1 00:00:15,356 --> 00:00:22,716 Speaker 1: Pushkin from Pushkin Industries. This is Deep Background, the show 2 00:00:22,756 --> 00:00:26,076 Speaker 1: where we explored the stories behind the stories in the news. 3 00:00:26,596 --> 00:00:30,596 Speaker 1: I'm Noah Feldman. The past few weeks, we've seen the 4 00:00:30,636 --> 00:00:34,236 Speaker 1: federal government taking measures to stop a coronavirus that would 5 00:00:34,276 --> 00:00:38,676 Speaker 1: have been almost unimaginable not too long ago. The President 6 00:00:38,716 --> 00:00:41,756 Speaker 1: declared a national emergency at the state and local level. 7 00:00:42,036 --> 00:00:45,116 Speaker 1: More and more mayors and governors have declared stay at 8 00:00:45,116 --> 00:00:48,356 Speaker 1: home orders. The US Mexico border is closed to non 9 00:00:48,436 --> 00:00:51,836 Speaker 1: essential travel, same with the border to Canada. Most travel 10 00:00:51,876 --> 00:00:55,356 Speaker 1: from the US to Europe has been suspended. Probably even 11 00:00:55,476 --> 00:00:58,596 Speaker 1: more things have changed since I recorded this podcast on 12 00:00:58,676 --> 00:01:02,716 Speaker 1: Monday evening. Does any of this federal response make sense? 13 00:01:03,276 --> 00:01:07,036 Speaker 1: Does the state response make sense? Are we acting based 14 00:01:07,076 --> 00:01:10,756 Speaker 1: on data, logic and reason? And what should we be doing? 15 00:01:11,756 --> 00:01:14,876 Speaker 1: To get a really expert perspective on this, I spoke 16 00:01:14,916 --> 00:01:19,276 Speaker 1: to doctor Farzad Moustashari during the Obama administration. Farzad was 17 00:01:19,316 --> 00:01:22,836 Speaker 1: the National Coordinator for Health and Information Technology at the 18 00:01:22,836 --> 00:01:27,036 Speaker 1: Department of Health and Human Services. Before that, he worked 19 00:01:27,076 --> 00:01:30,116 Speaker 1: for the Centers for Disease Control in the New York Office, 20 00:01:30,436 --> 00:01:34,076 Speaker 1: focusing on New York City public health. Now he's the 21 00:01:34,116 --> 00:01:39,116 Speaker 1: founder and CEO of Allidate, a healthcare technology company. Farzad 22 00:01:39,196 --> 00:01:41,596 Speaker 1: is one of the clearest and most rational people that 23 00:01:41,676 --> 00:01:44,036 Speaker 1: I know, and I knew he would have a lot 24 00:01:44,116 --> 00:01:48,316 Speaker 1: to say on this topic. Farzad, from very early in 25 00:01:48,356 --> 00:01:52,596 Speaker 1: this crisis, and I mean very early, you were loudly 26 00:01:52,716 --> 00:01:55,876 Speaker 1: saying on Twitter and I was following you closely, that 27 00:01:55,916 --> 00:01:58,916 Speaker 1: we didn't have a coherent national response strategy, even at 28 00:01:58,916 --> 00:02:01,356 Speaker 1: the conceptual level of knowing what we were trying to do. 29 00:02:02,076 --> 00:02:05,396 Speaker 1: Have your worries on that front been at all alleviated 30 00:02:05,516 --> 00:02:07,916 Speaker 1: or do you still think we have a lack of coherence? 31 00:02:08,036 --> 00:02:13,316 Speaker 1: Oh my god, I wish No. We don't have a plan, 32 00:02:13,796 --> 00:02:18,276 Speaker 1: and there's no clear criteria on when what are we 33 00:02:18,316 --> 00:02:21,956 Speaker 1: trying to do in each community at what stage? And 34 00:02:22,036 --> 00:02:24,636 Speaker 1: when are we in containment and we're trying to do 35 00:02:24,756 --> 00:02:27,436 Speaker 1: contact tracing and stamp out the sparks as they're coming 36 00:02:27,476 --> 00:02:29,916 Speaker 1: in and keep it out, And when are we trying 37 00:02:29,916 --> 00:02:33,356 Speaker 1: to do social distancing and mitigation, And when are we 38 00:02:33,396 --> 00:02:38,916 Speaker 1: going full bore on suppression and doing these extreme measures, 39 00:02:39,796 --> 00:02:42,436 Speaker 1: and when are we going to get out right? So 40 00:02:42,676 --> 00:02:45,716 Speaker 1: we have a plan that says a fifteen day plan 41 00:02:45,836 --> 00:02:50,236 Speaker 1: to slow the growth. What happens on day sixteen. Noah, 42 00:02:50,596 --> 00:02:51,996 Speaker 1: I was hoping you were going to tell me that. 43 00:02:52,356 --> 00:02:54,876 Speaker 1: I mean, you know you're asking the wrong guy. One 44 00:02:54,876 --> 00:02:57,916 Speaker 1: of us is actually a public health specialist. Well, I'm 45 00:02:57,956 --> 00:02:59,996 Speaker 1: telling you, on day sixteen, you know what it's gonna 46 00:02:59,996 --> 00:03:02,396 Speaker 1: look like. It's going to look bad. If we had 47 00:03:02,436 --> 00:03:07,236 Speaker 1: done a miraculous job of slowing down transmission, we still 48 00:03:07,276 --> 00:03:11,676 Speaker 1: would be seeing mounting case of hospitalizations, ICU cases and 49 00:03:11,836 --> 00:03:15,276 Speaker 1: deaths on day fifteen, purely based on the people who 50 00:03:15,276 --> 00:03:19,756 Speaker 1: are already infected. So I think we have to have 51 00:03:19,796 --> 00:03:23,116 Speaker 1: a plan that says these are the measures, these are 52 00:03:23,116 --> 00:03:26,436 Speaker 1: the data points that we look to to decide when 53 00:03:26,476 --> 00:03:30,916 Speaker 1: we take these extreme economy crippling measures, and this is 54 00:03:30,916 --> 00:03:34,396 Speaker 1: when we get out of them. And we don't have 55 00:03:34,476 --> 00:03:36,676 Speaker 1: that right now. But not only do we not have 56 00:03:36,756 --> 00:03:39,916 Speaker 1: the plan, we don't have the plan to get to 57 00:03:39,996 --> 00:03:42,996 Speaker 1: the plan to get the data that we would need 58 00:03:43,036 --> 00:03:46,316 Speaker 1: to be able to make that plan effective. Right because 59 00:03:46,396 --> 00:03:50,796 Speaker 1: we're doing testing and the promise here has been testing 60 00:03:51,156 --> 00:03:53,476 Speaker 