PROJECT SUMMARY Tuberculosis (TB) remains the leading infectious cause of death due to a single pathogen and is a leading cause of death among individuals living with HIV. Improved TB control in high HIV prevalence settings requires new approaches for interrupting TB transmission. Recent studies have revealed substantial heterogeneity in community risk factors for TB, as well as in TB transmission and prevalence, even within high-density urban centers in Africa. Untargeted community-based interventions for active TB case finding in high HIV prevalence settings demand substantial resources to implement yet have not reliably produced population-level benefits. We hypothesize that more precisely targeted TB interventions, informed by whole genome sequencing of M. tuberculosis isolates from all culture-positive TB patients, will result in more effective TB control, and may also have efficiency benefits when compared with less focused community-based interventions in high HIV burden settings. Based on previous studies and preliminary data from our study site in Blantyre, Malawi (where adult HIV prevalence is around 20% and nearly 80% of notified TB cases are HIV seropositive), we believe that HIV care settings and other locations will be identified as TB transmission hotspots where infectious TB cases are in contact with highly susceptible individuals under poor infection control conditions. In this project, we propose to use data and specimens that have been collected from notified TB patients from all diagnostic centers in the city of Blantyre, Malawi between 2015 and the start of our study to accomplish three specific aims: (Aim 1) To synthesize prospectively-collected demographic, spatial and genomic data to illuminate patterns and critical drivers of local TB transmission dynamics in high HIV prevalence settings; (Aim 2) To develop and apply locally-calibrated mathematical models to investigate the potential impact and cost- effectiveness of spatially-targeted TB interventions informed by high-resolution information on locations and sources of infection in high HIV prevalence settings, and (Aim 3) To formally assess the value of information afforded by whole genome sequencing and to estimate the costs and cost-effectiveness of building local capacity for sequencing and analysis of pathogen genomic data.