From 2014-2015, a massive outbreak of Ebola occurred, mostly in West Africa. More than 11,000 people died of this disease in that region alone [source: Centers for Disease Control and Prevention (CDC)]. With the outbreak of the virus occurring in some of the poorest countries in the world, it was difficult to get medical information to citizens, and there was little infrastructure to combat the disease. A major concern in the global fight against Ebola was understanding where the virus was spreading in order to determine the areas with the most urgent needs for aid. And this is where data science stepped in.
Using real-time mapping software, scientists and public health workers can track the disease across Africa and predict the most vulnerable areas that might succumb to an outbreak in the future. Culling together data points about the location of bat species (the likely carrier of the Ebola virus), population density, travel time from the nearest major settlement, and a handful of other factors, scientists can get in front of the disease.
The mapping tool was rolled out at a workshop in February 2016. "I can easily go through the maps and see specifically the districts in Ghana where the niche of Ebola virus is, where is there likely going to be an outbreak, and then from there we can do the animal surveillance," said attendee Dr. Richard Suu-Ire, head of the wildlife veterinary unit in Ghana that is responsible for collecting bat samples for Ebola surveillance in his country [source: Fortunati].