Wikipedia May Predict The Next Global Health Crisis

Scientists may one day be able to predict epidemics simply by analyzing what people are searching on the Internet.

Researchers at the Los Alamos National Laboratory in New Mexico found that a surge in Wikipedia traffic for certain disease-related articles predicted the large-scale spread of illnesses in several world locations, sometimes as long as 28 days before official spikes were recorded. The findings were published online Thursday in PLOS Computational Biology.

Unlike Google flu trends, which uses search data to reflect where outbreaks are happening, the Wikipedia analysis can predict an outbreak. Nicholas Generous, the study’s lead researcher and a digital epidemiologist for the lab, said the finding may one day become a tool to help public health officials decide to mount prevention or vaccination campaigns, or help hospitals prepare for a wave of patients.

“It kind of beats the older versions of disease surveillance, where the patient gets sick, goes to the doctor, the doctor writes up the report, sends it to the county epidemiologist, who aggregates it upward and then it gets reported by the state,” Generous said in a phone interview with The Huffington Post. “It can be kind of a lengthy process, but if —> Read More Here


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