Speaker 1: Pushkin from Pushkin Industries. This is Deep Background, the show
Speaker 1: where we explored the stories behind the stories in the news.
Speaker 1: I'm Noah Feldman. The past few weeks, we've seen the
Speaker 1: federal government taking measures to stop a coronavirus that would
Speaker 1: have been almost unimaginable not too long ago. The President
Speaker 1: declared a national emergency at the state and local level.
Speaker 1: More and more mayors and governors have declared stay at
Speaker 1: home orders. The US Mexico border is closed to non
Speaker 1: essential travel, same with the border to Canada. Most travel
Speaker 1: from the US to Europe has been suspended. Probably even
Speaker 1: more things have changed since I recorded this podcast on
Speaker 1: Monday evening. Does any of this federal response make sense?
Speaker 1: Does the state response make sense? Are we acting based
Speaker 1: on data, logic and reason? And what should we be doing?
Speaker 1: To get a really expert perspective on this, I spoke
Speaker 1: to doctor Farzad Moustashari during the Obama administration. Farzad was
Speaker 1: the National Coordinator for Health and Information Technology at the
Speaker 1: Department of Health and Human Services. Before that, he worked
Speaker 1: for the Centers for Disease Control in the New York Office,
Speaker 1: focusing on New York City public health. Now he's the
Speaker 1: founder and CEO of Allidate, a healthcare technology company. Farzad
Speaker 1: is one of the clearest and most rational people that
Speaker 1: I know, and I knew he would have a lot
Speaker 1: to say on this topic. Farzad, from very early in
Speaker 1: this crisis, and I mean very early, you were loudly
Speaker 1: saying on Twitter and I was following you closely, that
Speaker 1: we didn't have a coherent national response strategy, even at
Speaker 1: the conceptual level of knowing what we were trying to do.
Speaker 1: Have your worries on that front been at all alleviated
Speaker 1: or do you still think we have a lack of coherence?
Speaker 1: Oh my god, I wish No. We don't have a plan,
Speaker 1: and there's no clear criteria on when what are we
Speaker 1: trying to do in each community at what stage? And
Speaker 1: when are we in containment and we're trying to do
Speaker 1: contact tracing and stamp out the sparks as they're coming
Speaker 1: in and keep it out, And when are we trying
Speaker 1: to do social distancing and mitigation, And when are we
Speaker 1: going full bore on suppression and doing these extreme measures,
Speaker 1: and when are we going to get out right? So
Speaker 1: we have a plan that says a fifteen day plan
Speaker 1: to slow the growth. What happens on day sixteen. Noah,
Speaker 1: I was hoping you were going to tell me that.
Speaker 1: I mean, you know you're asking the wrong guy. One
Speaker 1: of us is actually a public health specialist. Well, I'm
Speaker 1: telling you, on day sixteen, you know what it's gonna
Speaker 1: look like. It's going to look bad. If we had
Speaker 1: done a miraculous job of slowing down transmission, we still
Speaker 1: would be seeing mounting case of hospitalizations, ICU cases and
Speaker 1: deaths on day fifteen, purely based on the people who
Speaker 1: are already infected. So I think we have to have
Speaker 1: a plan that says these are the measures, these are
Speaker 1: the data points that we look to to decide when
Speaker 1: we take these extreme economy crippling measures, and this is
Speaker 1: when we get out of them. And we don't have
Speaker 1: that right now. But not only do we not have
Speaker 1: the plan, we don't have the plan to get to
Speaker 1: the plan to get the data that we would need
Speaker 1: to be able to make that plan effective. Right because
Speaker 1: we're doing testing and the promise here has been testing
Speaker 1: more tests. Everyone who wants a test can get it.
