Coronavirus in Context: Making Sense of All the Data

[MUSIC PLAYING]

Hi, everyone. You're watching Coronavirus in Context. I'm Dr. John Whyte, Chief Medical Officer at WebMD. Are you getting confused by all the numbers, charts, graphs? To really help give a primer in how to understand what's going on, including in your local area, I've asked Dr. F. Perry Wilson, Associate Professor of Medicine at Yale, to join me. Dr. Wilson, thanks for taking time this morning.

Good to be with you again.

There's a lot of numbers out there. There's a lot of graphs. You know, what did you look to in terms of matrices to get a good handle on-- on what's happening with COVID?

Well, there's a couple of things. Obviously, the-- the easiest to wrap your head around is the number of cases, right? The number of people who have tested positive for coronavirus. We've recently exceeded 50,000 cases a day, um, which is a record.

But there's a lot tied up in that. We often wonder whether we're picking up more cases, for example, just because of more testing. So you do want to dig in a little bit more to figure out what's going on.

One of the things that I look at is the percent of tests that come back positive.

This positivity rate that [INAUDIBLE].

F. PERRY WILSON: The positivity rate, exactly.

OK.

If you, uh, increase the number of tests but there's not really any increased disease transmission, then the positivity rate of those tests will go down. On the other hand, if there's more disease transmission, you might see the positivity rate of those tests stay stable or even go up.

And in fact, that is what we're seeing in large parts of the country right now. We're seeing positivity rates rising despite additional tests. And that really tells you that there is increased transmission. Um, finally--

Is there a number that you look at in terms of absolute positivity, meaning just what the number is versus relative? Like, I've seen numbers that have said it should be below 10%. But then I've also seen other numbers that say it should be less than 5%. Or do you simply look at what the trend is?

I think the trend is really important to get a sense of which direction we're moving in with the epidemic. The WHO does say that if you are testing enough, then that number should be less than 10%. And so for example, we had a number of states, uh, like Florida and Arizona, where the testing-- the positivity rate was above 20%. I mean, just a crazy amount, suggesting a lot more testing needs to go on.

The WHO also recommended that your positivity rate should be less than 5% before you have a reopening of society. So we're really not there. But I think the trend is critical to understand how the epidemic is evolving.

Has the accuracy of testing changed? Do we have different tests than we did, say, a month ago?

The main test, uh, the sort of nasal swab tests that people are familiar with-- there are a number of different companies making them. But they've always been relatively accurate when they're positive. We know there's a decent false negative rate, which hasn't changed very much-- which might be due to the fact that it's such a hard test to administer. You really have to dig into the nose a lot there.

So that test hasn't changed too much. But positives really are positive. But we also, of course, have these new antibody tests. And the data there is a lot more mixed.

We're going to come to that. But I also want to talk about, you mentioned a number of cases, the positivity, the number of deaths. And we always talk about, we're 10 to 14 days behind.

But I want to point out a data point that shi-- that says that in the US, for the past 10 weeks COVID deaths have been decreasing to less than 600 a day versus a couple thousand in March. So even if we take into account that 10 to 14 days, how do you factor into that it's been decreasing for 10 weeks?

Well, uh, I think the 10 to 14 day lag in between infection and death is not exactly how to think about this. Because what happens, particularly when you have a discrete event like a reopening-- you know, a date when all of a sudden the restaurants are open-- is you get these rolling waves of infection. So you get a group of people that are infected, you know, kind of initially. And then they, of course, infect more people, and they infect more people.

And so you can think of this almost as a generational thing, where every several weeks you get a successive generation of these infections as the disease spreads. And so the lag might be quite a bit longer than the sort of two-week period that's the average time between infection and death.

The other thing is that the people getting infected now tend to be a bit younger than who were getting infected before. And we know the death rate is lower there, so we might not see as strong a signal. But I will point out that death rates are now rising in Arizona, which was one of the first states to show a significant case-related spike.

So I, I, you know, I think we're going to see those death rates climbing. And that's-- that's bad news.

But this also goes to the fact that one should look at data in their local area. Is that correct? Because much of the data that is presented on the news is national. And it may be different for you in New Haven versus me in Washington versus someone else in New York or Los Angeles. Would you agree with that, that really one should focus on what's happening in their local area, as well as perhaps surrounding counties, um, and cities?

Well, I-- there's a bit of a double-edged sword to that. Um, there can be, uh, a sense that you are in a, a safe space if you're not being reported about on the news, you know? You're not-- you're not Dallas. You're not Florida. And that might lead people to engage in behaviors that-- that aren't as safe, like not social distancing, uh, going to large indoor gatherings and not wearing masks.

But we know there's a lot of transmission that is below the surface here. So I think it is important to know what's going on in your immediate surroundings. It's important to keep your head on a swivel, as we usually say. But not to get a false sense of complacency--

Where do you go to for your data sources?

I go to a lot of different places.

