This alarming conclusion came after a research team from Ashoka University developed an advanced simulation model called BharatSim, capable of simulating human interactions in homes, workplaces, and markets.
When applied to the Namakkal region of southern India, a major poultry hub with more than 1,600 farms, the results showed that the avian influenza virus (H5N1) could spread from initial contacts to a wide community spread in just two days.
According to the simulated model, the epidemic chain begins with the infection of workers in farms or wet markets, after which the virus is transmitted to their family members, and then spreads through their daily interactions in workplaces, schools, and public places.
The real danger lies in the fact that even a slight delay in implementing control measures could prevent the outbreak from being contained. Simulations indicate that preventative culling of birds loses most of its effectiveness if delayed more than ten days after the initial detection of an outbreak among birds. Isolation of human cases should begin as soon as two infections are detected, while targeted vaccination programs need to be launched immediately in high-risk areas.
The researchers emphasize that these findings are of exceptional importance in light of the unprecedented spread of highly pathogenic avian influenza currently occurring in Europe, which has so far led to the culling of hundreds of millions of birds and threatened food security in many regions.
Although human infections remain limited, global health experts warn that mutated strains of the virus could have the potential to spark the next global pandemic.
Researchers point out that the narrow window for effective intervention means that the early stages of an outbreak are the only golden opportunity available to health authorities. Once widespread community transmission begins, the only remaining options are the most restrictive public health measures, such as lockdowns, mandatory mask-wearing, and mass vaccination campaigns—measures that come at a high social and economic cost.
In an effort to turn these warnings into practical tools, the research team is working on developing an early warning system based on real-time computer modeling, which can analyze initial case reports and provide immediate recommendations to control outbreaks before they get out of control, in a scientific effort aimed at giving the world a better chance to face future pandemic threats.
