1 00:00:03,560 --> 00:00:07,080 Speaker 1: Hi everyone, I'm Katie Kuric and this is next question. 2 00:00:08,840 --> 00:00:11,480 Speaker 1: Best Selling author Michael Lewis has a real knack for 3 00:00:11,600 --> 00:00:16,680 Speaker 1: extracting page turning drama out of otherwise mundane and complicated 4 00:00:16,720 --> 00:00:23,480 Speaker 1: subjects like the housing bubble, bond sales, and baseball stats. 5 00:00:24,120 --> 00:00:27,400 Speaker 1: Several of those nonfiction books have been turned into award winning, 6 00:00:27,560 --> 00:00:31,880 Speaker 1: celebrity packed films like The Big Short, mortgage backed securities, 7 00:00:32,600 --> 00:00:37,120 Speaker 1: sub prime loans, tranches. It's pretty confusing, right, does it 8 00:00:37,159 --> 00:00:40,760 Speaker 1: make you feel bored? We're stupid? Well, it's supposed to 9 00:00:41,200 --> 00:00:44,600 Speaker 1: add moneyball John Be's on base percentage with four seven, 10 00:00:45,000 --> 00:00:49,960 Speaker 1: Damon's on base and I'll made this with Add that 11 00:00:50,080 --> 00:00:57,080 Speaker 1: up and you get divided by three. That's what we're 12 00:00:57,080 --> 00:01:04,920 Speaker 1: looking for. Three ball players, three ball players. Who's is now? 13 00:01:05,000 --> 00:01:08,560 Speaker 1: Michael Lewis is taking a crack at our pandemic reality, 14 00:01:08,959 --> 00:01:12,200 Speaker 1: which is still unfolding. His new book is called The 15 00:01:12,240 --> 00:01:17,160 Speaker 1: Premonition of Pandemic Story through the lens of three really 16 00:01:17,200 --> 00:01:22,360 Speaker 1: remarkable scientists. Michael tries to unravel the government's gross mismanagement 17 00:01:22,360 --> 00:01:25,800 Speaker 1: of the COVID response that's led to nearly six hundred 18 00:01:25,840 --> 00:01:30,640 Speaker 1: thousand deaths, which is among the World's Worst Outcomes. You'll 19 00:01:30,680 --> 00:01:32,920 Speaker 1: get to hear from one of the main characters in 20 00:01:32,959 --> 00:01:36,360 Speaker 1: the book later in this episode, but for now, let's 21 00:01:36,400 --> 00:01:41,760 Speaker 1: start with Michael Lewis. So, Michael Lewis, first of all, 22 00:01:42,040 --> 00:01:44,840 Speaker 1: so great to have you again on the podcast. And 23 00:01:45,280 --> 00:01:49,440 Speaker 1: how crazy is it that your last book, The Fifth Risk, 24 00:01:50,240 --> 00:01:53,080 Speaker 1: was all about, quote, what happens when the people in 25 00:01:53,200 --> 00:01:57,280 Speaker 1: charge of managing risks have no interest in them and 26 00:01:57,640 --> 00:02:02,400 Speaker 1: boom the pandemic hits were you basically proves your thesis. 27 00:02:04,160 --> 00:02:07,200 Speaker 1: You know, I don't want to gloat about this. It's 28 00:02:07,200 --> 00:02:09,520 Speaker 1: not an attractive it's not an attractive way to go 29 00:02:09,560 --> 00:02:13,160 Speaker 1: through life, but I did. The point of The Fifth 30 00:02:13,240 --> 00:02:15,800 Speaker 1: Risk was you don't know what's gonna happen. Right. We 31 00:02:15,919 --> 00:02:19,760 Speaker 1: have this instrument called the government that is uniquely suited 32 00:02:19,800 --> 00:02:22,480 Speaker 1: to deal with certain kinds of problems, and there's no 33 00:02:22,560 --> 00:02:26,240 Speaker 1: other instrument to deal with them, and pandemic disease is 34 00:02:26,320 --> 00:02:28,959 Speaker 1: one of