NEW DELHI– As the H5N1 avian influenza virus continues to evolve rapidly with the potential to pose a serious threat to human health, Indian researchers have used an artificial intelligence-based model to map how the virus could spill over from birds to humans and eventually spread between people.
The study, published in the journal BMC Public Health, uses BharatSim, an ultra-large-scale agent-based simulation framework originally developed for Covid-19 modeling, to describe the sequential stages of a zoonotic spillover involving H5N1.
“We modelled the possibility of initial spillover events of H5N1 from birds to humans, followed by sustained human-to-human transmission,” said Philip Cherian and Gautam I. Menon of the Department of Physics at Ashoka University in Haryana, according to the paper.
“Our model describes the two-step nature of outbreak initiation, showing how crucial epidemiological parameters governing transmission can be calibrated given data for the distribution of the number of primary and secondary cases at early times,” the researchers added.
Avian influenza H5N1 first emerged in China in the late 1990s and has since caused sporadic human infections. With South and Southeast Asia home to some of the world’s fastest-growing poultry markets, the region is widely considered a likely hotspot for an initial outbreak.
According to the World Health Organization, 990 human H5N1 cases were reported across 25 countries between 2003 and August 2025, resulting in 475 deaths and a fatality rate of about 48 percent.
The researchers found that culling infected birds is the most effective measure to contain H5N1 outbreaks, whether in farms or wet markets, but only if no primary human infection has already occurred.
“In our study of the tertiary attack risk, we found that even if an infection of a primary case occurs, onward infections are limited if cases are isolated and their household contacts quarantined,” the researchers said. “However, once tertiary contacts are infected, establishing control becomes impossible unless far more stringent measures are applied, including a total lockdown.”
The study emphasized that intervention during the earliest stages of an outbreak is critical.
“Once community transmission takes over, cruder public-health measures such as lockdowns, compulsory masking, and large-scale vaccination drives are the only options left,” the researchers said.
The findings highlight how large-scale AI-driven models can help policymakers test containment strategies in real time and improve understanding of the epidemiology of emerging infectious diseases before widespread transmission takes hold. (Source: IANS)
