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 | | News@NATURE.COM |  |  | Published online: 12 August 2004; | doi:10.1038/news040809-13
Gravity equations give rise to measles model
Emma MarrisDisease shown to spread to big cities rather than small towns.


| Large cities attract people and disease alike. © Alamy |
| The
pattern of epidemics could be predicted more accurately by taking into
account how attractive different sizes of cities are to visitors. A new
model uses equations originally developed to calculate the
gravitational pull between planets.
Theoretical
ecologist Ottar Bjørnstad, from Penn State University in University
Park, took inspiration from Andrew Cliff, an economic geographer from
the University of Cambridge, UK. In the 1970s, Cliff proposed that the
equations used to calculate how planets are attracted to each other
could also be used to predict how people with contagious disease would
move. The shared idea is that a bigger place, whether planet or city,
is more attractive.
Bjørnstad
and his colleagues have now tested the idea, using exhaustive data on
childhood measles in England and Wales, and publish their results in The American Naturalist1.
They combined a model of how an epidemic plays itself out locally with
the idea that the infection is more likely to hop from a small town to
the capital than to a nearby small town to predict where the disease
was likely to move next.
The
model has four parameters: relating to the likelihood that someone will
travel to a distant place instead of a close one; the likelihood that
if someone travels they will go to a place of a particular size; the
transmission rate of the visitor in the visited place (for example,
children visiting family are likely to be around fewer children than
when they are in school); and a final factor involving the varying
rates of travel of people from small and large towns.
Everyone thought it was beautiful work.  |

Pejman Rohani Ecologist, Georgia University |
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|  |  | The
model was able to predict the course of the measles infections
described by the British data. "The exciting thing for us was to go
from the common sense to the predictive network," Bjørnstad says. "We
can answer: which is going to be next? A town of 100,000 people that is
40 miles away or a town of 200,000 people that is 40 miles away?"
Building patterns
The
researchers are now collaborating with the John E. Fogarty
International Center, a branch of the US National Institutes of Health
that specializes in overseas projects. Bjørnstad is using the centre's
global influenza data to determine whether the model applies to flu as
well.
Bjørnstad
presented his work at the Ecological Society of America meeting in
Portland, Oregon, last week. "It got an excellent response," says
Pejman Rohani, an ecologist from the University of Georgia in Athens,
Georgia, who saw the talk. "Everyone thought it was beautiful work."
Rohani
says he expects to use the model in his own research, but added a
caveat: "The method that they developed is based on data from the
pre-vaccine era, so there are important technical issues if you are
trying to do what they've done in the modern vaccine era."
At
the same meeting, Bjørnstad's student, Laura Warlow, showed that the
model also did well at predicting the timing of outbreaks of phocine
distemper virus, which causes a measles-like illness in seals. Seals
tend to congregate on the beach in piles called haul-outs. Big
haul-outs, like big cities, attract more infection.
Warlow
says one advantage of the model is that it isn't necessary to worry
about why certain haul-outs are popular, or why people like to go to
big cities. "You definitely do not need to know why," she says. "The
disease doesn't care."
References
- Xiz Y., Bjornstad O. & Grenfell B. Am. Nat., 164. 267 - 281 (2004). | Article | PubMed |
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