Making Sense of COVID-19 (and Trying to Stay Calm)

Update: More recent iterations are available:

Like most folks I know, I’ve been feeling increasingly stressed about the Coronavirus pandemic. I had done my best to educate myself and prepare, but I’ve been surprised by how scared and anxious I’ve been this past week.

Early on, my social media feed was invaluable at helping me understand what was happening. Now, it’s just causing me stress. Yesterday, I decided to try to limit my social media (and media) exposure. Instead, I would check the daily new cases graph once-ish a day, then just live my life. I’ve been primarily using worldometer, but I switch to The New York Times (which is updated more frequently and comes with news summaries) when I get antsy.

My reasoning was simple. Coronavirus is here in the U.S., and it’s spreading. (Because of lack of testing, we likely have many more cases than currently reported.) We missed our opportunity for containment, so now it’s all about mitigation. Most of the commentary doesn’t offer any real insight into how we’re actually doing in that regard, so I’m better off mostly ignoring it. The curve gives me real data on how we’re doing.

The problem is that it’s hard for me to gauge anything from this data other than that we’re on the growth-side of the curve, which I already know. I decided to map some additional data onto the curve to see if that helped. I looked at three other countries: China, South Korea, and Italy. China and South Korea have, by all accounts, handled things well. I’m not sure if Italy is handling things poorly, but — by all accounts — things are going poorly there. I figured that comparing these three data sets with the U.S. curve would give me a better sense of how we’re doing and what to possibly expect.

I looked at roughly a month of data for all four countries. Cases in South Korea, Italy, and the U.S. all started coming up around the same time, so I could actually use data from the same time period. Thing started blowing up in China roughly a month earlier, so I took the earlier data and mapped it onto the current time period. The key step I took that I haven’t seen in any other charts so far was to normalize the data by population (South Korea = 0.15; Italy = 0.19; U.S. = 1; China = 4.35).

Here’s what I came up with:

The orange curve is the U.S. data. The dotted line is a worst-case projection based on where we actually are based on death rate. (See Mona Chalabi’s excellent Instagram post, which uses analysis from Tomas Pueyo, for more on this.) I did not do a worst-case projection for South Korea (which could also be about 10 times off), Italy (which could be as much as 100 times off), or China (Mona didn’t include China in her graphic). I also didn’t represent the spike in China’s data that arose when they changed how they were testing, as it’s accounted for in the peak and subsequent data.

Here’s how I read this: China did an amazing job of managing the situation. South Korea had an awful spike, and somehow managed to turn it around. Italy — wow. Things are not good in Italy. Right now, we in the U.S. are doing okay, but it’s still very early, and it remains to be seen what our curve will look like. However, at least now I have some points of comparison.

Doing this exercise made me feel much better. Feedback (especially critiques and corrections) encouraged! Stay diligent, keep your (physical) distance, wash your hands, and take care of yourselves!

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