Sampling a network to catch the flu

Current methods to monitor flu epidemics rely on contemporaneous data from random people seeking health care. But in social networks, some members are more connected than others, and theorists have long known that the central-most hubs, by virtue of their greater exposure, are more likely to catch and spread a contagion (see the article by Mark Newman in PHYSICS TODAY, November 2008, page 33 ). The question is how to find the hubs. A phenomenon known as the friendship paradox—"your friends have more friends than you do"—offers a strategic path. To appreciate the paradox, proposed by sociologist Scott Feld in 1991, imagine a group of randomly chosen people, each asked to name a friend. Extroverts are named more often than loners, and the nominated friends will have, on average, more social ties than the nominators. How many more depends on the variance in the distribution of ties. Nicholas Christakis of Harvard University and James Fowler of the University of California, San Diego, have now tested the paradox as a basis for early detection of an outbreak. After the H1N1 epidemic emerged last year but before vaccines were available, they divided 744 Harvard undergraduates into two groups. As shown in the figure, of the 8% eventually infected, those in the friend group tended to get the flu earlier than those in the random group. The trend was discernable a full 46 days prior to the epidemic’s peak, a result that sheds light on spreading processes in networks and how to anticipate them. (N. A. Christakis, J. H. Fowler, PLoS One 5, e12948, 2010 .)—R. Mark Wilson