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Speaker 1: Pushkin from Pushkin Industries. This is Deep Background, the show

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Speaker 1: where we explore the stories behind the stories in the news.

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Speaker 1: I'm Noah Feldman. As the COVID nineteen pandemic continues, antibody

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Speaker 1: tests are gradually becoming increasingly available to ordinary people. You

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Speaker 1: can get one online, and some employers are even requiring

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Speaker 1: that people take them to go back to their jobs.

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Speaker 1: But how accurate are these tests really? And if it

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Speaker 1: turns out that you do have antibodies that show you've

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Speaker 1: been exposed to coronavirus, what does that actually mean about

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Speaker 1: what you should or shouldn't be doing. Next. Here to

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Speaker 1: answer these questions is doctor Alex Marson. He's a biologist

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Speaker 1: and an infectious disease doctor. He's a tenured professor of

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Speaker 1: microbiology and immunology at the University of California in San Francisco,

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Speaker 1: where he's the director of the Gladstone Institute of Genomic

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Speaker 1: Commune Knowledge. Alex, thank you so much for joining me. Alex,

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Speaker 1: your lab ordinarily does high throughput genomic engineering research, which

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Speaker 1: is very cutting it stuff. And then when the COVID

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Speaker 1: nineteen pandemic started, you went to your lab team and

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Speaker 1: you said, okay, we're completely changing course. We're going from

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Speaker 1: the highest tech to relatively lower tech, and we're going

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Speaker 1: to look at the antibody tests that are out there

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Speaker 1: and we're going to see if they work. So, first

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Speaker 1: of all, what gave you the idea to do this?

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Speaker 1: It's a great question, and looking back, it was really

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Speaker 1: it was a confluence of a few things. It was necessity,

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Speaker 1: and it was really in many ways motivated more by

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Speaker 1: the people in my lab, or equally by the people

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Speaker 1: in my lab as it was by me. Our lab

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Speaker 1: was shut down. People weren't able to go in and

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Speaker 1: work on their normal projects, but there was a real

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Speaker 1: feeling in the lab that people had expertise and motivation

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Speaker 1: to try to figure out what they could to be

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Speaker 1: useful in the midst of this pandemic. It was really

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Speaker 1: inspiring for me to see grad students and post docs

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Speaker 1: and technicians who were looking for ways to contribute, and

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Speaker 1: if anything, I was able to help channel and put

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Speaker 1: together collaborations to enable their desire to help out. And

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Speaker 1: so we saw a huge flood into the market of

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Speaker 1: antibody tests that were becoming available. And actually one of

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Speaker 1: the motivations for me was I got a text message

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Speaker 1: from a friend of mine not in science here in

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Speaker 1: the Bay Area, who showed me that she was testing

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Speaker 1: herself for antibodies on one of these home diagnostic kits,

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Speaker 1: And so I started wondering, what are the basic test

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Speaker 1: performance characteristics of these kits? There were so many that

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Speaker 1: were becoming available. We wanted to see could we assign

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Speaker 1: some rough numbers to how reliable these tests actually are?

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Speaker 1: And so that was really the fundamental goal of this

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Speaker 1: study was to say, could we get our hands on

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Speaker 1: as many of these test devices as possible and see

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Speaker 1: what kind of information they actually give and don't keep

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Speaker 1: us in suspensey longer? How were they so? There was

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Speaker 1: a range. They're so polite. This is the boring answer

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Speaker 1: that which was not totally unexpected. Some were reasonably good

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Speaker 1: and some were not going to be very useful in

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Speaker 1: this And one of the major determinants is how specific

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Speaker 1: they are. And especially in a disease like this, where

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Speaker 1: there's in many parts of the world is still relatively

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Speaker 1: low prevalence, the chance of misinterpreting these results due to

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Speaker 1: false positives is very high, and so one of the

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Speaker 1: major things that we wanted to check was are these

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Speaker 1: giving us results that are going to be confused by

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Speaker 1: false positives, perhaps because they're misinterpreting antibio against other viruses,

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Speaker 1: like other common coronaviruses that cause common colds. So we

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Speaker 1: wanted to see, in a population where we know there's

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Speaker 1: no Saris CoV two infection, how many people in that

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Speaker 1: negative population had antibodies on each of these devices, And

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Speaker 1: so this was really, in many ways the meat of

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Speaker 1: this study. We took one hundred and eight blood specimens

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Speaker 1: that had been frozen down well before the pandemic, going

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Speaker 1: back to twenty eighteen and before, and we asked how

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Speaker 1: many of those blood samples showed evidence of antibodies with

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Speaker 1: these commercial tests that were popping up, and we saw

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Speaker 1: a range. Many of them found a lot of evidence

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Speaker 1: of antibodies against saris CoV two in these samples where

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Speaker 1: we know that it shouldn't be there, and so those

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Speaker 1: results are really disabling for a proper interpretation of these tests.