1: more tests. Everyone who wants a test can get it. 61 00:03:53,676 --> 00:03:55,196 Speaker 1: And let me tell you, my friends who are in 62 00:03:55,236 --> 00:03:58,796 Speaker 1: the public health world are tearing their hair out saying 63 00:03:59,156 --> 00:04:03,716 Speaker 1: we don't just need more tests. We need to get 64 00:04:03,796 --> 00:04:07,596 Speaker 1: actual insights from those tests. We need, for example, to 65 00:04:07,716 --> 00:04:12,276 Speaker 1: know among all the people, how many tests are positive, 66 00:04:12,316 --> 00:04:15,156 Speaker 1: what percent of tests are positive. But right now we're 67 00:04:15,156 --> 00:04:18,436 Speaker 1: only getting the positives. Secretary Esar said, I don't know 68 00:04:18,476 --> 00:04:20,956 Speaker 1: how many tests are done. We don't know how many 69 00:04:20,956 --> 00:04:22,996 Speaker 1: tests are being done. So when we see an increase 70 00:04:23,036 --> 00:04:26,076 Speaker 1: in the number of positives, is that the infections getting 71 00:04:26,076 --> 00:04:29,676 Speaker 1: worse or that we're testing more people. So you've described 72 00:04:29,796 --> 00:04:34,556 Speaker 1: a very very grammar situation. Now you have seen public 73 00:04:34,556 --> 00:04:37,516 Speaker 1: health issues from a broad range of perspectives. You've seen 74 00:04:37,556 --> 00:04:41,596 Speaker 1: it as a New York City public health official, so 75 00:04:41,676 --> 00:04:44,756 Speaker 1: that was the local. You've seen it from the federal 76 00:04:44,836 --> 00:04:49,156 Speaker 1: level at HHS. Now you're seeing it from the private sector. 77 00:04:49,916 --> 00:04:53,156 Speaker 1: You're almost uniquely qualified, it seems to me to say 78 00:04:53,196 --> 00:04:56,036 Speaker 1: what we could realistically do now, So let's be as 79 00:04:56,076 --> 00:04:59,796 Speaker 1: concrete as we positive can and productive. What would be 80 00:04:59,876 --> 00:05:04,036 Speaker 1: your top, say, three recommendations to our national leadership of 81 00:05:04,076 --> 00:05:06,556 Speaker 1: what to do. Yeah, let me focus on the testing 82 00:05:06,556 --> 00:05:10,076 Speaker 1: issue for the three recommendations, because I do think that's 83 00:05:10,076 --> 00:05:12,476 Speaker 1: the biggest priority is for us to get some value 84 00:05:12,756 --> 00:05:16,236 Speaker 1: out of the testing. That's beginning to roll out Number one, 85 00:05:17,036 --> 00:05:21,756 Speaker 1: we need to set up what's called a zero survey. 86 00:05:22,636 --> 00:05:26,156 Speaker 1: And this is something that as an Epidemic Intelligence Service 87 00:05:26,196 --> 00:05:29,316 Speaker 1: officer of the CDC station in New York City, we 88 00:05:29,396 --> 00:05:32,116 Speaker 1: had this outbreak of West Nile virus that killed a 89 00:05:32,116 --> 00:05:35,156 Speaker 1: bunch of people, and we said, but we don't know 90 00:05:35,516 --> 00:05:38,156 Speaker 1: if it's really deadly to old people or if a 91 00:05:38,156 --> 00:05:41,636 Speaker 1: lot of people get infected and only a small number die. 92 00:05:41,876 --> 00:05:44,796 Speaker 1: So we need to go literally door to door to 93 00:05:44,956 --> 00:05:48,396 Speaker 1: collect blood from people to test their blood to see 94 00:05:48,396 --> 00:05:52,276 Speaker 1: if they've been exposed to this virus that was in 95 00:05:52,356 --> 00:05:55,316 Speaker 1: nineteen ninety nine. We need to do that in New 96 00:05:55,396 --> 00:05:59,916 Speaker 1: Rochelle now. So that's number one. So that's set up 97 00:05:59,916 --> 00:06:03,116 Speaker 1: a zero study, which is literally a door to door, 98 00:06:03,156 --> 00:06:05,556 Speaker 1: door to door. Will you gather data from each individual 99 00:06:05,556 --> 00:06:08,076 Speaker 1: person who is infected and from those who were not 100 00:06:08,196 --> 00:06:11,356 Speaker 1: visibly infective and evaluate that data. That's right, and the 101 00:06:11,396 --> 00:06:13,396 Speaker 1: takeaway you'll get from that is what what will you 102 00:06:13,476 --> 00:06:16,036 Speaker 1: learn from that study? Will learn of a hundred people 103 00:06:16,076 --> 00:06:18,996 Speaker 1: infected with the virus, how many end up going to 104 00:06:19,036 --> 00:06:21,316 Speaker 1: the emergency room, being hospitalized, being in an ICU, and 105 00:06:21,356 --> 00:06:24,916 Speaker 1: being dead. Because let me tell you, that number is 106 00:06:24,996 --> 00:06:28,676 Speaker 1: not two point three percent, and it's probably not one percent. 107 00:06:28,916 --> 00:06:32,836 Speaker 1: It's probably smaller. The fatality rate, the infection fatality rate 108 00:06:33,636 --> 00:06:39,036 Speaker 1: is probably much lower, and that's important why because what's 109 00:06:39,036 --> 00:06:42,916 Speaker 1: gonna save us is herd immunity. At the end of 110 00:06:42,956 --> 00:06:46,436 Speaker 1: the day, we have to use the fact that people 111 00:06:46,516 --> 00:06:51,036 Speaker 1: are immune from this, whether through vaccination or through infection. 112 00:06:51,756 --> 00:06:54,676 Speaker 1: And the good news would be if there are a 113 00:06:54,676 --> 00:06:58,756 Speaker 1: lot of unnoticed infections of people who are now immune 114 00:06:59,316 --> 00:07:04,836 Speaker 1: and can dampen the spread of this outbreak, walk me 115 00:07:04,876 --> 00:07:08,556 Speaker 1: through this. So we do this close fine grand analysis. 