Cost-Effectiveness Study on the Use of Novel Drug-Resistant Tuberculosis Diagnostics and Tuberculosis Preventive Treatment to End Tuberculosis

Abstract

Background: Tuberculosis (TB) remains a major global health challenge, particularly in high-burden settings and among people with HIV. Achieving the World Health Organization (WHO) End TB Strategy requires improved detection of drug-resistant TB (DR-TB) and effective scale-up of tuberculosis preventive treatment (TPT). However, economic evidence to guide the adoption of novel diagnostic technologies and optimized TPT delivery strategies remains limited. This thesis aimed to generate policy-relevant economic evidence to inform TB diagnostic and prevention strategies across diverse high-burden settings.

Methods: Three complementary studies were conducted. First, a stochastic decision-analytic model was developed to evaluate the cost-effectiveness of targeted next-generation sequencing (tNGS) for DR-TB detection in India, South Africa, and Georgia, compared with existing drug susceptibility testing (DST) strategies. Second, a multi-country micro-costing study estimated health system costs of TPT delivery across high-burden settings using standardized bottom-up and top-down costing approaches. Third, a hybrid decision-analytic model integrating a decision tree and Markov framework evaluated the cost-effectiveness of four TPT delivery strategies among people with HIV: (1) standard of care, (2) universal 3HP, (3) TPT with shared decision-making , and (4) TPT with shared decision making plus enhanced adherence support (as a scenario analysis). Outcomes were expressed as incremental cost per disability-adjusted life year (DALY) averted, with uncertainty assessed through deterministic, probabilistic, and scenario analyses.

Results: Across the three studies, the findings provide economic evidence for strengthening TB control across the care cascade. For the detection of DR-TB, the economic value of diagnostic innovation tNGS varied across settings, reflecting differences in existing drug susceptibility testing practices and test costs, highlighting the importance of local context when considering the adoption of new diagnostic technologies to enable appropriate treatment selection and reduce the risk of ongoing transmission and further development of drug resistance. For TB prevention, understanding true TPT delivery costs is essential, and the micro-costing analysis showed that drugs and human resources were the primary cost drivers, providing national programs with realistic, regimen-specific estimates for informed budgeting and resource allocation. Finally, for maximizing preventive treatment impact, combining shorter regimens with patient-centred support delivered the greatest health gains. The strategy providing TPT with shared decision making and enhanced adherence support was cost-effective at $235 per DALY averted, demonstrating that investing in adherence support is both clinically and economically justified. Together, these findings show that effective TB control requires aligning diagnostic investments with local infrastructure, using comprehensive cost data to guide resource allocation, and pairing effective preventive treatment with patient support to ensure treatment completion.

Conclusions: This thesis includes several key pieces of economic evidence, which, taken together, will inform strategic investment decisions across the TB care cascade, from prevention, through detection and treatment. These findings provide actionable evidence to guide national TB programs and global policy efforts toward TB elimination while using resources to ensure the most value for money.