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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. Today we have a return guest, and

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Speaker 1: in fact, he may be the most important guest that

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Speaker 1: we've had this year. It's Mark Lipsitch, whom I spoke

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Speaker 1: to first back in February. He's professor of epidemiology at

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Speaker 1: the Harvard chance School of Public Health. He's director of

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Speaker 1: the Center for Communicable Disease Dynamics there then. He was

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Speaker 1: then and has continued to be one of these central

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Speaker 1: voices in sounding the warning about COVID nineteen and in

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Speaker 1: modeling what good responses look like and figuring out what's

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Speaker 1: going to happen next. With the election coming and the

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Speaker 1: possibility of vaccines on the horizon, I wanted to reconnect

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Speaker 1: with Mark to see how he reads the current situation. Mark,

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Speaker 1: thank you so much for being here. I feel like

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Speaker 1: I've lived a lifetime since we spoke in February when

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Speaker 1: you were in an early warning mode. But I bet

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Speaker 1: you've lived ten or one hundred lifetimes since then. How

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Speaker 1: you've slept is hard for me to even imagine. Let

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Speaker 1: me start by just asking you how are you holding

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Speaker 1: up in this process? Doing okay? It's frustrating to be

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Speaker 1: watching governments, including our own national government, ignoring very clear science,

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Speaker 1: and as we now know, deliberately ignoring it from the

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Speaker 1: very earliest times. It's encouraging that our local and state

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Speaker 1: government are trying much harder to do good things. And

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Speaker 1: there's still a huge amount of uncertainty about what the

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Speaker 1: best approaches given all the trade offs, and so that's

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Speaker 1: what keeps me awake at night right now. There is

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Speaker 1: an enormous amount of uncertainty. But one thing that's sort

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Speaker 1: of remarkable is that a paper that you published with

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Speaker 1: co authors described a model, or of models, of what

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Speaker 1: might happen if we had intermittent shutdowns and reopenings, And

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Speaker 1: to oversimplify it vastly, you showed a kind of sign curve,

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Speaker 1: a kind of up and down curve of how things

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Speaker 1: would go. And sure enough, we had the first loop

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Speaker 1: up of that curve, then we had a decline, then

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Speaker 1: we had reopenings, and now we're on our way back up.

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Speaker 1: So to the extent anything in real life ever matches

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Speaker 1: a model, we seem to be matching, at least so

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Speaker 1: far early stage. The model that you designed. How do

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Speaker 1: you think about that? I mean, do you think that,

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Speaker 1: in fact, that model so far does seem to be

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Speaker 1: fitting the data. When we published that model and Science

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Speaker 1: in March, we stated clearly that it was neither a

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Speaker 1: prediction nor an endorsement, but a description of what might

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Speaker 1: happen and what the consequences might be. And it wasn't

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Speaker 1: an endorsement because it's obviously a miserable process, and it

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Speaker 1: wasn't a prediction because we didn't know how people and

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Speaker 1: governments would risk. And I think it turned out to

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Speaker 1: be a little more true than we really expected in

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Speaker 1: some respects in the general pattern. I think what's less

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Speaker 1: true is that we imagined in that model, or we've

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Speaker 1: made an assumption in that model that each round of

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Speaker 1: control measures would be sort of similar to the previous

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Speaker 1: round in terms of its level of effect. But I

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Speaker 1: think what we didn't factor in was fatigue and the

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Speaker 1: sense that politically and psychologically the same level of control

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Speaker 1: measures doesn't seem to be feasible in many places. That

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Speaker 1: was feasible the first time people were up for one

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Speaker 1: one very intense lockdown in some places, and maybe not

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Speaker 1: too many more. The logical implication of what you just said, Mark,

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Speaker 1: sounds like that there's a real possibility that we're not

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Speaker 1: just headed up for another peak roughly at the point

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Speaker 1: where the peak was last time in terms of number

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Speaker 1: of cases, but that we're actually headed for a potentially

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Speaker 1: substantially higher peak. I think the potential is there. I mean,

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Speaker 1: the population remains largely uninfected and still susceptible. There are

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Speaker 1: pockets that have experienced very intense infection, but much of

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Speaker 1: the country and much of the world remains uninfected, and

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Speaker 1: so at a population level, we're kind of not that

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Speaker 1: much more protected than we were at the beginning of this,

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Speaker 1: and so I think it will be more There will

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Speaker 1: be peaks in more different places at roughly the same time,

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Speaker 1: because the virus has had time to spread out geographically,

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Speaker 1: so it's not mainly in urban centers in the US anymore.

