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7 months ago
An AI Epidemiologist Sent the First Warnings of the Wuhan Virus

 
Originally published in Wired.com, January 25, 2020

The BlueDot algorithm scours news reports and airline ticketing data to predict the spread of diseases like those linked to the flu outbreak in China.

On January 9, the World Health Organization notified the public of a flu-like outbreak in China: a cluster of pneumonia cases had been reported in Wuhan, possibly from vendors’ exposure to live animals at the Huanan Seafood Market. The US Centers for Disease Control and Prevention had gotten the word out a few days earlier, on January 6. But a Canadian health monitoring platform had beaten them both to the punch, sending word of the outbreak to its customers on December 31.

BlueDot uses an AI-driven algorithm that scours foreign-language news reports, animal and plant disease networks, and official proclamations to give its clients advance warning to avoid danger zones like Wuhan.

Speed matters during an outbreak, and tight-lipped Chinese officials do not have a good track record of sharing information about diseases, air pollution, or natural disasters. But public health officials at WHO and the CDC have to rely on these very same health officials for their own disease monitoring. So maybe an AI can get there faster. “We know that governments may not be relied upon to provide information in a timely fashion,” says Kamran Khan, BlueDot’s founder and CEO. “We can pick up news of possible outbreaks, little murmurs or forums or blogs of indications of some kind of unusual events going on.”

Khan says the algorithm doesn’t use social media postings because that data is too messy. But he does have one trick up his sleeve: access to global airline ticketing data that can help predict where and when infected residents are headed next. It correctly predicted that the virus would jump from Wuhan to Bangkok, Seoul, Taipei, and Tokyo in the days following its initial appearance.

Khan, who was working as a hospital infectious disease specialist in Toronto during the SARS epidemic of 2003, dreamt of finding a better way to track diseases. That virus started in provincial China and spread to Hong Kong and then to Toronto, where it killed 44 people. “There’s a bit of deja vu right now,” Khan says about the coronavirus outbreak today. “In 2003, I watched the virus overwhelm the city and cripple the hospital. There was an enormous amount of mental and physical fatigue, and I thought, ‘Let’s not do this again.’”

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