The Deceptively Simple Number Sparking Coronavirus Fears
Here’s what the oft-cited R0 number tells us about the new outbreak—and what it doesn’t.
Updated February 4, 2020, at 10:35 a.m.
When a new disease emerges, health organizations turn to a seemingly simple number to gauge whether the outbreak will spread. It’s called the basic reproduction number—R0, pronounced R-naught—and though useful for decision makers, it’s a nightmare for public communication. In brief, R0 is the average number of people who will catch the disease from a single infected person, in a population that’s never seen the disease before. If R0 is 3, then on average every case will create three new cases. But even though it seems incredibly straightforward, it’s hard to calculate and tricky to interpret.
R0 is important because if it’s greater than 1, the infection will probably keep spreading, and if it’s less than 1, the outbreak will likely peter out. So it offers vital information to organizations and nations as they consider how to respond to an outbreak—such as the one the world is currently experiencing.
In December, a previously unknown coronavirus, now called 2019-nCoV, emerged in the Chinese city of Wuhan. There have been more than 4,500 confirmed cases, the majority of which have been in mainland China. But several dozen cases have been detected in more than 15 other countries, and as the outbreak has spread, so has fear. Public-health researchers have sped to estimate the R0 of the new disease, and as they have shared their findings, this number has fueled several alarmed missives on social media.
In the past week, at least six teams of researchers, along with the World Health Organization, have published estimates of R0 for the new coronavirus. All these groups used different methods, but their results have been mostly consistent, with estimates hovering between 2 and 3. WHO was a little more conservative than the others, with estimates of 1.4 to 2.5. One Chinese team is a clear outlier, with estimates of 3.3 to 5.5. And a British-led group initially published a high average value of 3.8 last week before revising it downward to 2.5 as new data emerged.
In the intervening time, however, some observers seized upon the 3.8 number, with one Harvard epidemiologist describing it as “thermonuclear pandemic level bad” in a tweet that was retweeted more than 16,000 times, before he took it down. That’s a dubious interpretation, and here are six reasons why.
First, the R0 estimates for the new coronavirus are in line with those for many other diseases. They’re similar to those for SARS (2 to 5) and HIV (also 2 to 5), and considerably lower than those for measles (12 to 16).
Second, a bigger R0 doesn’t necessarily mean a worse disease. Seasonal flu has an R0 that hovers around 1.3, and yet it infects millions of people every year. SARS had an R0 of 2 to 5 and infected just over 8,000 people. The number is a measure of potential transmissibility. It does not actually tell you how fast a disease will spread.
“People make the mistake of thinking that a high R0 means that you’re inevitably going to end up with a pandemic, and that’s not what it means at all,” says Maia Majumder from Harvard Medical School, who published one of the seven estimates for the new virus. In her view, if the number is higher than 1, we should take the disease seriously. But exactly how high it is beyond that threshold isn’t very informative at this stage.
Why? Because third, R0 is an average. Let’s say the virus has an R0 of 2. This could mean that every single infected person passes the virus to two other people. It could also mean that one infected person is a “super-spreader” who infects 100 people, while 49 infected people infect no one. These two scenarios have radically different implications for what will happen during an outbreak.
Super-spreader events are dangerous for health-care workers, but counterintuitively, they can sometimes be a good sign. They suggest that most infected people won’t actually perpetuate the outbreak, while the most problematic cases “may be more likely to be recognized due to their dramatic nature,” writes David Fisman of the University of Toronto. This attention can mean that control measures are put in place more readily, he explained in a posting to the ProMED email list. Other coronaviral diseases, such as SARS and MERS, involved super-spreader events, although it’s still too early to say if 2019-nCoV will have the same.
Fourth, R0 is not easy to calculate. That’s especially true in the early days of an epidemic, when it’s not even clear how many cases there have been. Some people might have been infected without showing symptoms. Others might not have reported their symptoms to health authorities. Absent clear data on who has the disease, let alone how they’re moving around and interacting with other people, scientists have to calculate R0 by doing complicated simulations using a variety of possible methods. That’s why early estimates can vary so wildly, and why they should be taken with a grain of salt.
Fifth, R0 is not some magical, immutable property of the virus itself. It depends on how likely someone is to be infected after contact with an infectious person, and how often such contact occurs—and these quantities are also affected by how societies deal with a virus. When SARS first emerged, transmission dynamics played out very differently in China and Canada, which is why the virus’s R0 values cover a wide range, from 2 to 5. “In places with good infection control, where you can isolate cases as soon as they happen, you’ll see a lower R0 than, say, in places where an outbreak initially took off,” Majumder says.
The current R0 estimates for the new coronavirus are specific to Wuhan, and mostly to the era before people knew about the virus. New estimates will emerge as the virus spreads to places that are now aware of and watching for it. “Likely, these will all be significantly lower,” says Kristian Andersen, a virologist at the Scripps Research Translational Institute.
Sixth, R0 is not destiny. It is a measure of a disease’s potential. And once nations realize that a new disease exists, they can actively screen for it, check that health-care workers are using proper protection, and instigate quarantines. Even simple steps such as hand-washing might make a difference. All these measures could potentially lower the chances that the virus will spread and ensure that its actual transmission rate—the quantity known simply as R—is less than R0, and ideally less than 1. There are a few reassuring signs: One study suggests that patients are now being isolated just one day after showing symptoms, as opposed to six days after at the start of the outbreak.
None of this should be cause for complacency. The new virus is a serious threat, and the world should absolutely start considering what to do if containment measures fail. But at a time of great uncertainty, people grasp for solid answers, and numbers seem to offer them.
This new virus has emerged at a time when scientists have more avenues than ever for publishing their data and comparing notes. That can be a good thing, since fast and open communication can help bring diseases to heel more quickly. The risk is that a complicated number is released without context into a world that doesn’t know how to think about it. “Getting these R0 values out very rapidly is super important,” Andersen says. “But the way that some people and news outlets have interpreted what they mean … that part is problematic.”