116 00:07:08,636 --> 00:07:11,156 Speaker 1: It tells us with much more accuracy than we presently 117 00:07:11,196 --> 00:07:13,636 Speaker 1: know of the number of people who are exposed to 118 00:07:13,676 --> 00:07:16,116 Speaker 1: the virus, how many will be hospitalized, and how many 119 00:07:16,156 --> 00:07:20,396 Speaker 1: will die. Then with that information we can make a 120 00:07:20,436 --> 00:07:25,236 Speaker 1: better prediction about at what point we can start relying 121 00:07:25,316 --> 00:07:28,676 Speaker 1: on people who are immune to start getting back into 122 00:07:28,676 --> 00:07:30,436 Speaker 1: the world. Is that right? And then we need an 123 00:07:30,476 --> 00:07:33,196 Speaker 1: antibody test to test if people had been exposed, because 124 00:07:33,196 --> 00:07:34,956 Speaker 1: there are lots of people out there on your hypothesis 125 00:07:35,156 --> 00:07:37,556 Speaker 1: who've been exposed and haven't gotten sick and now aren't 126 00:07:37,556 --> 00:07:40,276 Speaker 1: going to get the virus again. Assuming that it works 127 00:07:40,316 --> 00:07:42,916 Speaker 1: like other viruses and not like the common cold where 128 00:07:42,916 --> 00:07:45,436 Speaker 1: you can keep on getting it. That's right. So this 129 00:07:45,476 --> 00:07:47,476 Speaker 1: would give us the data which would then move us 130 00:07:47,476 --> 00:07:49,996 Speaker 1: in the direction of enabling what what's the picture of 131 00:07:49,996 --> 00:07:52,476 Speaker 1: the world where we've got this data and where we 132 00:07:52,516 --> 00:07:55,076 Speaker 1: have an antibody test and we can say, Okay, you know, 133 00:07:55,156 --> 00:07:57,716 Speaker 1: Noah's been exposed, but he didn't get sick, so he 134 00:07:57,756 --> 00:07:59,316 Speaker 1: can now go out there and do what. If I'm 135 00:07:59,316 --> 00:08:00,916 Speaker 1: a doctor, I can go back to work as a doctor. 136 00:08:01,276 --> 00:08:03,556 Speaker 1: If I'm running an ordinary shop, can I go back 137 00:08:03,556 --> 00:08:05,356 Speaker 1: and work in my ordinary shop now? Because I'm not 138 00:08:05,396 --> 00:08:07,836 Speaker 1: going to infect anybody exactly. The first use of this 139 00:08:08,036 --> 00:08:11,756 Speaker 1: is honestly to inform our models of the world. If 140 00:08:12,036 --> 00:08:13,636 Speaker 1: we're going to say that this thing is going to 141 00:08:13,716 --> 00:08:16,276 Speaker 1: go on until thirty percent of the population or twenty 142 00:08:16,276 --> 00:08:19,516 Speaker 1: percent of the population is infected, well, how many ICU 143 00:08:19,556 --> 00:08:23,116 Speaker 1: beds is that it's a very different story if every 144 00:08:23,996 --> 00:08:26,836 Speaker 1: ten people who get infected one of them needs an 145 00:08:26,916 --> 00:08:28,916 Speaker 1: ICU bed versus if it's one hundred, versus if it's 146 00:08:28,916 --> 00:08:32,036 Speaker 1: a thousand. So the first thing it informs is the 147 00:08:32,036 --> 00:08:34,596 Speaker 1: state of the situation we're in right now where we 148 00:08:34,676 --> 00:08:37,796 Speaker 1: desperately need to know and do not know what the 149 00:08:37,876 --> 00:08:39,836 Speaker 1: impact of this is going to be on our healthcare 150 00:08:39,876 --> 00:08:42,956 Speaker 1: resources and facilities in the search capacity because we don't 151 00:08:42,996 --> 00:08:47,716 Speaker 1: know the ratio between infected and the cases. This is 152 00:08:47,756 --> 00:08:51,356 Speaker 1: super helpful. So basically number one priority is you can't 153 00:08:51,396 --> 00:08:53,076 Speaker 1: plan if you don't know what actually is going to 154 00:08:53,116 --> 00:08:56,036 Speaker 1: happen in the world. And this information is so basic 155 00:08:56,396 --> 00:08:58,356 Speaker 1: to figuring out what's going to happen that we can't 156 00:08:58,356 --> 00:09:01,236 Speaker 1: do intelligent planning really without it. Correct And I was 157 00:09:01,276 --> 00:09:04,116 Speaker 1: talking to a modeler from a university near you who 158 00:09:04,196 --> 00:09:07,716 Speaker 1: was saying, I don't know that the future could go 159 00:09:08,476 --> 00:09:11,156 Speaker 1: you know, many many different directions, And I said, what 160 00:09:11,316 --> 00:09:13,276 Speaker 1: is the piece of data you need to make your 161 00:09:13,316 --> 00:09:17,116 Speaker 1: models have smaller variants in terms of the outcomes. And 162 00:09:17,476 --> 00:09:20,196 Speaker 1: she said, what I need more than anything else is 163 00:09:20,236 --> 00:09:23,556 Speaker 1: I need to know the percent infected. So okay, let's 164 00:09:23,596 --> 00:09:25,756 Speaker 1: do that. The other application of it is what you said, 165 00:09:25,836 --> 00:09:29,156 Speaker 1: which is and some have posited this, well, maybe we 166 00:09:29,196 --> 00:09:33,236 Speaker 1: could have, you know, green bracelets for people who are 167 00:09:33,516 --> 00:09:36,396 Speaker 1: already immune and they could end up helping run the 168 00:09:36,436 --> 00:09:39,156 Speaker 1: society while the rest of us are in lockdown. I 169 00:09:39,196 --> 00:09:42,436 Speaker 1: don't know about that use of the antibody testing, but 170 00:09:42,836 --> 00:09:45,836 Speaker 1: let's start with the epidemiologic uses. So that's number one. 171 00:09:46,116 --> 00:09:50,556 Speaker 1: Number two is we need to know within a given 172 00:09:50,796 --> 00:09:57,396 Speaker 1: city whether we're seeing widespread disease outbreak or not. And 173 00:09:57,956 --> 00:10:00,796 Speaker 1: right now, in the absence of any guidance, in the 174 00:10:00,836 --> 00:10:05,916 Speaker 1: absence of data, individual governors and mayors and others have 175 00:10:06,076 --> 00:10:10,396 Speaker 1: made individual decisions, and I'm telling in some places it 176 00:10:10,436 --> 00:10:13,396 Speaker 1: was too late, and I can also tell you in 177 00:10:13,436 --> 00:10:17,476 Speaker 1: some places it's too early. And this is the problem 178 00:10:17,516 --> 00:10:21,956 Speaker 1: with the germ of truth that the kind of cynics 179 00:10:22,036 --> 00:10:24,356 Speaker 1: are having out there, of like, oh, this is