Speaker 1: And let me tell you, my friends who are in
Speaker 1: the public health world are tearing their hair out saying
Speaker 1: we don't just need more tests. We need to get
Speaker 1: actual insights from those tests. We need, for example, to
Speaker 1: know among all the people, how many tests are positive,
Speaker 1: what percent of tests are positive. But right now we're
Speaker 1: only getting the positives. Secretary Esar said, I don't know
Speaker 1: how many tests are done. We don't know how many
Speaker 1: tests are being done. So when we see an increase
Speaker 1: in the number of positives, is that the infections getting
Speaker 1: worse or that we're testing more people. So you've described
Speaker 1: a very very grammar situation. Now you have seen public
Speaker 1: health issues from a broad range of perspectives. You've seen
Speaker 1: it as a New York City public health official, so
Speaker 1: that was the local. You've seen it from the federal
Speaker 1: level at HHS. Now you're seeing it from the private sector.
Speaker 1: You're almost uniquely qualified, it seems to me to say
Speaker 1: what we could realistically do now, So let's be as
Speaker 1: concrete as we positive can and productive. What would be
Speaker 1: your top, say, three recommendations to our national leadership of
Speaker 1: what to do. Yeah, let me focus on the testing
Speaker 1: issue for the three recommendations, because I do think that's
Speaker 1: the biggest priority is for us to get some value
Speaker 1: out of the testing. That's beginning to roll out Number one,
Speaker 1: we need to set up what's called a zero survey.
Speaker 1: And this is something that as an Epidemic Intelligence Service
Speaker 1: officer of the CDC station in New York City, we
Speaker 1: had this outbreak of West Nile virus that killed a
Speaker 1: bunch of people, and we said, but we don't know
Speaker 1: if it's really deadly to old people or if a
Speaker 1: lot of people get infected and only a small number die.
Speaker 1: So we need to go literally door to door to
Speaker 1: collect blood from people to test their blood to see
Speaker 1: if they've been exposed to this virus that was in
Speaker 1: nineteen ninety nine. We need to do that in New
Speaker 1: Rochelle now. So that's number one. So that's set up
Speaker 1: a zero study, which is literally a door to door,
Speaker 1: door to door. Will you gather data from each individual
Speaker 1: person who is infected and from those who were not
Speaker 1: visibly infective and evaluate that data. That's right, and the
Speaker 1: takeaway you'll get from that is what what will you
Speaker 1: learn from that study? Will learn of a hundred people
Speaker 1: infected with the virus, how many end up going to
Speaker 1: the emergency room, being hospitalized, being in an ICU, and
Speaker 1: being dead. Because let me tell you, that number is
Speaker 1: not two point three percent, and it's probably not one percent.
Speaker 1: It's probably smaller. The fatality rate, the infection fatality rate
Speaker 1: is probably much lower, and that's important why because what's
Speaker 1: gonna save us is herd immunity. At the end of
Speaker 1: the day, we have to use the fact that people
Speaker 1: are immune from this, whether through vaccination or through infection.
Speaker 1: And the good news would be if there are a
Speaker 1: lot of unnoticed infections of people who are now immune
Speaker 1: and can dampen the spread of this outbreak, walk me
Speaker 1: through this. So we do this close fine grand analysis.
Speaker 1: It tells us with much more accuracy than we presently
Speaker 1: know of the number of people who are exposed to
Speaker 1: the virus, how many will be hospitalized, and how many
Speaker 1: will die. Then with that information we can make a
Speaker 1: better prediction about at what point we can start relying
Speaker 1: on people who are immune to start getting back into
Speaker 1: the world. Is that right? And then we need an
Speaker 1: antibody test to test if people had been exposed, because
Speaker 1: there are lots of people out there on your hypothesis
Speaker 1: who've been exposed and haven't gotten sick and now aren't
Speaker 1: going to get the virus again. Assuming that it works
Speaker 1: like other viruses and not like the common cold where
Speaker 1: you can keep on getting it. That's right. So this
Speaker 1: would give us the data which would then move us
Speaker 1: in the direction of enabling what what's the picture of
Speaker 1: the world where we've got this data and where we
Speaker 1: have an antibody test and we can say, Okay, you know,
Speaker 1: Noah's been exposed, but he didn't get sick, so he
Speaker 1: can now go out there and do what. If I'm
Speaker 1: a doctor, I can go back to work as a doctor.
