Researchers observed a 150% increase in published health events since 2022, marking a significant shift from earlier years when disease surveillance relied heavily on manual, human-led monitoring. This rise coincided with the deployment of an artificial intelligence–powered surveillance tool by the National Centre for Disease Control (NCDC).
Health Sentinel Processes Millions of Articles
NCDC introduced ‘Health Sentinel’—an AI tool developed by New Delhi–based WadhwaniAI—in April 2022. Since then, the system has processed over 300 million news articles in 13 languages and identified more than 95,000 unique health events across India. Public health experts at NCDC shortlisted over 3,500 events as potential outbreaks.
Furthermore, researchers reported that between April 2022 and April 2025, the tool helped issue more than 5,000 real-time alerts to health authorities, potentially accelerating outbreak detection across the country.
Automation Reduces Manual Workload Dramatically
Traditionally, health officials manually scanned newspapers, journals, and online reports to detect unusual health events. However, this labor-intensive approach became increasingly impractical as the volume of daily published content surged.
By contrast, Health Sentinel’s automated system reduced manual workload by nearly 98%, while still maintaining a human-in-the-loop approach. Epidemiologists review and verify the AI-flagged events before forwarding them to district and state authorities.
Shift from Passive Reporting to AI-Enabled Event Detection
Earlier, India’s disease surveillance system relied mainly on passive reporting, where health authorities analyzed data submitted by physicians and hospitals. As a result, informal sources—such as digital news and online media—gained prominence for early outbreak detection.
As reported by The Hindu, the study’s authors emphasized that the explosion in online content made manual screening unmanageable. Consequently, they proposed integrating AI to extract outbreak-related information rapidly and at scale.
AI Dominates Event Detection in Recent Years
By 2024, 96% of events published by the national surveillance system came from Health Sentinel, while only 4% resulted from manual scanning. This trend underscores the growing role of AI-based tools in strengthening public health surveillance.
Event-Based Surveillance Pilots Show Promise
In parallel, researchers continue to test complementary surveillance models. For example, a study published in the Indian Journal of Medical Research piloted an event-based surveillance (EBS) system in six private hospitals in Kasaragod, Kerala. The system analyzed case records of patients admitted with acute febrile illness (AFI) and used an algorithm to identify illness clusters.
Between May and December 2023, the algorithm screened nearly three-fourths of more than 4,500 AFI cases. It detected 88 clusters, most of which were linked to severe acute respiratory illness, acute encephalitis syndrome, or AFI with rash. Health officials verified 10 clusters as outbreak events, including dengue and COVID-19. The authors noted that the EBS pilot enhanced early outbreak detection and could be adopted in high-risk districts.
Growing Research on AI and Online Data for Surveillance
Past studies reinforce the relevance of online data in public health monitoring. A 2020 review in the Journal of Biomedical Informatics examined 148 studies from 2010–2019 and found that machine learning played a major role in social-media–based surveillance. Nearly one-fourth of the studies focused on flu-related monitoring, with Twitter emerging as the most widely used platform.
Similarly, a 2017 study in the American Journal of Tropical Medicine and Hygiene highlighted how news-based data can help overcome delays in reporting confirmed cases of infections such as dengue.
Conclusion
Together, these findings demonstrate that AI-driven tools and event-based surveillance systems provide faster, more scalable approaches to detecting infectious disease outbreaks. As disease threats evolve, integrating automated systems with expert human verification may significantly strengthen India’s public health preparedness.