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Speaker 1: It's now in the Midwest and the plains, in parts

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Speaker 1: of the country that are much more rural, and it's

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Speaker 1: just more widespread outside the major ports of entry and

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Speaker 1: places connected to those. So I think it will be

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Speaker 1: more widespread, very likely. But how high a peak we

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Speaker 1: have really depends on the timing and strength of our reaction,

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Speaker 1: and that is so uncoordinated in this country and also

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Speaker 1: between countries, that it's hard to make a general prediction.

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Speaker 1: Deaths are trending obviously in the wrong direction, though they

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Speaker 1: seem to be less as a percentage of all cases

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Speaker 1: than they were previously. Is that because of better treatments?

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Speaker 1: Is it because of a broader awareness of the number

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Speaker 1: of people who have diseases? Ie? More testing the President's

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Speaker 1: favorite line, why the disparity? I think it's very clear

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Speaker 1: that there's more testing and that we're detecting a higher

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Speaker 1: fraction of all the people who are infected with this

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Speaker 1: virus than we were at the beginning. Still a very

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Speaker 1: low fraction, but more, and therefore the denominator swells and

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Speaker 1: the ratio of deaths to known cases goes down. The

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Speaker 1: really interesting question is how much better we're getting at

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Speaker 1: treating those cases that do occur. And there have been

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Speaker 1: a couple of articles relatively limited populations and imperfect methodology,

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Speaker 1: as it always is in this kind of situation, that

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Speaker 1: suggests that when people get to the hospital or get

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Speaker 1: to the ICU, they are more likely to survive, which

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Speaker 1: you would expect given that clinicians learn all sorts of things,

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Speaker 1: not just what drugs they can use, and there's sort

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Speaker 1: of one and a quarter good drugs right now that

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Speaker 1: are available, but also other details of the clinical management

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Speaker 1: that make it more likely that the hundredth patient will

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Speaker 1: survive than that the first one that someone has seen survives.

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Speaker 1: So every expectation is that the death rate of those

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Speaker 1: people who get severe disease would be going down. The

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Speaker 1: data have been very limited so far, two papers that

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Speaker 1: I'm aware of, and some data from Florida that I've

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Speaker 1: seen that maybe suggests the opposite that there isn't a change.

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Speaker 1: So I think it's too early to declare victory, and

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Speaker 1: certainly there are still a lot of people dying per case,

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Speaker 1: but I think there's some hints that we're getting better.

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Speaker 1: It's an absence of evidence mostly right now, and that

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Speaker 1: will be an important question to figure out going forward.

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Speaker 1: I'm almost loath to ask you about the so called

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Speaker 1: Great Bearington Declaration because I know that your view is

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Speaker 1: that it was false and problematic, and you've joined a

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Speaker 1: counter declaration, but it's been so much in the news

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Speaker 1: that we can't completely avoid it. What's wrong with the

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Speaker 1: so called Great Bearington Declaration and the perspective that it takes.