much 180 00:10:24,396 --> 00:10:30,316 Speaker 1: ado and we're overreacting. Well, in some cities, maybe we are, 181 00:10:31,076 --> 00:10:34,876 Speaker 1: but we don't know which. And so we need to 182 00:10:34,916 --> 00:10:38,436 Speaker 1: have a systematic way of using the tests that we 183 00:10:38,516 --> 00:10:42,036 Speaker 1: have and using the information we've already collected to be 184 00:10:42,076 --> 00:10:45,196 Speaker 1: able to know is this virus spreading. Is it at 185 00:10:45,236 --> 00:10:47,756 Speaker 1: the point where there's sparks we can stamp out with 186 00:10:48,156 --> 00:10:51,676 Speaker 1: contact tracing, or it's too late to start to stamp 187 00:10:51,756 --> 00:10:53,956 Speaker 1: out sparks. The whole house is on fire and you 188 00:10:54,036 --> 00:10:56,356 Speaker 1: need to just turn the hose on and slow it 189 00:10:56,396 --> 00:10:59,236 Speaker 1: down and make it go a little less fast. And 190 00:10:59,316 --> 00:11:01,396 Speaker 1: how would we find out this information and number two. 191 00:11:01,396 --> 00:11:04,356 Speaker 1: If number one is door to door study, number two 192 00:11:04,476 --> 00:11:08,036 Speaker 1: is just massive testing. I take it. Actually, it's not 193 00:11:08,116 --> 00:11:11,756 Speaker 1: the number of tests, it's how you do the tests. Okay, 194 00:11:11,876 --> 00:11:13,836 Speaker 1: tell me more about that. How do you do the tests? Yeah? 195 00:11:13,916 --> 00:11:17,276 Speaker 1: The big problem is that we have two different public 196 00:11:17,276 --> 00:11:19,476 Speaker 1: health reporting systems in this country. And if you just 197 00:11:19,476 --> 00:11:21,356 Speaker 1: think about it, it kind of makes sense. Noah. Right, 198 00:11:21,836 --> 00:11:24,596 Speaker 1: you go into the doctor's office and they draw your 199 00:11:24,596 --> 00:11:27,436 Speaker 1: blood and they send it to the lab. The lab 200 00:11:27,476 --> 00:11:30,036 Speaker 1: then gets a positive result and they report it to 201 00:11:30,116 --> 00:11:33,196 Speaker 1: the public health authorities. Right, that is the laboratory arm 202 00:11:33,316 --> 00:11:37,596 Speaker 1: of public health reporting. What information does the lab have 203 00:11:37,836 --> 00:11:40,476 Speaker 1: about you? Almost none? I take it. I just know 204 00:11:40,716 --> 00:11:42,956 Speaker 1: that's your blood sample. Yeah. They know your name, and 205 00:11:42,996 --> 00:11:45,796 Speaker 1: they know your day of birth, and maybe you're addressed, 206 00:11:45,996 --> 00:11:50,276 Speaker 1: maybe not, depending Right. They don't know your symptoms, they 207 00:11:50,276 --> 00:11:52,996 Speaker 1: don't know your exposures. They don't know if you're hospitalized 208 00:11:53,196 --> 00:11:56,596 Speaker 1: or going to be hospitalized, And which is why the CDC, 209 00:11:57,236 --> 00:12:01,596 Speaker 1: in the Morbidity Immortality Weekly Report, the flagship publication of 210 00:12:01,596 --> 00:12:04,556 Speaker 1: the CDC, had their first case report of forty two 211 00:12:04,636 --> 00:12:08,636 Speaker 1: hundred plus cases positive cases in the United States. They said, 212 00:12:08,836 --> 00:12:11,916 Speaker 1: we do not know the hospitalization status of half of them, 213 00:12:14,076 --> 00:12:17,596 Speaker 1: So we didn't even know the age of ten percent 214 00:12:17,756 --> 00:12:22,876 Speaker 1: of the positive cases. So giving more testing done in 215 00:12:22,996 --> 00:12:27,276 Speaker 1: lab core and quest and hospital labs that end up 216 00:12:27,476 --> 00:12:31,956 Speaker 1: flooding the public health system with cases that we know 217 00:12:32,076 --> 00:12:36,476 Speaker 1: nothing about is not helpful. It's not getting more testing 218 00:12:36,516 --> 00:12:40,156 Speaker 1: out there, it's we want to have tests done where 219 00:12:40,196 --> 00:12:44,916 Speaker 1: the laboratory results are tied to the key clinical and 220 00:12:44,956 --> 00:12:47,556 Speaker 1: epidemologic data for us to make sense of it. So 221 00:12:47,596 --> 00:12:51,436 Speaker 1: that key data is is this person part of a 222 00:12:51,556 --> 00:12:54,156 Speaker 1: known cluster? What is their exposure? Did they travel? Do 223 00:12:54,236 --> 00:12:56,676 Speaker 1: they know someone? Do they who has it? That? We 224 00:12:56,676 --> 00:13:00,196 Speaker 1: should ask people basically on a form at the same 225 00:13:00,236 --> 00:13:02,236 Speaker 1: time as they're having their blood drawn, that forms should 226 00:13:02,236 --> 00:13:04,396 Speaker 1: be filled out. That's the simplest form of this, right, 227 00:13:04,996 --> 00:13:07,116 Speaker 1: And we should also ask them, oh, do you have 228 00:13:07,116 --> 00:13:10,836 Speaker 1: any symptoms? When did those symptoms start. With those two 229 00:13:10,876 --> 00:13:14,916 Speaker 1: pieces of data and the person's age in county, I 230 00:13:14,956 --> 00:13:17,836 Speaker 1: can now construct an epicurve and I can tell you 231 00:13:17,916 --> 00:13:20,596 Speaker 1: with those pieces of data, is the outbreak in this 232 00:13:20,636 --> 00:13:24,436 Speaker 1: city getting better or worse? But I need both parts 233 00:13:24,476 --> 00:13:27,516 Speaker 1: of that data. I need the clinical and epidemiologic risk 234 00:13:27,556 --> 00:13:31,636 Speaker 1: factor data and I need the lab data so where 235 00:13:31,756 --> 00:13:35,396 Speaker 1: can we get both of those pieces of data. We 236 00:13:35,476 --> 00:13:40,156 Speaker 1: have to set up sentinel surveillance sites where at the 237 00:13:40,356 --> 00:13:43,956 Speaker 1: cost of getting the lab test, you also will have 238 00:13:43,996 --> 00:13:46,876 Speaker 1: to fill out the form. So this is where not 239 00:13:46,956 --> 00:13:50,036 Speaker 1: just blasting the tests out there, but actually setting up 240 00:13:50,116 --> 00:13:55,436 Speaker 1: some planful places where in an emergency room, every person 241 00:13:55,476 --> 00:13:58,156 Speaker 1: who comes in with fever cough is going to get tested. 