Speaker 1: If I'm running an ordinary shop, can I go back
Speaker 1: and work in my ordinary shop now? Because I'm not
Speaker 1: going to infect anybody exactly. The first use of this
Speaker 1: is honestly to inform our models of the world. If
Speaker 1: we're going to say that this thing is going to
Speaker 1: go on until thirty percent of the population or twenty
Speaker 1: percent of the population is infected, well, how many ICU
Speaker 1: beds is that it's a very different story if every
Speaker 1: ten people who get infected one of them needs an
Speaker 1: ICU bed versus if it's one hundred, versus if it's
Speaker 1: a thousand. So the first thing it informs is the
Speaker 1: state of the situation we're in right now where we
Speaker 1: desperately need to know and do not know what the
Speaker 1: impact of this is going to be on our healthcare
Speaker 1: resources and facilities in the search capacity because we don't
Speaker 1: know the ratio between infected and the cases. This is
Speaker 1: super helpful. So basically number one priority is you can't
Speaker 1: plan if you don't know what actually is going to
Speaker 1: happen in the world. And this information is so basic
Speaker 1: to figuring out what's going to happen that we can't
Speaker 1: do intelligent planning really without it. Correct And I was
Speaker 1: talking to a modeler from a university near you who
Speaker 1: was saying, I don't know that the future could go
Speaker 1: you know, many many different directions, And I said, what
Speaker 1: is the piece of data you need to make your
Speaker 1: models have smaller variants in terms of the outcomes. And
Speaker 1: she said, what I need more than anything else is
Speaker 1: I need to know the percent infected. So okay, let's
Speaker 1: do that. The other application of it is what you said,
Speaker 1: which is and some have posited this, well, maybe we
Speaker 1: could have, you know, green bracelets for people who are
Speaker 1: already immune and they could end up helping run the
Speaker 1: society while the rest of us are in lockdown. I
Speaker 1: don't know about that use of the antibody testing, but
Speaker 1: let's start with the epidemiologic uses. So that's number one.
Speaker 1: Number two is we need to know within a given
Speaker 1: city whether we're seeing widespread disease outbreak or not. And
Speaker 1: right now, in the absence of any guidance, in the
Speaker 1: absence of data, individual governors and mayors and others have
Speaker 1: made individual decisions, and I'm telling in some places it
Speaker 1: was too late, and I can also tell you in
Speaker 1: some places it's too early. And this is the problem
Speaker 1: with the germ of truth that the kind of cynics
Speaker 1: are having out there, of like, oh, this is much
Speaker 1: ado and we're overreacting. Well, in some cities, maybe we are,
Speaker 1: but we don't know which. And so we need to
Speaker 1: have a systematic way of using the tests that we
Speaker 1: have and using the information we've already collected to be
Speaker 1: able to know is this virus spreading. Is it at
Speaker 1: the point where there's sparks we can stamp out with
Speaker 1: contact tracing, or it's too late to start to stamp
Speaker 1: out sparks. The whole house is on fire and you
Speaker 1: need to just turn the hose on and slow it
Speaker 1: down and make it go a little less fast. And
Speaker 1: how would we find out this information and number two.
Speaker 1: If number one is door to door study, number two
Speaker 1: is just massive testing. I take it. Actually, it's not
Speaker 1: the number of tests, it's how you do the tests. Okay,
Speaker 1: tell me more about that. How do you do the tests? Yeah?
