IBM Researchers Assess Ebola Virus Transmission With Big Data Analytics

IBM researchers have used big data analytics to evaluate the impact of infected animal carriers in the spread of the Ebola virus among humans.

The company said Friday it partnered with researchers at Montclair State University to release a publication that contains an open-source computational model designed to help study the spread of Ebola from animals to people.

Ebola is not carried primarily by humans but becomes a human-borne disease through contact with infected carrier animals, such as bats and snakes, in an occurrence called a spillover event, IBM noted.

The open-source computational model accounts for random spillover events from infected animals to humans and demonstrates the danger of overlooking control of the infection route, the company added.

During the 2014 Ebola outbreak in West Africa, various researchers produced mathematical models and computer simulations to study the course of the disease and explore the potential impact of interventions.

Few models explicitly included the presence of infected animals and none considered the random nature of the spillover events, according to IBM.

IBM’s research arm also released computational models through the Eclipse Foundation’s free Spatio-Temporal Epimidemiological Modeling framework to support researchers’ efforts to optimize resource allocation and address the disease-spread chain.

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