If you want to know what’s up with the flu at the moment, you have a few choices: You can get the latest information at Google Flu Trends. Or you can get the official word from the Centers for Disease Control and Prevention, which is based on data that’s by now a couple of weeks old.
But a report in the journal Science finds that quicker isn’t necessarily better.
This story started in 2008, when scientists at Google realized that they could measure flu activity by tracking when people searched for flu-related terms. They created a handy site called Google Flu Trends. And it works pretty well — some of the time. But don’t bank on it.
“It missed by a huge amount last year and actually, it turns out, it’s been missing by a fair amount for several years,” says David Lazer, a professor of political science and computer science at Northeastern University. He says Google Flu Trend whiffed during the 2013 flu season.
“It’s like bases loaded and bottom of the ninth, striking out on three pitches. They predicted twice as many flu cases as the CDC later said there were.”
Lazer has written a critique of Google Flu Trends in the latest issue of Science. He finds that the data collected painstakingly from around the country and forwarded to the CDC is still much better, even with the time lag.
“You could just have used old CDC data — two or three weeks old — and have projected forward, and done a better job than Google Flu Trends,” he says.
So does this make Google’s approach worthless?
“Not at all,” he says. “Not at all. I think, actually, the core idea is a terrific one.”
Lazar thinks Google could improve its system with the help of outside scientists if it were less secretive about what exactly it’s doing to get its results.
But he sees some inherent problems, as well. Google is always refining its search methods, which is good for people doing Google searches, but not so good for analyzing that data — consistency is important in science.
“If we know ahead of time [that] flu is going to really peak in the next few weeks, we need to start getting additional resources to help manage all these patients who are going to be coming in,” says Andrea Dugas, a professor at the Johns Hopkins University School of Medicine and an emergency room doctor.
During past outbreaks, Hopkins has actually opened up new areas of the hospital to care for flu patients. Dr. Dugas and her colleagues have been working to improve those predictions, looking at various methods to do that.
“The most accurate of those models was the one that looked at the confirmed flu cases,” she says. “That one was the most accurate in predicting what was going to happen in the following week.”
When they added in the Google Flu Trends data, their prediction improved, she says, but not by a lot.
“Adding that in really helped refine the model and give us a better prediction,” she says, “but the main driver for that was the number of flu cases.”
She and Dr. Richard Rothman at Hopkins have developed an app called Flucast to help hospitals predict the ebb and flow of flu.
Another free app, called Flu Near You, also maps out flu trends, based on reports that individuals submit through the app.
Dr. Dugas says Google’s approach is no substitute for lab tests, hospital reports and on-the-ground data. And it’s important to note that it’s not tracking actual flu caused by influenza viruses — rather, it’s identifying common symptoms like fever, cough and sore throat.
Google didn’t provide a scientist to comment for this story, but a Google report notes one shortcoming: They sometimes get a flood of searches simply when there’s a lot of flu in the news. So Google updated the flu tracker system last fall to help reduce the errors that result from that.