them. And the fact that kind of like 35 00:02:29,080 --> 00:02:31,800 Speaker 1: then the Trump people rolled in and didn't pay much 36 00:02:31,840 --> 00:02:33,840 Speaker 1: attention to the government and said it was basically the 37 00:02:33,880 --> 00:02:36,480 Speaker 1: problem and didn't get the transition briefings and all that. 38 00:02:37,120 --> 00:02:39,880 Speaker 1: I did have this terror like what's gonna happen? How 39 00:02:39,919 --> 00:02:42,200 Speaker 1: is it gonna kill me? And and I didn't have 40 00:02:42,400 --> 00:02:44,519 Speaker 1: I didn't have any specific sense of like what was 41 00:02:44,520 --> 00:02:46,840 Speaker 1: gonna happen next, But I thought one of these risks 42 00:02:46,840 --> 00:02:49,960 Speaker 1: is gonna become reality and then you're gonna see what 43 00:02:50,080 --> 00:02:53,760 Speaker 1: happens when you when you just abdicate the responsibility. So 44 00:02:53,800 --> 00:02:55,639 Speaker 1: that's what's got me interested in the in writing in 45 00:02:55,680 --> 00:02:57,400 Speaker 1: the book in the first place was just like, well, 46 00:02:57,520 --> 00:03:02,720 Speaker 1: it happened, what happens next? You might be the only writer, author, 47 00:03:02,840 --> 00:03:07,679 Speaker 1: reporter Michael who doesn't point a finger squarely in Trump's direction. 48 00:03:08,000 --> 00:03:10,360 Speaker 1: And in fact, one of the people you profile in 49 00:03:10,400 --> 00:03:15,080 Speaker 1: your book says, basically, Trump is a comorbidity of a 50 00:03:15,200 --> 00:03:19,720 Speaker 1: larger disease. Can you explain what he meant by that? Yeah. 51 00:03:19,880 --> 00:03:22,320 Speaker 1: All of the characters in the book, the three main characters, 52 00:03:22,320 --> 00:03:26,600 Speaker 1: had been engaged pretty intensely with the question of what 53 00:03:26,800 --> 00:03:30,000 Speaker 1: happens if a pathogen lands in America and it starts 54 00:03:30,040 --> 00:03:34,160 Speaker 1: to spread well before Trump, and they had all seen 55 00:03:34,320 --> 00:03:36,760 Speaker 1: that the tools we had to deal with it were inadequate. 56 00:03:36,800 --> 00:03:39,080 Speaker 1: They had all seen that, particularly the CDC was not 57 00:03:39,200 --> 00:03:42,040 Speaker 1: really up to controlling disease. It was more like we're 58 00:03:42,080 --> 00:03:44,960 Speaker 1: like an academic institution, and that they could all see 59 00:03:45,280 --> 00:03:47,760 Speaker 1: that we didn't have a system of public health, like 60 00:03:47,840 --> 00:03:50,240 Speaker 1: it just didn't exist. What we have is these people 61 00:03:50,240 --> 00:03:52,760 Speaker 1: who were in this extraordinary role of being local public 62 00:03:52,800 --> 00:03:56,560 Speaker 1: health officers, and that they they're kind of tasked with 63 00:03:56,800 --> 00:04:00,240 Speaker 1: battlefield command on the ground, but they aren't real source. 