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Mobile app could track foodborne illness with a single tweet

Shawn Campbell/flickr

Upstate researchers have found a way predict the likelihood of getting sick after visiting a particular restaurant. The system is called Nemesis and monitors tweets made by restaurant patrons on the popular social media website, Twitter. It then detects likely cases of foodborne illness in close to real-time.

Many people tweet on devices that are GPS enabled, and Nemesis uses this to figure out which restaurant they ate at. It continues to track their tweets for 72 hours after a restaurant visit, to detect whether or not they’ve become ill.

Researcher Vincent Silenzio says the system could help address a major public health issue affecting millions of people every year.

“Food poisoning and food borne illness in and of itself is a huge, huge public health conundrum and in the US alone is responsible for almost $80 billion worth of economic costs per year,” Silenzio said.

Silenzio acknowledges that the system is not perfect - not everyone tweets and when they do it’s not always about their health. But, he says the strength of the system lies in the large amount of data it can access.

An individual case could be unrelated to a restaurant visit, but when multiple people have a similar experience, the numbers are revealing.

The app is not available to the public, but Silenzio says they’re working on refining it for release in the not too distant future.

WXXI/Finger Lakes Reporter for the Innovation Trail