# Overall numbers won't show the English strain coming

*\[Epistemic status: half-baked thoughts that might be wrong. Apologies if this point has already been made.\]*

*\[Edit:* [*here's*](https://ericneyman.wordpress.com/2021/01/03/overall-numbers-wont-show-the-english-strain-coming/) *a version of this post that is meant for a more general audience.\]*

Here is a plot of daily new positive COVID tests in the U.S. in the first half of March 2020.

![](https://39669.cdn.cke-cs.com/rQvD3VnunXZu34m86e5f/images/d66e1eb6d1e97d616c2fbbba1971cc12d826ba201fcdc535.png)

While the rationalist community figured out the whole exponential growth thing in February, it's no surprise that the general public was worried by mid-March: the virus was *here* and was growing *fast*. This was evident by the time there were 1,000 new positive tests per day. The lockdown began around mid-March, which is way worse than if it had begun in early March, but *much, much better* than if it had begun in late March, by which time we had tens of thousands of new positive tests per day.

The situation with the English strain is different. One way in which it's better is that we now have adequate testing. But there's a scary way in which it's worse.

The reason that the chart above is scary is because on any given day there were many times more cases than just a week before. I won't cherry-pick March 15th, but e.g. on March 12th there were 7 times more cases than on March 5th. And the reason that this trend was so evident is that the exponential growth drowned out any day-to-day noise.

This won't be the case with the English strain, at least if the general public (or public officials) use overall numbers to guide their planning. That's because, instead of seeing an exponential trend, i.e. something like $$cases(t) = 1.3^t$$ plus noise, we'll be looking at something like $$cases(t) = 200,000 + 1.3^t$$ plus noise (where 200,000 is the currently dominant strain and 1.3^t is the contribution from the English strain). Here's a simulation of what that looks like if the noise is normal with standard deviation 25%.

![](https://39669.cdn.cke-cs.com/rQvD3VnunXZu34m86e5f/images/22729ce23b7c1de2d882b03f2e8a8925fb41ca01e033ca87.png)

cases(t) = 200,000 + 1.3^t + random noise

Remember that people starting freaking out about COVID around when there were 1,000 new positive tests per day. So here's my question: where on this chart does the English strain first contribute 1,000 new positive tests per day? The answer:

Day 27

On the other hand, I don't think the general public will start worrying about the new strain until it starts adding to the *overall numbers* substantially, i.e. sometime between day 40 and day 50.

This means that, because there's already a high baseline case count (plus noise), I expect the general public's reaction time to lag by **two or three weeks**. (Edit: it's no complicated and I no longer stand by this particular number -- though I stand by the overall point. See the edit at the bottom of my post.)

Now, there are factors going in the other direction:

*   We are testing way more, so "1000 positive tests" now isn't a fair comparison to "1000 positive tests in March".
*   We're already exercising our quarantine muscles. We won't have to re-learn everything (e.g. "wear masks") from scratch.

At the same time, one reason to expect people to react *less* is that COVID isn't a scary new thing; it's already here, seemingly a known quantity.

But in any case, I think there's reason to expect our reaction to the English strain to be slower, and that's pretty scary.

*(EDIT: Bucky* [*correctly points out*](https://www.lesswrong.com/posts/9jHwiXMvctJfWBCtm/overall-numbers-won-t-show-the-english-strain-coming?commentId=X2ARrdmtHTsHQ6dAq) *that the constant 1.3 is too large. I've* [*made an attempt*](https://www.lesswrong.com/posts/9jHwiXMvctJfWBCtm/overall-numbers-won-t-show-the-english-strain-coming?commentId=X2ARrdmtHTsHQ6dAq) *to correct for that, though I'm no longer sure how to directly compare this situation to March.)*