A new article in the journal Preventive Medicine says researchers might be able to learn more about HIV outbreaks — and even help to prevent them — by coupling location data from certain tweets with location data on reported HIV cases.
Medical researchers at UCLA and Virginia Tech used an algorithm to find nearly 10,000 tweets containing words that suggested risky behavior, out of more than 550 million tweets that they collected over six months in 2012. Those researchers found “a significant relationship” between the number of risky-behavior tweets and the number of HIV cases in various locations.
The finding is just the latest indication that tweets can help the medical community track and prepare for the spread of disease. Still, the authors of the article in Preventive Medicine warned that the age of the data used in their field limits the usefulness of these studies, highlighting the fact that their study used 2009 data on HIV cases.