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.

As the 2009 influenza season approached, Christakis and Fowler decided to put these basic features of a social network to work, contacting 319 Harvard undergraduates who in turn named a total of 425 friends. Monitoring the two groups both through self-reporting and data from Harvard University Health Services, the researchers found that, on average, the friends group manifested the flu roughly two weeks prior to the random group using one method of detection, and a full 46 days prior to the epidemic peak using another method.

"We think this may have significant implications for public health," said Christakis. "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. 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."

"If you want a crystal ball for finding out which parts of the country are going to get the flu first, then this may be the most effective method we have now," said Fowler. "Currently used methods are based on statistics that lag the real world – or, at best, are contemporaneous with it. We show a way you can get ahead of an epidemic of flu, or potentially anything else that spreads in networks."

Indeed, the authors note that the same method could be used very widely – to anticipate epidemics of behaviors like drug use or even the diffusion of ideas or fashions.

John Glasser, a mathematical epidemiologist at the Centers for Disease Control in Atlanta, GA, who was not involved in this research, said: "Christakis' and Fowler's provocative study should cause infectious disease epidemiologists and public health practitioners alike to consider the social contexts within which pathogens are transmitted. This study may be unique in demonstrating that social position affects one's risk of acquiring disease. Consequently, epidemiologists and social scientists are modeling networks to evaluate novel disease surveillance and infection control strategies."



Source-Eurekalert