Indian scientists predict how bird flu could spread to humans

For years, scientists have warned that avian flu – better known as H5N1 – could one day jump dangerously from birds to humans and trigger a global health crisis.

Avian flu – a type of flu – is entrenched throughout South and Southeast Asia and has occasionally infected humans since its emergence in China in the late 1990s. From 2003 to August 2025, the World Health Organization (WHO) reported 990 human cases of H5N1 in 25 countries, including 475 deaths, a mortality rate of 48%.

In the United States alone, the virus has affected more than 180 million birds, spread to more than 1,000 dairy herds in 18 states and infected at least 70 people — most of them farmworkers — causing several hospitalizations and one death. In January, three tigers and a leopard died at a wildlife rescue center in the Indian city of Nagpur, due to the virus that commonly infects birds.

Symptoms in humans mimic those of a severe flu: high fever, cough, sore throat, muscle pain and, sometimes, conjunctivitis. Some people have no symptoms. The risk to humans remains low, but authorities are monitoring the H5N1 virus closely for any changes that could make it easier to spread.

This concern is behind new peer-reviewed modeling by Indian researchers Philip Cherian and Gautam Menon of Ashoka University, which simulates how an H5N1 outbreak could spread in humans and what early interventions could stop it before it spreads.

In other words, the model published in the journal BMC Public Health uses real-world data and computer simulations to determine how an outbreak might spread in real life.

“The threat of an H5N1 pandemic in humans is real, but we can hope to prevent it through better surveillance and a more agile public health response,” Professor Menon told the BBC.

According to the researchers, a bird flu pandemic would start quietly: a single infected bird would transmit the virus to a human – most likely a farmer, a market worker or someone who handles poultry. From there, the danger lies not in the first infection but in what happens next: sustained human-to-human transmission.

Because real epidemics start with limited and messy data, researchers turned to BharatSim, an open-source simulation platform originally designed for modeling Covid 19, but versatile enough to study other diseases.

The key takeaway for policymakers, researchers say, is how narrow the window for action can be before an outbreak spirals out of control.

The paper estimates that once the number of cases exceeds approximately two to ten, the disease is likely to spread beyond primary and secondary contacts.

Primary contacts are people who have had direct, close contact with an infected person, such as family members, caregivers or close colleagues. Secondary contacts are those who have not met the infected person but have been in close contact with a primary contact.

If households of primary contacts are quarantined when only two cases are detected, the outbreak can almost certainly be contained, the research shows.

But by the time 10 cases are identified, it is extremely likely that the infection has already spread throughout the population, making its trajectory virtually indistinguishable from a scenario without early intervention.

To keep the study grounded in real-world conditions, the researchers chose the model of a single village in Namakkal district, Tamil Nadu, in the heart of India’s poultry belt.

Namakkal is home to more than 1,600 poultry farms and some 70 million chickens; it produces more than 60 million eggs per day.

A village of 9,667 inhabitants was generated using a synthetic community (households, workplaces, market spaces) and seeded with infected birds to mimic real exposure. (A synthetic community is a computer-generated artificial population that mimics the characteristics and behaviors of a real population.)

In the simulation, the virus begins at a workplace – a medium-sized farm or wet market – first spreads to people there (primary contacts), then spreads to others (secondary contacts) with whom they interact at home, school and other workplaces. Homes, schools and workplaces formed a fixed network.

By tracking primary and secondary infections, researchers estimated key indicators of transmission, including the basic reproduction number, R0, which measures the number of people to whom, on average, an infected person transmits the virus. In the absence of an actual pandemic, the researchers instead modeled a range of plausible transmission speeds.

Then they tested what happens when different interventions – culling birds, quarantining close contacts and targeted vaccination – come into play.

The results were brutal.

Culling birds works – but only if it’s done before the virus infects a human.

If a spillover occurs, timing becomes everything, the researchers found.

Isolation of infected people and household quarantine can stop the spread of the virus in the secondary stage. But once tertiary infections appear – friends of friends or contacts of contacts – the epidemic spirals out of control unless authorities impose much stricter measures, including lockdowns.

Targeted vaccination helps raise the threshold at which the virus can persist, even if it does not change the immediate risk within households.

The simulations also highlighted a delicate trade-off.

Quarantine, introduced too early, keeps families together for long periods of time – and increases the risk that infected people will pass the virus on to those they live with. Introduced too late, it does not help at all to slow the epidemic.

Researchers say this approach has caveats.

The model is based on a synthetic village, with fixed household sizes, workplaces and daily travel patterns. It does not include simultaneous outbreaks sown by migratory birds or by poultry networks. It also doesn’t account for changes in behavior – mask-wearing, for example – once people know the birds are dying.

Seema Lakdawala, a virologist at Emory University in Atlanta, adds another caveat: This simulation model “assumes very efficient transmission of influenza viruses.”

“Transmission is complex and not all strains are equally effective,” she says, adding that scientists are also beginning to understand that not everyone infected with seasonal flu spreads the virus in the same way.

She says emerging research shows that only “a subset of flu-positive individuals actually expels infectious flu virus into the air.”

This mirrors the super-spreading phenomenon observed with Covid-19, although it is much less well characterized for influenza – a shortcoming that could strongly influence how the virus spreads within human populations.

What would happen if the H5N1 virus took hold in the human population?

Dr Lakdawala believes this will “cause a significant disruption, probably more like 2009”. [swine flu] pandemic rather than Covid-19″.

“This is because we are better prepared for an influenza pandemic. We know of approved antivirals that are effective against H5N1 strains as an early defense and we have stockpiled H5 vaccine candidates that could be deployed in the short term.”

But complacency would be a mistake. Dr Lakdawala says that if the H5N1 virus becomes established in humans, it could reassociate – or mix – with existing strains, amplifying its impact on public health. Such a mix could reshape seasonal flu, triggering “chaotic and unpredictable seasonal epidemics.”

Indian modelers say simulations can be run in real time and updated as data comes in.

With improvements – better reporting times, asymptomatic cases – they could give public health officials something invaluable in the early hours of an outbreak: insight into what actions matter most, before the containment window closes.

Follow BBC News India on Instagram, YouTube, X And Facebook.