Monitoring Wikipedia hits could help researchers determine how many people have been affected by the flu.
A research team developed a method for estimating how high influenza levels are in the U.S. by monitoring the amount of traffic on certain flu-related Wikipedia pages, a PLOS news release reported.
This new method could determine flu data up to two weeks before the Centers for Disease Control and Prevention is able to gather their data; It could also estimate the "week of peak influenza activity" 17 percent more often than Google Flu Trends data.
In order to make their findings the researchers looked at the number of times certain Wikipedia articles had been viewed between December of 2007 and August 2013.
The model proved to "perform well" in average flu season conditions and even in cases such as the H1N1 pandemic in 2009 that received an onslaught of media attention.
"Each influenza season provides new challenges and uncertainties to both the public as well as the public health community. We're hoping that with this new method of influenza monitoring, we can harness publicly available data to help people get accurate, near-[real-time] information about the level of disease burden in the population," the researchers said, the news release reported.
The model was created by David McIver and John Brownstein; the study was published in the journal PLOS Computational Biology.
Symptoms of influenza include: "Fever* or feeling feverish/chills; Cough; Sore throat; Runny or stuffy nose; Muscle or body aches; Headaches; Fatigue (tiredness); Some people may have vomiting and diarrhea, though this is more common in children than adults," the CDC reported.
Most people who develop the flu will recover within two weeks, but some people can develop dangerous and sometimes fatal complications such as pneumonia. Other possible complications include "bronchitis, sinus and ear infections," the CDC reported.
