The
advantage of an increasingly interconnected physical world has
generated a dangerous by-product: the threat of major pandemics such as
HIV-AIDS, SARS, or more recently the threat of pandemic influenza. In
an attempt to forecast with accuracy the spread and worldwide impact of
epidemics, an international team of researchers from CNRS, CEA, the
University Paris-Sud and Indiana University (US), has studied the role
played by air travel in this process.1
For
the first time, scientists were able to access the International Air
Transport Association database: This includes information from the
largest 3100 airports in the world, 265 airlines (including number of
passengers on each flight) and their flight connections (99% of all
international air traffic). By matching this information with disease
patterns from cities and census information from 220 countries, they
were able to achieve significant predictions.
The
research team, led by Alessandro Vespignani, CNRS researcher and
professor of informatics at the University of Indiana, used a
stochastic model (a statistical process in time involving random
variables) to obtain evolving maps of contamination levels or to
monitor the disease evolution.
Researchers
took into account two factors with opposing effects on predictability.
On the one hand, a large airport has many connecting flights, which
reduces predictability (any passenger can travel to one of 200 possible
destinations). “On the other hand, we were able to identify which
routes were the most widely used, a factor that increases
predictability,” states Alain Barrat, co-author of the study and
researcher at the Theoretical Physics laboratory of Orsay.2 Therefore routes through which an epidemic spreads can be identified, and the accuracy of those predictions can be quantified.
This
study is extremely useful since it gives government and health agencies
a reliable reading of how a global epidemic spreads. “Inclusion of
additional data, such as hygienic conditions in various countries or
seasonal travel forecasts can make these predictions even more
accurate,” concludes Barrat.
Saman Musacchio