Social networks can help in predicting epidemics

Facebook and Twitter aren't just idle distractions. In fact, those sites and other social networks--even ones not based in cyberspace--can help epidemiologists predict flu outbreaks and other epidemics, researchers from Harvard University and the University of California, San Diego, report in the journal PLoS One.

By asking more than 300 randomly chosen Harvard students to name some of their friends and then tracking the two groups independently, the researchers were able to speed up detection of influenza in the group of friends by two weeks with one method. Another method helped them detect an outbreak 46 days before the epidemic peaked, according to HealthDay News. The success is likely due to the fact that those at the center of a social network often are more likely than the average person to contract a contagious illness. "Hence, the careful collection of information from a sample of central individuals within human social networks could be used to detect contagious outbreaks before they happen in the population-at-large," the report reads.

"We think this may have significant implications for public health," lead author Dr. Nicholas Christakis, a professor of medicine, medical sociology and sociology at Harvard, says in a press release. "Public health officials often track epidemics by following random samples of people or monitoring people after they get sick. But that approach only provides a snapshot of what's currently happening."

But, Christakis adds, "By simply asking members of the random group to name friends, and then tracking and comparing both groups, we can predict epidemics before they strike the population at large. This would allow an earlier, more vigorous, and more effective response."

For further details:
- view the paper in PLoS One
- see this HealthDay story

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