News

Twitter Could Be Used To Predict HIV Outbreaks

By

Twitter may be used to help predict HIV outbreaks, according to a recent study The Business-Standard reported.

Researchers from the University Of California, Los Angeles (UCLA) found that it may be possible to predict sexual risk and drug-related behaviors by monitoring tweets, mapping where those messages come from and linking them with data on the geographical distribution of HIV cases, The Business-Standard reported.  This could potentially prevent outbreaks.

In previous studies, the use of various drugs had been associated in previous studies with HIV sexual risk behaviors and transmission of infectious disease, researchers said. 

"Ultimately, these methods suggest that we can use 'big data' from social media for remote monitoring and surveillance of HIV risk behaviors and potential outbreaks," Sean Young, assistant professor of family medicine at the David Geffen School of Medicine at UCLA and co-director of the Center for Digital Behavior at UCLA, told The Business-Standard.

For the study, investigators analyzed more than 550 million tweets posted between May 26 and Dec. 9, 2012, and created an algorithm to find words and phrases associated with risky sexual and drug activity such as "sex" or "get high." They then plotted the tweet on a map to see if it originated from an area with a high HIV history, NBC News reported.

The algorithm captured 8,538 tweets indicating sexually risky behavior and 1,342 suggesting stimulant drug use.

California (9.4 per cent), Texas (9.0 per cent), New York (5.7 per cent) and Florida (5.4 per cent) were the states with the largest proportion of geo-located tweets both general as well as HIV-related.  Researchers found a significant relationship between those indicating risky behavior and counties where the highest numbers of HIV cases were reported. 

Researchers hope to use the information to predict where HIV cases may occur and set up prevention efforts in those areas.

The study was published in the journal Preventive Medicine.

© 2024 University Herald, All rights reserved. Do not reproduce without permission.
Join the Discussion
Real Time Analytics