Researchers from the University of Rochester in New York used Twitter to predict flu trends among individuals up to eight days before symptoms became present, according to a recent article in New Scientist. The researchers analyzed 4.4 million tweets over a one month time span in 2010 that were tagged with GPS location data from more than 630,000 users in New York City. After developing an algorithm that could differentiate between phrases such as "I am so sick of this traffic!" and actual declarations of illness, the researchers then sorted through the information and predicted with 90 percent accuracy whether an individual would become sick.
Similarly, earlier this year, researchers affiliated with Harvard Medical School and Massachusetts General Hospital used Twitter to forecast a cholera outbreak in Haiti two weeks before health officials in the country reported the epidemic. Article