Krieger: In mid-July we did a version 2, building out state pages to provide two other pieces of information that were key to understanding the picture. We think of these state pages as showing our work. We started adding how many positive cases you are seeing every day, and also added testing volume. As you triangulate those pieces of information you could say, oh, OK, it’s around 1, so it’s neither shrinking nor growing exponentially and the base is small. So net-net I’m less worried than I was in mid-March when R was well over 1, and there were a lot of cases. But we’re not out of the woods yet either.
You also have a tab that’s kind of a time machine that shows what the picture was like at some past dates. Obviously, in March things looked awful, and then went on a course of improvement. But if I hit the little button that says “two months ago,” it’s clear that things now are worse than they were at the beginning of the summer. We’re going backwards!
Systrom: You’re absolutely right—albeit off a smaller base. If we leave it alone, it will grow to the same levels as it was before. A really interesting point is that there are many states where the end of sheltering, which we show, aligns with either the low in the dip or the point when it crosses 1.0 again. Which is to say that stopping the sheltering clearly reaccelerated cases. That is not to say that it was the right or wrong decision—there are economic costs as well. But if you were just considering the rate of growth of the infection, sheltering helped. And removing sheltering didn’t help. And that is clearly shown through those graphs. If you look at Iowa and Minnesota, it’s very clear that the second the shelter stops, everything goes back up again.
It seems obvious that when people aren’t sheltered, the virus is more likely to spread. But it’s still disheartening that we are going in the wrong direction. Do you feel that we’re not learning anything from this? Who is looking at the data and who is acting on it?
Systrom: We are clearly learning what it takes to manage this, meaning what does it take to get R to a value that is manageable such that we don’t overwhelm our health systems. At the same time, there is an economic cost of shutting everything down and keeping people out of work, keeping people out of school. I’m not the right person to ask about what the balance is between the economic cost and the health cost. But I think in some ways we are also normalizing this state. If we jumped back to how we were seeing things in March, I think we’d be horrified about where we are. But since we’ve been in it for a long time, it’s in some way normalized and therefore we normalize the behavior that leads to these curves.
Krieger: The question to ask as we move forward is, if you’re going to have that balance and interplay between sheltering and reopening, how do you track what’s going on so that you don’t overshoot the opening? The combination of R and case count is a really good one to keep your finger on the pulse and understand how that is changing. And then, two, how do you make sure that your response today is better than your response was three months ago.
Systrom: It is really important to point out that there was a time when the federal government said not to wear masks. I remember wearing a mask out to a local shop and getting yelled at for wearing a mask. But that was three months ago. Now you go out and almost everyone is wearing a mask. So we clearly have learned a lot about what does and does not affect transmission and I think we have changed our behavior such that we can be more open economically and still see the declines in cases we’ve seen, say, in California. But don’t forget we are still seeing on the order of like 4,000 to 5,000 new cases per day in California, which sounds small but that adds up pretty quickly. So we are by no means out of the woods.