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College of Science

Physical Address:
Mines 321

Mailing Address:
875 Perimeter Drive MS 3025
Moscow, ID 83844-3025

Phone: (208) 885-6195

Fax: (208) 885-6904

Email: science@uidaho.edu

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Confronting Ebola with Computers

A computer model of ebola
A computer model shows the interaction of a glycoprotein found in Ebola (shown in red) and corresponding antibodies (shown in blue).

New working group uses advanced modeling techniques to understand evolution, spread of deadly virus

By Tara Roberts

Roughly 20,000 Ebola virus disease cases in western Africa led to more than 8,000 deaths in 2014.

To help track and treat the disease – and potentially other viruses – in the future, researchers across disciplines at the University of Idaho have formed the Ebola Working Group.

The group, a subset of the university’s newly formed Collaboratorium for Modeling Complex Problems, is tackling two projects designed to better understand Ebola and how it spreads.

Modeling Evolutionary Factors

The working group’s first project, led by associate physics professor Marty Ytreberg, uses computer models to determine the implications of ongoing and possible future evolution in Ebola. These models could help evaluate vaccine effectiveness and help health officials be on the lookout for dangerous mutations.

In December, the National Science Foundation awarded Ytreberg and his team of biology and physics faculty and students a $72,000, one-year grant for the project through its Rapid Response Research program.

Vaccine makers use proteins from the Ebola virus to elicit an immune response – the production of antibodies – in the body. However, the current vaccines are being developed using an Ebola strain that caused outbreaks beginning in 1976.

“Since the vaccine is not being made from the identical strain that’s circulating now, we’re asking how the antibodies that are being generated might interact with the virus,” says Holly Wichman, a University Distinguished Professor of biological sciences and a member of Ytreberg’s team.

The team’s model will provide a framework to analyze viral mutations and their effects in real time.

“We want to be in a position so that as new data come in, we’ll be able to very quickly throw that into our models and see how the proteins will be impacted,” Ytreberg said.

The project also will evaluate the same proteins to see what future evolution could occur. The team hopes to identify potential mutations that could significantly disrupt how well a vaccine works, as well as reduce the natural immunity gained by people who have had the disease in the past. These mutations could be put on a “watch list” for world health officials.

The team’s Ebola research builds on previous viral modeling projects at UI – including one published recently in the journal Public Library of Science ONE – that created evolutionary models of a virus that attacks bacteria.

“It’s a really good demonstration of the importance of basic research for applied research,” Wichman says.

Modeling Social Factors

The working group’s second project also uses computer models – this time, to track how social, cultural and geographic factors affect the way Ebola spreads.

The team, led by associate statistics professor and epidemiologist Michelle Wiest, brings together faculty and students in statistics, philosophy, biology, mathematics and political science to examine the issue from multiple angles.

“The social and cultural context in which this outbreak is occurring has a huge impact on how many cases we’re seeing in different areas, and who is getting sick,” Wiest says.

For example, health officials have worked with communities to understand culturally appropriate ways to handle Ebola victim’s bodies.

“An important part of the transmission is from dead bodies to the living caretakers of those bodies,” Wiest says. “They’ve had to roll out burial teams to help bury the bodies not only safely, but also with dignity.”

The team’s model will predict where the Ebola outbreak – which has plateaued in many areas – might persist.

“We anticipate there’s going to be pockets where transmission is still occurring and could then be a reservoir from which future outbreaks could arise,” Wiest says.

The model will also identify what data isn’t yet being gathered in the field, but could help researchers better track the outbreak.

a venn diagram representing the Collaboratorium for Modeling Complex Problems
A Venn diagram representing the Collaboratorium for Modeling Complex Problems

Models for the Future

In addition to providing long-term tools to help groups like the World Health Organization and the Centers for Disease Control and Prevention fight Ebola, the Ebola Working Group expects their research to provide techniques that will apply to other diseases.

“It’s not that difficult to think of infectious diseases that do or could occur in Idaho and similar social conditions that lead to increased likelihood of transmission of those diseases,” Wiest says. “This work could help inform and prepare us to respond to outbreaks locally.”

The Ebola Working Group is also just the first among what the researchers hope will be many projects launched by the Collaboratorium for Modeling Complex Problems.

The Collaboratorium is administered under the UI College of Science and the Center for Modeling Complex Interactions. With assistance from the college, the Office of Research and Economic Development and the Institute for Bioinformatics and Evolutionary Studies, the Collaboratorium working space will open in the Mines Building early this spring. All students and faculty are welcome to get involved.

“The intent is to make the Collaboratorium a university-wide resource,” Wichman says.

Contact

College of Science

Physical Address:
Mines 321

Mailing Address:
875 Perimeter Drive MS 3025
Moscow, ID 83844-3025

Phone: (208) 885-6195

Fax: (208) 885-6904

Email: science@uidaho.edu

Web: College of Science