Knowledge of whether a disease epidemic is unfolding in a community is crucial for public health officials and policymakers. Models suggest that vaccinating even a third of the population against influenza in a metropolis like New York City or Chicago can save lives and shorten the epidemic’s course—but only if implemented early enough. Unfortunately, current methods to monitor flu epidemics rely on contemporaneous data from random people seeking outpatient care, information that lags behind the course of the epidemic by a week or more.
Social networks, such as the network of real-life contacts in a city, are heterogeneous: Some members are more connected, or central, than others. Theorists know that the centralmost hubs, by virtue of their greater exposure, are most 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 them?...
