Applications of Network Research to the Spread of Swine Flu

Zoltan Toroczkai, professor of physics and director of the Center for Complex Network Research, has yielded statistical models that reflect real-life patterns in the spread of diseases. The studies show, somewhat surprisingly, that long-range travelers, such as those who take airline trips or delivery drivers who have person-to-person contact when they get a signature, for example, are among those chiefly responsible for the explosive growth of an outbreak.

"What you're looking for is the super-spreaders, namely people or groups of people whose behavior has the most effect on disease spread," Toroczkai says. Toroczkai was involved in a nine-year, $30 million study at Los Alamos National Laboratory that studied the influence of social contact networks on disease spread. By using extended census data complemented by mobility diaries kept by thousands of people, an in-silico, virtual model of a city and its population was developed allowing researchers to draft detailed quarantine and vaccination strategies in case of a smallpox outbreak.

Unwitting carriers of disease sometimes travel considerable distance in an attempt to avoid outbreaks near home, but they wind up infecting more people in new places. Officials responding to swine flu these days are urging calm to avoid such a spread
of the disease. "You will see more and more statements saying, 'Don't panic.' If there is no panic, we know how to control disease spread," Toroczkai says. "Panic will create too many unknowns for the administration to deal with. That's why they say to stay home
and especially don't travel. That's the most efficient way of stopping the disease. While the Los Alamos study, and subsequently many others provided efficient methods dealing with outbreaks, they have all been drawn assuming the regular, every-day patterns of interaction amongst people. Once people's mobility and interaction patterns change as a result of the news of an outbreak, these models become useless in the face
of too many unkowns.

Toroczkai's current research involves social networks, using a database of cell phone calls, with the callers' identities concealed, to track their travel and communication patterns. Major sporting events or breaking news, such as the 9/11 terrorist attack, can
cause major changes in those patterns, the study shows, which provides valuable information about how a society responds in case of disasters or global emergencies. This hopefully will give some of the needed clues to develop mitigation strategies that now would include the adaptive behavior of the social network under extreme conditions.