All that chatter on social media may be more valuable than we think, say researchers who are mining the postings for clues about how to best control infectious disease.
According to the researchers, who reported their findings in the journal Science, applying mathematical models to what people are talking about on Facebook and Twitter could help scientists to better understand how contagious diseases spread, and how people react to outbreaks.
“Social media and other data sources can be tapped for insights into how people will react when faced with a new disease control measure or the threat of infectious disease,” study author Chris Bauch, a professor of Applied Mathematics at the University of Waterloo, said in a statement. “We can create models from this data that allows researchers to observe how social contagion networks interact with better-known biological contagion networks.”
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What people share on social media can sometimes predict the spread of ideas about diseases like the flu, for example, or beliefs about vaccinations. The researchers looked at the social media reactions to issues like childhood immunizations, acceptance of quarantine during the SARS outbreak and public health messages related to infections like influenza.
“If highly connected nodes in the social network (such as celebrities) suggest that the vaccine carries risks, the resulting perception of vaccine risks can propagate quickly through the social network, fueling a vaccine scare and a drop in vaccine coverage,” they write. Cough cough, Jenny McCarthy. But such social connectivity can also help to prevent biological contagion through imitated or culturally promoted behaviors, like covering your mouth when you cough. And control of the SARS virus was largely possible because the general public was accepting of the quarantines.
Bach and his co-author Alison Galvani from Yale University argue that social media should get more attention as a means of gauging how people will respond to disease control measures. Collecting data from social networks could be used to understand behavior, and predict how a population may respond to control measures, which is valuable for public health workers. And there is a precedent for using such behaviors to predict responses and altering public health campaigns accordingly. Some models predicted that uptake of the cervical cancer vaccine uptake would be low due to concerns about its connection to sexually transmitted diseases, and when that ended up being true, public health officials took more aggressive measure to ensure that parents, girls and boys were aware of the benefits of the vaccine.
The researchers are continuing to study how social media can tie together both social contagion and biological contagion networks to better predict how diseases spread — and how to stop them.