4 min readDec 2, 2025 02:55 PM IST
First published on: Dec 2, 2025 at 08:49 AM IST
In a room on Shyam Nath Marg, New Delhi, a surveillance team sits in front of a large screen monitoring the diseases that health workers across the country have reported, be it typhoid, malaria or flu among 50 others. As soon as there is an uptick in the numbers of any disease, the team gets active and raises an alert for the affected area. Health workers in a bloc, district or state get active. They start looking for cases actively, test people, quarantine those suspected to have the infection, or take other measures to ensure that it does not spread.
This is the Integrated Health Information Platform, the online portal that collects data from over 1.5 lakh health workers and facilities. A near real-time reporting of diseases from all levels of healthcare — be it the ANMs or midwives who go door to door, the distant primary health centres, the district hospitals, and even the tertiary care centre — have made swift treatment and containment of any disease possible. While health workers have been reporting diseases for years in the traditional paper file format, it took at least a week to reach Delhi and then some more time for analysis. “Now we are moving from a detective towards a predictive model, where we can take action to prevent outbreaks,” said Dr Ranjan Das, director, National Centres for Disease Control (NCDC).
Started in the middle of the pandemic in 2021, the platform has been working on innovations to raise quicker alerts.
AI and the news
Other than the data reported by health facilities and workers, the surveillance team can also monitor what is happening across the country through newspaper reports. An AI component has been developed to scan through news articles with mentions of unusual clusters of diseases or cases with uncommon symptoms. “Earlier, it would also flag traffic crashes or deaths due to natural disasters. Over time, the algorithm has learnt what we are looking for. Now, it accurately flags news of say several people getting diarrhoea or fainting,” said Dr Himanshu Chauhan, head, Integrated Disease Surveillance Programme. The AI can automatically scan through several newspapers in 13 different languages. “Once an alert is raised by the AI, the officers here do a preliminary check on whether the alert is plausible, and then pass it on to the local teams for verification and initiation of any public health activity if needed,” said Dr Das.
The AI system has processed nearly 300 million news articles since its inception, a 150% increase in such alerts. But, that’s not all.
Community Reporting
Now, the same portal has a section where anyone can report unusual health events. This way the NCDC hopes to make the community a partner in keeping it safe. “People can submit details of any unusual health events they see in their neighbourhood on the platform by providing basic details such as name, age and the place a person lives,” said Dr Chauhan.
The same process of verification and then action will follow. This will make the process of identifying and responding to disease clusters faster.
The disease surveillance body will now use this data, along with data from laboratories, climate and weather data, patterns of people’s movements among others to predict outbreaks. “Once any predictive model is created, there will always be outcomes different from predictions. But we are working to create and train the model to ensure as little chance of error as possible,” said Dr Chauhan.
A near real-time reporting of diseases from all levels of healthcare have made swift treatment and containment of any disease possible. (Photo: Getty) 
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