242 00:13:58,276 --> 00:14:01,316 Speaker 1: Or in a doctor's office we set up doctors offices, 243 00:14:01,716 --> 00:14:05,516 Speaker 1: we set up sentinel testing sites, or at a drive 244 00:14:05,556 --> 00:14:08,596 Speaker 1: through clinic a drive through testing site, we make sure 245 00:14:08,676 --> 00:14:12,476 Speaker 1: that we collect both pieces of information. That's how this 246 00:14:12,516 --> 00:14:15,516 Speaker 1: is going to get done. And right now I have 247 00:14:15,956 --> 00:14:24,236 Speaker 1: heard roughly nobody create an actual funded plan to resource 248 00:14:24,356 --> 00:14:29,516 Speaker 1: the development of dedicated testing sites that collect the information 249 00:14:29,636 --> 00:14:34,356 Speaker 1: at scale sufficient to answer these questions? Why far as odd? 250 00:14:34,436 --> 00:14:36,956 Speaker 1: Why is it the case that if something is as 251 00:14:36,956 --> 00:14:40,036 Speaker 1: straightforward as you're describing it as being the sentinel sites, 252 00:14:40,076 --> 00:14:42,556 Speaker 1: and I take it it's called sentinel because it gives 253 00:14:42,596 --> 00:14:44,356 Speaker 1: you an early warning of what's going on, or in 254 00:14:44,356 --> 00:14:46,756 Speaker 1: this case and not so early warning. Why is it 255 00:14:46,796 --> 00:14:48,876 Speaker 1: the case that no one is proposing that? And if 256 00:14:48,876 --> 00:14:51,716 Speaker 1: I could make the question even a little meaner, you know, 257 00:14:51,796 --> 00:14:55,756 Speaker 1: you were National Coordinator for Health IT for the Federal 258 00:14:55,796 --> 00:14:58,516 Speaker 1: Department of Health and Human Services in the Obama administration. 259 00:14:59,356 --> 00:15:02,476 Speaker 1: Why was this not part of what your team or 260 00:15:02,516 --> 00:15:05,876 Speaker 1: the broader HHS community was trying to have in a 261 00:15:05,916 --> 00:15:08,796 Speaker 1: contingency plan for the day that you knew perfectly well 262 00:15:08,836 --> 00:15:10,956 Speaker 1: would some day come where a crisis like this would 263 00:15:10,956 --> 00:15:15,716 Speaker 1: break out. Because we as humans lurch from panic to 264 00:15:15,876 --> 00:15:21,996 Speaker 1: panic in periods of complacency. That's what we do. We 265 00:15:22,076 --> 00:15:26,196 Speaker 1: all do that, and there are some more extreme examples 266 00:15:26,236 --> 00:15:31,276 Speaker 1: of where we let complacency take root. But I don't 267 00:15:31,276 --> 00:15:36,356 Speaker 1: think anyone is blameless in forgetting you just forget what 268 00:15:36,396 --> 00:15:39,076 Speaker 1: it feels like to be in this moment, Like we 269 00:15:39,116 --> 00:15:40,836 Speaker 1: should make a list of the shit we're going to 270 00:15:40,956 --> 00:15:43,756 Speaker 1: fix during the period of complacency between panic and panic. 271 00:15:43,796 --> 00:15:46,316 Speaker 1: Like we should make that list, and we should now, 272 00:15:47,556 --> 00:15:50,556 Speaker 1: and we should just stick to it for God's sake 273 00:15:50,956 --> 00:15:55,116 Speaker 1: and get it done. What's the barrier though, to simply 274 00:15:55,236 --> 00:15:59,196 Speaker 1: a national edict from CDC that says, Hey, everybody in 275 00:15:59,196 --> 00:16:02,716 Speaker 1: the country who's testing you must simultaneously fill out this 276 00:16:02,756 --> 00:16:05,476 Speaker 1: form which we're posting online right now, and you must 277 00:16:05,516 --> 00:16:08,836 Speaker 1: ask the patient about the progress of his or her symptoms. 278 00:16:08,876 --> 00:16:10,996 Speaker 1: I mean, it sounds like of all the interventions we've 279 00:16:11,076 --> 00:16:13,036 Speaker 1: you know, we can imagine that sounds like a pretty 280 00:16:13,036 --> 00:16:15,276 Speaker 1: inexpensive one, except for the coordination of the data, which 281 00:16:15,276 --> 00:16:19,316 Speaker 1: I recognize would take some work. So look, the US 282 00:16:19,316 --> 00:16:24,036 Speaker 1: system really does delegate public health to stay local officials. 283 00:16:24,436 --> 00:16:30,876 Speaker 1: The CDC is an incredibly powerful institution, but mostly through guidance, yes, funding, 284 00:16:31,596 --> 00:16:36,236 Speaker 1: but expertise, and ultimately they need to be the ones 285 00:16:36,516 --> 00:16:40,156 Speaker 1: who are front and center, who are speaking with the 286 00:16:40,236 --> 00:16:44,356 Speaker 1: voice of evidence based public health to the American people 287 00:16:44,356 --> 00:16:46,796 Speaker 1: about what the strategy should be. And let me ask you, 288 00:16:47,396 --> 00:16:49,516 Speaker 1: when was the last time the CDC was at the 289 00:16:49,556 --> 00:16:54,556 Speaker 1: podium at the Coronavirus Task Force. It's been some days. 290 00:16:54,756 --> 00:16:57,956 Speaker 1: It's been many, many, many days, so we have not 291 00:16:58,156 --> 00:17:01,876 Speaker 1: heard from and shook it. But to be fair, the 292 00:17:01,956 --> 00:17:04,196 Speaker 1: CDC doesn't have to be at the I mean, that 293 00:17:04,276 --> 00:17:06,636 Speaker 1: has some symbolic meeting, but the CDC doesn't have to 294 00:17:06,636 --> 00:17:09,276 Speaker 1: be at the podium to issue a guidance on this, 295 00:17:09,636 --> 00:17:12,556 Speaker 1: especially if it sees itself as, among other things, the 296 00:17:12,596 --> 00:17:16,316 Speaker 1: coordinator of National Data. I mean, if we had the 297 00:17:16,316 --> 00:17:18,436 Speaker 1: head of the CDC here and asked her, you know, 298 00:17:18,516 --> 00:17:20,476 Speaker 