Speaker 1: The big problem is that we have two different public
Speaker 1: health reporting systems in this country. And if you just
Speaker 1: think about it, it kind of makes sense. Noah. Right,
Speaker 1: you go into the doctor's office and they draw your
Speaker 1: blood and they send it to the lab. The lab
Speaker 1: then gets a positive result and they report it to
Speaker 1: the public health authorities. Right, that is the laboratory arm
Speaker 1: of public health reporting. What information does the lab have
Speaker 1: about you? Almost none? I take it. I just know
Speaker 1: that's your blood sample. Yeah. They know your name, and
Speaker 1: they know your day of birth, and maybe you're addressed,
Speaker 1: maybe not, depending Right. They don't know your symptoms, they
Speaker 1: don't know your exposures. They don't know if you're hospitalized
Speaker 1: or going to be hospitalized, And which is why the CDC,
Speaker 1: in the Morbidity Immortality Weekly Report, the flagship publication of
Speaker 1: the CDC, had their first case report of forty two
Speaker 1: hundred plus cases positive cases in the United States. They said,
Speaker 1: we do not know the hospitalization status of half of them,
Speaker 1: So we didn't even know the age of ten percent
Speaker 1: of the positive cases. So giving more testing done in
Speaker 1: lab core and quest and hospital labs that end up
Speaker 1: flooding the public health system with cases that we know
Speaker 1: nothing about is not helpful. It's not getting more testing
Speaker 1: out there, it's we want to have tests done where
Speaker 1: the laboratory results are tied to the key clinical and
Speaker 1: epidemologic data for us to make sense of it. So
Speaker 1: that key data is is this person part of a
Speaker 1: known cluster? What is their exposure? Did they travel? Do
Speaker 1: they know someone? Do they who has it? That? We
Speaker 1: should ask people basically on a form at the same
Speaker 1: time as they're having their blood drawn, that forms should
Speaker 1: be filled out. That's the simplest form of this, right,
Speaker 1: And we should also ask them, oh, do you have
Speaker 1: any symptoms? When did those symptoms start. With those two
Speaker 1: pieces of data and the person's age in county, I
Speaker 1: can now construct an epicurve and I can tell you
Speaker 1: with those pieces of data, is the outbreak in this
Speaker 1: city getting better or worse? But I need both parts
Speaker 1: of that data. I need the clinical and epidemiologic risk
Speaker 1: factor data and I need the lab data so where
Speaker 1: can we get both of those pieces of data. We
Speaker 1: have to set up sentinel surveillance sites where at the
Speaker 1: cost of getting the lab test, you also will have
Speaker 1: to fill out the form. So this is where not
Speaker 1: just blasting the tests out there, but actually setting up
Speaker 1: some planful places where in an emergency room, every person
Speaker 1: who comes in with fever cough is going to get tested.
Speaker 1: Or in a doctor's office we set up doctors offices,
Speaker 1: we set up sentinel testing sites, or at a drive
Speaker 1: through clinic a drive through testing site, we make sure
Speaker 1: that we collect both pieces of information. That's how this
Speaker 1: is going to get done. And right now I have
Speaker 1: heard roughly nobody create an actual funded plan to resource
Speaker 1: the development of dedicated testing sites that collect the information
Speaker 1: at scale sufficient to answer these questions? Why far as odd?
Speaker 1: Why is it the case that if something is as
Speaker 1: straightforward as you're describing it as being the sentinel sites,
Speaker 1: and I take it it's called sentinel because it gives
Speaker 1: you an early warning of what's going on, or in
Speaker 1: this case and not so early warning. Why is it
Speaker 1: the case that no one is proposing that? And if
Speaker 1: I could make the question even a little meaner, you know,
Speaker 1: you were National Coordinator for Health IT for the Federal
Speaker 1: Department of Health and Human Services in the Obama administration.
Speaker 1: Why was this not part of what your team or
Speaker 1: the broader HHS community was trying to have in a
Speaker 1: contingency plan for the day that you knew perfectly well
Speaker 1: would some day come where a crisis like this would
Speaker 1: break out. Because we as humans lurch from panic to
Speaker 1: panic in periods of complacency. That's what we do. We
Speaker 1: all do that, and there are some more extreme examples
Speaker 1: of where we let complacency take root. But I don't
Speaker 1: think anyone is blameless in forgetting you just forget what
Speaker 1: it feels like to be in this moment, Like we
Speaker 1: should make a list of the shit we're going to
Speaker 1: fix during the period of complacency between panic and panic.
Speaker 1: Like we should make that list, and we should now,
Speaker 1: and we should just stick to it for God's sake
Speaker 1: and get it done. What's the barrier though, to simply
Speaker 1: a national edict from CDC that says, Hey, everybody in
Speaker 1: the country who's testing you must simultaneously fill out this
Speaker 1: form which we're posting online right now, and you must
Speaker 1: ask the patient about the progress of his or her symptoms.