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Speaker 1: If we want to use these antibody tests to measure

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Speaker 1: in a population how many people have actually been infected,

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Speaker 1: they would cloud that picture strongly, and many of the

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Speaker 1: cases detected would actually be false positives. And if we

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Speaker 1: wanted to give an individual patient information. We could give

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Speaker 1: them very misleading information if we gave them false positives

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Speaker 1: and said that they had been infected with stars Cove

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Speaker 1: two when in fact they had it. But I want

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Speaker 1: to caveat that there were a handful that seemed reasonable,

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Speaker 1: and even one test showed one hundred percent specificity, meaning

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Speaker 1: no false positives at all, meaning no false positives in

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Speaker 1: the limited number that we tested. I've been thinking about

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Speaker 1: the fact that in many ways, the way that people

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Speaker 1: responded to our results was a Rorschach test of how

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Speaker 1: they wanted to see these results or how they were

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Speaker 1: predisposed to see these results. And I've been struck by

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Speaker 1: some of the news coverage, which really ranged from saying

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Speaker 1: antibody tests show great promise to these are complete hooks.

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Speaker 1: And my true interpretation is actually somewhere in between that

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Speaker 1: in some ways we got out in front of ourselves

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Speaker 1: where in response to a pandemic, many many suppliers started

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Speaker 1: racing into this market, and it wasn't a total shock

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Speaker 1: to me that we saw arrange. I think what was

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Speaker 1: a bit surprising was that these tests were becoming available

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Speaker 1: to individuals in some cases before this basic information was available,

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Speaker 1: and so we felt like we were just building in

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Speaker 1: that gap. One thing I've been sensing a lot of

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Speaker 1: recently is that as more and more states begin gradual

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Speaker 1: kinds of opening, lots of people are now saying, gee,

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Speaker 1: you know I was sick in March at one point,

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Speaker 1: or I had a long lunch with someone whom I

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Speaker 1: found out later turns out to have had it. Maybe

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Speaker 1: I should look into having an antibody test now. And

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Speaker 1: one question that they asked me, probably because they have

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Speaker 1: heard me talking about your results, is how reliable are

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Speaker 1: these tests now? I don't know what to tell them,

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Speaker 1: So I'm asking you, what would you say under these circumstances.

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Speaker 1: I have companies on the whole taken the lessons of

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Speaker 1: your research and figured out so that more of the

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Speaker 1: tests that are available now are like the better ones

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Speaker 1: that you saw. So there were probably at least one

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Speaker 1: hundred different companies that are offering different tests, and these

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Speaker 1: will pop up in different in different settings. We tested

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Speaker 1: sampling of these. We tested about twelve of these different tests,

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Speaker 1: and we have a website available so that people could

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Speaker 1: compare our results to whatever test information may be becoming available.

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Speaker 1: How would people find that website? What should they be

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Speaker 1: looking for the COVID Testing Project dot org. Now, keep

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Speaker 1: in mind it's a preprint, it has not yet been

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Speaker 1: peer reviewed, and it's a small sample, and so it's

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Speaker 1: not intended to guide any kinds of clinical interpretation, but

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Speaker 1: it provides some basic information. We've been in conversation with

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Speaker 1: a larger testing effort that has now come up as

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Speaker 1: part of a governmental effort. The National Cancer Institute is

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Speaker 1: now doing a large test in concert with the FDA,

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Speaker 1: where FDA is going to be assessing tests for antibodies

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Speaker 1: going forward with the National Cancer Institute. And there's another

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Speaker 1: website on the National Cancer as website and on the

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Speaker 1: FDA website that you can look and find information about

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Speaker 1: commercial tests that are now undergoing evaluation by the FDA.