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Speaker 1: I think the Great Barrington Declaration starts from a premise

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Speaker 1: that most of us would agree with, which is that

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Speaker 1: the current state of response is miserable in that it's

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Speaker 1: depriving us of many features of our lives. It's causing

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Speaker 1: unemployment and other harms to humans, and it's no fun

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Speaker 1: at all, and even the details are no fun. Wearing

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Speaker 1: a mask is not pleasant, and everyone wants to get

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Speaker 1: back to normal. The part of it that is insidious,

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Speaker 1: in my view, is not the desire to get back

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Speaker 1: to normal, but the notion that that is consistent with

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Speaker 1: some kind of way of protecting the vulnerable. And there's

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Speaker 1: just no evidence that that is possible. There's no place

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Speaker 1: that I'm aware of that has successfully let the epidemic

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Speaker 1: spread and at the same time protected the vulnerable. Sweden

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Speaker 1: is the sort of most famous example, and they nobody

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Speaker 1: thinks that they did a good job of protecting their

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Speaker 1: nursing homes and the vulnerable people that are less often

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Speaker 1: discussed are immigrants and members of ethnic minorities and racial

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Speaker 1: minorities in this country and in Sweden. Many of the

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Speaker 1: early cases and severe cases were in Somali immigrants and

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Speaker 1: in other less integrated communities. And so when you say

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Speaker 1: protect the vulnerable, people imagine that you can just sort

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Speaker 1: of seal off nursing homes, which is problematic and probably

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Speaker 1: not effective in itself. But the vulnerable is a larger

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Speaker 1: group than just the very old and infirm. It's a

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Speaker 1: mixed group, some of whom we know about and some

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Speaker 1: of whom we don't. So the notion that we can

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Speaker 1: stop transmission to those who are most at risk, first

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Speaker 1: that we can identify them, which is imperfect, and second

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Speaker 1: that we can somehow wall them off from society, which

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Speaker 1: has just not been demonstrated. So as a claim by

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Speaker 1: a group of scientists, this seems to be a lot

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Speaker 1: of aspiration and very little scientific description of how it

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Speaker 1: would be done. You joined a very detailed counter declaration.

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Speaker 1: You're one of the first people to join it. It's

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Speaker 1: now got thousands and thousands of scientists who also joined it.

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Speaker 1: Was what you just said. The essential takeaway for you

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Speaker 1: of that documentary? Does it go beyond Yeah? I think

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Speaker 1: that's why I signed the document. And it's impossible to

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Speaker 1: speak for all the people who signed a document, of course,

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Speaker 1: but in my view, there's a shared desire to get

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Speaker 1: back to some kind of normal and a responsibility if

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Speaker 1: you propose a way to do that, to propose a

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Speaker 1: way that is effective and for which there's evidence. I

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Speaker 1: think what's the next step for those of us who

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Speaker 1: don't think that that's an effective approach, is that we

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Speaker 1: need to figure out how to do it by some

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Speaker 1: other means. And I think the best evidence right now

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Speaker 1: is that a combination of very widespread mask use and

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Speaker 1: consistent mask use, really insisting on social distancing when encountering

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Speaker 1: other people, and increasingly making available cheap and frequent tests

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Speaker 1: so that people can understand their status is in my view,

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Speaker 1: the best combination of measures that will keep things at

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Speaker 1: bay while we search for vaccines and therapeutics. So I

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Speaker 1: think that's the next step is to figure out an

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Speaker 1: alternative plan. But in the meanwhile, we have these blunt

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Speaker 1: instruments of shutting down parts of the economy, which in

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Speaker 1: some cases are necessary in order to slow things down

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Speaker 1: and maintain the integrity of the healthcare system. I want

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Speaker 1: to ask you about both stages of this alternative and

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Speaker 1: that you're describing, and I guess my first one is

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Speaker 1: to ask how alternative it really is. I mean the

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Speaker 1: mask use has been part of the approach thus far,

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Speaker 1: that insisting on social distancing has been part of the approach.

