The flu in the United States is on track to bottom out by the end of the year, returning to levels seen nine months ago, before the first case of H1N1 hit the U.S. That forecast is from three University of Chicago professors who have created a new method for predicting the spread of the disease. The professors, Nicholas Polson and Hedibert Lopes at the university's Booth School of Business and Vanja Dukic in the Department of Health Studies, are using data from Google Flu Trends, which tracks the flu, and applying a mathematical model that aims to do the one thing Google can't yet do: predict what will happen next. The same modeling approaches, with minor alterations, could be applied to other infectious disease epidemics, such as avian flu, SARS or measles. Google created its Flu Trends tool after it discovered that the searches people conduct when they are sick with the flu can be mathematically tied to the actual spread of the flu.
