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When deadly
bird flu strikes, six degrees of separation could be the distance from here to
hell. Even if a vaccine is found to be effective, it may be impossible to
produce enough shots for everybody quickly enough, so authorities would have to
decide how to use the doses they have in the most effective way. Researchers
are now proposing a new strategy for targeting shots that could, at least in
theory, stop a pandemic from spreading along the network of social
interactions.
Vaccinating
selected people is essentially equivalent to cutting out nodes of the social
network. As far as the pandemic is concerned, it’s as if those people no longer
exist. The team’s idea is to single out people so that immunizing them breaks
up the network into smaller parts of roughly equal sizes. Computer simulations
show that this strategy could block a pandemic using 5 to 50 percent fewer
doses than existing strategies, the researchers write in an upcoming Physical Review Letters.
“The
strategy is to disintegrate the network,” says study coauthor Shlomo Havlin of
“The idea
of splitting a network into equal subnetworks is very simple, yet quite
successful,” comments network-theory expert Dirk Brockmann of Northwestern
University in
The hard
part could be getting enough information about the structure of social networks
to know which nodes to target, says Alessandro Vespignani, a physicist at
Network-theory
researchers have often assumed that one of the most efficient ways of blocking
a pandemic is to immunize people who have the largest number of social connections.
However, most people are separated from most other people by the proverbial six
degrees of separation, and removing only the highly connected nodes might
leave, say, 10 degrees of separation — but the people are still connected. The
pandemic could still spread over large swaths of society, albeit at a slower
pace. Meanwhile, Havlin and his team say, many doses of vaccine could be used
in parts of the networks that have already been isolated and shrunk down.
“You’ve
just got to use the doses you’ve got in a more clever way,” says coauthor H.
Eugene Stanley of
To test
their idea, the researchers designed a computer program that singles out the
nodes that, when removed, will break up the network into parts of equal sizes.
They tested it on models of several different types of networks. Their method
was faster at stopping a simulated pandemic than was removing the highly
connected nodes, they report.
In one of
the most dramatic illustrations of their technique, the researchers simulated
the spread of a pandemic using data from a Swedish study of social connections,
in which more than 310,000 people are represented and connected based on
whether they live in the same household or they work in the same place. With
the new method, the epidemic spread to about 4 percent of the population,
compared to nearly 40 percent for more standard strategies, the team reports.
Found in: Body & Brain, Mathematics and Science & Society
- Colizza,
V. ... and A. Vespignani. 2007. Modeling the Worldwide Spread of
Pandemic Influenza: Baseline Case and Containment Interventions. Public
Library of Science Medicine 4 (Jan. 23): e13
doi:10.1371/journal.pmed.0040013




