Dr. Kamran Khan, at St. Michael's Hospital with a diagram of flight paths, began working on his predictive system in the wake of the 2003 SARS crisis.
When viruses book a flight
June 30, 2009
HEALTH REPORTER
If a deadly infectious disease – the Ebola virus, or maybe something new and more sinister – were to break out in a remote region of the world, a team of Toronto doctors could predict how and where it would spread around the globe.
The first-of-its-kind system quickly analyzes commercial air traffic patterns to determine where emerging infectious diseases might travel and to pinpoint potential hotbeds of infection.
Experts say getting a clear picture of how jumbo jets can transport disease to the far corners of the Earth will help them better prepare for a global epidemic and give them a head start in controlling a disease outbreak.
The Toronto team tested their system during the first wave of the H1N1 flu epidemic. They analyzed the flight itineraries of more than 2.3 million passengers who departed from Mexico during March and April 2008 to see how the virus would spread one year later, and found the international destinations of travellers closely linked with confirmed cases of the H1N1 virus.
The validation results were published online yesterday in the New England Journal of Medicine.
"Our project was based on the assumption that where people move, infectious diseases of people will move in tandem," said project leader Dr. Kamran Khan, an infectious disease physician and scientist at St. Michael's Hospital. "That's intuitive, but the principle was not absolutely proven. And so H1N1 has shown for the first time, in a pandemic setting, that analyzing global air travel works and that we should consider using this tool in the future for responding to threats and also in preparing for threats before they occur."
Dr. Michael Gardam, director of infectious diseases prevention and control for the Ontario Agency for Health Protection and Promotion, said the system was a potent tool for predicting the spread of infectious disease, especially those with short incubation periods and that cause disease in most people.
"For example, if you had a big outbreak of measles in sub-Saharan Africa, you could tell which countries were going to receive cases within a day and tell them 'Be prepared for this, educate your physicians about what this is going to look like, and get your vaccines ready,' " said Gardam, who worked on the project in his role as medical director of infection prevention and control at the University Health Network.
"It often doesn't take much of an early warning to make a phenomenal difference in (controlling) epidemics."
Kahn began working on the predictive system, called the BIO.DIASPORA Project, in the wake of the 2003 SARS crisis.
"It became abundantly clear that this disease was not spreading around the world in a random fashion, it was spreading around the world in a very systematic way," he said. "This disease had to respect the architecture of the airline transportation network. ... I felt if we could understand how the world moves through air travel, perhaps we can apply that knowledge to better anticipate how infectious diseases of people are likely to spread around the world."
Kahn and his team spent five years creating a system to store data on air traffic patterns. Right now, it takes one day to generate a prediction of how a disease may spread. But Kahn said that will soon be whittled down to one hour and that his team is working toward tapping into real-time data.