India Plans AI-Driven Predictive Surveillance For Pandemic Preparedness

India is preparing to shift from conventional 'detective-style' disease tracking to a forward-looking, predictive surveillance system powered by advanced technologies including Artificial Intelligence (AI), real-time analytics and digital intelligence tools.

Officials say the transition, aimed at spotting early warning signs even before an outbreak takes shape, will dramatically improve response speed, decision-making and containment efforts, in an effort towards India's pandemic preparedness strategy.

One of the programme's key components, the Media Scanning and Verification Cell (MSVC), uses an AI model to scan millions of news reports daily across 13 languages.

The system extracts structured information on disease type, location and scale. Since 2022, it has analysed more than 300 million articles and identified over 95,000 unique health events--an improvement of nearly 150 per cent over manual tracking, while reducing surveillance teams' workload by 98 per cent.

Dr Himanshu Chauhan, Additional Director at the National Centre for Disease Control (NCDC) and head of the Integrated Disease Surveillance Programme (IDSP), said the change builds on the strong performance of AI-enabled event detection systems already deployed on the Integrated Health Information Platform (IHIP).

At the heart of this capability lies the "Health Sentinel', described by NCDC officials as a "digital watchdog" that flags unusual surges in infections such as dengue and chikungunya. Experts review these alerts before field verification. The upcoming predictive framework will build on this technology to forecast disease patterns and trigger interventions even before the first case is detected.

Dr Chauhan noted that the newly operational Metropolitan Surveillance Units (MSUs) under the PM-Ayushman Bharat Health Infrastructure Mission (PM-ABHIM) are already demonstrating their value. He cited a recent incident involving suspected paediatric Acute Encephalitis Syndrome (AES) cases in Chhindwara, Madhya Pradesh, where the MSU Nagpur raised an early alarm. This enabled rapid coordination between state authorities and the Central Surveillance Unit. The National Joint Outbreak Response Team (NJORT), supported by ICMR, NIE and CDSCO, was deployed immediately to conduct on-ground assessments.

According to NCDC Director, Prof (Dr) Ranjan Das, the AES episode shows how India's surveillance network is evolving to detect atypical clinical patterns swiftly, even in complex urban environments. "It highlights the collaborative surveillance model that IDSP and NCDC are strengthening," he said.

Experts say the new predictive system will integrate AI-based event monitoring with laboratory data, climate trends, mobility patterns and digital diagnostics. The enhanced network is expected to help authorities:

Detect early warning signals before symptoms appear - Mobilise emergency teams and resources swiftly - Improve district-level risk management - Prevent large outbreaks using advanced forecasting

Dr Das emphasised that the upgraded approach aligns with the government's vision of building a future-ready public health system capable of tackling infectious diseases, climate-driven risks and emerging health threats.

As India accelerates its move toward predictive intelligence, officials believe the integration of AI-driven monitoring with rapid response mechanisms could significantly boost national health security. "The shift from reactive to anticipatory surveillance is now underway--data-driven, intelligent and predictive," Dr Das said.