64 00:04:00,360 --> 00:04:03,240 Speaker 1: They've been starved or resources for a generation. And the 65 00:04:03,320 --> 00:04:07,080 Speaker 1: focus oddly had not been for a long time on 66 00:04:07,520 --> 00:04:11,360 Speaker 1: like pandemics, it had been on bio terrorism, if it 67 00:04:11,680 --> 00:04:14,480 Speaker 1: had been on other things. So these people could see that, 68 00:04:14,600 --> 00:04:17,160 Speaker 1: all right, it doesn't matter who's president. We we have 69 00:04:17,680 --> 00:04:19,480 Speaker 1: a problem, like we have a problem that we don't 70 00:04:19,480 --> 00:04:23,040 Speaker 1: have the tool to deal with this. So when they 71 00:04:23,040 --> 00:04:25,640 Speaker 1: would not say that Trump helped, they would say something like, 72 00:04:25,960 --> 00:04:29,960 Speaker 1: we once had this machine. It worked pretty well. We 73 00:04:30,000 --> 00:04:32,880 Speaker 1: allowed it to rust and decay and it was still 74 00:04:32,880 --> 00:04:35,280 Speaker 1: sort of creaking down the highway, and then came a 75 00:04:35,320 --> 00:04:37,640 Speaker 1: president who took a sledge hander to it. But it 76 00:04:37,720 --> 00:04:40,479 Speaker 1: was it was the machine was not it was not 77 00:04:40,520 --> 00:04:43,039 Speaker 1: in good shape when he was elected. So so that 78 00:04:43,120 --> 00:04:45,839 Speaker 1: they weren't they they think of him as more symptom 79 00:04:45,920 --> 00:04:48,599 Speaker 1: than cause it's sort of like the same spirit that 80 00:04:48,680 --> 00:04:51,800 Speaker 1: elected him led to the corrosion of the machine in 81 00:04:51,839 --> 00:04:54,800 Speaker 1: the first place. But you also write that George W. 82 00:04:55,000 --> 00:05:00,240 Speaker 1: Bush actually set things in motion for pandemic preparedness after 83 00:05:00,279 --> 00:05:03,800 Speaker 1: reading The Great Influenza by John M. Berry, and that 84 00:05:03,880 --> 00:05:07,240 Speaker 1: was about the nineteen eighteen pandemic. Uh and he read 85 00:05:07,279 --> 00:05:10,559 Speaker 1: it when he was on vacation, and he decided something 86 00:05:10,640 --> 00:05:14,039 Speaker 1: needs to be done about this. So does George W. 87 00:05:14,160 --> 00:05:17,280 Speaker 1: Bush deserve a little more credit than he is getting 88 00:05:17,320 --> 00:05:21,000 Speaker 1: in terms of at least seen that this was a 89 00:05:21,000 --> 00:05:24,440 Speaker 1: potential threat to the country in the world. He deserves 90 00:05:24,520 --> 00:05:27,080 Speaker 1: huge credit. I mean, I'm a little surprised to find 91 00:05:27,120 --> 00:05:30,720 Speaker 1: myself saying that, but he deserves huge credit. And he 92 00:05:30,720 --> 00:05:33,039 Speaker 1: he was freaked out, in a freaked out state of 93 00:05:33,040 --> 00:05:34,719 Speaker 1: mind when he read it, because not only did he 94 00:05:34,760 --> 00:05:36,839 Speaker 1: have nine eleven in the rear view mirror, but he 95 00:05:36,880 --> 00:05:40,440 Speaker 1: had Katrina basically on his desk, and it was like, 96 00:05:40,480 --> 00:05:43,040 Speaker 1: what else could go wrong? And he reads this book 97 00:05:43,120 --> 00:05:45,040 Speaker 1: about nineteen eight and he turns to someone in the 98 00:05:45,040 --> 00:05:47,960 Speaker 1: White House and he says, what's our pandemic plan? And 99 00:05:47,960 --> 00:05:50,360 Speaker 1: the person says, we don't. We don't have one. And 100 00:05:50,920 --> 00:05:53,360 Speaker 1: it was it was a really interesting case of how 101 00:05:53,480 --> 00:05:56,440 Speaker 1: fast the government can move when the president's piste off, 102 00:05:56,880 --> 00:05:59,599 Speaker 1: it was, you know, a couple of weeks from that 103 00:05:59,640 --> 00:06:04,800 Speaker 1: moment to him using a rapidly sketched out plan by 104 00:06:04,839 --> 00:06:07,120 Speaker 1: a doctor who was in the White House name region 