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Can analytics predict epidemics?

Blog: Decision Management Community

Angrew Ng published an interesting article “Stopping Coronavirus” in his Jan 29 issue of The Batch. It talks about a Canadian company that analyzes online information to predict epidemics spotted the upsurge in coronavirus at least a week ahead of public-health authorities. Link

What’s new: Canadian startup BlueDot alerted customers to the outbreak in the Chinese city of Wuhan on New Year’s Eve, Wired reported. The U.S. Centers for Disease Control and Prevention issued its warning on January 6, and the World Health Organization followed suit three days later. The respiratory illness as of this writing has infected more than 6,000 people and killed more than 130, mostly in China.
How it works: Founded in 2014, BlueDot aims to stop the spread of infectious diseases by giving healthcare workers early warning, so they can identify and treat people who become infected.

Behind the news: In 2008, Google undertook a similar effort to forecast influenza outbreaks based on search terms entered by users. In initial research, Google Flu Trends tracked the number of cases two weeks faster than the CDC. However, it dramatically underestimated the peak of the 2013 flu season and was shuttered soon afterward. Subsequent analysis concluded that the algorithm overfit seasonal search terms unrelated to flu.

Why it matters: Rapid detection of new diseases is crucial to avoid global pandemics. Virulent diseases often can be contained if they’re caught early enough, but every hour compounds the number of people exposed and thus the number of cases. An epidemic can quickly overwhelm healthcare systems, leaving people even more exposed.
We’re thinking: It’s hard to know how well today’s techniques will play out tomorrow. But the ability to catch potential pandemics before they explode is too valuable not to try.

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