The friendly way to catch the flu

Your friends are probably more popular than you are. And this ''friendship paradox'' may help predict the spread of infectious disease.

 
The largest component, 714 people, of the social network studied by Fowler and Christakis, on Dec. 8, 2009. Infected individuals are colored red, friends of infected individuals are colored yellow, and circle size is proportional to the number of friends infected. A movie tracks the spread of the flu from 1 September through 31 Dec 2009.
Photo Credit: Courtesy James Fowler, UC San Diego

Nicholas Christakis, professor of medicine, medical sociology and sociology at Harvard University, and James Fowler, professor of medical genetics and political science at the University of California, San Diego, used the paradox to study the 2009 flu epidemic among 744 students. The findings, the researchers say, point to a novel method for early detection of contagious outbreaks.

Analysing a social network and monitoring the health of its central members is an ideal way to predict an outbreak. But such detailed information simply doesn't exist for most social groups, and producing it is time-consuming and expensive.

The ''friendship paradox,'' first described in 1991, potentially offers an easy way around this. Simply put, the paradox states that, statistically, the friends of any given individual are likely more popular than the individual herself. Take a random group of people, ask each of them to name one friend, and on average the named friends will rank higher in the social web than the ones who named them.

If this is hard to fathom, imagine a large cocktail party with a host holding court in the center while, at the fringes, a few loners lean against the walls staring at their drinks. Randomly ask the party-goers to each name a friend, and the results will undoubtedly weigh heavily in the direction of the well-connected host. Few people will name a recluse.

And just as they come across gossip, trends and good ideas sooner, the people at the center of a social network are exposed to diseases earlier than those at the margins.