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This paradigm shift will significantly enhance the country’s ability to detect outbreaks before they escalate, leading to faster decision-making, prompt response and proactive containment.
National Center for Disease Control (NCDC) officials said the move builds on the success of AI-based event surveillance systems already in use under the Integrated Health Information Platform (IHIP) of the Integrated Disease Surveillance Program (IDSP).
The Media Scanning and Verification Cell (MSVC) is leveraging an AI-powered pipeline that scans millions of online news reports daily in 13 Indian languages, extracting structured health event data including type, location and scale of the disease.
He said the system has processed more than 300 million news articles since 2022, flagging more than 95,000 unique health-related events – a 150 per cent increase in detection capability compared to manual systems, with a 98 per cent reduction in workload for surveillance teams.
This transformative technology, known as Health Sentinel, acts as a “digital watchdog” that automatically identifies unusual increases in diseases like dengue, chikungunya and other public health threats, which is then verified by experts for accuracy.
The shift to predictive surveillance will leverage these powerful analytical capabilities to be able to anticipate disease trends and intervene before the first case appears, marking a major advance in India’s pandemic preparedness, an official said.
Further cementing this transformation, the newly established Metropolitan Surveillance Units (MSUs) under the PM-Ayushman Bharat Health Infrastructure Mission (PM-ABHIM) have demonstrated real-time surveillance capabilities, officials said.
In a recent incident involving suspected pediatric acute encephalitis syndrome (AES) cases in Chhindwara district of Madhya Pradesh, MSU Nagpur immediately informed the central monitoring unit about the incident, thereby enabling rapid coordination between stakeholders in both the states.
Rapid expert deployment by the National Joint Outbreak Response Team (NJORT) in collaboration with ICMR, NIE and CDSCO helped scale up the immediate regional response.
Officials said the case reflects the developed capacity of India’s surveillance ecosystem to rapidly detect abnormal clinical patterns and initiate early intervention even in complex urban health settings.
This approach also underlines the focus on collaborative surveillance that IDSP, NCDC have initiated and further strengthened.
Experts say the upcoming predictive model will integrate AI surveillance, laboratory intelligence, climate data, population movement patterns and digital diagnostics to predict the outbreak trajectory.
This proactive disease intelligence network will empower health officials to detect early warning signs before clinical manifestation, rapidly mobilize resources and field teams, and strengthen district-level risk mitigation.
Additionally, it will prevent large-scale outbreaks through advanced forecasting.
Officials stressed that the change is in line with the government’s vision to build a future-ready public health system, enhancing national preparedness against infectious diseases, climate-related health risks and potential pandemics.
As India moves towards this predictive model, the integration of AI-powered surveillance and technology-enabled rapid response mechanisms promises to transform health security with the potential to save thousands of lives through timely, targeted action.
“From being reactive to being predictive – the future of disease surveillance in India is now data-driven, intelligent and predictive,” another official said.