Social media help predict Ebola outbreaks

Social media help predict Ebola outbreaks (Screenshot: healthmap.org)

Spanish scientists are relying on social media and mobile phones and the use of key words such as "fever" to track public health threats.

Scientists focused on predicting outbreaks of diseases such as Ebola have found new allies: technology and social networks.

They allow for an analysis of key search words on the internet like "fever" to monitor diseases and can also be used to screen phone calls to track hospital transfers.

In addition to analysing enormous amount of data from blogs, sites, tweets, and social health accounts, technology has caused a revolution in the world of statistics and the methods of creating predictive scientific models

"The more information available, the better the predictions; in other words, we gain in speed and quality," Rosa Elvira Lillo Rodriguez, a professor in the Department of Statistics at the Carlos III University in Madrid, said in an interview with Efe.

Also, according to the professor, developments such as the emergence of online health information and call-monitoring technology for the purpose of establishing routes for hospitalisation are extremely helpful.

Professor Lillo also said that the strength of such tools lies in their ability to create a "health map", an application developed by epidemiologists and software experts at the Boston Children's Hospital in the US. This application monitors digital information and allows for the tracking of public health threats.

The app collects information stored on social networks, local news websites, online journalism, blogs, governmental websites and medical-oriented social networks, among other sources, scanning for possible outbreaks of certain diseases.

Thanks to the analysis of the large amounts of data gathered, the application revealed months ago that an unknown haemorrhagic fever was spreading in Africa, nine days before the World Health Organisation announced the first Ebola outbreak.

The professor explained that these tools apply "stochastic processes" which seek "mathematical processes to model randomness with parameters calculated based on data from different sources".

And even though the health infrastructure in Africa is "very weak", mobile phones are a widespread commodity, especially in urban areas.

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