Big Data helps control Ebola epidemic

“We’ve never had this large-scale, anonymised mobile phone data before as a species,” says Nuria Oliver, a scientific director at mobile phone company Telefonica.

In the age of international travel it is much easier for diseases to spread abroad, particularly when they have an incubation period of up to 21 days, like Ebola. We are far away from the epicenter of the Ebola crisis and yet this deadly virus is making a very large impact on me. Our loved ones are Humanitarians and Doctors, and as the virus threatens to break through borders and spread its unwelcome wings, we see them prepare systematically, doing their part to assist with the massive global effort to control the spread of the disease. Europe and the US are consequently on high alert and implementing screening at some airports. But at least in the digital age, tracking the movement of potentially infected people is a lot easier.

“Big data analytics is about bringing together many different data sources and mining them to find patterns,” says Frances Dare, managing director of Accenture Health.

Being in the Data analytics and Big Data field we are heartened to see just how data is impacting the effort. In recent weeks, there have been some very interesting articles that have explained the role of Big Data in the Ebola control effort. We would like to share with you bit and pieces from these articles, just so that you can get a sense of the importance of data and how in the years to come, this sector will have an even larger role to play in the detection and control of such outbreaks and epidemics.

But let’s back track a bit. For those of you unfamiliar with Data Analytics and the Big Data phenomenon, let us try and explain what it is. Today data is collected everywhere: whether it’s purchase or transaction records, weather sensors, posts to social media sites, digital pictures and videos, or even cell phone GPS signals. According to Wikipedia we create one billion gigabytes of data every day. What’s more astonishing is that as much as 90% of that data has been created in the last two years alone. Data Analytics is the process of capturing, curating, storing, searching, sharing, transferring, analyzing and visualizing this data, so that insights can be drawn to improve business profitability. When the data is so large that it is impossible to analyze using traditional methods, we call it Big Data. Today Data is changing the way we live in so many ways. It is being used in medicine to predict the outbreak of diseases, doctors and hospitals are using data to make diagnosis, companies are using data to manipulate the way we shop, data is being used to make our cities smarter…the list is endless.

Another report in BBC explains how port, train and flight data collected by a big data analytics company which has developed an Ebola-tracking app, is helping track potentially infected people and helping identify who they may have come into contact with. This is extremely relevant as tracking the movement of potentially infected people can help curtail cross border spread of the disease.

While big-data analytics are often championed by the private sector, its potential use by aid workers has been somewhat overlooked. The technology enables vast swathes of data from a diverse array of sources to be aggregated and filtered, with irrelevant information removed along the way.

We all hope that this virus will soon be contained and the loss of lives minimized. In the meantime, let’s all stay informed and do our part to stay healthy and safe.

By analysing social media, such as blogs, online forums and Twitter, we can find early warning signs of health events Frances Dare, Accenture Health