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Speaker 1: They have some limit to how much they're going to

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Speaker 1: be followed. I mean, my kids are in school a

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Speaker 1: couple of days a week, and they report great efforts

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Speaker 1: to adhere to social distancing and mask wearing. But let's

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Speaker 1: say imperfect enforcement and imperfect efforts also by kids. And

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Speaker 1: I can anecdotally report the same of my world, you know,

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Speaker 1: in social interactions. As long as it was warm out,

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Speaker 1: that was a real effort to always be outside and

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Speaker 1: to maintain social distancing. But there's erosion around the edges

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Speaker 1: on that, and so I'm wondering whether that step, that

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Speaker 1: component is different and also if it's practically in the

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Speaker 1: real world sustainable at scale. Well, I think that is

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Speaker 1: a fair question. And the Swiss Cheese image that's been

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Speaker 1: making the rounds of every intervention being imperfect and together

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Speaker 1: you make an impermeable barrier with a lot of holes

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Speaker 1: in each layer is an appealing one because all of

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Speaker 1: these things are both not perfectly effective and not perfectly practical.

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Speaker 1: But having said that, Massachusetts, where you're describing, is on

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Speaker 1: a global scale doing pretty well, and the hospitals are

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Speaker 1: not overwhelmed right now, and that's to a large degree

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Speaker 1: because of both early shutdowns a part of the economy,

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Speaker 1: and then relatively adherent population to those social distancing norms.

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Speaker 1: So I think while cases are rising here as they

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Speaker 1: are almost everywhere, it is important to say that places

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Speaker 1: that have embraced masks and social distancing have on the

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Speaker 1: hole done better than places that haven't. And within the

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Speaker 1: US there's a lot of variation, and of course there

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Speaker 1: are a lot of other factors, and you can argue

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Speaker 1: about the causal relationship, but there are large variations and

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Speaker 1: how much people use masks and large variations and how

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Speaker 1: bad the epidemic has gotten. We'll be right back. Let's

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Speaker 1: talk about a world where we have vaccines, but imperfect

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Speaker 1: vaccines that in any case take a while to roll

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Speaker 1: out and get to reach everybody. But imagine we have

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Speaker 1: some vaccines that work at fifty percent efficacy or above,

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Speaker 1: Leaving aside the technical problem of how long it will

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Speaker 1: take to get them to people, how effective in a

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Speaker 1: process of moving US towards group immunity is it to

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Speaker 1: have a say, fifty percent efficacious vaccine that some percentage

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Speaker 1: of the population is taking How much does that speed

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Speaker 1: up our process or does it actually not make that

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Speaker 1: much difference? But we have to maintain mask wearing, social distancing,

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Speaker 1: and some business closures regardless. If a large faction of

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Speaker 1: the population took fifty percent efficacious vaccine, and that vaccine

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Speaker 1: was efficacious against infection and transmission as well as against symptoms,

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Speaker 1: it would make a huge difference. It would not stop

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Speaker 1: transmission by itself, because we have to get the reproduction

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Speaker 1: number down from probably three or so down to below

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Speaker 1: one in order to stop transmission, and this would be

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Speaker 1: at best a fifty percent hit even if everybody took it,

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Speaker 1: but down to one and a half would mean that

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Speaker 1: even uncontrolled, it would grow more slowly. There would be

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Speaker 1: more time to make control measures. There would be greater

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Speaker 1: effects of things like mask wearing and the less burdensome

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Speaker 1: interventions because you could layer fewer interventions on top and

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Speaker 1: then keep the virus under control. So fifty percent infection

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Speaker 1: blocking vaccine would be obviously worse than a eighty percent,

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Speaker 1: but a lot better than what we have now. Isn't

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Speaker 1: there a dynamic game theory problem, though, which is if

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Speaker 1: vaccine were out there, and if people thought that it worked,

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Speaker 1: that would probably lead many people to be less careful

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Speaker 1: with masks and social distancing. I mean, it's going to

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Speaker 1: be hard to say to people, here's your vaccine, it

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Speaker 1: works somewhat well, but keep on everything you're doing and

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Speaker 1: don't really change your lives that much. I think that's

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Speaker 1: a concern. But I also think that we would be

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Speaker 1: able to get away with a lot less adherence to

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Speaker 1: mask wearing and all those other things if half the

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Speaker 1: population were protected by the vaccine, and if some of

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Speaker 1: the people who weren't protected against infection perhaps were at

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Speaker 1: least protected against severe disease. So I mean, unfortunately, this

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Speaker 1: is a problem that we're trying to solve on a

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Speaker 1: time frame of a year or two, when this kind

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Speaker 1: of problem is typically solved over a time scale of decades.

