The U.S. Centers for Disease Control and Prevention (CDC) reports that the 2014 Ebola epidemic is the largest in history, affecting multiple countries in West Africa. As of February 26, 2015, the CDC had tracked 23,816 cases, and Ebola had already claimed nearly 10,000 lives.
Previously known as Ebola hemorrhagic fever, Ebola is a rare and deadly disease caused by infection with one of four identified Ebola virus strains. Study into how Ebola passes among individuals, as well as monitoring outbreaks and infection clusters, is critical in assisting with rapid response efforts mitigating the spread outside of infected regions and into other parts of the world, including the United States. Unfortunately, the World Health Organization (WHO) reports continuing problems tracking the spread of the virus.
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A team of 30 researchers and scientists on Virginia Bioinformatics Institute (VBI)’s Ebola rapid response team initially provided the U.S. Department of Defense’s Defense Threat Reduction Agency (DTRA) and West Africa’s Ministries of Health (MOH) with short-term forecasts on vaccine production and disease spread. However, as the number of Ebola cases climbed, VBI moved to agent-based computational modeling to provide more in-depth analysis of the epidemic, including regional travel and social interactions and their impact on the spread of the outbreak outside of the infected regions and into other parts of the world. The new method is helping the team to better understand how Ebola is transmitted, to predict infection ‘hot spots’ and to provide vital data to assist with policy recommendations and interventions.
A cluster of extremely high-performance compute and storage resources allows VBI to create the highly detailed models that provide vital insight, and to address a mix of data- and compute-heavy computational requirements while keeping pace with aggressive, rapid data growth. DataDirect Networks (DDN) SFA high-performance storage engine-based GRIDScaler GPFS parallel file system has enabled VBI to deploy the robust cyber-infrastructure needed to support creation of a global synthetic population totaling more than three-quarters of a billion people. The computational models include multiple variants, such as
- detailed demographics
- family structures
- travel patterns and similar activities
to help model what could happen as the outbreak spreads throughout West Africa.
The VBI system also allows seamless integration with different data types and offers the ability to support a variety of modeling applications and data analysis tools, including
- EpiFast, a very fast simulation for producing a broad class of interventions
- EpiSimdemics, for yielding highly-detailed and flexible, complex dynamic interventions with rich disease specifications
- Indemics, interactive, SQL-based queries of simulations and very fast specifications of novel interventions.
“With DDN, we’ve attained a fast, reliable parallel file system to handle all our different workloads. DDN was best suited for our mix of computational models, while delivering both the capacity and performance demanded by multiple users who need to access different data at the same time,” said Kevin Shinpaugh, Ph.D., Director of IT and High Performance Computing at Virginia Bioinformatics Institute.
With the new method in place, VBI’s Network Dynamics and Simulation Science Laboratory (NDSSL) has worked in partnership with the institute’s Advanced Computing and Informatics Laboratories (ACIL) to handle a variety of different workloads. In one instance, VBI was able to meet a stringent 48-hour deadline from the Department of Defense, when completing intensive modeling for recommended locations for emergency treatment units in Sierra Leone, Guinea and Liberia.
- Video: Virginia Bioinformatics Institute | Accelerated Ebola Outbreak Response: https://www.youtube.com/watch?v=49-GUBxrt-M.
