Hashtags Help the FSA Monitor Food Illnesses

Social media data may help detect and prevent food illness outbreaks

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It’s happened to all of us at least once. You’ve just finished eating the leftover chicken dinner you found in your fridge and suddenly feel a bit queasy. Out of habit, you tweet “Don’t feel so good. #barf.” What you may not have considered is that your use of hashtags such as #sick and #barf are becoming helpful in monitoring and managing food poisoning outbreaks.

The Food Standards Agency (FSA), which is responsible for monitoring U.K.’s food safety and hygiene, claims it can spot major illness outbreaks at least two weeks earlier using Twitter, reports The Telegraph. In addition, the data can be forwarded to the NHS so that medical facilities can prepare for Norovirus or other illness outbreaks.

Food safety data isn’t just limited to Tweets and hashtags, either. Photos on social networks such as Twitter, Facebook, and Instagram can also indicate unhealthy or unsafe practices, undercooked food, burned food, and food that is improperly or badly prepared, which can help the FSA provide information and guidance for healthier and safer food preparation practices.

Social media platforms have increasingly become important tools in the healthcare and food safety industries. Yelp, the popular restaurant review site, has been used to track food poisoning in the past by flagging words like sick, vomit, and diarrhea. In 2014, Yelp reviews led to approximately 900 cases being uncovered and reported to public health officials. Earlier this year, researchers using a system called nEmesis were also able to use tweets with #upsetstomach to track down 480 counts of food poisoning in New York.

According to Poppy, the FSA analyzed hashtags people used while suffering from Norovirus and, through the use of software, found spikes that corresponded with several outbreaks. The goal, according to Poppy, is to eventually use tweets and social media data to reveal where the outbreaks are occurring based on users’ locations. The data, when used with geographical location, can narrow the outbreak down to specific towns, which can be crucial to detecting and preventing food illnesses.

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