Tweeting Disease — How MappyHealth Predicts Outbreaks

Can Twitter predict disease outbreaks? That’s the question the makers behind MappyHealth wanted to discover.

MappyHealth mines twitter data looking for health term trends. The app tracks disease terms and associated qualifiers to present these social trends.

Brian Norris is the Co-Founder of MappyHealth. He told Chris Dorobek on the DorobekINSIDER program that, “we have found that every term and condition trend tracked on our site has a band of “social noise”. This social noise is the everyday ebb and flow of tweets associated with a certain term. Spikes in volume and duration signal events that occur related to these terms. These events could be both positive and negative.”

MappyHealth was the winning submission of 33 applicants in a Health and Human Services developers’ challenge, “Now Trending: #Health in My Community,” sponsored by ASPR.


“MappyHealth uses opensource twitter API’s to ingest tweets about certain disease terms. Then we apply algorithmic equations to it to present disease trends,” said Norris.


“MappyHealth uses more than 200 qualifiers to help track the disease. Qualifiers like “I have,” “I’m sick,” “epidemic,” and “hospital.”

Different Types of Tweets

“Sensor based location tweets are gathered based on geo-location data provided with the tweet. These geo locations are associated with our map view and aggregated in several ways,” said Norris, “User profile location tweets are gathered based on profile location data entered into the Twitter profile of a user. This information is not geo location based. This information is not confirmed nor required by Twitter when a user sets up a profile.”


“We don’t want to incite panic, the apps is all about awareness,” said Norris.


“This was the first competition that either me or my co-developers have been apart of,” said Norris, “it really inspired us and made us see a lot of opportunity that open source and competitions like this one can bring about.”

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