How Can Big Data Help Against Ebola?

As the disease is spreading, we look at how data can play a vital role in the fight


Ebola is one of the most talked about and terrifying developments in the world today. Governments don’t know how to deal with it and the response from health organisations seems to be only denting the problem. So what technology do we have that could have been used to lessen the impact and help out in the future?

Big Data.

Through the use of data, Healthmap pinpointed the potential outbreak on March 14th, a full 9 days before WHO formally announced the epidemic. It used social data from blog posts written by healthcare professionals who were treating people with ebola-like symptoms and people who were sharing these on social media, to pinpoint that there was an ebola outbreak in Guinea.

This use of openly available data to help predict an upcoming epidemic has been held up as a victory for it’s use over traditional information gathering and news reporting. If it had been taken more seriously when it was flagged in early March, then perhaps we would be in a stronger position now in fighting the spread of the disease.

However, this is not the full extent of the story. It was only flagged on March 14 after a press conference from the minister of health from Guinea on March 13, which was conducted in French. The difficulty is both that with isolated communities who are effected, they don’t regularly use the internet and that monitoring systems are often only monitoring English language posts. As most of the initial posts would have been in French, it would not have had much effect.

Also, it can only have a certain effect as it looks at social posts about certain aspects and will often not include some of the primary groups who have been effected. For instance, those who tend to be effected first by diseases are the very old and the very young, the two groups who are least likely to be able to use social media in this context.

However, monitoring alone is not the only way that data can be used to help with ebola.

We saw with the way data was used for the Haiti earthquake relief, that it can help to co-ordinate equipment and personnel, putting them in the right place at the right time. This is certainly the case with ebola. Data from hospitals for the number of people being treated for ebola, where they are and what they need, means that vital medical supplies and personnel can be sent to the areas where they can make the most difference.

Seeing where the virus is being spread through the way a population is moving is an important element to predicting how to stop it. It is for this reason that a West African mobile carrier has given access to data from it’s many users to allow people’s movements to be seen and thus where future outbreaks may occur.

It will be through this kind of open data sharing that the most effective work can be done, essentially the more invasive the data is, the more insight it will give. It goes against much of what people want to do with their data, it will allow for doctors to treat in a more effective way and governments to prevent it’s future spread.

Although data will allow for many different solutions to the problem, the truth is that it will only be through medicine and doctors that this disease will be beaten. If you are interested in helping with this, you can contribute to the Red Cross at


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Big Data Innovation, Issue 7