Speaker 1: I mean, it sounds like of all the interventions we've
Speaker 1: you know, we can imagine that sounds like a pretty
Speaker 1: inexpensive one, except for the coordination of the data, which
Speaker 1: I recognize would take some work. So look, the US
Speaker 1: system really does delegate public health to stay local officials.
Speaker 1: The CDC is an incredibly powerful institution, but mostly through guidance, yes, funding,
Speaker 1: but expertise, and ultimately they need to be the ones
Speaker 1: who are front and center, who are speaking with the
Speaker 1: voice of evidence based public health to the American people
Speaker 1: about what the strategy should be. And let me ask you,
Speaker 1: when was the last time the CDC was at the
Speaker 1: podium at the Coronavirus Task Force. It's been some days.
Speaker 1: It's been many, many, many days, so we have not
Speaker 1: heard from and shook it. But to be fair, the
Speaker 1: CDC doesn't have to be at the I mean, that
Speaker 1: has some symbolic meeting, but the CDC doesn't have to
Speaker 1: be at the podium to issue a guidance on this,
Speaker 1: especially if it sees itself as, among other things, the
Speaker 1: coordinator of National Data. I mean, if we had the
Speaker 1: head of the CDC here and asked her, you know,
Speaker 1: why haven't you done this, what would she be saying,
Speaker 1: I don't know. I don't know, Noah. And to me,
Speaker 1: one of my proudest career experiences was being at this CDC.
Speaker 1: It's a fantastic institution with thousands of incredible experts, and
Speaker 1: I just do not understand why they have not been
Speaker 1: frem and center and leading in the way that they
Speaker 1: know how to in this experience. I just I'm baffled,
Speaker 1: and I don't have a good answer for you. We'll
Speaker 1: be back in just a moment. You've given us one
Speaker 1: in two suggestions, super clear, what's your third biggest recommendation?
Speaker 1: So the third piece of this is a system that
Speaker 1: I did play some part in really designing or creating
Speaker 1: some twenty years ago, which has now become commonplace practice
Speaker 1: in public health, which is called syndromic surveillance. And this
Speaker 1: is saying remember I talked about how long it takes
Speaker 1: and the data problems of getting a lap specimen confirmed
Speaker 1: with say coronavirus. The idea here was, well, people go
Speaker 1: to live their lives, and they register in the emergency room,
Speaker 1: and there's a piece of data collected for that, and
Speaker 1: they go buy medications and the phazinc at the pharmacy,
Speaker 1: and it goes deep at the counter, and you could
Speaker 1: gather up all those little bits and drabs of the
Speaker 1: exhaust of administrative data that governs our lives, and you
Speaker 1: can actually put it to purpose, putting your finger on
Speaker 1: the pulse of the city's health in real time and detect.
Speaker 1: At that time, we were thinking bioterrorism. Now we're thinking
Speaker 1: coronavirus pandemic. And it turns out we spend hundreds of
Speaker 1: millions of dollars. And as part of the health information
Speaker 1: technology transformation that I helped push, we required hospitals to
Speaker 1: report every emergency room visit to these state public health
Speaker 1: systems in syndromes where you could group them and say,
Speaker 1: does the person come in have a GI syndrome or
Speaker 1: a respiratory syndrome or a flu syndrome? And so we
Speaker 1: have the system. You don't have to build it. Now,
Speaker 1: you don't have to recreate it. We've spent a lot
Speaker 1: of money and resolved all the governance issues in state
Speaker 1: and local blah blah blah, and we're not using it.
Speaker 1: And again you're gonna asked me, why aren't we using it?
Speaker 1: I don't know, I don't know. I do not know.
