ICMR Rolls Out AI Tool under National One Health Mission to Predict Pandemics

By using artificial intelligence to process genomic information, regional disease patterns and environmental indicators, the system has aimed to detect unusual clusters and flag potential outbreaks in advance.

The Indian Council of Medical Research (ICMR) has introduced an AI tool under the National One Health Mission to detect zoonotic, viral and bacterial threats early, aiming to shift India from reactive outbreak response to predictive pandemic surveillance.

By using artificial intelligence to process genomic information, regional disease patterns, and environmental indicators, the system aims to detect unusual clusters and flag potential outbreaks in advance.

The National One Health Mission was conceptualised to address the growing intersection between human health, livestock, wildlife and ecosystems. The COVID-19 crisis exposed the need for early detection systems capable of identifying pathogens before they overwhelm healthcare systems.

Nearly 60% of emerging infectious diseases globally are zoonotic in origin, according to international health agencies, underscoring the importance of surveillance beyond hospitals. India, with its dense population, expanding urbanisation and close human-animal interaction, remains particularly vulnerable to zoonotic spillovers.

The AI tool under ICMR is expected to monitor viral infections such as Nipah, Zika and coronavirus strains, alongside bacterial threats including anthrax and plague. Parasitic diseases like Kala Azar will also be tracked.

By analysing symptom patterns, laboratory reports, livestock health data and environmental triggers such as rainfall, flooding and vector density, the system aims to generate risk alerts. The objective is not only to detect outbreaks but to predict them through pattern recognition and trend modelling.

Authorities have invited expressions of interest from organisations capable of building advanced AI-enabled pathogen surveillance platforms. The emphasis remains on real-time analytics, genomic surveillance and cross-sectoral data integration.

Health experts note that AI tools can accelerate decision-making by identifying anomalies that may otherwise be overlooked in fragmented reporting systems.

This shift reflects a broader move from reactive containment strategies to proactive risk mitigation. Earlier outbreaks, including Nipah in Kerala and recurrent vector-borne infections in several states, have demonstrated the need for faster detection.

With AI-driven modelling, policymakers may gain critical time to deploy containment measures, allocate medical resources and inform the public.

However, experts caution that the success of such AI tools will depend on robust data governance, privacy safeguards and reliable digital infrastructure. Integrating multiple data streams across states and sectors requires coordination and sustained investment.

Ethical oversight will also be necessary to prevent algorithmic bias and ensure responsible use of health data.

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