A big-picture look at the world’s worst Ebola epidemic: West Africa, 2013-2016

a good understanding of how evolution works, along with strong critical thinking skills and an ability to spot trends and anomalies.

“Andrew is wonderfully curious,” Bedford said of Rambaut. “The community working on Ebola was really lucky that he was involved in all of this. And Gytis is faster than anyone I can think of. If Andrew or I think of a question and ask Gytis about it, he’ll have some beautiful figure to show us an hour later.”

Next steps: more speed, more data-sharing
Because speed is critical in an outbreak, Bedford wants to make the analysis process even faster, just as new technologies have sped up sequencing.

“We’d like basically to make some of the core analyses in this paper, and the animation [that Dudas made of the virus’ spread] something that can just happen,” he said.

To this end, he and a longtime collaborator, Dr. Richard Neher of the University of Basel in Switzerland, have designed a tool called nextstrain to analyze and track genetic mutations during outbreaks. Anyone can download the source-code from GitHub, run genetic-sequencing data for the outbreak they are following through the pipeline and build a web page showing a phylogenetic tree, or genetic history, of the outbreak. The innovation recently won the first-ever international Open Science Prize.

“If there is a next [epidemic], and there is faster data-sharing,” Bedford said, “you can have analyses out the door very quickly.”

But the challenge of getting scientists to share data remains. Despite the precedent set by the response to the Ebola epidemic, Bedford and Dudas point out that fewer researchers have shared Zika virus genomes from the more recent crisis in Brazil, Central America and the Caribbean. In part, they said, that may be because the Zika virus is more difficult to sequence than Ebola, making researchers more prone to guard their rare sequences for publication.

The Ebola epidemic began while Dudas was working on his Ph.D., and the data-sharing that ensued impressed the young researcher deeply. “My standards for what collaboration is supposed to look like have been set pretty high,” he said.

“There are still some people who think that genome sequencing is effectively stamp collecting,” Dudas continued. “You might collect samples, and you might sequence them and look in retrospect at the outbreak. But all the sequencing that’s been done leading up to this publication was essentially being done in real time. And each analysis was then used to go back to the field and make decisions. It’s a way to understand what’s driving an epidemic.”

— Read more in Gytis Dudas et al., “Virus genomes reveal factors that spread and sustained the Ebola epidemic,” Nature (12 April 2017) (DOI: 10.1038/nature22040)