Researchers have been incorporating real datasets on the world air-transport network into models of disease dynamics.
Five hundred years ago, the spread of disease was largely constrained by the main mode of transportation of the time: people traveling on foot. An outbreak in one town would slowly ripple outward with a pattern similar to what occurs when a rock drops onto a surface of still water. The Black Death moved across 14th century Europe in much this way, like concentric waves unfurling across the continent.
Today, disease migrates across populations and geography with a curiously different pattern. In 2003, SARS first appeared in China, then spread to Hong Kong, then turned up from there in Europe, Canada and the United States. Plot the spread of the disease on a map of the world, and its movement looks downright random.
What has changed dramatically in the intervening centuries is not necessarily the diseases themselves, but human mobility networks. Dirk Brockmann, a theoretical physicist and professor of complex systems at Northwestern University, has long been interested in how evolving modes of long-distance transportation have changed many things: disease dynamics, the spread of information, the transport of species from one ecosystem to others where they don’t belong.
For about a decade, Brockmann and other researchers have been incorporating real datasets on the world air-transport network into models of disease dynamics. They can simulate an outbreak in one location and estimate its arrival in another. But early on, Brockmann noticed that models created by him and other colleagues often produced strikingly similar results, even with simulations built on different assumptions about infection rates, disease dynamics, seasonality, or the age structure of infected populations.
NEXT STORY Telework Week Participation Skyrockets