Evaluation of chest X-ray with automated interpretation algorithms for mass tuberculosis screening in prisons: a cross-sectional study.

Background: The World Health Organization (WHO) recommends systematic tuberculosis (TB) screening in prisons. Evidence is lacking for accurate and scalable screening approaches in this setting. We aimed to assess the accuracy of artificial intelligence-based chest x-ray interpretation algorithms for TB screening in prisons.

Detection of M. tuberculosis in the environment as a tool for identifying high-risk locations for tuberculosis transmission.

Tuberculosis (TB) remains a leading cause of infectious mortality globally, yet most cases cannot be epidemiologically linked even with extensive contact investigations and whole genome sequencing. Consequently, there remain major gaps in our understanding of where and when M. tuberculosis (Mtb) exposures occur.

Pooling Sputum Samples for Efficient Mass Tuberculosis Screening in Prisons.

Background: Although systematic tuberculosis screening in high-risk groups is recommended by the World Health Organization (WHO), implementation in prisons has been limited due to resource constraints. Whether Xpert Ultra sputum pooling could be a sensitive and efficient approach to mass screening in prisons is unknown.

Methods: In total, 1280 sputum samples were collected from incarcerated individuals in Brazil during mass screening and tested using Xpert G4.