An artificial intelligence (AI)–driven disease monitoring tool deployed by the National Centre for Disease Control (NCDC) in 2022 has helped issue over 5,000 real-time outbreak alerts to health authorities across India, according to a new study.
Developed by WadhwaniAI, a New Delhi–based healthcare AI solutions provider, the ‘Health Sentinel’ system dramatically reduced manual surveillance workload by up to 98%, enabling faster outbreak detection, improved epidemic preparedness, and a more proactive public health response, the study (pre-print, pending peer review) suggests.
AI in Public Health Surveillance
Under the International Health Regulations (IHR), nearly 200 countries are obligated to operate robust national disease surveillance systems. India’s Integrated Disease Surveillance Programme (IDSP) traditionally relied on manual media scanning to track unusual health events — a time-consuming and labour-intensive process.
The AI-powered Health Sentinel tool automates this process by monitoring news content from print, electronic, and digital media sources, significantly improving the speed and scale of early outbreak detection.
Multilingual AI Scanning Tracks Health Threats Nationwide
According to the study, Health Sentinel scanned media reports every day in 13 languages, covering diverse regions across the country.
The research notes, “From April 2022 till date, Health Sentinel has processed over 300 million news articles and identified over 95,000 unique health events across India, of which more than 3,500 potential outbreaks were flagged by NCDC epidemiologists.”
Researchers from WadhwaniAI also share that between April 2022 and April 2025, the system generated over 5,000 real-time alerts to state and district health authorities.
AI Replaces Manual Scanning With Human-in-the-Loop Verification
“Traditionally, identifying disease events required manual scanning of newspapers, journals, and reports. With Health Sentinel, this manual process has been replaced by an automated AI system, while still keeping a human-in-the-loop to ensure epidemiologists verify information before alerts are issued ,” said Parag Govil, national programme lead for global health security at WadhwaniAI.
Traditional passive reporting systems — where health facilities report infections — often delay outbreak recognition. As online media volumes soar, manual monitoring is no longer feasible.
The study highlights including epidemiologists from NCDC, highlight that AI-driven surveillance platforms like Health Sentinel can help overcome these challenges by:
- Rapidly identifying unusual health events
- Filtering massive volumes of daily news content
- Reducing manual workload
- Improving outbreak response times
- Strengthening national and global health security
