Abstract for: Dynamic Modelling of Improved Diagnostic Testing to Reduce Amplification of Drug-Resistant Tuberculosis in High Burden Settings

Drug-resistant tuberculosis (DR-TB) poses a major challenge to global control and elimination efforts. Unfortunately, many forms of drug resistance are not detected by current rapid diagnostic tests, leading to higher treatment failure and mortality rates, as well as amplification of drug resistance that can result in multi-drug resistant TB (MDR-TB). New diagnostic tools, such as GeneXpert XDR and targeted Next-Generation Sequencing are potential point of care technologies that detect a wider range of drug resistance. This study aims to use dynamic modelling to determine the impact of improved diagnostic testing in high-burden TB settings, using the Philippines and Thailand as case studies. The model will quantify the impact of different DR-TB diagnostic tools and strategies on total DR-TB prevalence, incidence and mortality over a 10-year period. A cost-effectiveness analysis will be conducted to compare the incremental cost-effectiveness ratio (ICER) across each strategy, considering disability-adjusted life years (DALYs) averted and TB testing and treatment costs under each strategy, to better inform future health policy.