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Speaker 1: So the short answer is, let the buyer beware. Right,

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Speaker 1: you may not even be able to find reliable information

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Speaker 1: online about whether a given test you're taking is reliable

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Speaker 1: or not. That's true. I think we're starting to see

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Speaker 1: now some of the larger commercial vendors that have traditionally

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Speaker 1: been major suppliers of lab diagnostics entering into this field

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Speaker 1: and playing a bigger role. That these large vendors get

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Speaker 1: into it. There's a hope that there's more consistency and

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Speaker 1: more quantitative information on the levels of antibodies and also

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Speaker 1: on the test performance characteristics. With the rapid diagnostics, not

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Speaker 1: only is there variation among the different vendors, but there's

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Speaker 1: some anecdotal reports that even within something bearing a label

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Speaker 1: of one particular vendor, there may be batch variation, and

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Speaker 1: so the picture is even more clouded with these rapid diagnostics.

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Speaker 1: So the one takeaway there would be, if you really

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Speaker 1: really feel like you have to get the test, send

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Speaker 1: it away. Don't do one of these rapid diagnostic tests

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Speaker 1: at home. If it looks like a pregnancy test, probablesion

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Speaker 1: rely on it. So we've been thinking a lot about

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Speaker 1: this going forward, about what are the possible ways that

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Speaker 1: you could have an efficient testing algorithm. So if someone

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Speaker 1: does a home pregnancy test, what's the first thing they

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Speaker 1: do with that information. If it's a positive, well, they

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Speaker 1: go to their doctor and they get a lab based test.

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Speaker 1: And so maybe there's some opportunity to do something like

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Speaker 1: that where there's a more complex algorithm that could be devised,

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Speaker 1: where there's multiple tests that are used for confirmatory testing,

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Speaker 1: where it's either a combination of home diagnostics or a

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Speaker 1: combination of home diagnostics and lab based to expand the

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Speaker 1: testing infrastructure without sacrificing sensitivity or specificity. That requires some

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Speaker 1: more thought about exactly how that algorithm is designed, but

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Speaker 1: I think these types of test performance numbers are the

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Speaker 1: basic building block that you would use to design an

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Speaker 1: algorithm like that. Going forward, let's talk about what someone

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Speaker 1: could actually do if they did one of these tests

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Speaker 1: it was reasonably reliable and they got a positive. Given

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Speaker 1: the relative uncertainty that's out there, what would it mean

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Speaker 1: for someone who said, well, I've tested positive. If anything.

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Speaker 1: I think that there's really two measurements of what it means.

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Speaker 1: One is how likely is it that it's actually giving

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Speaker 1: reliable information about whether or not you've been infected? And

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Speaker 1: the other implicit question, which I think is what people

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Speaker 1: really care about, is what information is it giving you

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Speaker 1: about how likely you are to get reinfected in the future.

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Speaker 1: And so let me tackle both of those. The first

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Speaker 1: is we are getting to a point where some of

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Speaker 1: these better tests, especially the lab based diagnostics, are starting

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Speaker 1: to give reasonably reliable information about whether or not there

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Speaker 1: are in fact antibodies present in an individual's blood. The

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Speaker 1: second piece is much more complicated, What do we actually

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Speaker 1: hell someone who has a positive antibody test. I think

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Speaker 1: no matter how many times we say in the news

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Speaker 1: that we can't yet tell someone if they have a

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Speaker 1: positive antibody test, they're actually protected from future infection. People

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Speaker 1: have such a strong intuition and desire for antibodies to

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Speaker 1: mean immunity that I'm concerned that there will be an

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Speaker 1: implicit behavioral message that people are safe from prior infection

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Speaker 1: and should take on risks and go into the community

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Speaker 1: and do things that they wouldn't otherwise do without real

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Speaker 1: science to back up to that behavior. So I think

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Speaker 1: right now we're starting the next round as a community

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Speaker 1: of scientific fact finding to start saying how can we

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Speaker 1: advise people about risk of future infection if they do

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Speaker 1: test positive for antibodies. There's really a big range of

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Speaker 1: what infectious disease doctors can come to expect from what

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Speaker 1: antibodies and prior infection mean for the prospects of symptoms

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Speaker 1: and contagion on reinfection, there's a few lines of evidence

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Speaker 1: that we as scientists are really looking for that will

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Speaker 1: firmly tell us that we can give the recommendation to

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Speaker 1: someone that they will be protected. The first are starting

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Speaker 1: to emerge now, and these are animal studies. There have

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Speaker 1: now been a few animal studies, including one published just

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Speaker 1: recently in Science by Dan Baruk's group that looked at

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Speaker 1: Reese's macaques infected with SARS CoV two and then reinfected

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Speaker 1: upon infection, The monkeys developed signs of immunity and reinfection

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Speaker 1: was far less severe. There might be small amounts of

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Speaker 1: virus that actually infected the monkeys, but they seem to

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Speaker 1: clear it relatively and quickly and didn't have signs of

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Speaker 1: infection similar to the first infection, So that's highly promising.

