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First real-time flu forecast successful
Date:12/3/2013

roach is analogous to weather forecasting, which employs real-time observational data to reduce model forecasts error. In the last year, the researchers slightly modified the system to be more representative of flu rather than flu and other respiratory problems. Nevertheless, there was unusual level of "noise" in the data related to problems with Google Flu Trends.

How did this happen? One explanation is the high number of media stories about the flu, including some about the flu forecasting system itself. The result was a spike in people using Google to research the flu, which could have overloaded the Flu Trends algorithm. It's an irony not lost on Dr. Shaman. "There was a tremendous amount of media attention accorded to the flu last year. I was part of the problem myself," he says. Another factor may have been the particular strain of flu in circulation. "The flu was very virulent and was making people very sick, more so than previous seasons," says Dr. Shaman. Again this could have led to spike in flu-related Google search queries. (In October, Google announced that it has revised the Flu Trends, which Dr. Shaman hopes will make flu forecasting more accurate.)

The system will be put back in action as soon as the flu season begins again. "Right now there are few cases of the flu, but as soon as the needle starts to move, we will start making predictions," says Dr. Shaman. This season the forecasts will be more readily available to the public on a website hosted by Columbia's Mailman School of Public Health expected to launch in the coming weeks.

Worldwide, influenza kills an estimated 250,000 to 500,000 people each year, according to the World Health Organization. In the U.S. 3,000-49,000 die from the flu every year, and about 45% of Americans were vaccinated for the flu, according to the CDC.


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Contact: Timothy S. Paul
tp2111@columbia.edu
212-305-2676
Columbia University's Mailman School of Public Health
Source:Eurekalert

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