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ORNL Staff Support Award-Winning Biosurveillance Project

Computational scientists participate in multi-institutional effort to standardize epidemiological models  

Two researchers from the US Department of Energy’s Oak Ridge National Laboratory (ORNL) are part of an award-winning team using mathematical models to better understand the spread of diseases.

ORNL colleagues Laura Pullum, a senior computer science researcher, and computer scientist Arvind Ramanathan collaborated with a multi-institution team that included researchers from NASA, Johns Hopkins University, the Santa Fe Institute, and Tulane University to create the Biosurveillance Analytics Resource Directory (BARD). Based at Los Alamos National Laboratory (LANL), BARD serves as a repository for detailed information on the uses, level of detail, and other aspects of epidemiological models, with the end goal of guiding the community in standardizing and simplifying models so that nonexperts can also use them to guide decision-making.

BARD netted the collaboration the Outstanding Research Article in Biosurveillance in the Impact on the Field category at the 2016 International Society for Disease Surveillance conference December 6–8 in Atlanta.

Though researchers have used mathematical models for disease surveillance since the 18th century, modern-day computers have allowed researchers to reach new heights in understanding how epidemics form and spread.

Therein lies the problem, though—as computing technology has enabled quicker, more comprehensive model production, research teams around the world create their own models in hopes of applying them to real-world biosurveillance scenarios.

“There are many models on different aspects of biosurveillance, each with their own underlying assumptions,” Pullum said. “We wanted to create a standard view into biosurveillance models.”

The BARD review team wanted to answer questions pertaining to a model’s use before including it in the database. By clarifying and defining the purpose, scope, computational infrastructure needed, and verification methods used on a model, researchers can help government decision-makers decide quickly which model would best address a particular biosurveillance goal, be it a disease outbreak or a bioterror attack.

Pullum and Ramanathan were asked to be part of the BARD review team because of the researchers’ experience developing the Oak Ridge Biosurveillance Toolkit (ORBiT). Pullum and Ramanathan developed ORBiT to integrate datasets related to health care, environment, and climate data to help more accurately identify biological threats, evaluate how a disease spreads, and pinpoint hot spots for disease.

LANL researchers wanted experts in epidemiological model design that represented other government institutions, private companies, and academia to evaluate BARD’s effectiveness. Pullum and Ramanathan’s experiences with ORBiT made them good candidates. “I also wanted to focus on validating these tools,” Pullum said. “In many cases, validation is provided by the developers themselves, so there needs to be a more thorough, independent review prior to decision-maker use of the tools.”

Researchers at LANL will continue to develop and expand BARD’s capabilities. 

Oak Ridge National Laboratory is supported by the US Department of Energy’s Office of Science. The single largest supporter of basic research in the physical sciences in the United States, the Office of Science is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.