Give us a couple [INAUDIBLE].

Yeah, I mean, so obviously, the-- the Johns Hopkins is-- is the sort of gold standard reporting source, um, which has a great graphical interface, uh, that you can easily find on the web. Um, the COVID tracking project, which collates testing as well as positivity data from every state in the country, uh, which I believe is run by The Atlantic, is really great if you want to get a sense of those test positivity rates. They also show you hospitalization rates and death rates on a state-by-state level. So those are some really good resources.

Let's talk about antibody testing, because when we talked a couple months ago, there was a different perspective on antibody testing. People were thinking we were going to be able to create a shield of immunity based on a test, or, you know, passports, you know, based on antibody status. Where are we today on the concept of antibody testing and its usefulness for an individual?

Antibody testing has been a real trouble spot in this one. Um, just to remind people, antibody testing is-- the idea, the hope is that if you're past the infection-- the infection's over and you confirm that you had it by showing you have these antibodies-- what we've learned recently is that many of these tests have false positive rates. So they'll tell you you, you're, you might be protected when you're not that-- that are, you know, not insignificant.

We also have learned that there's a good number of people who, despite testing positive for antibodies in general, might not have protective antibodies, the kind that can prevent infection. And so no, there's no antibody passports. There's no immunity passports coming anytime soon. What the place for antibody testing is is for surveillance of how the disease is progressing. Um, we need--

For public health officials primarily.

Exactly. Exactly. So-- so public health surveys, you know, as broadly as possible to see, you know, what percent of the population in this very discrete area has been exposed?

Mm-hm.

Because that helps so much in modeling how the disease can spread.

What about if you're just curious? Is it worthwhile to get an antibody test? Is there any harm?

I think there is a harm, to be honest. Um, if, uh-- because there is a false positive rate, you might be falsely reassured. And even if you do have the antibodies, we-- we still, the test does not tell you if they're the protective kind of antibodies or not.

Now, if you had a very classic COVID-like illness-- severe fever and respiratory distress, especially if you have a positive COVID test, a positive nasal swab test-- well, then the antibody test, if it comes back positive, might reassure you that, yes, you really have been through this. But I think for the vast majority of people, um, it's not a good option just to take an antibody test to-- to find out.

Where are we on herd immunity? Um, you know, classically we think it's 70% to be effective. Um, other studies have recently suggested it-- it could be as low as 40% have the same protection. And there's been some preliminary data that shows New York City alone, you know, herd immunity may be, you know, 20%, 25%. So where are we in terms of herd immunity?

Yeah. Um, well it's a-- it's a pretty simple concept to figure out what this target percentage is. Um, to give an example, if every person with COVID infects two other people on average, well then, if 50% of people are immune, then one out of those two other people is immune on average, which means they can only infect one other person and we're-- we're flat, right? So the herd immunity percentage is directly related to how, uh, how much on average someone infects someone else.

And as you point out, we think with COVID, because it's about two to three people that the average person infects, that herd immunity would occur between 50%, 60%, 75%, uh, population. And this is the bad news. We are nowhere close to that. The CDC, uh, seroprevalence data suggests that about 5% of the country has been exposed to coronavirus.

This is way higher than the number of cases we've documented. It's about 10 times higher than the number of cases we've documented. But it's only 1/12 the number of cases we need to think that herd immunity alone will stem the tide of the pandemic. So without taking those other precautions, we're-- you know, we're not even into the second inning of this thing. And of course, there have already been 125,000 deaths.

So in my opinion, you know, waiting for herd immunity to save us is a-- is a-- is a really ineffective approach, a potentially disastrous approach.

I wanna go back to your other point, where you said that, you know, the incidence, the number of cases, may actually be 10 times what is reported. If that's the case, what's your response to the argument if the number of cases is actually 10 times what we think it is, um, but the number of deaths are largely the same-- although, there's some data that recently came out that says it could be an underestimate. What does that say about the lethality, the lethalness of COVID-19? Do we need to rethink that?

Well, I think we've been clear all along that the observed fatality rate is-- is higher. We-- we've always known there are cases that aren't coming to our attention I'll point out that the observed fatality rate in the United States right now is 5%-- which, if that were the true fatality rate of--

It's very high, yes. Yes.

It would be a disaster of kind of, you know, apocalyptic proportions, so. So if it's in fact 0.5%, well, it's still pretty darn lethal, especially compared to the other respiratory viruses we think about, like flu. And of course, you don't need math to tell you that. You can just look at the fact that 125,000 people have died already. We've blown every prior flu season, including the swine flu season, completely out of the water. So this-- this is not benign, regardless of how many, uh, cases have-- have gotten below the surface.

Well, Dr. Wilson, I want to thank you for taking the time today to help us understand all these different numbers. And I hope we can come back to you in another month or so and check in, and see where we are on, uh, COVID-19.

Anytime. I hope we have, uh, some better news in a month.

And thank you for watching Coronavirus in Context.