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Speaker 1: How that will translate to humans remains to be seen,

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Speaker 1: and there's two levels of questions. One is will people

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Speaker 1: they be contagious because that's also something people care about.

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Speaker 1: Can you go back to work and not worry about

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Speaker 1: spreading it to more vulnerable people that you also come

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Speaker 1: in contact with, and that will require time. We'll be

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Speaker 1: right back in the monkey studies. Were they able to

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Speaker 1: determine whether they were infectious to others or were they

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Speaker 1: only able to determine how much they showed symptoms or

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Speaker 1: clear the virus. It looked like they were really only

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Speaker 1: able to see evidence of symptoms and quick viral clearance

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Speaker 1: and really pretty limited levels of virus infection, if any.

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Speaker 1: Because that seems hugely significant, right, I mean, if it

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Speaker 1: were to turn out that what was observed in monkeys

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Speaker 1: was also replicated in humans, so that you would get

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Speaker 1: a much milder case the next time around, that would

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Speaker 1: be very reassuring to individuals. But if you had a

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Speaker 1: mild case and we're still infectious to others, we don't

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Speaker 1: want you going back out into public at that point.

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Speaker 1: And we definitely don't want you walking around and thinking

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Speaker 1: that you're effectively immune because you could be as much

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Speaker 1: of a spreader as the next person. Right, So that

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Speaker 1: these data are incredibly important and to my knowledge or

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Speaker 1: not yet available for this particular virus. So the upshot

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Speaker 1: of that for an ordinary person, just to bring it

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Speaker 1: back to the you know, our hypothetical person who's thinking, So,

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Speaker 1: now this person takes a test, it's a send away

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Speaker 1: test from a reliable deliverer. Having done due diligence, our

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Speaker 1: person now thinks that he's been exposed and has antibodies,

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Speaker 1: and he says, Okay, now I'm going to go out

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Speaker 1: and go about my business and interact with people, and

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Speaker 1: the takeaway for that person is not so fast. Yeah,

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Speaker 1: you know this was brought home poignantly to me recently.

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Speaker 1: I had a conversation with a close family friend who

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Speaker 1: called me up and said, should I take an antibody test?

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Speaker 1: I really want to be able to see my grandson?

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Speaker 1: And I said, look, I would love to be able

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Speaker 1: to tell you that a positive antibody test could safely

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Speaker 1: mean this, that you could you would be protected, but

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Speaker 1: we don't yet have that information. I so deeply understand

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Speaker 1: the yearning to have that level of security, but trained

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Speaker 1: as a doctor, I don't feel that I yet have

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Speaker 1: enough information and to say that the test result would

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Speaker 1: allow me to actually recommend that you'd be safe to

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Speaker 1: go and change your behavior in any way that you

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Speaker 1: wouldn't otherwise. And although it's hard to put numbers on

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Speaker 1: these things, how confident would you have to be? I mean,

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Speaker 1: I understand that as a physician, you want to be cautious, right.

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Speaker 1: You don't want to say to somebody you know what,

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Speaker 1: you'll be fine and then have it turn out to

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Speaker 1: be the case that they're in some small tale of

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Speaker 1: the data where they actually were still able to get

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Speaker 1: it again or to give it again. But how confident

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Speaker 1: would you have to be to say to somebody, yeah,

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Speaker 1: you know what on the whole once you've had the

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Speaker 1: positive antibody test, this is basically almost certainly going to

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Speaker 1: be all right. Though I'm making you no promises. I

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Speaker 1: would like to see the human data. So I just

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Speaker 1: told you in detail about the experiment in the monkey model.

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Speaker 1: I think that we really need some basic information from humans. Now.

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Speaker 1: Some people have been advocating strongly for actually doing what

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Speaker 1: I just told you was done to the monkeys, to

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Speaker 1: actually doing that in humans, and there's been a group

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Speaker 1: of scientists that have signed letters talking about advocating for

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Speaker 1: human trials of actually active infection. Now, this has been

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Speaker 1: done for other coronaviruses in the past, the kind that

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Speaker 1: caused common colds, and for something that causes mild symptoms

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Speaker 1: like a common cold, that may be an acceptable risk.

