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The R0 of COVID-19: Dealing with the misconceptions

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This post will try to rip apart some misconceptions around the basic reproduction number of an infection defined as R0 and, more precisely, the R0 of COVID-19, the new Coronavirus disease first identified in Wuhan, China. You’ll learn to debate my imaginary nemesis Chad who has no clue about R0 and COVID-19 but likes to pretend.

The battle against the new Coronavirus member, called COVID-19, continues. Unfortunately, the day of writing this (Wednesday, 12 February 2020), the prospects look a bit bleaker, as the Hubei province – where the virus was first discovered – reported 242 new deaths, bumping the Chinese death toll up to at least 1350 people.

How do we deal with the overwhelming information about this virus? We’ve all the right to be worried; after all, an epidemic is getting nasty, and the news sites are not glowing with optimism. On the contrary, we hear and see terrifying stories. About the fast spread, countries closing borders for people with fever, and random people falling on the streets. And we hear and read numbers. Many use numbers to explain this virus’s local, regional, and global effects.

Have you heard about the R0 of COVID-19 yet?

Suddenly it felt like everybody was talking about R0 without grasping its meaning.

“Don’t you know? The R0 is now reaching high numbers.” That’s that typical bro-dude talking. That bro, conveniently standing between the snack table and fridge at your friend’s housewarming party. You know, the dude that nods at random people coming in and giving other people noogies. The one that has a one-syllable name like Chu… Chuff..? Chud..? Chad!!! His name is Chad!

Chad has been reading the news, and he’s telling you all about the disease. But you’re starting to get suspicious of his actual knowledge. You’re finding gaps here and there in his arguments but cannot pinpoint what’s wrong with them.

Luckily, the Embassy’s got your back and will review Chad’s comments skeptically. After this post, you should be able to approach Chad and tell him, “Chad, you know I like you and all, but we need to talk; we need to rectify some of your arguments for the sake of human sanity. Dammit, Chad! We need to fix these arguments for your own sake!”

But before we get into this battle…  

What does R0 mean?

R0 (or R-nought, meaning R nothing) is a mathematical term that represents the basic reproduction number of pathogen infections. In simple terms, R0 denotes the expected number of individuals that, on average, will receive a transmittable disease from an infected individual. Not only that, but the calculations to reach an R0 also assume that all individuals are susceptible to the disease, meaning that they haven’t been infected or vaccinated against it.

It’s worth repeating. R0 estimates the average number of susceptible people that get the disease from another infected person. So, if we assume that the R0 of COVID-19 is 2, then every infected person will infect two susceptible individuals. And these two will transfer the virus to two others, and those two will, in turn, affect two, and… you know how this continues.

R0 of COVID-19 example where R0 is 2.
A representation depicting an R0 of 2. The Conversation, CC BY-ND

R0 is a neat way to estimate the severity of a pathogen outbreak or epidemic, such as COVID-19, and start preparing the defenses. For instance, if R0 is below 1, the virus spread will eventually die out. But, if R0 is greater than 1, then… well, yes, then it’s time to start thinking of strategies because it’s probable that the virus will spread.

Now…

Chad claims that the R0 of COVID-19 is 5.5

Well, Chad has been following the news, it seems. But pretty selectively. Since R0 values are based on mathematical models, the approach to reaching a number differs depending on the researchers’ methods.

Once COVID-19 broke out, I imagine epidemiologists worldwide spurted to their computers to start calculating. While most of these groups and organizations – including the World Health Organization (WHO) – were consistent with R0 values, estimating numbers between 2 and 3, other groups retrieved higher values (up to 5.5). They were few but damn, do sensation-seeking media sites love those wonderfully high numbers! But let’s remember that most teams that estimated the R0 of COVID-19 were more modest.   

Also, remember that the estimates may vary between countries, regions, or continents, depending on where the outbreak started. The reason is that some countries are better prepared to battle and isolate the virus, which is a factor that affects the R0, for example, COVID-19.   

So, tell Chad that 5.5 might have appeared in the media but might also be an overestimation. That is if he even listens to you. At this point, he’s playing beer pong (still next to the fridge, though).  

Chad believes vaccine campaigns can lower the R0 of COVID-19

Nope! Go back to the “What does R0 mean” part and show Chad what R0 means.

 

“R0 estimates the average number of susceptible people that get the disease from another infected person.”

The keyword here is “susceptible”. That means that the poor hypothetical individuals getting infected in these calculations have never been exposed to the pathogen, for example, COVID-19, or have never been vaccinated. By its definition, R0 never considers vaccinated people, which means you can protect whole populations, and your R0 will remain the same (assuming you re-use the same method).

