On the last day of 2019, an artificial intelligence warning system run by Toronto startup BlueDot flagged a news report from China about a mysterious pneumonia strain in the city of Wuhan. The system, which sifts through 100,000 articles and online posts daily in 65 languages, alerted BlueDot’s human employees, who immediately saw parallels to the deadly SARS outbreak in 2003.
After switching to a system based on data from billions of airline passenger itineraries, BlueDot was able to determine almost instantaneously which cities worldwide were most at risk if the mystery illness spread. The company quickly sent out warnings to health authorities and other clients about what would come to be called the coronavirus outbreak, which has so far infected almost 100,000 people and killed more than 3,000 as of early March.
“Outbreaks don’t care whether it’s New Year’s Eve or not,” says Dr. Kamran Khan, CEO at BlueDot and a medical professor at the University of Toronto. “In order to get in front of these diseases and threats, we have to move even faster than they do.”
It’s a far cry from when Khan started BlueDot about seven years ago. Back then, mapping the potential spread of a virus and alerting authorities could take several weeks. And reluctant governments would sometimes sit on the data for weeks or months after that.
But the era of A.I. and big data has revolutionised tracking and forecasting the path of infectious disease outbreaks like that of the coronavirus. Fuelled by algorithms that can translate languages and distinguish between different meanings—Anthrax, the heavy metal band, versus anthrax, the infectious disease—BlueDot and its rivals suck up all the data they can to uncover potential epidemics.
This story is from the April 2020 edition of Fortune India.
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This story is from the April 2020 edition of Fortune India.
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