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Speaker 1: The question is would it be an acceptable risk here,

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Speaker 1: perhaps in a young, healthy individual. I would advocate that

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Speaker 1: that's not necessary and perhaps not ethical. In this case.

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Speaker 1: I think that there's still high enough rates of transmission

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Speaker 1: that well designed studies and high risk individuals should be

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Speaker 1: able to give us this information, not quite as rapidly,

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Speaker 1: but rapidly enough that we can interpret them. So I

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Speaker 1: think what we really need is a carefully designed epidemiological

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Speaker 1: study that aggregates all the data from everyone who's had

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Speaker 1: antibody testing and watches them carefully over time, especially in

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Speaker 1: situations where they'd be high risk if they're healthcare workers

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Speaker 1: and high incidence regions, and ask the question very carefully

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Speaker 1: and numerically, what degree of protection do we actually see

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Speaker 1: in the people who have antibodies? Do they get infected

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Speaker 1: and do they spread to their context? Are we moving

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Speaker 1: in a direction where we're going to have to rely

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Speaker 1: on two kinds of tests simultaneously, where we're going to

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Speaker 1: have to rely both on swab testing of whether people

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Speaker 1: have the virus in real time and also on an

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Speaker 1: antibody test. Or are we heading for a world where

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Speaker 1: one of these will predominate over the other. I strongly

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Speaker 1: believe that we need both, and we need to be

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Speaker 1: very clear about what information we'll get from each of

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Speaker 1: those types of tests. The virus testing is the gold

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Speaker 1: standard for seeing who is infected with this virus SARS

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Speaker 1: CoV two, and that is what happens when people get

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Speaker 1: the nose or throat swab. Increasingly this is moving to

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Speaker 1: saliva testing, which I think is very promising and perhaps

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Speaker 1: more scalable. Those are looking for the presence of the

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Speaker 1: virus itself inside of an individual. After about a week

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Speaker 1: on average, we start to see the evidence of the

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Speaker 1: virus itself will wane, and by about two weeks or

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Speaker 1: three weeks with some variability, we'll see that people who

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Speaker 1: have been infected will start to produce antibodies against the

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Speaker 1: stars covi two and that's where we'll be able to

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Speaker 1: detect the presence of antibodies, and those will stay up

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Speaker 1: for some period of time, although the exact period of

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Speaker 1: how long they'll be detectable we still don't know. We

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Speaker 1: have to trace that out farther. But by looking at

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Speaker 1: both of those, we'll get information both about early infection

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Speaker 1: and later information about who had been infected in the past.

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Speaker 1: And if we want to accurately put together measurements of

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Speaker 1: prevalence across a population, transmission dynamics, mortality, we really need

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Speaker 1: information from both of those, and likewise, for back to work,

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Speaker 1: we also need information from both of those. We've talked

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Speaker 1: a lot now about will the antibody testing help us

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Speaker 1: determine who's safe to go back to work, and we've

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Speaker 1: talked about the pieces of knowledge that we still need

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Speaker 1: about immunity which will start to guide whether antibody tests

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Speaker 1: can tell us whether some people are safe to go

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Speaker 1: back to work. But virus testing itself is also important

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Speaker 1: for knowing who it goes back to work. One of

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Speaker 1: the key things that we know about transmission of this

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Speaker 1: virus is that it often occurs from asymptomatic individuals before

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Speaker 1: or they even know that they have symptoms, or even

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Speaker 1: some people who may never go on to have symptoms.

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Speaker 1: And the only way that we could really tell whether

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Speaker 1: people are infectious is if we screen for the presence

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Speaker 1: of the virus itself. Now this may sound unusual, but

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Speaker 1: there was an article in stat News recently about a

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Speaker 1: model for this from the adult film industry. It's almost

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Speaker 1: too good, yes go on. In response to the HIV

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Speaker 1: epidemic in a group of very high risk workers, there

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Speaker 1: had to be a model for how to figure out

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Speaker 1: how to pe get people back to work with relative safety,

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Speaker 1: because most HIV testing that done is actually based on

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Speaker 1: antibodies against HIV, but those come up relatively late. Again,

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Speaker 1: they don't come up in the earliest acute phases of

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Speaker 1: infection for HIV, they wouldn't come up for the earliest

