IBM uses big data to detect Ebola's spread in animals

IBM researchers have announced new strategies in detecting and treating Ebola. They are using big data analytics to identify infected animal carriers, previously unstudied as a spread of the disease, to understand how the disease spreads.

In 2014, the West African Ebola virus killed more than 11,000 people. Identifying and treating the disease became the top priority of researchers and governmental agencies around the world. While many of these attempts used epidemiological modeling, they did not identify the risk of animal carriers and how they affected the spread of the disease.  

“By addressing the source of infection earlier in the disease-spread we believe that it increases the probability that an entity like the World Health Organization (WHO) can not only reduce an Ebola outbreak, but also help to prevent a possible pandemic,” said Simone Bianco, research staff member, IBM Research-Almaden. “It is important and should not and cannot be understated.”

The model developed by IBM, available here, accounts for spillover events from infected animals spreading the disease to humans. This information fills the gap of missing analytics and shows the route of the infection, improving understanding why the virus is present in certain populations.