisMod-MR 2.1 simultaneously estimated incidence, prevalence, and mortality stratified by age and sex. A population attributable fraction method then disaggregated burden by HIV status and drug-resistance profile — including multidrug-resistant TB — and separately attributed fractions of burden to alcohol use, smoking, and elevated fasting plasma glucose. Disability-adjusted life-years were calculated as the combined sum of years of life lost and years lived with disability.
The scope here is genuinely significant. GBD studies of this scale represent the most methodologically rigorous attempts to reconcile heterogeneous national data systems into comparable estimates, and the 1990–2023 timeframe captures both the HIV-driven TB resurgence and the COVID-era disruption to TB services. The MDR-TB stratification is particularly valuable, as drug-resistant strains have consistently outpaced control efforts and represent a distinct epidemiological challenge from drug-sensitive disease. The risk factor attribution — linking alcohol, tobacco, and glycemic dysregulation to TB burden — shifts the conversation toward prevention pathways that fall outside traditional infectious disease infrastructure. Critically, this remains a modelling study, inheriting the limitations of underlying surveillance quality, which varies enormously across high-burden settings. Its primary contribution is establishing a 2023 baseline against which the impact of funding disruptions can be measured in future analyses.