Popular Web Site Used to Predict Epidemic Patterns

Inspiration comes from the most unexpected places. An international team of scientists discovered a mathematical law that can be used to predict the spread of an infectious disease across the country. The key to their discovery? Wheresgeorge.com, a recreational Web site that allows people to track dollar bills by serial number.

    One of the researchers, Lars Hufnagel, a post-doctoral fellow at the Kavli Institute for Theoretical Physics at the University of California, Santa Barbara, said the team was looking for a way to understand how diseases spread geographically inside a country. Airline travel routes can be used to predict international infection patterns, he explained, but domestic travel takes too many forms to successfully use any one as an indicator.

    They were looking for something quantifiable that traveled the way diseases travel but was not specific to any illness, he said. The wheresgeorge data were such a good match because currency, like disease, is almost always attached to humans when it travels.

    Human travel has no scale, Hufnagel said, because people frequently travel short distances, sometimes travel moderate distances, and occasionally travel long distances. But the team found that human travel in the United States could be described by a mathematical formula known as a scaling law.

    Scaling laws, which look a little like logarithmic functions to the unsophisticated, are used to determine proportionality. The laws give a sense of perspective to observers, allowing them to understand variables. A simple example of scaling: Geologists often put a hammer next to a rock when they photograph it for their records. By using a hammer of constant size, the scientists can use a formula to compare the size of rocks in two different photographs.

    It turns out that a simple scaling law can describe the way humans travel and predict how a disease spreads.

    “The scaling law is always the same -- from a few miles up to across the country,” Hufnagel said about the formula that describes human travel. “It doesn’t depend on where in the United States you are.”

    The next step, according to Hufnagel, is to couple this information about how disease spreads geographically with local infection data that demonstrate how infections spread from person to person. Such data show how many people one sick person infects.

    Together these data can be used to create a model, which the team plans to test by simulating past disease epidemics and comparing their predictions to the actual event.

    Although the statistical laws discovered by the wheresgeorge study are specific to the United States, Hufnagel believes the findings will translate to other developed nations with sophisticated transportation systems.

“I would be very surprised if it is different,” he said