Abstract
Rapid, accurate, sputum-free tests for tuberculosis (TB) triage and confirmation are urgently needed to close the widening diagnostic gap. We summarise key technologies and review programmatic, systems, and resource issues that could affect the impact of diagnostics. Mid-to-early-stage technologies like artificial intelligence-based automated digital chest X-radiography and capillary blood point-of-care assays are particularly promising. Pitfalls in the diagnostic pipeline, included a lack of community-based tools. We outline how these technologies may complement one another within the context of the TB care cascade, help overturn current paradigms (eg, reducing syndromic triage reliance, permitting subclinical TB to be diagnosed), and expand options for extra-pulmonary TB. We review challenges such as the difficulty of detecting paucibacillary TB and the limitations of current reference standards, and discuss how researchers and developers can better design and evaluate assays to optimise programmatic uptake. Finally, we outline how leveraging the urgency and innovation applied to COVID-19 is critical to improving TB patients' diagnostic quality-of-care.