Advertisement

Sociability Could Be Key to Flu Prevention

With a novel identification strategy, health authorities may be able to identify potential flu outbreaks earlier by tracking more vulnerable individuals, Harvard researchers say.

The study, published Wednesday by Harvard Medical School professor Nicholas A. Christakis and his research partner, James H. Fowler ’92, identified and collected reports from more sociable individuals whose frequent interactions with friends render them more vulnerable to flu breakout.

In their research, Christakis and Fowler relied on the “friendship paradox”—the social phenomenon maintaining that people generally have friends more sociable than themselves, and that people are more likely to befriend a person with many friends. During the H1N1 flu outbreak last year, Christakis and Fowler—who is a professor at the University of California, San Diego School of Medicine—analyzed self-reported flu symptoms from two groups of people at the College.

One group comprised 319 undergraduates, and the other included 425 people the first group named as friends.

Christakis and Fowler found that the second group reported flu symptoms significantly earlier than when the flu outbreak’s peak occurred.

Advertisement

According to the “friendship paradox,” this group should have comprised people who are more sociable and thus more likely to catch the flu.

The study’s results show that early detection of potential flu outbreaks is possible, Christakis said, adding that vaccinations could be administered more efficiently by targeting people at the center of social networks.

The traditional method of flu prevention requires vaccinating many people, which can be time-consuming, he said.

In contrast, “if you vaccinate the very central people, you will be likely to interrupt the flow of the virus,” Christakis said, referring to people at the center of social networks as the “sentinels” of disease.

Christakis—who is also the Pforzheimer House Master—and Fowler noted in the study that their findings could be applied to other diseases that spread in social networks.

—Staff writer Sirui Li can be reached at sli@college.harvard.edu.

Tags

Advertisement