105 00:06:07,200 --> 00:06:09,960 Speaker 1: kaya you know, just a few pages to ask for 106 00:06:10,040 --> 00:06:13,279 Speaker 1: seven billion dollars from Congress, could go about planning for 107 00:06:13,320 --> 00:06:16,320 Speaker 1: a pandemic. And you can trace back to that moment 108 00:06:17,000 --> 00:06:19,760 Speaker 1: not only my main couple of my main characters, but 109 00:06:20,400 --> 00:06:22,560 Speaker 1: the whole plan to have a vaccine that that was 110 00:06:22,640 --> 00:06:25,160 Speaker 1: not based on using chicken eggs. I mean that the 111 00:06:25,520 --> 00:06:29,160 Speaker 1: reason we have vaccines so fast now is stuff they 112 00:06:29,200 --> 00:06:31,960 Speaker 1: did back then. So that was an example that's sort 113 00:06:31,960 --> 00:06:34,039 Speaker 1: of a shiny bright spot, like an example of the 114 00:06:34,080 --> 00:06:37,360 Speaker 1: government taking on a problem figuring out how to deal 115 00:06:37,400 --> 00:06:41,760 Speaker 1: with it. The problem is the strategy they cooked up 116 00:06:42,240 --> 00:06:47,320 Speaker 1: for how to limit death and disease before the vaccine arrives, 117 00:06:47,760 --> 00:06:50,880 Speaker 1: which is wholly original. All the social distancing that came 118 00:06:50,920 --> 00:06:54,800 Speaker 1: out of their plan. It was swallowed and understood hook 119 00:06:54,839 --> 00:06:57,960 Speaker 1: line and sinker bout foreign countries who the CDC explained 120 00:06:58,000 --> 00:07:00,640 Speaker 1: it to, and we never really got minds around it. 121 00:07:01,040 --> 00:07:03,279 Speaker 1: We were never prepared to do the things that you 122 00:07:03,320 --> 00:07:06,400 Speaker 1: needed to do to contain a virus. Well, if George W. 123 00:07:06,600 --> 00:07:11,400 Speaker 1: Bush deserves credit, conversely, does Barack Obama deserves some of 124 00:07:11,400 --> 00:07:15,280 Speaker 1: the blame for letting this apparatus rust, as you said, 125 00:07:15,360 --> 00:07:18,760 Speaker 1: to a point where it had been corroded so significantly 126 00:07:18,920 --> 00:07:21,440 Speaker 1: that Trump just had to put a sledgehammer to it 127 00:07:21,720 --> 00:07:24,920 Speaker 1: and destroy it. No, it's more complicated than that. So 128 00:07:25,080 --> 00:07:27,960 Speaker 1: that if you'd ask those guys in the Bush white House, 129 00:07:28,120 --> 00:07:31,000 Speaker 1: who's one of them stayed on into the Obama White 130 00:07:31,000 --> 00:07:34,160 Speaker 1: House and brought his fellows back to help deal with 131 00:07:34,200 --> 00:07:36,720 Speaker 1: the pandemic that didn't happen, the two thousand nine swine 132 00:07:36,760 --> 00:07:41,280 Speaker 1: flu pandemic, they would say it was a decade long 133 00:07:41,480 --> 00:07:45,800 Speaker 1: anyway process to implementing this plan, and that they'd say 134 00:07:45,800 --> 00:07:48,560 Speaker 1: a couple of things. They'd say, One that Obama made 135 00:07:48,560 --> 00:07:51,920 Speaker 1: the same mistake every other president made in the very beginning, 136 00:07:52,200 --> 00:07:54,600 Speaker 1: but then corrected. And the mistake was to kind of 137 00:07:54,600 --> 00:07:59,640 Speaker 1: shove to one side pandemic risk, meaning it wasn't it 138 00:07:59,720 --> 00:08:02,560 Speaker 1: wasn't immediately on the National Security Council as a thing 139 00:08:02,600 --> 00:08:06,960 Speaker 1: that