Targeting TB transmission hotspots to find undiagnosed TB in South Africa: a genomic, geospatial and modeling study (TARGET- TB)

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Project Summary Despite renewed public health efforts, including more effective treatment, tuberculosis (TB) incidence has reduced only incrementally, an effect driven by the inability to contain community TB transmission. Early identification and treatment of infectious individuals is central to breaking the chain of transmission and is limited by the fact that up to 40% of incident TB cases remain undiagnosed. The associated prolonged duration of infectiousness and delays in treatment initiation contributes significantly to ongoing TB transmission. Undiagnosed cases comprise diseased individuals who have been missed by the healthcare system and those without symptoms (subclinical TB) where the ability to transmit TB is unknown. In our preliminary data, using active case finding and whole blood RNA biomarker, we identified subclinical TB disease at proportions that approach or exceed that of symptomatic active TB. These cases were associated with the presence of viable bacilli in the sputum, pointing to a large potentially infectious pool of individuals. In high-transmission settings, highly targeted approaches like household contact investigation will capture only a small proportion of TB cases, yet general-population approaches are too inefficient to be practical. New case finding methods are needed that increase diagnostic yield through targeted screening in high-prevalence and high-transmission subpopulations. In low-incidence settings, standard mapping tools have been used to identify target populations for enhanced case-finding. Whether similar methods are sufficient in endemic settings is unknown and critical to advance new case-finding approaches. To develop appropriate strategies, we must first understand the mechanisms and spatial patterns of community-level TB transmission that include subclinical TB. Advances in spatial and genomic statistical modeling coupled with sensitive diagnostics now enable evaluation of spatially targeted TB screening in high-burden communities. We hypothesize that transmission hotspots harbor large number of individuals with undiagnosed and subclinical TB that when targeted can improve efficiency of TB case finding. In Aim 1, we determine the proportion of TB transmission that occur within spatially organized hotspots. In Aim 2, we test whether spatially targeted case-finding will be more effective and efficient than broader approaches for identifying active and subclinical prevalent TB. To accomplish our aims, we incorporate innovative spatial statistical modeling with Bayesian phylodynamic methods to infer TB transmission using whole genome sequencing data, and use novel RNA biomarker and Xpert Ultra with chest radiography to detect prevalent TB in the community. If undetected prevalent TB, including subclinical forms are, in fact, concentrated in locales of transmission, this would have important and practical implications for targeted community TB screening strategies as a means to identify infectious individuals early and interrupt transmission by early initiation of TB treatment.