A COVID-19 detective tracks disease trail with genetic clues

By Robert Langreth
In a few short weeks, Seattle-based biologist Trevor Bedford, 38, has emerged as one of the most famous epidemiologists in the world. His frequent tweets are seized upon by many of the globe’s top scientists and health policy makers. So far he has more than 170,000 Twitter followers, with thousands more joining every day.

But, unlike traditional epidemiologists, this disease detective working from his lab at the Fred Hutchinson Cancer Research Center, doesn't do fieldwork to track down Covid-19 patients’ contacts. Instead, Bedford and a handful of colleagues — spanning the globe from Seattle to Basel, Switzerland, and Wanaka, New Zealand —analyse hundreds of virus genomes from patient samples to trace where outbreaks came from, how they spread from one corner of the Earth to the next and, most important, detecting early signs of infection clusters.

The team’s analytic approach relies on tracking how viruses mutate over time as they spread from person to person. In the case of the coronavirus, whose RNA consists of about 30,000 genetic bases or letters, it mutates about twice a month. These minor mutations tend not to change the potency of the virus. But they provide clues for genetic detectives to chart how they shift subtly over time, allowing them to create sprawling “family” trees, or phylogenies, that show how the coronavirus has spread from one part of the world or country to the next.

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So far Bedford’s findings, which he summarizes promptly on Twitter, have been eerily on the mark, fueling his sudden celebrity status among fellow scientists and public health experts.

“Trevor Bedford offered some of the most careful analysis of this pandemic from the very beginning,” former Food and Drug Administration Commissioner Scott Gottlieb wrote in a March 14 tweet. “His estimates on the emerging epidemic in U.S. should be taken very seriously.”

Three weeks ago, when U.S. authorities still thought they might have the coronavirus somewhat under control, Bedford was among the first to argue that it had already been circulating undetected in the Seattle area for weeks. Virus-genome analyses suggested to Bedford that the very first patient in Washington in January, a 35-year-old man who had recently visited Wuhan, China, somehow infected someone else, allowing the disease to spread undetected for all that time around the Seattle area.

“There are some enormous implications here,” Bedford said in a nine-part Twitter thread on February 29 that has since been retweeted thousands of times. “I believe we're facing an already substantial outbreak in Washington State that was not detected until now due to narrow case definition requiring direct travel to China.”

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This genome work differs markedly from traditional epidemiology that focuses heavily on identifying infected patients and tracking all their contacts. “Instead of talking to people about who they have been in contact with and shoe-leather epidemiology, we use the genetics of pathogens to see how they are spreading and how they are transmitting around the world,” says Emma Hodcroft, a molecular epidemiologist at the University of Basel who works closely with Bedford.

Genome sequencing has gradually become a more and more powerful tool over for tracking diseases. In the 2014 Ebola outbreak in West Africa, genome analyses helped trace the origin to a transmission strain that had been missed, allowing the disease to spread quietly for months in Sierra Leone. But that work took months to perform. Recently, genome sequencing has become a standard tool for tracing the source of bacteria-tainted produce.

Twitter has also become a crucial tool. Bedford says he has long written Twitter threads to accompany his scientific papers. But the coronavirus has moved so swiftly he hasn't had time for scientific papers lately. Once the first genome came out in January, “I basically started doing science over Twitter,” he says.

Along with the science sometimes comes an inspirational call to arms. “We can bring this epidemic under control,” he wrote in a thread that was retweeted 5,000 times. “This is the Apollo program of our times. Let's get to it.”

In his 19-part March 18 Twitter thread, Bedford offers way to do just that. One path out of the crisis, he says, could be via a massive effort to roll out in-home testing kits and drive-through sites to spot cases early on and then combine those with cellphone location data to trace all the previous movements of those who test positive.

He says he finds his newfound Twitter fame a bit bewildering. “This has been very, very surreal,” says Bedford, who's been working 16-hour days since the outbreak started. “I am getting all this attention for doing this, and meanwhile everyone else's lives are being upended in terrible ways.”

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One of his key collaborators, Richard Neher, is a computational biologist at the University of Basel. Neher says the two scientists hit upon the idea of tracking virus evolution in real time using an interactive website after meeting at a conference at the University of California Santa Barbara in 2014. Their original idea was focused on influenza evolution, with the goal of helping vaccine makers predict which strains are likely to spread around the world in the next flu season. But over time their website, Nextstrain.org, evolved to include data from multiple outbreaks including Zika, Enterovirus D68 and Ebola.

When the coronavirus hit, Bedford and Neher had customized software ready to roll for rapidly analyzing hundreds of virus genomes. “We hit the ground running here because all of this basic infrastructure was in place,” Neher says.

Since then, Nextstrain has become a 24/7 operation, staffed with researchers at Bedford’s and Neher’s labs in Seattle and Basel, along with another scientist in New Zealand. With global coverage, someone is always on call to start analyzing data as soon as a new viral genome is released to gisaid.org, a website where scientists are posting the information. It takes about 20 to 30 minutes to analyze a new viral genome, allowing the website to be updated frequently.

Bedford sees his work as expanding, not replacing, the utility of existing virus-tracing methods, providing new data streams to complement traditional epidemiology. And while the evidence he gathers stops short of proving a chain of transmission, “my suspicion is almost everything we have seen in the Seattle area is part of the same transmission chain,” he says.

He started analyzing coronavirus genomes from China as soon as they began to flow into public databases on January 10th. At the time, health authorities were claiming that the virus had limited ability to spread between people. But Bedford found something alarming: The viral genomes were too similar to derive from viruses from different animals infecting people on multiple occasions. Instead, the genome data suggested that someone had acquired it from a single infected animal around early December — and it had been spreading from person to person ever since.

“This genomic data represented one of the first and strongest indications of sustained epidemic spread,” Bedford said in a Jan. 31 blog post. “I spent the week of Jan 20 alerting every public health official I know.”

Bedford and Neher are limited by the amount of genome data that is available. So far almost 1,000 patients have had their viral genomes analyzed, out of more than 350,000 people who have been infected. There are few virus genome sequences from New York, which has surpassed Washington as the hardest-hit state in the country. Overwhelmed testing centers often don't have manpower to spare to do genome analysis when so many people are having trouble getting test results.

Even so, a basic picture is emerging: Most of the coronavirus clusters now spiraling out of control in Europe and the United States likely date back to community spread that had been quietly percolating for many weeks.

“We were thinking ,” Neher says, “it was all in China and China's problem, but that was not true."