A study suggests that an increase in visits to Wikipedia pages about a particular disease can predict its next outbreak.
Los Alamos National Laboratory in the US had their researchers examine 14 infectious disease outbreaks and use Wikipedia traffic data to compare if they could actually predict upsurges of diseases.
It was remarkable how the team was able to forecast all the outbreaks up to 28 days in advance, by just looking at the trending page views.
A researcher named Sara Del Valle from Los Alamos National Laboratory in New Mexico said that ''A global disease-forecasting system will change the way we respond to epidemics. In the same way we check the weather each morning , individuals and public health officials can monitor disease incidence and plan for the future based on today's forecast.''
The study revealed that, influenza outbreaks in the United States, Poland, Japan and Thailand, dengue fever in Brazil and Thailand, and turberculosis in China and Thailand were tracked.
The researchers were able to anticipate all the diseases except for the Chinese tuberculosis upsurge in China.
The study was published in the journal PLOS Computation Biology.
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