responsibility. Bush has sort of elevated it for I 140 00:08:06,960 --> 00:08:09,720 Speaker 1: don't know about months. Obama kind of put it to 141 00:08:09,720 --> 00:08:11,680 Speaker 1: one side, but then brought it back quickly. And the 142 00:08:11,720 --> 00:08:14,840 Speaker 1: Obama administration actually did a really good job of trying 143 00:08:14,840 --> 00:08:18,720 Speaker 1: to institutionalize pandemic response in the White House. The Trump 144 00:08:18,720 --> 00:08:22,000 Speaker 1: administration got rid of that, and uh, and that that 145 00:08:22,080 --> 00:08:25,440 Speaker 1: was a problem. The other problem, I think and is 146 00:08:25,600 --> 00:08:29,360 Speaker 1: it's bigger than Obama. It's generational. It's sort of like 147 00:08:29,680 --> 00:08:31,400 Speaker 1: if it's a sin, I don't think of it as 148 00:08:31,440 --> 00:08:34,199 Speaker 1: a sin. It's like a cinemomission. In the case of 149 00:08:34,240 --> 00:08:37,520 Speaker 1: that administration, is that there is this argument that the 150 00:08:37,640 --> 00:08:40,600 Speaker 1: only way we're going to deal with these problems really 151 00:08:40,600 --> 00:08:44,120 Speaker 1: well is is pretty serious government reform, and it means 152 00:08:44,160 --> 00:08:48,200 Speaker 1: actually reforming institutions like the CDC. I think the characters 153 00:08:48,200 --> 00:08:51,240 Speaker 1: in the Bush administration who cooked up our pandemic plan 154 00:08:51,320 --> 00:08:55,080 Speaker 1: made one big mistake. They overestimated the ability of the 155 00:08:55,120 --> 00:08:58,720 Speaker 1: CDC to execute it. So they they thought, we embedded 156 00:08:58,720 --> 00:09:02,199 Speaker 1: in the CDC and we're done. It's good. The CDC 157 00:09:02,400 --> 00:09:04,680 Speaker 1: will run this thing like a like a war general. 158 00:09:05,160 --> 00:09:08,520 Speaker 1: And they overestimated the kind of the willingness, the bravery, 159 00:09:08,679 --> 00:09:12,000 Speaker 1: the capacities of the CDC, because all along the CDC 160 00:09:12,200 --> 00:09:15,120 Speaker 1: had been becoming for you know, it's been on a 161 00:09:15,120 --> 00:09:18,960 Speaker 1: steady drift for decades to becoming this kind of highly 162 00:09:19,000 --> 00:09:23,000 Speaker 1: politicized academic institution. You know, that was so shocking to me. 163 00:09:23,040 --> 00:09:26,120 Speaker 1: I mean, the CDC, as you point out in your book, 164 00:09:26,320 --> 00:09:29,920 Speaker 1: is so dysfunctional, and I guess the downward slide began 165 00:09:30,040 --> 00:09:35,040 Speaker 1: in the late seventies. I mean, basically, what happened to 166 00:09:35,080 --> 00:09:38,160 Speaker 1: the CDC. It lost its independence, as you say, it 167 00:09:38,280 --> 00:09:43,440 Speaker 1: became politicized, and the White House in essence had too 168 00:09:43,480 --> 00:09:46,319 Speaker 1: much control over it, and it became less and less 169 00:09:46,400 --> 00:09:50,640 Speaker 1: and less independent. Is that a fairer yes? Synopsis. Yeah, 170 00:09:50,640 --> 00:09:53,520 Speaker 1: it's a very curious thing, the relationship between the White 171 00:09:53,559 --> 00:09:56,160 Speaker 1: House and the CDC. But you go, what happened was 172 00:09:56,280 --> 00:09:58,800 Speaker 1: there was a there was a mistake the CDC made 173 00:09:58,840 --> 00:10:01,840 Speaker 1: back way back in the seven when it took charge 174 00:10:02,120 --> 00:10:05,280 Speaker 1: of what looked like a dead lea virus coming to America. 