### A: “Transmissibility” in infectious disease means how readily it is passed from one person to another, given the peculiarities of a specific time and place (in this case, in the UK this Fall).

Transmissibility is measured in numbers with something called R-value. The R-value for the old SARS-CoV-2 variant was hovering right around 1 (in the UK, this Fall), but the new variant’s R-value is more like 1.4-1.7 (that is, up to 70% higher). Like compound interest rates, even a very small shift in the R-value in either direction can make a huge difference after some time passes. A 70% jump is a big deal and a big problem–and it has lots of people worried.

What can you do? Stay SMART, of course! The same protection measures work on the new variant.

Transmissibility of an infectious disease is measured by looking at how many people were sick at one point–say, two weeks ago–and comparing it to how many people are infected at a later time–say, today. This ratio gives an average of how many new infections stem from each of today’s infections. The measure is called the effective reproductive number, R-value, Rt, or simply R.*

The new viral variant** called B.1.1.7 is making headlines because it has an R-value that is as much as 70% higher than the previous commonly circulating variant. Though the estimates we have right now are rough, 70% more transmissible is a BIG difference and a big problem. We’ll go through some examples to see why.

R-value is specific to the place, time, and conditions where it is measured and it changes as conditions change. Up until the middle of November or so, the R-value for the UK was hovering around 1 (or a bit more). That’s an epidemic that’s not losing steam, but it’s under control. When R is 1, each infected person leads to one more infected person. People get sick and recover at about the same rate.

Then the new SARS-CoV-2 variant B.1.1.7 began to spread in the UK. Based on what happened to the number of cases after this variant was detected, scientists estimate that the R-value of this new variant is about 70% higher. An R-value of 1.7 is an epidemic that is most certainly *not* under control.

The sharp increase in transmissibility has led to calls to turn up the dial on restrictions in the UK. As molecular biologist & science journalist Kai Kupferschmidt put it, this means our wiggle room just got smaller. “Or, if you think of it in terms of the Swiss cheese model, we can afford fewer, smaller holes in the cheese.”

WHY this variant is more transmissible is not known. Maybe it sticks to cells better. Maybe it likes to live in the upper respiratory tract where it can be spread more readily. Maybe it produces more copies of itself. Maybe it’s figured out how to use Tiktok (ok that theory seems unlikely). We’ll be watching for more info.

However, just knowing that it has a higher R-value is an important signal all by itself because the R-value determines how steep the epidemic curve gets. Remember the “flatten the curve” calls? Flattening the curve means *lowering the R-value.* And raising the R-value will steepen the curve. Because the effect of changes in R are exponential–like compound interest–even a tiny change has a huge effect. And 70% is not tiny.

Let’s look at the implications. We’ll use a simple example to show the impact of different R-values on an epidemic. In this example population, we’ve simplified the case fatality rate to be a flat 1.7%, and ignore differences in risk by age.*** In each case, we’ll start with 1,000 people who are currently infected.

➡️ For an R-value of 1, 1000 infected people today means 1000 actively infected people in 3 months. In total, over those 3 months, about 10,000 people will get the disease. About 160 will die. These were the waters the UK was sailing up until November.

↘️ When R is less than 1, each infected person leads to *fewer* cases later, or a shrinking number of cases over time. Let’s look at an R-value that is 70% less than 1. For an R-value of 0.3, 1000 infected people today means 0 actively infected people in 3 months. Meanwhile, a total of 1,425 people will get it over those 3 months, and just 24 will die.

And finally, let’s look at a couple of the credible estimates for the R-value for SARS-CoV-2 variant B.1.1.7.

↗️ Lowest estimate for R of variant B.1.1.7 = 1.36: 1000 infected people today = 21,000 people who are actively infected in 3 months. Meanwhile, 62,000 in total will be infected, and 1,100 will die.

⬆️ Median estimate for R of variant B.1.1.7 = 1.52: 1000 infected people today = 68,000 people who are actively infected in 3 months. 160,000 will be infected in total, and 2,700 will die.

⬆️☣️⬆️ High estimate for R of variant B.1.1.7 = 1.68: 1000 people infected today = nearly 200,000 people who are actively infected in 3 months. Over 400,000 people will get COVID-19, and 6,800 of them will die.

So stay 🇸 🇲 🇦 🇷 🇹! As far as we know, all the laws of physics still apply to the new variant. We need to do all the same things, but more and more consistently. Find the holes in your layers of protection and make them smaller wherever you can.

🇸 ↔️ Space: Keep your distance from other people.

🇲 😷 Masks: Keep your nose + mouth covered.

🇦 💨Air: Keep it fresh.

🇷 🔁 Restrict: Keep your circle small.

🇹 ⏲️Time: Keep your interactions brief.

Other helpful twitter threads from respected scientists:

Virologist & clinician Dr. Muge Cevik

Epidemiologist Dr. Deepti Gurdasani

* Rt is specific to a certain time, place, population, and conditions. It is also sometimes incorrectly referred to as R0/R-nought, which is a related measure of transmissibility, but not what we’re talking about here.

** Is it a strain or a variant? What’s the difference anyway? It’s technically a variant, but most people are using these terms interchangeably.

*** Obviously, that’s not a realistic assumption, but it’s useful here to illustrate how important a 70% increase in transmissibility is at the population level.

If you want to play around with these numbers yourself, here’s the online calculator we used to estimate them: https://gabgoh.github.io/COVID/index.html.