How big data is beating Ebola

Computational epidemiologists at Virginia Bioinformatics Institute (VBI) have been working to combat the world’s largest and deadliest outbreak of Ebola. - See more at: http://www.information-age.com/technology/information-management/123459120/how-big-data-beating-ebola#sthash.CTk2zlgo.dpuf

Computational epidemiologists at Virginia Bioinformatics Institute (VBI) have been working to combat the world’s largest and deadliest outbreak of Ebola. VBI’s Bryan Lewis writes - See more at: http://www.information-age.com/technology/information-management/123459120/how-big-data-beating-ebola#sthash.CTk2zlgo.dpuf

Computational epidemiologists at Virginia Bioinformatics Institute (VBI) have been working to combat the world’s largest and deadliest outbreak of Ebola. VBI’s Bryan Lewis writes - See more at: http://www.information-age.com/technology/information-management/123459120/how-big-data-beating-ebola#sthash.CTk2zlgo.dpuf

Computation Epidemiologists at Virginia Bioinformatics Institute (VBI) have been working to track the Ebola outbreak

INFORMATION AGE    by Brian Lewis                               March 5, 2015

When the Ebola virus started spreading and we realised we were dealing with a major outbreak, there were 30 researchers and scientists on VBI’s rapid response team that initially provided the U.S. Department of Defense and West African’s Ministries of Health (MOH) with short-term forecasts on disease spread. 

However, as the number of Ebola cases climbed, VBI moved to agent-based computational modeling to provide more in-depth analysis of how the disease might spread.

The only way to accurately do this was to create an adaptable set of global synthetic populations. These detailed demographics, family structures, travel patterns and activities were used to help model what would potentially happen as the disease spread.

 The synthetic data was created in such a way that it mirrored actual census, social, transit and telecommunications data patterns from the targeted population, whilst omitting personally identifiable information. We built entire virtual cities on local, regional and global levels.

To support the outbreak modeling, we needed a mix of computations, which meant the compute and storage would have to be both powerful and flexible to handle the various workloads. Some of the models we were running required a lot of data, while others had to have a constant stream of information which requiring parallel processing of the data.