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Speaker 1: phases of SARS CoV two. So that means that there

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Speaker 1: would be an individuals who could be acutely infected with

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Speaker 1: HIV who would be infectious before they would be detectable

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Speaker 1: with an antibody. And so the adult film industry has

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Speaker 1: come up with a very aggressive testing strategy that depends

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Speaker 1: not on the antibody tests used for most individuals, but

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Speaker 1: on actual viral testing that would sensitively detect the presence

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Speaker 1: of virus at earlier time points. And individuals have to

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Speaker 1: get tested at very regular intervals to be cleared to

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Speaker 1: go back to work. On the set of an adult

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Speaker 1: film industry, I think it's every fourteen days they have

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Speaker 1: to get clear to go back to work. And there's

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Speaker 1: a whole infrastructure set up with thought about privacy and

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Speaker 1: also coming up with a plan for how individuals would

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Speaker 1: get treated if they were to test positive, and also

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Speaker 1: how contact tracing would be done to identify people that

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Speaker 1: have been exposed. And so all this has been actually

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Speaker 1: carefully thought about in one industry where there's a high

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Speaker 1: risk of viral infection. Now, as a result of this pandemic,

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Speaker 1: all industries are at high risk of infection as people

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Speaker 1: go back to work, and I think we have to

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Speaker 1: give some similar thought. I don't mean to over extend

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Speaker 1: this analogy. HIV is a chronic virus, sarrys. CoV two

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Speaker 1: is not is something that will get cleared, and so

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Speaker 1: the dynamics are quite different. But I think we have

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Speaker 1: to think about how can we detect early cases, asymptomatic

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Speaker 1: cases and have infrastructure in place to make sure that

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Speaker 1: positive cases get treated and traced, to limit the spread

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Speaker 1: of infection and to limit mortality and morbidity. The idea

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Speaker 1: that we could borrow a protocol from the adult film

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Speaker 1: industry is its delicious and it would certainly be fascinating

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Speaker 1: if that ended up being being applied more broadly. Can

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Speaker 1: I see a totally outside the box quirky question that

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Speaker 1: I've noticed in talking to different people, I've noticed that

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Speaker 1: serious scientists all say stars CoV two, and they almost

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Speaker 1: never say COVID nineteen. Why it seems to me like

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Speaker 1: a little insider outsider code. I've actually realized this recently

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Speaker 1: talking to some people that this is confusing. I think

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Speaker 1: the simplest way to explain this is by analogy to

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Speaker 1: HIV and AIDS. AIDS is the disease caused by HIV

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Speaker 1: and STARS. CoV two is the virus that causes COVID

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00:22:29,436 --> 00:22:32,276
Speaker 1: nineteen the disease, And so when we're really talking about

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Speaker 1: the mechanics of infection, scientists will gravitate to talking about

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Speaker 1: the name of the virus rather than the syndrome that

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Speaker 1: it causes, since there's a wide range of outcomes of

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Speaker 1: what the virus may actually do, and so COVID nineteen

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00:22:45,316 --> 00:22:47,156
Speaker 1: is actually just the name of the syndrome. So it's

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Speaker 1: the person is suffering from COVID nineteen having been infected

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Speaker 1: with the stars CoV two exactly. And I think that

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00:22:53,116 --> 00:22:57,756
Speaker 1: actually has been a genuine source of confusion. When will

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Speaker 1: your lab be able to be up and running and

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00:22:59,676 --> 00:23:04,836
Speaker 1: doing its ordinary but not normal science. We have started

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00:23:04,996 --> 00:23:10,036
Speaker 1: going back to work now at a drastically reduced capacity.

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Speaker 1: One eighth of the lab is able to work now,

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Speaker 1: and we're able that people are going in with masks

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Speaker 1: and keeping their distance from each other and working in isolation.