1: why haven't you done this, what would she be saying, 299 00:17:21,116 --> 00:17:23,636 Speaker 1: I don't know. I don't know, Noah. And to me, 300 00:17:24,396 --> 00:17:30,796 Speaker 1: one of my proudest career experiences was being at this CDC. 301 00:17:31,916 --> 00:17:36,636 Speaker 1: It's a fantastic institution with thousands of incredible experts, and 302 00:17:36,796 --> 00:17:40,716 Speaker 1: I just do not understand why they have not been 303 00:17:40,796 --> 00:17:43,756 Speaker 1: frem and center and leading in the way that they 304 00:17:43,876 --> 00:17:47,956 Speaker 1: know how to in this experience. I just I'm baffled, 305 00:17:47,996 --> 00:17:50,476 Speaker 1: and I don't have a good answer for you. We'll 306 00:17:50,516 --> 00:18:02,276 Speaker 1: be back in just a moment. You've given us one 307 00:18:02,276 --> 00:18:05,716 Speaker 1: in two suggestions, super clear, what's your third biggest recommendation? 308 00:18:05,916 --> 00:18:09,676 Speaker 1: So the third piece of this is a system that 309 00:18:09,756 --> 00:18:15,556 Speaker 1: I did play some part in really designing or creating 310 00:18:16,036 --> 00:18:19,956 Speaker 1: some twenty years ago, which has now become commonplace practice 311 00:18:20,036 --> 00:18:23,996 Speaker 1: in public health, which is called syndromic surveillance. And this 312 00:18:24,076 --> 00:18:27,236 Speaker 1: is saying remember I talked about how long it takes 313 00:18:27,236 --> 00:18:30,836 Speaker 1: and the data problems of getting a lap specimen confirmed 314 00:18:30,956 --> 00:18:35,276 Speaker 1: with say coronavirus. The idea here was, well, people go 315 00:18:35,356 --> 00:18:39,356 Speaker 1: to live their lives, and they register in the emergency room, 316 00:18:39,356 --> 00:18:41,516 Speaker 1: and there's a piece of data collected for that, and 317 00:18:41,556 --> 00:18:45,356 Speaker 1: they go buy medications and the phazinc at the pharmacy, 318 00:18:45,396 --> 00:18:48,036 Speaker 1: and it goes deep at the counter, and you could 319 00:18:48,076 --> 00:18:51,796 Speaker 1: gather up all those little bits and drabs of the 320 00:18:51,916 --> 00:18:56,276 Speaker 1: exhaust of administrative data that governs our lives, and you 321 00:18:56,316 --> 00:18:58,796 Speaker 1: can actually put it to purpose, putting your finger on 322 00:18:58,836 --> 00:19:01,996 Speaker 1: the pulse of the city's health in real time and detect. 323 00:19:02,396 --> 00:19:05,276 Speaker 1: At that time, we were thinking bioterrorism. Now we're thinking 324 00:19:05,316 --> 00:19:09,796 Speaker 1: coronavirus pandemic. And it turns out we spend hundreds of 325 00:19:09,836 --> 00:19:13,876 Speaker 1: millions of dollars. And as part of the health information 326 00:19:13,916 --> 00:19:18,916 Speaker 1: technology transformation that I helped push, we required hospitals to 327 00:19:18,996 --> 00:19:23,836 Speaker 1: report every emergency room visit to these state public health 328 00:19:23,996 --> 00:19:27,196 Speaker 1: systems in syndromes where you could group them and say, 329 00:19:27,436 --> 00:19:30,316 Speaker 1: does the person come in have a GI syndrome or 330 00:19:30,316 --> 00:19:33,476 Speaker 1: a respiratory syndrome or a flu syndrome? And so we 331 00:19:33,556 --> 00:19:36,356 Speaker 1: have the system. You don't have to build it. Now, 332 00:19:36,476 --> 00:19:39,076 Speaker 1: you don't have to recreate it. We've spent a lot 333 00:19:39,076 --> 00:19:41,796 Speaker 1: of money and resolved all the governance issues in state 334 00:19:41,836 --> 00:19:44,756 Speaker 1: and local blah blah blah, and we're not using it. 335 00:19:45,116 --> 00:19:47,796 Speaker 1: And again you're gonna asked me, why aren't we using it? 336 00:19:48,156 --> 00:19:51,876 Speaker 1: I don't know, I don't know. I do not know. 337 00:19:52,036 --> 00:19:55,556 Speaker 1: But the only place that has made that information publicly 338 00:19:55,596 --> 00:20:00,036 Speaker 1: available is New York City. It's literally the website that 339 00:20:00,156 --> 00:20:03,276 Speaker 1: we built fifteen years ago still works, and you can 340 00:20:03,316 --> 00:20:08,756 Speaker 1: go on that website. You can google ep query Queer 341 00:20:08,916 --> 00:20:12,956 Speaker 1: y Syndrome Surveillance, and you can go there and you 342 00:20:12,996 --> 00:20:16,356 Speaker 1: can click on the box that says influenza like illness 343 00:20:16,436 --> 00:20:19,916 Speaker 1: or respiratory and you can see the percent of all 344 00:20:19,956 --> 00:20:24,116 Speaker 1: emergency room visits daily up until I think Friday. They 345 00:20:24,116 --> 00:20:26,756 Speaker 1: have data in there now and you can look at 346 00:20:26,916 --> 00:20:30,276 Speaker 1: daily rates of emergency room visits in every emergency room 347 00:20:30,316 --> 00:20:32,676 Speaker 1: in New York City, what percent of them were for 348 00:20:32,756 --> 00:20:35,956 Speaker 1: respiratory syndrome or flu like syndrome. And what you will 349 00:20:35,956 --> 00:20:38,196 Speaker 1: see is that what has happened in the past two 350 00:20:38,196 --> 00:20:42,756 Speaker 1: weeks has never happened in New York City before. I've 351 00:20:42,796 --> 00:20:46,436 Speaker 1: been looking at this data for twenty years. Never ever 352 00:20:46,836 --> 00:20:52,276 Speaker 1: have I seen a spike in illness that sharp, that steep, 353 00:20:52,516 --> 00:20:59,076 Speaker 1: that fast. Four thousand, six hundred cases of respiratory illness 354 00:20:59,196 --> 00:21:03,716 Speaker 1: or influenza like illness presented to emergency rooms in New 355 00:21:03,796 --> 00:21:07,516 Speaker 1: York City last Thursday, a year ago. That day it 356 00:21:07,596 --> 00:21:12,596 Speaker 1: was sixteen hundred, almost a threefold increase in those visits. 