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  Updated: Tuesday, March 07, 2006

New model to predict spread of disease through air travel
Research tracks patterns of illness from air travel
By Matt Cunningham  | Indiana Daily Student | Tuesday, March 07, 2006

After months of research, four scientists at the School of Informatics have unveiled a mathematical framework that could serve as a way to predict the spread of disease through air travel.

The study was published in a recent edition of the "Proceedings of the National Academy of Science." The computational model was stochastic, meaning it took into account random variations across a broad range of factors. The study used census data and a database provided by the International Air Transport Association.

Never before has such a detailed amount of airline information been employed in this type of research. The database of the International Air Transport Association includes all commercial airports in the world and the flight connections among them, as well as the number of passengers traveling on a given route.

Using this information, numerical simulations were carried out by more than 10,000 equations simultaneously to achieve the predictions. The database included information from 265 airlines, which comprises 99 percent of all international air traffic. Disease patterns from cities and census information obtained from 3,100 cities in 220 countries supplemented the database information.

"I think the major implication of the research is the fact that we can now start studying the reliability of global epidemic forecasts," said informatics professor Alessandro Vespignani. "This will provide policy makers with a more informed way to look at risk assessment and strategy evaluation."

Research associate Vittoria Colizza said the study will be useful in the development of strategies for containing the spread of an emerging disease.

"This stochastic model can be applied to a variety of diseases," Colizza said. "Once you have this model you can apply it to whatever disease you want."

She cautioned that in order to implement a disease the first consideration should be "specific infection dynamics of each disease."

"Regarding infection dynamics, one would need to specify the infectiousness of the virus and the typical evolution of the disease in an individual by identifying the stages of the disease and the average periods an individual spends in each of those stages," Colizza said.

Zoltan Toroczkai, deputy director of the Center for Nonlinear Studies at Los Alamos National Laboratory in New Mexico, is involved with similar research. He is working on macro simulations of city epidemics. He complimented IU researchers on incorporating realistic mobility models derived from the airline database in studying epidemic networks.

Toroczkai said these research efforts are important due to an increasing connectedness within populations. Cheaper and easier methods of travel invite more physical contact, which Toroczkai said represents vulnerability for the world.

"Diseases can easily take advantage of this small-world character of the contacts and virtually overtake the population in a very short time," Toroczkai said. "Research is paramount for understanding the implications of the increased connectivity and for designing strategies of counteraction and defense. Professor Vespignani and his group's work is an excellent piece of research targeting to fill this gap."


 
 


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