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Speaker 1: So we're going to be chipping away with a lot

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Speaker 1: of imperfect solutions. But I think even a modestly effective vaccine,

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Speaker 1: if it blocks transmission, will make a huge difference, or

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Speaker 1: if it works in the most vulnerable people, either of

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Speaker 1: those would vastly improve our lives. Once it's distributed. It

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Speaker 1: won't solve all the problems we can't know this for sure, obviously,

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Speaker 1: but it does strike me that among people who will

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Speaker 1: be skeptical of a vaccine, it won't want to take it.

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Speaker 1: The idea that a vaccine only works roughly half the

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Speaker 1: time might be used by critics and skeptics as a

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Speaker 1: reason not to take the vaccine. Yeah. Well, I think

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Speaker 1: that's been true for flu vaccines for a long time,

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Speaker 1: and flu vaccine uptake is not great, although it's better

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Speaker 1: this year, I think because people are nervous about getting

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Speaker 1: something that would get them in contact with the healthcare system.

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Speaker 1: But yes, a better vaccine would be better in many ways,

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Speaker 1: including in public confidence, so we can hope for that.

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Speaker 1: But the fifty percent floor that's been set by the

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Speaker 1: FDA is not the desired level. It's the minimal level.

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Speaker 1: My takeaway from what you've been saying, though, is that

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Speaker 1: if indeed we get a vaccine, even if it's pretty

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Speaker 1: effective and reaches many many people, we're not in a

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Speaker 1: scenario where things will be quote unquote back to normal

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Speaker 1: anytime soon, including at the moment when many many people

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Speaker 1: begin to get the vaccine, which just by a some shit,

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Speaker 1: let's imagine, would be the fall of twenty twenty one,

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Speaker 1: which seems to be the soonest that you could get

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Speaker 1: very very broad uptake. It sounds like we're going to

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Speaker 1: be continuing with some hybrid version of our social distancing

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Speaker 1: and masking. Well beyond that, am I reading you right?

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Speaker 1: I think if it's eighty or ninety percent effective and

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Speaker 1: widely accepted, then we might be back to something approaching normalcy.

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Speaker 1: I also think that we will learn other things in

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Speaker 1: the process. I mean, I think the evidence is accumulating

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Speaker 1: that schools are, if they take basic precautions, not sites

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Speaker 1: of major transmission. They may be sites where people who

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Speaker 1: are infected get together because they've been infected in the

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Speaker 1: community and it looks like their outbreaks. But the frequency

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Speaker 1: of outbreaks in schools with reasonable is low, not zero,

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Speaker 1: but low. So I think that aspect of our society,

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Speaker 1: as we learn more about how to do it safely

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Speaker 1: and keep some level of normalcy, might get back to

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Speaker 1: normal along the way, And that will be boosted by

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Speaker 1: the fact that at least the adults initially will be

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Speaker 1: protected if we have a vaccine. So I think that's

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Speaker 1: an example. But other aspects of our society, we hopefully

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Speaker 1: will learn something about how we can operate them more safely.

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Speaker 1: So I think we shouldn't assume that our knowledge is

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Speaker 1: going to be stuck here. And one of the things

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Speaker 1: that's been really disappointing is as the CDC and to

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Speaker 1: some extent other public health authorities in other countries, but

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Speaker 1: especially the CDC, has been hobbled by interference from above.