Speaker 1: But the only place that has made that information publicly
Speaker 1: available is New York City. It's literally the website that
Speaker 1: we built fifteen years ago still works, and you can
Speaker 1: go on that website. You can google ep query Queer
Speaker 1: y Syndrome Surveillance, and you can go there and you
Speaker 1: can click on the box that says influenza like illness
Speaker 1: or respiratory and you can see the percent of all
Speaker 1: emergency room visits daily up until I think Friday. They
Speaker 1: have data in there now and you can look at
Speaker 1: daily rates of emergency room visits in every emergency room
Speaker 1: in New York City, what percent of them were for
Speaker 1: respiratory syndrome or flu like syndrome. And what you will
Speaker 1: see is that what has happened in the past two
Speaker 1: weeks has never happened in New York City before. I've
Speaker 1: been looking at this data for twenty years. Never ever
Speaker 1: have I seen a spike in illness that sharp, that steep,
Speaker 1: that fast. Four thousand, six hundred cases of respiratory illness
Speaker 1: or influenza like illness presented to emergency rooms in New
Speaker 1: York City last Thursday, a year ago. That day it
Speaker 1: was sixteen hundred, almost a threefold increase in those visits.
Speaker 1: It is an incredibly powerful tool for seeing what is
Speaker 1: going on in the community. And is it actually don't
Speaker 1: tell me that we have it? How many cases tell me?
Speaker 1: Is it causing enough illness in the community to make
Speaker 1: a difference to be seen in the data? And we
Speaker 1: have it in more than just New York City. We
Speaker 1: could look at it potentially in every state. And for
Speaker 1: reasons that I do not understand that data is not
Speaker 1: currently the centerpiece of our surveillance and response to this outbreak.
Speaker 1: What am I not asking you about that you see
Speaker 1: over the horizon going back to the national level as
Speaker 1: a potential problem that we haven't yet flagged. And I'm
Speaker 1: asking you that not because of your expertise only, but
Speaker 1: because you flagged a lot of the problems that we've
Speaker 1: been seeing earlier than other people did. So when you
Speaker 1: look now two weeks or three weeks or even a
Speaker 1: few months down the road, what do you see as
Speaker 1: the most serious problems that are also not being discussed.
Speaker 1: I'm really interested in this confluence of politics and policy
Speaker 1: and data around when we go to these extreme measures
Speaker 1: and when we come out, and particularly if we're not
Speaker 1: able to mobilize suppression effectively enough that we can go
Speaker 1: back to reclaim containment. That's what we have to be
Speaker 1: able to do to get out of this crisis without
Speaker 1: twenty thirty forty fifty percent of the population infected. Is
Speaker 1: we have to reclaim containment. We have to put out
Speaker 1: the fire and then really assemble crack teams of public
Speaker 1: health workers who can go around, stamp and out sparks
Speaker 1: much better than we've done before. And if we can't
Speaker 1: do that, then we will be continually faced over the
Speaker 1: next eighteen months until a vaccine hopefully hopefully is developed,
Speaker 1: where we're going to be facing economic ruination and trying
Speaker 1: to decide make those hard trade offs between how much
Speaker 1: can we ease up and then see more people dying
Speaker 1: and then push back down again, And every policymaker is
Speaker 1: going to be having to make that, Every elected official
Speaker 1: is going to be making that decision based on their
Speaker 1: own environment. So I hope that we can reclaim containment.
Speaker 1: I really really do. But if not, I think we're
Speaker 1: in for eighteen months of what I fear will be
Speaker 1: somewhat haphazard decision making around when to close, when to open,
Speaker 1: when to reclose, when to reopen back and forth. As
Speaker 1: far as said before I let you go, I do.
Speaker 1: A lot of people are wondering is there any hope here?
