Tuberculosis surveillance at mass gatherings: Opportunities, challenges, and future directions

Mass gatherings (MGs) bring large, often mobile populations into close contact, creating environments that can facilitate tuberculosis (TB) transmission, particularly among vulnerable groups such as people living with HIV, the elderly, and attendees from high-burden regions. Evidence from Hajj and other MGs, including the Kumbh Mela, indicates gaps in TB detection, with 0.7–2.9% of pilgrims found to have undiagnosed active disease. Despite these risks, MG health services typically focus on acute outbreaks and emergencies, leaving TB largely unaddressed. Emerging digital health and artificial intelligence tools such as mobile screening units, symptom apps, AI-assisted chest X-rays, and cough sound analysis offer rapid triage, real-time monitoring, and targeted identification of symptomatic or high-risk attendees without requiring universal screening. When deployed strategically, these technologies can strengthen detection, support linkage to care, and complement routine MG medical services. This review examines the opportunities, challenges, and future directions for integrating AI and digital tools into TB surveillance at MGs, highlighting context-specific, ethically grounded, and scalable approaches to enhance TB control in high-risk, resource-limited settings.