The Indian Council of Medical Research (ICMR) has rolled out an artificial intelligence-driven surveillance system under the National One Health Mission, aimed at predicting and detecting potential pandemics before they escalate.

The new tool is designed to shift India’s public health approach from reactive outbreak management to predictive surveillance. By analysing genomic data, regional disease trends and environmental indicators, the AI system seeks to identify unusual clusters of infections and flag possible threats at an early stage.

The National One Health Mission was conceived to address the growing link between human health, animals and ecosystems. The COVID-19 pandemic highlighted the urgent need for early-warning systems capable of identifying pathogens before they strain healthcare infrastructure.

According to global health agencies, nearly 60% of emerging infectious diseases are zoonotic, meaning they originate in animals. With its large population, rapid urbanisation and close human-animal interaction, India remains vulnerable to such spillover events.

Under the initiative, the AI platform is expected to monitor viral infections such as Nipah, Zika and different coronavirus strains, along with bacterial diseases including anthrax and plague. Parasitic illnesses like Kala Azar will also be tracked.

The system will process data from laboratory reports, symptom patterns, livestock health records and environmental factors such as rainfall, flooding and vector density. Using pattern recognition and trend modelling, it aims to generate risk alerts and forecast potential outbreaks.

Authorities have invited expressions of interest from organisations to develop advanced AI-enabled pathogen surveillance platforms. The focus will be on real-time analytics, genomic surveillance and integration of cross-sectoral data.

Health experts say such AI tools can support faster decision-making by identifying anomalies that may be missed in fragmented reporting systems. Previous outbreaks, including Nipah cases in Kerala and recurring vector-borne diseases in several states, have underscored the need for quicker detection and response.

Officials believe AI-driven modelling could give policymakers valuable lead time to deploy containment measures, allocate medical resources and issue public advisories.

However, experts caution that the effectiveness of the system will depend on strong data governance, privacy safeguards and reliable digital infrastructure. Seamless integration of data across states and sectors will require sustained coordination and investment, along with ethical oversight to prevent bias and misuse of health information.