Speaker 1: You know? Is it all doom and gloom? What are
Speaker 1: your thoughts on that? Earlier I was much more freaked
Speaker 1: out when no one was talking about it. It was
Speaker 1: just freaking me out. And now I'm actually much less
Speaker 1: freaked now that everyone's talking about it, because what I
Speaker 1: am seeing is, even in the absence of a plan,
Speaker 1: even in the absence of a strategy, even in the
Speaker 1: absence of data, I'm seeing massive behavior change in society,
Speaker 1: each person, each company, each school, each mayor deciding for themselves,
Speaker 1: each person deciding for themselves that they're gonna live life
Speaker 1: a little bit differently. I'm not seeing very much handshaking
Speaker 1: right now. I'm not going to any conferences that airports
Speaker 1: are deserted. Like. This stuff doesn't have to be perfect
Speaker 1: to work, and I think it's working. We don't know
Speaker 1: if it's working. We won't probably for several weeks at
Speaker 1: least under the best of circumstances. But I'm optimistic that
Speaker 1: it's working because the average number of contacts just has
Speaker 1: to come down. That's all we're trying to do to
Speaker 1: go from an effective reproductive number of two point five
Speaker 1: are not down to and are effective of less than one. Well,
Speaker 1: what that means is that if you had ten contacts
Speaker 1: a week before, you want to get down a four
Speaker 1: on average. If you can do that, will beat this thing. Right,
Speaker 1: The number of new infections that each person causes will
Speaker 1: be less than one, and this thing will extinguish on
Speaker 1: its own. If before, on average, you went to the
Speaker 1: gym five days a week, and now you go no
Speaker 1: more than two. If everybody did that, this thing would
Speaker 1: snuff out. And I think some people are not doing it.
Speaker 1: Other people are doing it to a great much greater extent,
Speaker 1: and on average, I really do think all of us,
Speaker 1: acting individually, are making a difference. So keep doing it, America.
Speaker 1: Despite all of the stuff I talked about, at the
Speaker 1: bottom line, what matters is can we change our habits?
Speaker 1: And that for me, the bright glimmer of hope here
Speaker 1: is Japan. Actually, because Japan did not pump out a
Speaker 1: ton of testing, but that what they did do is
Speaker 1: they embraced their sense of responsibility to each other. And
Speaker 1: I think that is in some ways more feasible for
Speaker 1: us to embrace than you know, contact tracing tens of
Speaker 1: thousands of people in New York City every day. Well,
Speaker 1: if Americans can pull together by staying not together, then
Speaker 1: maybe they can accomplish exactly what you're what you're talking about, Brazza,
Speaker 1: thank you for helping us not go completely off the rails,
Speaker 1: but simultaneously, thanks for the clarity and honesty and directness
Speaker 1: of your analysis. Thank you. Noah, Well, there you have.
Speaker 1: Farzad Mustashari, whose whole career has been trying to leverage
Speaker 1: data for public health, is very worried that we do
Speaker 1: not have the kind of data that we need and
Speaker 1: that it's not entirely clear we can get it without
Speaker 1: a substantial change in policy. That said, he does not
Speaker 1: think that the world is over. And it's significant to
Speaker 1: my mind that somebody who was in his own terms,
Speaker 1: freaking out about this a month ago is now calmer
Speaker 1: than he was and does believe that our efforts at
Speaker 1: social distancing may be having good effects, imprecise and imperfect
Speaker 1: though they are, so it's a mixed picture. We could
Speaker 1: be doing a lot better, we could be doing this
Speaker 1: a lot more rationally, but we're not facing in his view,
Speaker 1: the kind of existential threat that we cannot defeat based
Speaker 1: on the social distancing techniques that are presently being used.
Speaker 1: Until next time, be safe, take care of yourselves, maintain
Speaker 1: that distance. Deep Background is brought to you by Pushkin Industries.
Speaker 1: Our producer is Lydia Jeane Caught with research help from Zooequin.
Speaker 1: Mastering is by Jason Gambrell and Martinezalez. Our showrunner is
Speaker 1: Sophie mcibbon. Our theme music is composed by Luis gera
Speaker 1: special thanks to the Pushkin Brass, Malcolm Gladwell, Jacob Weisberg
Speaker 1: and Mia Lovel. I'm Noah Feldt. I also write a
Speaker 1: regular column from Bloomberg Opinion, which you can find at
Speaker 1: Bloomberg dot com slash felt. To discover Bloomberg's original slate
Speaker 1: of podcasts, go to Bloomberg dot com slash Podcasts. You
Speaker 1: can follow me on Twitter at Noah rfeld This is
Speaker 1: Deep Background.