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Speaker 1: One of their functions would normally be to very actively

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Speaker 1: be seeking epidemiological evidence on what is safe and what

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Speaker 1: is not safe, and that part of their function has

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Speaker 1: been very limited in this epidemic. So I think we

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Speaker 1: will keep learning things, and I'm somewhat optimistic in that

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Speaker 1: sense that we will as we chip away at the problem,

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Speaker 1: we will find ourselves getting closer to normal. But it's

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Speaker 1: not going to be quick and it's not going to

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Speaker 1: be complete. I agree with that. Are there any country

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Speaker 1: models that are positive models from your perspective still at

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Speaker 1: this moment? I think the models of Germany and Luxembourg

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Speaker 1: and probably some other countries like them, which had big

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Speaker 1: surges at the beginning, got them under control and now

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Speaker 1: have very widespread testing. Still not universal, but Luxembourg has

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Speaker 1: actually tested most of its population at least once, which

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Speaker 1: is a step in the direction of widespread, easily available

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Speaker 1: testing for anybody who's curious whether they're infected. Those are positive,

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Speaker 1: but of course they're also both going up in the

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Speaker 1: number of cases, so it's not a full solution. And

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Speaker 1: then of course New Zealand and Vietnam and some others

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Speaker 1: have had much better outcomes than we and those are

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Speaker 1: two different situations. One we don't really understand what's exactly

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Speaker 1: happened in Vietnam, and with New Zealand it was very

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Speaker 1: very early both lockdown and extremely good contact tracing on

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Speaker 1: an island. So and then thinking about Korea, you know,

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Speaker 1: there was a very very large outbreak and it was

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Speaker 1: brought down through very intense surveillance, test and trace and

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Speaker 1: the like, with some degree of lockdowns, but probably a

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Speaker 1: level of surveillance that is not replicable here. What has

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Speaker 1: happened to surveillance here. At the beginning of the outbreak,

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Speaker 1: there was an enormous amount of discussion in the public

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Speaker 1: square and also in policy circles about contact tracing, and

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Speaker 1: we did episodes on it several and yet as it's

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Speaker 1: turned out, that hasn't functioned as a central prong of

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Speaker 1: the approach. Just about anywhere in the United States. Yeah,

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Speaker 1: tech tracing works in combination with other measures, and it works.

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Speaker 1: I think I've made the analogy of you don't clean

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Speaker 1: up an oil spill with paper towels. Contact tracing is

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Speaker 1: paper towels. So when the number of cases is down

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Speaker 1: to a number where you can detect almost all of them,

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Speaker 1: where you can rapidly get test results because your system

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Speaker 1: for testing isn't overwhelmed, and where you can rapidly make

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Speaker 1: contact with the people who you need to and they

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Speaker 1: are willing to talk to the contact tracers and the like,

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Speaker 1: then contact tracing can make a big difference. It's a

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Speaker 1: mopping up exercise. It's not a large scale control exercise

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Speaker 1: because it's scales with the number the need, scales with

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Speaker 1: the number of cases. And so when you have thousands

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Speaker 1: of cases a day in a jurisdiction of modest size,

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Speaker 1: then you just can't keep up, and you especially can't

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Speaker 1: keep up when testing capacity is limited and the time

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Speaker 1: to get a test result is many days. In New Zealand,

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Speaker 1: by the time they're contact tracing was really in full speed.

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Speaker 1: It was all happening very very quickly, so that people

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Speaker 1: were being found even before they became symptomatic contacts were

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Speaker 1: being found even before they became symptomatic, so that was

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Speaker 1: a measure of how efficiently it worked. But that could

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Speaker 1: work in the tens and even can work in the hundreds,

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Speaker 1: it can't work in the thousands. Mark, what am I

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Speaker 1: not asking you that I should be asking you at

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Speaker 1: this stage of play? I guess the question there's a

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Speaker 1: question of would we do any better than next time?

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Speaker 1: And what would determine if we did any better the

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Speaker 1: next time? And by the next time, you don't mean

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Speaker 1: the next round of this, you mean the next pandemic,

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Speaker 1: if we had it to do over again, or if

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Speaker 1: we have to deal with stars three and some future time,

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Speaker 1: what would determine it? And I mean, I think there

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Speaker 1: are many many answers to that. I think there are

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Speaker 1: two that really strike me. One is leadership and clear

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Speaker 1: messaging from the top of the federal government in our case,

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Speaker 1: or the national government in other countries, that is science based,

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Speaker 1: clear about what we know and don't know, and leads

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Speaker 1: by example by showing on television the practices that are

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Speaker 1: being recommended enacted by the people recommending them. And that

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Speaker 1: was pretty much what we had in two thousand and nine.

