Wikipedia Could Forecast Global Disease Outbreaks

Research published in PLOS Computational Biology has suggested that Wikipedia articles could make it possible to monitor and forecast increases and outbreaks of diseases around the world.

Los Alamos National Laboratory's Dr Sara Del Valle and her team have successfully monitored influenza outbreaks in the United States, Poland, Japan and Thailand, dengue fever in Brazil and

Thailand, and tuberculosis in China and Thailand.

Together, they were able to forecast all but one of these outbreaks (tuberculosis in China) at least 28 days in advance. What the results suggest is that people are searching for disease-related information on cyber information giant before they seek proper medical attention.

Their research paper shows the potential to transfer models across different regions; that is, one can “train” a computer model using public health data in one location and implement the model in another region. For example, researchers could create models using data from Japan to track and forecast disease in Thailand. This is particularly important for countries that do not offer reliable disease data.

Sara Del Valle said: “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 goal of this research is to build an operational disease monitoring and forecasting system with open data and open source code. This paper shows we can achieve that goal.”