An increase in visits to Wikipedia pages about a disease can predict its next outbreak, a study suggests. Researchers from the Los Alamos National Laboratory in the US examined 14 infectious disease outbreaks and used Wikipedia traffic data to compare if they could predict upsurges of diseases. Also Read - Google Maps to soon start showing COVID-19 outbreak in local areas
The team was able to forecast all the outbreaks upto 28 days in advance, just looking at the page view trends.”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,” said researcher Sara Del Valle from Los Alamos National Laboratory in New Mexico. Also Read - 16 iOS apps with dark mode that take advantage of Apple iPhone X's OLED panel
For the study, influenza outbreaks in the United States, Poland, Japan and Thailand, dengue fever in Brazil and Thailand, and tuberculosis in China and Thailand were tracked. Except for the Chinese tuberculosis upsurge in China, the researchers were able to anticipate all the diseases. Also Read - Wikipedia's new 'page preview' feature to make browsing easy
The study was published in the journal PLOS Computational Biology.