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Speaker 1: For H one N one flu and that was a

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Speaker 1: milder illness, but that aspect worked much better. And then

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Speaker 1: the other piece is the information systems are just antiquated

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Speaker 1: by information systems, I mean everything from the ability to

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Speaker 1: test a random group of people in order to estimate

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Speaker 1: how much virus activity there is, all the way through

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Speaker 1: how that gets reported, Having the number of tests available

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Speaker 1: you need at the front end, and having the information

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Speaker 1: systems to report them in meaningful and interpretable ways. I

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Speaker 1: think that's really something that sets the country that have

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Speaker 1: responded effectively apart from those that haven't. And I think

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Speaker 1: that's a huge job for many countries in the world,

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Speaker 1: including ours, and decentralization as a challenge for that. Let's

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Speaker 1: imagine that we get vaccines and over the next couple

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Speaker 1: of years we eventually get stars covy two under control.

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Speaker 1: When we look back from a distance of a decade,

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Speaker 1: are we likely to think, well, we made lots of mistakes,

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Speaker 1: but on the whole we got pretty lucky. The overall

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Speaker 1: numbers of deaths could have been way, way worse. It

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Speaker 1: could have been a worse variant. Or are we likely

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Speaker 1: to think that wasn't really a model of what we

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Speaker 1: should not do of getting it wrong, and we really

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Speaker 1: need to massively improve on that. I think we're going

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Speaker 1: to look back with a lot of regret about how

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Speaker 1: much we let happen that didn't need to happen, and

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Speaker 1: how long we delayed the response, and how little we

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Speaker 1: use our internationally famous biotech expertise to solve problems in

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Speaker 1: the country as a whole. I mean, focusing on the

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Speaker 1: United States, just comparing across states is really remarkable, and

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Speaker 1: comparing across countries is also remarkable, as was done in

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Speaker 1: a recent article by Elisabolinski and zecommanual where they compared

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Speaker 1: the sort of beginning, middle, and recent part of the pandemic.

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Speaker 1: And at the beginning the US was like a lot

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Speaker 1: of other countries. But in the middle and more recently

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Speaker 1: we have just messed it up in a way that

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Speaker 1: most of the rest of the rich world has not.

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Speaker 1: So there's a lot of things that could have gone

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Speaker 1: a lot better. The evidence of that is just comparisons

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Speaker 1: across states and across nations. Mark, thank you for coming back,

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Speaker 1: thank you for being so clear, and above all, thank

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Speaker 1: you for the extraordinary work that you're continuing to do

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Speaker 1: every day. As we continue to come to terms of

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Speaker 1: the pandemic. Thank you for having me. Listening to Mark

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Speaker 1: Lipsitch's take eight months after we first had him on

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Speaker 1: the show was sobering, to say the least. On the

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Speaker 1: one hand, Mark thinks we've made many many mistakes and

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Speaker 1: that when we look back in retrospect, we're going to

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Speaker 1: be emphasizing our failures rather than our successes. It's also

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Speaker 1: true that in the interim Mark and co authors designed

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Speaker 1: a model that now looks eerily prescient with respect to

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Speaker 1: what things look like when you shut them down, then

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Speaker 1: reopen them, and shut them down, and reopen them. Mark

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Speaker 1: was very clear that that model was not intended as

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Speaker 1: a prediction and certainly not intended as an endorsement, but

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Speaker 1: at least thus far, it does provide the best guidance

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Speaker 1: that we can find for thinking about what's going to

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Speaker 1: happen next. That means that the surge that we're facing

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Speaker 1: now may go up significantly, Mark says, but if we

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Speaker 1: respond with strong measures, it will go down again. In

