The scientific advances we need to stop COVID-19
The coronavirus pandemic pits all of humanity against the virus. The damage to health, wealth, and well-being has already been enormous. This is like a world war, except in this case, we’re all on the same side. Everyone can work together to learn about the disease and develop tools to fight it. I see global innovation as the key to limiting the damage. This includes innovations in testing, treatments, vaccines, and policies to limit the spread while minimizing the damage to economies and well-being.
This memo shares my view of the situation and how we can accelerate these innovations. (Because this post is long, it is also available as a PDF.) The situation changes every day, there is a lot of information available—much of it contradictory—and it can be hard to make sense of all the proposals and ideas you may hear about. It can also sound like we have all the scientific advances needed to re-open the economy, but in fact we do not. Although some of what’s below gets fairly technical, I hope it helps people make sense of what is happening, understand the innovations we still need, and make informed decisions about dealing with the pandemic.
In the first phase of the pandemic, we saw an exponential spread in a number of countries, starting with China and then throughout Asia, Europe, and the United States. The number of infections was doubling many times every month. If people’s behavior had not changed, then most of the population would have been infected. By changing behavior, many countries have gotten the infection rate to plateau and start to come down.
Exponential growth is not intuitive. If you say that 2 percent of the population is infected and this will double every eight days, most people won’t immediately figure out that in 40 days, the majority of the population will be infected. The big benefit of the behavior change is to reduce the infection rate dramatically so that, instead of doubling every eight days, it goes down every eight days.
We use something called the reproduction rate, or R0 (pronounced “are-nought”), to calculate how many new infections are caused by an earlier infection. R0 is hard to measure, but we know it’s below 1.0 wherever the number of cases is going down and above 1.0 wherever the number of cases is going up. And what may appear to be a small difference in R0 can lead to very large changes.
If every infection goes from causing 2.0 cases to only causing 0.7 infections, then after 40 days you have one-sixth as many infections instead of 32 times as many. That’s 192 times fewer cases. Here’s another way to think about it: If you started with 100 infections in a community, after 40 days you would end up with 17 infections at the lower R0 and 3,200 at the higher one. Experts are debating now just how long to keep R0 very low to drive down the number of cases before opening up begins.
Exponential decline is even less intuitive. A lot of people will be stunned that in many places we will go from hospitals being overloaded in April to having lots of empty beds in July. The whiplash will be confusing, but it is inevitable from the exponential nature of infection. [Continue reading…]