Related: Different age groups, different responses, and how we protect each other

Still, if you or Chad want to know, for instance, how a vaccination campaign has changed the infection rate of a pathogen, then I’ll point you toward the so-called effective reproduction number (R1). This one considers the current state of a population, which is a mix of susceptible and non-susceptible people. But let’s stick to R0 for the sake of this post.  

R0 is not unique to COVID-19, Chad

It’s not. Scientists have applied R0 since 1952 to model the spread of malaria, a disease caused by parasites. Of course, the analysis had a different name then, but it was the same as today’s definition of R0.

In other words, not only is R0 not a COVID-19-specific model, but it’s used to estimate the spread of any type of pathogen, including other viruses, bacteria, and parasites.  

And I know Chad said R0 was a COVID-19-specific thing. But Chad is also the guy high-fiving all other dudes whenever they pick a new beer from the fridge, finding it “radical” and starting half his sentences with “bro.” 

Chad now says R0 is a constant for COVID-19 (or any other pathogen-derived disease for that matter)

It’s easy to believe that R0 defines a pathogen’s inert ability to spread and cause diseases. After all, every time we encounter the R0 definition – in the news, social media, or standing next to Chad – it piggybacks with bad news. It makes sense; organizations like the WHO need some guidelines to make decisions and save our lives, and R0 is a good estimator of a pathogen’s reproductive number.

Still, that’s not to say that the definition is a pathogen-inert constant; there are three main factors that R0 calculations take into account:

The patient and the infection period

The longer you’re sick, the higher the probability you’ll spread the virus to other people. So, that’s going into the calculations.

Society and the person-to-person contact

How often do people come in contact with each other? Is the community densely populated? Do people get hospitalized immediately upon symptoms?

These factors and others that predict the contact rate or quarantine measures in society are considered. And, you guessed the correlation by now: more person-to-person contact pushes R0 up.

This means that R0 can depend on the country where the pathogen was first identified.

The pathogen (the COVID-19 virus, SARS-CoV-2 in this case) and the way it spreads

Finally, we turn our heads to the pathogen (or, like in this case, the virus causing COVID-19 called SARS-CoV-2) and ask, “HOW does it spread”. Because some pathogen routes are more efficient than others, the common flu or measles are airborne, and HIV and Ebola are transmitted through sexual contact or body fluids. Which one do you think spreads the fastest? The answer is airborne pathogens – like the one causing COVID-19.

Reacting to the R0 of COVID-19 is tough

You see now how the R0 is hard to estimate and why we find different values depending on the source, especially at the early stages of a virus outbreak. Researchers have to simulate all these factors. Some people might be infected without showing symptoms, and others have symptoms without reporting them. How do people move around and spread the virus to other people? How well does society manage patients? The math can become tough.

Related to this: How are virus infections diagnosed?

And things don’t get easier because R0 is only an average. Here are some outcomes from an R0 = 5, taking five people into account:

  • 5+5+5+5+5
  • 5+6+5+4+5
  • 0+0+0+4+21

All these three scenarios have the same average, which is 5, but as you see, the distributions vary from one example to another. While the R0 is evenly distributed in the first two, the last example represents a case where one person increases the average markedly, a so-called super spreader. In other words, the super-spreader example represents a situation that needs to be approached differently compared with the first two.

For example, while dangerous for healthcare professionals, “[…] superspreader events may be more likely to be recognized due to their dramatic nature, an outbreak driven by superspreaders may be more likely to attract the control measures needed to disrupt transmission,” writes David Fisman, MD, University of Toronto.

While having different estimates is unavoidable and completely understandable, my cynicism wants to ask you, “Which R0 values do you think sensation-seeking channels lean towards? The modest ones, perhaps? Hm?”

The intention

Now, I don’t want to leave you thinking that the fear of COVID-19 is entirely exaggerated. Indeed, we should be cautious and concerned and take all the necessary measures to reduce the spreading probability. After all, the virus is still spreading, and it’s going fast.

The intention here was to make you aware of the concept and the possible dangers when you blindly rely on a number. Chad, that last one is for you. Where’s Chad anyway?

Next time, we might talk about Big Pharma’s little secret, eating salad only, or maybe this time we finally get to read the vinegar-oil-water story. Who knows?

By the way, you’ve reached the end, so we’re guessing you kind of liked this post. If that’s the case, we’d appreciate it if you shared it with your friends and family on your favorite social media platform. If you have any comments, feedback, or doubts, go ahead and share them here or contact us. Gracias!

Santiago

Santiago Gisler, PhD, is a freelancing scientific and medical writer with a research background in cancer research, gene editing, and molecular genetics (genes and their regulation.) Santiago helps researchers, companies, and organizations to communicate engaging and clear scientific content.

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