NCDC to Deploy AI and Real-Time Data for Predictive Disease Surveillance

Officials said the upcoming system will integrate artificial intelligence (AI), climate indicators, population movement data, laboratory intelligence, and digital diagnostics to anticipate disease trajectories and strengthen public health preparedness.

The National Centre for Disease Control (NCDC) is moving to overhaul India’s disease surveillance framework by shifting from traditional detection methods to an AI-enabled predictive model capable of forecasting outbreaks in real time.

Officials said the upcoming system will integrate artificial intelligence (AI), climate indicators, population movement data, laboratory intelligence, and digital diagnostics to anticipate disease trajectories and strengthen public health preparedness.

Senior NCDC officials on Friday noted that the model is being designed to generate early warning signals by combining multiple streams of intelligence. The platform will build on the AI-based event surveillance systems currently used under the Integrated Health Information Platform (IHIP) of the Integrated Disease Surveillance Programme (IDSP).

A key component driving this transition is the Media Scanning and Verification Cell (MSVC), which already uses an AI-powered pipeline to scan millions of online news reports across 13 Indian languages every day. The system automatically extracts structured health-event information such as disease type, location, and event magnitude. Since 2022, the pipeline has processed over 300 million news articles and flagged more than 95,000 unique health-related events, helping authorities identify emerging threats.

Officials said the shift to predictive surveillance will leverage these datasets to model outbreak patterns before the first cases appear. By integrating environmental signals and mobility trends, the system aims to forecast disease risk at the district level and guide rapid deployment of field teams and medical resources.

The NCDC believes this transition will form a proactive disease intelligence network capable of identifying anomalies earlier than traditional reporting channels. The approach is expected to enable targeted interventions, faster containment efforts, and more coordinated public health responses during surges.

In addition to the national-level efforts, newly created Metropolitan Surveillance Units (MSUs) under the Pradhan Mantri Ayushman Bharat Health Infrastructure Mission (PM-ABHIM) have begun demonstrating real-time surveillance capabilities. A senior NCDC official said these units are expected to play a key role in supporting metropolitan outbreak forecasting and strengthening data pipelines feeding into the national predictive model.

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