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00:27:11,356 --> 00:27:14,236
Speaker 1: Mark's account, our goal is to try to keep things

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Speaker 1: under control until the vaccine comes to the rescue. Like

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Speaker 1: the cavalry. That brings us to the question of what

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Speaker 1: will happen when that vaccine is here. Mark makes it

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Speaker 1: really clear, and to me this is the most significant

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Speaker 1: upshot of our whole conversation that whether we get more

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Speaker 1: or less back to normal is going to depend almost

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Speaker 1: entirely on how effect of the vaccine is and how

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Speaker 1: many people take it. If it only has say, a

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00:27:39,836 --> 00:27:43,156
Speaker 1: fifty percent efficacy, then even if everybody takes it, we

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00:27:43,236 --> 00:27:46,116
Speaker 1: don't get down to an R zero low enough to

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Speaker 1: eliminate mask wearing, social distancing, and potentially a range of

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Speaker 1: other limits. If, on the other hand, a vaccine is

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00:27:53,756 --> 00:27:57,076
Speaker 1: eighty or ninety percent efficacious, and if it were able

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Speaker 1: to reach and be taken by a very very large

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Speaker 1: percentage of the population, we could actually begin to get

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Speaker 1: back to something resembling normal. So there are two questions

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Speaker 1: that we're going to need to know the answers to one,

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Speaker 1: how effective will these vaccines be? To how many people

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Speaker 1: will take them. Almost everything will turn on the answers

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00:28:20,396 --> 00:28:23,836
Speaker 1: to those two questions. With respect to effectiveness. We're going

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Speaker 1: to start beginning to know the answer sometime in the

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Speaker 1: winter as we begin to get published results of large

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Speaker 1: scale trials of the vaccines. And as for the second

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00:28:33,836 --> 00:28:36,316
Speaker 1: question of how many people a vaccine will reach, will

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Speaker 1: begin to get answers to those questions through this spring

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Speaker 1: and summer and into next fall. It's a long road,

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00:28:43,796 --> 00:28:46,756
Speaker 1: it's a painful road. It's not a road that anybody

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00:28:47,236 --> 00:28:50,196
Speaker 1: is enjoying, but it is a road on which we

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Speaker 1: do have some guidance, and Mark Lipsitch is a crucial

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Speaker 1: guide for this show, for me and for all of us.

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Speaker 1: On Saturday, we'll be continuing our special series Deep Bench

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Speaker 1: about the right word turn of the Supreme Court. Until

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00:29:07,236 --> 00:29:10,316
Speaker 1: the next time I speak to you, full, be safe

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00:29:10,516 --> 00:29:13,156
Speaker 1: and be well. Deep Background is brought to you by

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00:29:13,156 --> 00:29:17,116
Speaker 1: Pushkin Industries. Our producer is Lydia Gencott, our engineer is

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00:29:17,116 --> 00:29:20,796
Speaker 1: Martin Gonzalez, and our showrunner is Sophie Crane mckibbon. Theme

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00:29:20,876 --> 00:29:24,156
Speaker 1: music by Luis Guerra at Pushkin. Thanks to Mia Lobell,

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00:29:24,396 --> 00:29:28,156
Speaker 1: Julia Barton, Heather Faine, Carlie mcgliori, Mackie Taylor, Eric Sandler,

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00:29:28,236 --> 00:29:30,916
Speaker 1: and Jacob Weisberg. You can find me on Twitter at

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00:29:30,956 --> 00:29:34,076
Speaker 1: Noah ar Feldman. I also write a column for Bloomberg Opinion,

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00:29:34,236 --> 00:29:37,436
Speaker 1: which you can find at Bloomberg dot com. Slashfeld To

490
00:29:37,556 --> 00:29:40,916
Speaker 1: discover Bloomberg's original slate of podcasts. Go to bloomberg dot

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Speaker 1: com slash podcasts, and if you like what you heard today,

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Speaker 1: please write a review or tell a friend. This is

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Speaker 1: deep background