Reuven Cohen of Bar-Ilan University in Israel and his colleagues note that random immunization programs require that a large fraction of the population, typically 80 to 90 percent, be protected in order to stop the spread of disease. Alternatively, if enough information about the network and its connections is known, targeted immunization of the most highly connected individuals--so-called super-spreaders, who have the potential to infect a high number of people--can be effective. Unfortunately, such information is difficult to acquire. The researchers instead propose a tactic known as acquaintance immunization. In it, a percentage of the population is selected at random and asked to identify a friend. Those friends, in turn, are vaccinated. According to the team's calculations, because super-spreaders know so many people, there is a high probability that they will be named at least once. As a result, immunization of a much smaller fraction of the population can successfully halt disease transmission. In addition, the authors note that their approach "can be used even before the epidemic starts spreading, since it does not require any knowledge of the chain of infection."
The new approach could be helpful in regions in the developing world where there aren't enough vaccines to treat the entire population. In addition, Cohen and his colleagues note that the technique is relevant to other types of networks, including terrorist ones. "For terrorist networks," they write, "our findings suggest that an efficient way to disintegrate the network is to focus more on removing individuals whose name is obtained from another member of the network."