175 00:10:05,280 --> 00:10:07,240 Speaker 1: It looked like there was gonna be a swine flu outbreak. 176 00:10:07,280 --> 00:10:10,320 Speaker 1: There had been one, a little one in New Jersey 177 00:10:10,360 --> 00:10:14,640 Speaker 1: in the spring. They advocated rushing to vaccinate all Americans. 178 00:10:15,800 --> 00:10:18,240 Speaker 1: Some people died, not many, but anful people died from 179 00:10:18,240 --> 00:10:20,480 Speaker 1: the vaccine. And then they stopped vaccinating people in the 180 00:10:20,559 --> 00:10:24,400 Speaker 1: and the pandemic never happened. After that, the CDC director 181 00:10:24,520 --> 00:10:29,440 Speaker 1: ceases to be a career official who's got the protection 182 00:10:29,440 --> 00:10:33,320 Speaker 1: of a permanent public servant who the president just can't fire, 183 00:10:33,920 --> 00:10:36,640 Speaker 1: and who as also who runs the place for like 184 00:10:36,679 --> 00:10:39,160 Speaker 1: a decade or more and has a very long term 185 00:10:39,240 --> 00:10:43,080 Speaker 1: view of the institution. It's changed to a presidential appointing 186 00:10:43,080 --> 00:10:46,560 Speaker 1: to a political appointing, which means that almost implicitly that 187 00:10:46,640 --> 00:10:49,000 Speaker 1: the guy whoever, whoever is running the place is gonna 188 00:10:49,000 --> 00:10:51,440 Speaker 1: be running for eighteen months or two years. They're gonna 189 00:10:51,480 --> 00:10:53,319 Speaker 1: be on a much shorter leased with the White House. 190 00:10:53,600 --> 00:10:56,160 Speaker 1: They're gonna be of the political party of the president 191 00:10:56,240 --> 00:10:59,960 Speaker 1: most likely, they're gonna be and they're view they're gonna 192 00:11:00,040 --> 00:11:02,719 Speaker 1: your renter instead of a home right. They're gonna be 193 00:11:02,760 --> 00:11:06,360 Speaker 1: thinking of like, just avoid whatever the problems catastrophes of 194 00:11:06,360 --> 00:11:08,400 Speaker 1: the next eighteen months or two years are, rather than 195 00:11:08,679 --> 00:11:11,120 Speaker 1: build this institution for the moment it's going to be 196 00:11:11,200 --> 00:11:13,840 Speaker 1: most needed, which is in probably in the distant future. 197 00:11:14,400 --> 00:11:17,560 Speaker 1: To me, the story was so rich because this isn't 198 00:11:17,600 --> 00:11:19,480 Speaker 1: just the CDC. This has happened to a lot of 199 00:11:19,600 --> 00:11:23,280 Speaker 1: institutions in Washington. We have four thousand and something presidential 200 00:11:23,559 --> 00:11:27,040 Speaker 1: political appointees who come in and purport to run these places. 201 00:11:27,400 --> 00:11:29,880 Speaker 1: And it's just impossible. If you're if what you are 202 00:11:30,040 --> 00:11:33,520 Speaker 1: is an eighteen month visitors some vast institution, how are 203 00:11:33,520 --> 00:11:35,360 Speaker 1: you going to lead that place? And you really are 204 00:11:35,480 --> 00:11:37,280 Speaker 1: going to leave that place. You're gonna be better or 205 00:11:37,320 --> 00:11:39,720 Speaker 1: worse than the person who came before you. But no 206 00:11:39,880 --> 00:11:42,760 Speaker 1: company would do this right. You would never say I 207 00:11:42,880 --> 00:11:45,840 Speaker 1: got to