What began in mid-December as a mysterious cluster of respiratory illnesses has now killed at least six people, sickened hundreds more, and spread to five other countries, including the US. On Tuesday, American health officials confirmed the nation’s first case of the novel coronavirus: a Washington man hospitalized outside of Seattle last week with pneumonia-like symptoms. According to reports, he had recently traveled to Wuhan, but he says he did not visit the seafood market believed to be at the center of the outbreak.

The case adds to the mounting evidence that the virus is able to spread from person to person. Last week, the World Health Organization warned such transmission appeared possible. Newly released data makes it seem nearly certain. On Monday, Chinese authorities reported a sharp uptick in confirmed cases—from a few dozen to nearly 300, including more people like the US patient who’ve had no contact with the market in Wuhan. On Wednesday, the WHO will decide whether to declare the outbreak an international public health emergency. The question on their minds: “Just how bad could this thing get?”

If you’re asking yourself the same thing right now, you’ll be relieved to know it’s probably not pandemic bad. “The only agent that can do that, that we know of today, is influenza,” says Mike Osterholm, director of the Center for Infectious Disease Research and Policy at the University of Minnesota. Coronaviruses just don’t have pandemic potential. At most, they can cause multiple, geographically localized outbreaks.

But how big and deadly those outbreaks might get is still a puzzle waiting to be put together. And unfortunately, the information essential to assembling it—to understanding what the virus catchily labeled 2019-nCoV will do next—is only starting to trickle in. Is it going to spread hot and fast like its deadly SARS-causing cousin? Or will it lie low in an animal reservoir, periodically popping out to cause a few dozen deaths each year, like the related virus that causes MERS?

Scientists who’ve analyzed the DNA of patients say it’s too soon to tell. Trevor Bedford is an infectious disease biologist at the University of Washington and the Fred Hutchinson Cancer Center who has built open-source software to track emerging diseases using genetic data. When he plugged in 15 viral genomes released by Chinese and Thai health authorities, he discovered almost no mutations between them. The viruses inside each patient split off from a common ancestor in November 2019.

That likely means one of two things: The virus is spreading rapidly in animals in Wuhan and repeatedly crossing over to humans; or animals infected humans once or twice and it is now spreading rapidly among humans. “The DNA can’t distinguish those two scenarios,” says Bedford. “Only epidemiological data or DNA from the reservoir animal can.”

Although technologies have advanced considerably since SARS killed nearly 800 people in 2003, figuring out how new diseases spread is still an exercise in shoe-leather epidemiology. It all comes down to identifying new cases, interviewing patients, tracking down anyone they came in contact with, and then monitoring the heck out of them. Only then can you start plotting cases over time to see the shape and scope of an epidemic. None of that’s out there yet. “We don’t even know what the incubation period is or how lethal it is at this point,” says Anne Rimoin, an epidemiologist who studies emerging diseases at UCLA.

So far, Chinese health authorities have followed 988 people who’ve come into contact with infected patients in Wuhan, cleared 739 of them, and are still monitoring 249, according to official reports. They have yet to share information about individual cases with the rest of the world—essential details such as what their age and sex are, when they started developing symptoms, what they might have been exposed to, and what condition they’re currently in. That information could be vital to assessing the mortality risk factors associated with 2019-nCoV, says Maia Majumder, a public health researcher at the Computational Health Informatics Program based out of Harvard Medical School and Boston Children’s Hospital. “Then we could analyze what makes people who die from the infection different from the ones that recover.”



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