357 00:21:12,916 --> 00:21:17,556 Speaker 1: It is an incredibly powerful tool for seeing what is 358 00:21:17,596 --> 00:21:20,116 Speaker 1: going on in the community. And is it actually don't 359 00:21:20,116 --> 00:21:22,516 Speaker 1: tell me that we have it? How many cases tell me? 360 00:21:22,636 --> 00:21:25,796 Speaker 1: Is it causing enough illness in the community to make 361 00:21:25,796 --> 00:21:29,636 Speaker 1: a difference to be seen in the data? And we 362 00:21:29,756 --> 00:21:32,556 Speaker 1: have it in more than just New York City. We 363 00:21:32,636 --> 00:21:35,996 Speaker 1: could look at it potentially in every state. And for 364 00:21:36,076 --> 00:21:40,236 Speaker 1: reasons that I do not understand that data is not 365 00:21:40,796 --> 00:21:48,276 Speaker 1: currently the centerpiece of our surveillance and response to this outbreak. 366 00:21:49,876 --> 00:21:52,356 Speaker 1: What am I not asking you about that you see 367 00:21:52,556 --> 00:21:55,996 Speaker 1: over the horizon going back to the national level as 368 00:21:56,556 --> 00:21:58,876 Speaker 1: a potential problem that we haven't yet flagged. And I'm 369 00:21:58,876 --> 00:22:01,076 Speaker 1: asking you that not because of your expertise only, but 370 00:22:01,156 --> 00:22:03,876 Speaker 1: because you flagged a lot of the problems that we've 371 00:22:03,916 --> 00:22:06,836 Speaker 1: been seeing earlier than other people did. So when you 372 00:22:06,876 --> 00:22:09,556 Speaker 1: look now two weeks or three weeks or even a 373 00:22:09,636 --> 00:22:12,556 Speaker 1: few months down the road, what do you see as 374 00:22:12,596 --> 00:22:15,996 Speaker 1: the most serious problems that are also not being discussed. 375 00:22:17,196 --> 00:22:25,796 Speaker 1: I'm really interested in this confluence of politics and policy 376 00:22:26,556 --> 00:22:33,116 Speaker 1: and data around when we go to these extreme measures 377 00:22:33,116 --> 00:22:38,236 Speaker 1: and when we come out, and particularly if we're not 378 00:22:38,356 --> 00:22:43,996 Speaker 1: able to mobilize suppression effectively enough that we can go 379 00:22:44,116 --> 00:22:48,716 Speaker 1: back to reclaim containment. That's what we have to be 380 00:22:48,796 --> 00:22:53,116 Speaker 1: able to do to get out of this crisis without 381 00:22:53,116 --> 00:22:56,396 Speaker 1: twenty thirty forty fifty percent of the population infected. Is 382 00:22:56,436 --> 00:22:59,956 Speaker 1: we have to reclaim containment. We have to put out 383 00:22:59,956 --> 00:23:05,356 Speaker 1: the fire and then really assemble crack teams of public 384 00:23:05,396 --> 00:23:07,636 Speaker 1: health workers who can go around, stamp and out sparks 385 00:23:07,756 --> 00:23:11,956 Speaker 1: much better than we've done before. And if we can't 386 00:23:12,036 --> 00:23:15,436 Speaker 1: do that, then we will be continually faced over the 387 00:23:15,476 --> 00:23:21,036 Speaker 1: next eighteen months until a vaccine hopefully hopefully is developed, 388 00:23:21,556 --> 00:23:25,436 Speaker 1: where we're going to be facing economic ruination and trying 389 00:23:25,476 --> 00:23:29,956 Speaker 1: to decide make those hard trade offs between how much 390 00:23:29,996 --> 00:23:33,196 Speaker 1: can we ease up and then see more people dying 391 00:23:33,276 --> 00:23:39,076 Speaker 1: and then push back down again, And every policymaker is 392 00:23:39,116 --> 00:23:41,236 Speaker 1: going to be having to make that, Every elected official 393 00:23:41,356 --> 00:23:44,436 Speaker 1: is going to be making that decision based on their 394 00:23:44,476 --> 00:23:49,756 Speaker 1: own environment. So I hope that we can reclaim containment. 395 00:23:50,036 --> 00:23:52,836 Speaker 1: I really really do. But if not, I think we're 396 00:23:52,836 --> 00:23:57,156 Speaker 1: in for eighteen months of what I fear will be 397 00:23:57,316 --> 00:24:02,236 Speaker 1: somewhat haphazard decision making around when to close, when to open, 398 00:24:02,276 --> 00:24:06,516 Speaker 1: when to reclose, when to reopen back and forth. As 399 00:24:06,516 --> 00:24:08,836 Speaker 1: far as said before I let you go, I do. 400 00:24:09,836 --> 00:24:13,036 Speaker 1: A lot of people are wondering is there any hope here? 401 00:24:13,236 --> 00:24:15,236 Speaker 1: You know? Is it all doom and gloom? What are 402 00:24:15,236 --> 00:24:19,036 Speaker 1: your thoughts on that? Earlier I was much more freaked 403 00:24:19,036 --> 00:24:20,996 Speaker 1: out when no one was talking about it. It was 404 00:24:21,036 --> 00:24:25,596 Speaker 1: just freaking me out. And now I'm actually much less 405 00:24:25,596 --> 00:24:29,196 Speaker 1: freaked now that everyone's talking about it, because what I 406 00:24:29,196 --> 00:24:32,756 Speaker 1: am seeing is, even in the absence of a plan, 407 00:24:32,916 --> 00:24:34,956 Speaker 1: even in the absence of a strategy, even in the 408 00:24:34,956 --> 00:24:40,796 Speaker 1: absence of data, I'm seeing massive behavior change in society, 409 00:24:41,236 --> 00:24:46,836 Speaker 1: each person, each company, each school, each mayor deciding for themselves, 410 00:24:46,876 --> 00:24:51,996 Speaker 1: each person deciding for themselves that they're gonna live life 411 00:24:52,036 --> 00:24:55,756 Speaker 1: a little bit differently. I'm not seeing very much handshaking 412 00:24:56,156 --> 00:24:59,516 Speaker 1: right now. I'm not going to any conferences that airports 413 00:24:59,516 --> 00:25:03,676 Speaker 1: are deserted. Like. This stuff doesn't have to be perfect 414 00:25:03,796 --> 00:25:07,076 Speaker 1: to work, and I think it's working. We don't know 415 00:25:07,116 --> 00:25:11,156 Speaker 1: if it's working. We won't probably