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Speaker 1: To start returning to their long term projects. I again

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00:23:25,396 --> 00:23:29,436
Speaker 1: was inspired during this period until this where people were

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Speaker 1: so excited to have a chance to do the science

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Speaker 1: that they're passionate about, even if it wasn't their actual

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Speaker 1: PhD project, to be able to take the underlying skills

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Speaker 1: that they're cultivating and apply them, and people express real

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Speaker 1: gratitude to have the ability to work on stars copy

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00:23:45,756 --> 00:23:49,996
Speaker 1: two testing, COVID nineteen testing during this epidemic. And so

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Speaker 1: we're continuing some of this but also transitioning back to

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Speaker 1: the more long term science that we've been focused on

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Speaker 1: on crispergino engineering of human immune cells to try to

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Speaker 1: think about treating a wide range of human diseases. And

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Speaker 1: I think people are also glad to be continuing to

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Speaker 1: work on this pandemic, but think broadly about how they

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Speaker 1: can make contributions to human health even beyond that too. Well,

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Speaker 1: let me take the opportunity to thank your lab members

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00:24:18,076 --> 00:24:20,996
Speaker 1: and you for the contribution you've made on czars Cove two,

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Speaker 1: but also for the work you're doing all the time,

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00:24:23,916 --> 00:24:26,436
Speaker 1: and to wish you guys a good opportunity to get

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Speaker 1: back into the lab at more than one eighth and

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Speaker 1: go back to continuing to try to make the world

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Speaker 1: a little bit of a better place. Thank you very much,

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Speaker 1: Alex for your time. I walked away from my conversation

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Speaker 1: with Alex with a kind of mixed picture of developments

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Speaker 1: in the antibody testing space. On the one hand, I

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Speaker 1: heard some measured optimism from Alex that the originally not

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Speaker 1: that impressive tests that he discovered when he and his

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Speaker 1: lab went to measure the effectiveness of the antibody tests

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Speaker 1: at first are starting to get a little bit better,

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Speaker 1: especially those that are send away laboratory tests. That said,

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Speaker 1: despite this progress, Alex thinks it is still not soon

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Speaker 1: enough to tell people that once they have those antibodies

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Speaker 1: that they can go around treating life as normal, because

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Speaker 1: we still do not know what degree of immunity, if any,

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Speaker 1: is being conferred by the antibodies. For that will need

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Speaker 1: more time and more research. Alex also points out that

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Speaker 1: going forward, to get people back to work and get

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Speaker 1: the world open, we're going to need much more testing,

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Speaker 1: both testing of people who currently have the virus and

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Speaker 1: also antibody testing. So more tests remain a crucial desideratum

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Speaker 1: for reopening the economy, and last and definitely not least

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Speaker 1: Alex suggested that we may actually already have an available

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Speaker 1: model from industry that helps us know how to get

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Speaker 1: people back to work, the model of the HIV testing

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Speaker 1: protocols put in place by the adult film industry. If

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Speaker 1: it turns out that the adult film industry has something

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Speaker 1: significant to contribute to getting people back to work, that

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Speaker 1: will be one of the great surprises. Let us just

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Speaker 1: say of this entire strange COVID nineteen pandec and although

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Speaker 1: this may sound a little different immediately following a conversation

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Speaker 1: of adult films, until the next time I speak to you,

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00:26:19,636 --> 00:26:23,956
Speaker 1: be careful, be safe, and be well. Deep background is

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Speaker 1: brought to you by Pushkin Industries. Our producer is Lydia

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00:26:27,236 --> 00:26:30,676
Speaker 1: gene Cott, with research help from zooe Win and mastering

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00:26:30,676 --> 00:26:35,196
Speaker 1: by Jason Gambrel and Martin Gonzalez. Our showrunner is Sophie mckibbn.

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00:26:35,716 --> 00:26:39,036
Speaker 1: Our theme music is composed by Luis Guerra. Special thanks

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00:26:39,036 --> 00:26:42,756
Speaker 1: to the Pushkin Brass, Malcolm Gladwell, Jacob Weisberg, and Mia Loebell.

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00:26:43,436 --> 00:26:46,396
Speaker 1: I'm Noah Feldman. I also write a regular column for

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Speaker 1: Bloomberg Opinion, which you can find at Bloomberg dot com.

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00:26:49,916 --> 00:26:54,236
Speaker 1: Slash Feldman. To discover Bloomberg's original slate of podcasts, go

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00:26:54,316 --> 00:26:58,516
Speaker 1: to bloomberg dot com slash podcasts. And one last thing.

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Speaker 1: I just wrote a book called The Arab Winter, A Tragedy.

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Speaker 1: I would be delighted if you checked it out. You

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00:27:04,436 --> 00:27:06,076
Speaker 1: can always let me know what you think on Twitter

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00:27:06,316 --> 00:27:09,316
Speaker 1: about this episode, or the book or anything else. My

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00:27:09,396 --> 00:27:12,996
Speaker 1: handle is Noah R. Feldman. This is deep background