Using Google and Twitter to analyze public perceptions of vaccines can help determine when certain populations are potentially on the verge of an outbreak, according to a study published in PNAS.
For the study, researchers compiled tweets that referenced the measles-mumps-rubella vaccine and Google searches that mentioned the measles virus, then used artificial intelligence to classify the nature of tweets and searches. The social media posts and Google queries occurred in California and the U.S. at large prior to the 2014-15 Disneyland measles outbreak. By running the data through a mathematical model, researchers were able to predict the occurrence of the 2014-15 outbreak.
"What this study tells us is that the same mathematical theories used to predict tipping points in phenomena such as changing climate patterns can also be used to help predict tipping points in public health," said Chris Bauch, PhD, a professor of applied mathematics at the University of Waterloo in Canada. "By monitoring people's attitudes towards vaccinations on social media, public health organizations may have the opportunity to direct their resources to areas most likely to experience a population-wide vaccine scare, and prevent it before it starts."
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