for several weeks at 416 00:25:11,236 --> 00:25:15,436 Speaker 1: least under the best of circumstances. But I'm optimistic that 417 00:25:15,476 --> 00:25:19,596 Speaker 1: it's working because the average number of contacts just has 418 00:25:19,676 --> 00:25:21,916 Speaker 1: to come down. That's all we're trying to do to 419 00:25:22,036 --> 00:25:25,396 Speaker 1: go from an effective reproductive number of two point five 420 00:25:25,596 --> 00:25:29,556 Speaker 1: are not down to and are effective of less than one. Well, 421 00:25:29,596 --> 00:25:32,756 Speaker 1: what that means is that if you had ten contacts 422 00:25:32,876 --> 00:25:35,316 Speaker 1: a week before, you want to get down a four 423 00:25:35,516 --> 00:25:38,676 Speaker 1: on average. If you can do that, will beat this thing. Right, 424 00:25:38,756 --> 00:25:42,316 Speaker 1: The number of new infections that each person causes will 425 00:25:42,316 --> 00:25:44,476 Speaker 1: be less than one, and this thing will extinguish on 426 00:25:44,516 --> 00:25:47,356 Speaker 1: its own. If before, on average, you went to the 427 00:25:47,436 --> 00:25:49,916 Speaker 1: gym five days a week, and now you go no 428 00:25:50,036 --> 00:25:53,236 Speaker 1: more than two. If everybody did that, this thing would 429 00:25:53,236 --> 00:25:57,036 Speaker 1: snuff out. And I think some people are not doing it. 430 00:25:57,276 --> 00:26:01,156 Speaker 1: Other people are doing it to a great much greater extent, 431 00:26:01,476 --> 00:26:05,316 Speaker 1: and on average, I really do think all of us, 432 00:26:05,356 --> 00:26:09,476 Speaker 1: acting individually, are making a difference. So keep doing it, America. 433 00:26:10,076 --> 00:26:12,796 Speaker 1: Despite all of the stuff I talked about, at the 434 00:26:12,836 --> 00:26:16,756 Speaker 1: bottom line, what matters is can we change our habits? 435 00:26:16,796 --> 00:26:19,036 Speaker 1: And that for me, the bright glimmer of hope here 436 00:26:19,436 --> 00:26:24,716 Speaker 1: is Japan. Actually, because Japan did not pump out a 437 00:26:24,756 --> 00:26:28,276 Speaker 1: ton of testing, but that what they did do is 438 00:26:28,596 --> 00:26:33,596 Speaker 1: they embraced their sense of responsibility to each other. And 439 00:26:34,236 --> 00:26:38,316 Speaker 1: I think that is in some ways more feasible for 440 00:26:38,436 --> 00:26:43,556 Speaker 1: us to embrace than you know, contact tracing tens of 441 00:26:43,596 --> 00:26:47,836 Speaker 1: thousands of people in New York City every day. Well, 442 00:26:47,916 --> 00:26:51,716 Speaker 1: if Americans can pull together by staying not together, then 443 00:26:51,756 --> 00:26:55,116 Speaker 1: maybe they can accomplish exactly what you're what you're talking about, Brazza, 444 00:26:55,276 --> 00:26:58,516 Speaker 1: thank you for helping us not go completely off the rails, 445 00:26:58,836 --> 00:27:01,956 Speaker 1: but simultaneously, thanks for the clarity and honesty and directness 446 00:27:01,956 --> 00:27:05,596 Speaker 1: of your analysis. Thank you. Noah, Well, there you have. 447 00:27:05,916 --> 00:27:09,796 Speaker 1: Farzad Mustashari, whose whole career has been trying to leverage 448 00:27:10,156 --> 00:27:13,076 Speaker 1: data for public health, is very worried that we do 449 00:27:13,156 --> 00:27:15,276 Speaker 1: not have the kind of data that we need and 450 00:27:15,356 --> 00:27:17,876 Speaker 1: that it's not entirely clear we can get it without 451 00:27:17,916 --> 00:27:21,556 Speaker 1: a substantial change in policy. That said, he does not 452 00:27:21,716 --> 00:27:24,156 Speaker 1: think that the world is over. And it's significant to 453 00:27:24,236 --> 00:27:26,996 Speaker 1: my mind that somebody who was in his own terms, 454 00:27:27,196 --> 00:27:30,236 Speaker 1: freaking out about this a month ago is now calmer 455 00:27:30,396 --> 00:27:32,956 Speaker 1: than he was and does believe that our efforts at 456 00:27:32,956 --> 00:27:37,316 Speaker 1: social distancing may be having good effects, imprecise and imperfect 457 00:27:37,436 --> 00:27:40,156 Speaker 1: though they are, so it's a mixed picture. We could 458 00:27:40,156 --> 00:27:42,236 Speaker 1: be doing a lot better, we could be doing this 459 00:27:42,396 --> 00:27:46,076 Speaker 1: a lot more rationally, but we're not facing in his view, 460 00:27:46,276 --> 00:27:49,676 Speaker 1: the kind of existential threat that we cannot defeat based 461 00:27:49,756 --> 00:27:53,356 Speaker 1: on the social distancing techniques that are presently being used. 462 00:27:53,956 --> 00:27:57,796 Speaker 1: Until next time, be safe, take care of yourselves, maintain 463 00:27:57,876 --> 00:28:02,076 Speaker 1: that distance. Deep Background is brought to you by Pushkin Industries. 464 00:28:02,316 --> 00:28:06,396 Speaker 1: Our producer is Lydia Jeane Caught with research help from Zooequin. 465 00:28:06,956 --> 00:28:10,716 Speaker 1: Mastering is by Jason Gambrell and Martinezalez. Our showrunner is 466 00:28:10,716 --> 00:28:13,916 Speaker 1: Sophie mcibbon. Our theme music is composed by Luis gera 467 00:28:14,436 --> 00:28:18,036 Speaker 1: special thanks to the Pushkin Brass, Malcolm Gladwell, Jacob Weisberg 468 00:28:18,116 --> 00:28:21,356 Speaker 1: and Mia Lovel. I'm Noah Feldt. I also write a 469 00:28:21,356 --> 00:28:23,996 Speaker 1: regular column from Bloomberg Opinion, which you can find at 470 00:28:24,036 --> 00:28:28,356 Speaker 1: Bloomberg dot com slash felt. To discover Bloomberg's original slate 471 00:28:28,396 --> 00:28:32,676 Speaker 1: of podcasts, go to Bloomberg dot com slash Podcasts. You 472 00:28:32,676 --> 00:28:36,356 Speaker 1: can follow me on Twitter at Noah rfeld This is 473 00:28:36,396 --> 00:28:37,276 Speaker 1: Deep Background.