India set to transition from detective to predictive disease surveillance

India is set to make a major leap in strengthening public health security by shifting from a detective-style disease surveillance model to a predictive analysis model, integrating technologies such as artificial intelligence (AI), real-time data analytics and digital intelligence platforms.

The move aims to detect outbreaks before they escalate, helping health authorities identify early warning signals prior to clinical manifestation, mobilise resources rapidly, strengthen district-level risk mitigation and prevent large-scale public health outbreaks through advanced forecasting.

“The aim is to integrate all disease reporting systems under one surveillance system, the Integrated Health Information Platform(IHIP),” said Dr Ranjan Das, Director, National Centre for Disease Control (NCDC).

Officials said the shift builds on the success of AI-based event surveillance systems already in use under the IHIP of the Integrated Disease Surveillance Programme (IDSP), which monitors more than 50 diseases.

“AI picks up early warning signals — even a cluster of cases — and action is taken based on that,” an official said.

One example of NCDC’s AI-powered tools is the Media Scanning and Verification Cell (MSVC), which scans millions of news reports daily across 13 Indian languages. The tool filters reports related to diseases, their type and location. This information is shared with district authorities, triggering local investigation and response.

“The system has processed over 300 million articles since 2022, flagging over 95,000 unique health-related events — a 150 per cent increase in detection capacity over 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, detecting unusual spikes in diseases like dengue and chikungunya,” the official added.

Authorities are still debating whether to expand surveillance to social media platforms.

“We are discussing using social media for early warning disease control. However, we already have community reporting on IHIP, where citizens can report outbreaks. To filter out bots, reports require OTP verification before being sent to district surveillance teams,” the official added.

He said the shift to predictive surveillance would leverage these analytical capabilities to forecast disease trends and enable intervention even before the first case is reported.

“Typhoid, dengue, malaria and hepatitis A are among the common diseases reported daily by over 45,000 health facilities, including primary health centres and government hospitals. We monitor trends continuously and can identify states or districts where cases are rising,” the official said.

Further supporting the transition to predictive surveillance are the Metropolitan Surveillance Units (MSUs) set up under the PM-Ayushman Bharat Health Infrastructure Mission (PM-ABHIM).

“Metropolitan cities face challenges such as sanitation and waste disposal. These units provide field response for outbreaks,” another official said. For instance, during suspected paediatric Acute Encephalitis Syndrome (AES) cases in Chhindwara district, Madhya Pradesh, the MSU in Nagpur quickly flagged the occurrence to the Central Surveillance Unit, enabling coordination across two states,” another official said.

The NCDC is also collaborating with ministries and scientific institutions, such as the Indian Institute of Science and various IITs, to expand its disease surveillance capabilities.