India has the world’s largest burden of tuberculosis, accounting for an estimated 27% of global TB cases in 2022. In the same year, an estimated 2.8 million people developed TB in India, with approximately 331,000 TB-related deaths1.
Many cases remain undiagnosed and unreported, creating a persistent gap between estimated infections and known cases. Effective TB control depends on directing active case-finding efforts and resources to areas with the highest TB risk. VMTB helps identify these hotspots, enabling more targeted, efficient resource allocation.
Vulnerability Mapping for Tuberculosis (VMTB) is an AI-driven geospatial analytics solution that helps identify areas with a higher likelihood of TB risk, analyzing patterns between the location coordinates of notified TB cases and over 20 geospatial, sociodemographic and health-determining features.
These predictive insights let health authorities visualize TB risk more clearly and prioritize interventions where they're most needed, improving efficiency, strengthening case-finding, and supporting long-term reduction in TB burden.
Integrated within the Ni-kshay portal, deployed pan-India.
By mapping where vulnerability is highest, VMTB helps health systems move from a reactive to a targeted, proactive approach, reducing missed and delayed diagnoses, easing the burden on frontline teams through more focused screening, and improving access to care by directing outreach to areas of greatest need. It supports targeted interventions critical to reducing undiagnosed cases and strengthens progress toward TB elimination.
As these capabilities mature, VMTB holds strong potential for expansion beyond TB, supporting vulnerability identification and targeted interventions across other public health priorities where early risk detection and timely action are critical.