change your CEO every eighteen months, and they've 208 00:11:45,840 --> 00:11:49,680 Speaker 1: got to be of a particular political affiliation. Were you 209 00:11:49,760 --> 00:11:52,160 Speaker 1: shocked by that? Were you shocked? I mean, you wouldn't 210 00:11:52,200 --> 00:11:54,720 Speaker 1: have been shocked but because of the fifth risk. But 211 00:11:54,800 --> 00:11:56,600 Speaker 1: when it came to the c d C, was that 212 00:11:56,720 --> 00:11:59,640 Speaker 1: shocking to you? There was a combination of shock and 213 00:11:59,720 --> 00:12:03,440 Speaker 1: miss read because to me, the CDC had this, you know, 214 00:12:03,480 --> 00:12:06,360 Speaker 1: golden reputation. It was one of those bright spots in 215 00:12:06,360 --> 00:12:09,600 Speaker 1: the government. I would have thought it earned that reputation, 216 00:12:10,480 --> 00:12:13,520 Speaker 1: but it earned it like a long time ago, the fifties, 217 00:12:13,559 --> 00:12:17,000 Speaker 1: the sixties, the seventies, and then then things start to 218 00:12:17,000 --> 00:12:20,280 Speaker 1: get murkier. So yes, I was shocked by their behavior 219 00:12:20,280 --> 00:12:23,400 Speaker 1: in the pandemic. It's incredible that they're like preventing people 220 00:12:23,440 --> 00:12:26,160 Speaker 1: from being tested for COVID who come back from wulan 221 00:12:26,480 --> 00:12:28,760 Speaker 1: because their test doesn't work, or because they don't want 222 00:12:28,800 --> 00:12:30,280 Speaker 1: to find it because if they find it, they have 223 00:12:30,320 --> 00:12:32,360 Speaker 1: a problem with Trump because Trump doesn't want to find it. 224 00:12:32,640 --> 00:12:35,240 Speaker 1: That's that It shocked me that they issued all this 225 00:12:35,360 --> 00:12:38,760 Speaker 1: guidance that was wrong. All that stuff was shocking, But 226 00:12:38,800 --> 00:12:41,360 Speaker 1: there was this mystery attached to the shock. How did 227 00:12:41,400 --> 00:12:44,160 Speaker 1: it happen? Like, how did this place? It's not filled 228 00:12:44,160 --> 00:12:46,880 Speaker 1: with evil people, It's filled with probably really good people 229 00:12:46,960 --> 00:12:49,280 Speaker 1: who were just in a bad system. Like how did 230 00:12:49,360 --> 00:12:52,320 Speaker 1: it get so systematically wrong? That was the thing that 231 00:12:52,400 --> 00:12:55,040 Speaker 1: was the mystery to me and for my characters. You know, 232 00:12:55,200 --> 00:12:57,160 Speaker 1: Charity Dean, who was the main character of the book, 233 00:12:57,200 --> 00:13:00,760 Speaker 1: who's this local, this dynamic local public health office who's 234 00:13:00,840 --> 00:13:04,280 Speaker 1: fighting disease, you know, in hand to hand combat before 235 00:13:04,400 --> 00:13:09,079 Speaker 1: COVID finds that the CDC so interferes with her ability 236 00:13:09,120 --> 00:13:11,840 Speaker 1: to stop people from getting sick and dying that she 237 00:13:11,880 --> 00:13:15,160 Speaker 1: has to ban them from her investigations. I mean, she 238 00:13:15,160 --> 00:13:17,000 Speaker 1: she knew what was going to happen if they were 239 00:13:17,040 --> 00:13:19,560 Speaker 1: when there was a pandemic. It shocked me that it 240 00:13:19,600 --> 00:13:22,920 Speaker 1: had gotten that bad, that that it had gotten gotten 241 00:13:22,960 --> 00:13:25,840 Speaker 1: so un incapable of doing the thing it was supposed 242 00:13:25,880 --> 00:13:29,480 Speaker 1: to do. I'm thinking about the hippocratic oath, you know, 243 00:13:29,600 --> 00:13:32,280 Speaker 1: first do no harm, And it sounds like they were 244 00:13:32,320 --> 00:13:38,400 Speaker 1: actually proactively harmy, not just they weren't just inefficient and ineffectual. 