Institute For The Future

You're Not Popular Enough for the Flu Shot

I'm a little late to this great study by Nicholas Christakis and James Fowler about the possibilities of using social network analysis to predict flu outbreaks, but it's well worth highlighting. The premise of their study is that certain members of social networks can function as "sensors" that indicate the emergence of a flu or other outbreak. In effect, people who have lots of friends come into contact with lots of other people, get exposed to many more germs, and in this way, are much more likely to catch a flu or other contagious illness.

 

In an interview with Wired's Jonah Lehrer, Christakis and Fowler explain:

 

We compared the group of people who were named as friends to the group of people who were not. Consistent with what social network researchers call the ‘friendship paradox’, the people who were named as friends were significantly more central in the network than the people who weren’t. This is because people with more friends are more likely to be named as a friend.

 

And we found that the group of named friends got the flu about 14 days ahead of everyone else. That means that we could predict the course of the epidemic in the whole network two weeks in advance just by monitoring the people who were named as friends.

 

The really cool thing here is that, unlike current methods that focus on giving better information about what’s happening today, our method gives better information about what will happen in the future. In other words, this is early detection, not just rapid warning.

 

 

Immediately after, Lehrer asks about "the direct implications for the distribution of vaccines," which is fun to imagine for its potential to rub people the wrong way. Imagine showing up to your doctor's office for a seasonal flu shot only to find out you don't have enough friends to get the vaccine.

 

But there's a second, more generalizable point that Christakis and Fowler make in the interview:

 

People often ask us ‘what is the best type of network to have?’ and we often find ourselves giving that very unsatisfying answer, “It depends.” Because it does depend — for example, on what is flowing through the network.

 

If a deadly germ is flowing through the network, it would be better to be on the edge of the network and/or to have few or no friends. A hermit cannot get a communicable disease.

 

On the other hand, if a valuable piece of information is flowing through the network (e.g., about how to find a job), then it is better to be in the middle of the network, and/or to have more friends. People at the center are a shorter number of steps from everyone else, so on average they tend to find things out sooner.

 

 

And it's easy to spot these mixed effects of social status and network position in the research. Married people, for example are more likely to gain weight than single people, though other benefits to marriage seem to counteract weight gain. Or consider this study of Japanese smoking rates, which found, among other things, that "Japan has experienced a decrease in the prevalence of smoking among adolescents... [A]n increase in the proportion of students without friends...may have contributed to this decreasing trend."

 

So there you go: If you stay single, and don't have any friends, you, too, can avoid gaining weight or smoking cigarettes.

 

The broader point is that, in the coming decade, we'll have a much better sense of the different sorts of effects that being in a particular spot in a social network might have.

 

That said, while I'm confident that we'll see network analysis get much better, I think using that knowledge will be trickier. Or, put differently, I really don't want to have to show my pharmacist my Facebook page just to get vaccinated.