245 00:13:38,920 --> 00:13:43,760 Speaker 1: They were actually hindering science, which is crazy. Well, they're 246 00:13:43,800 --> 00:13:47,559 Speaker 1: hindering response right in their minds. Probably rightly, they were 247 00:13:47,640 --> 00:13:50,880 Speaker 1: doing science like you wait till all the data is 248 00:13:50,920 --> 00:13:53,840 Speaker 1: in before you allow any decisions to be made. You 249 00:13:53,880 --> 00:13:56,360 Speaker 1: make sure you have complete certainty so you don't make 250 00:13:56,400 --> 00:13:59,640 Speaker 1: any mistakes. You focus on like the you know, writing 251 00:13:59,640 --> 00:14:03,520 Speaker 1: the paper, rather than fighting the disease. And the problem 252 00:14:03,520 --> 00:14:06,680 Speaker 1: with disease war with with this kind of combat is 253 00:14:06,920 --> 00:14:10,040 Speaker 1: its battlefield you're making. You have to make decisions in 254 00:14:10,360 --> 00:14:13,760 Speaker 1: conditions of uncertainty because by the time you have certainty 255 00:14:13,840 --> 00:14:17,560 Speaker 1: is too late. By the time you have certainty, you 256 00:14:17,600 --> 00:14:20,600 Speaker 1: don't have four cases of COVID in America, you have fifty. 257 00:14:24,360 --> 00:14:26,960 Speaker 1: Up next, one of the real life doctors featured in 258 00:14:27,000 --> 00:14:30,400 Speaker 1: Michael's book, a member of a secret group of scientists 259 00:14:30,480 --> 00:14:44,080 Speaker 1: trying to save the country. That's right after this let's 260 00:14:44,080 --> 00:14:49,640 Speaker 1: talk about the Wolverines. So you find these three incredible 261 00:14:50,200 --> 00:14:53,840 Speaker 1: badass scientists. First of all, how did you find them? 262 00:14:53,880 --> 00:14:56,480 Speaker 1: How did you track them down? And what was your process? 263 00:14:56,520 --> 00:15:00,480 Speaker 1: Michael um, the three main care This came to me 264 00:15:00,520 --> 00:15:02,480 Speaker 1: in three different ways. So the fifth risk had a 265 00:15:02,560 --> 00:15:05,480 Speaker 1: jungle guy named Max Styre who runs something called the 266 00:15:05,520 --> 00:15:08,760 Speaker 1: Partnership for Public Service, who it's seeking to kind of 267 00:15:08,880 --> 00:15:11,800 Speaker 1: fix government. He said to me early on, you got 268 00:15:11,800 --> 00:15:14,600 Speaker 1: to talk to my uncle, who was the former US 269 00:15:14,840 --> 00:15:17,320 Speaker 1: Navy secretary, who said to me, if you're going to 270 00:15:17,400 --> 00:15:19,680 Speaker 1: write anything about this, you need to meet the Wolverines. 271 00:15:20,360 --> 00:15:22,560 Speaker 1: And I said, who the hell are the Wolverines And 272 00:15:22,600 --> 00:15:25,640 Speaker 1: he said, basically, they're kind of the secret group of 273 00:15:25,720 --> 00:15:28,680 Speaker 1: doctors who meet whenever there is like a had a 274 00:15:28,720 --> 00:15:31,480 Speaker 1: fear of disease, pandemic kind of problems, and they go 275 00:15:31,560 --> 00:15:33,720 Speaker 1: back and they're kind of the people who are responsible 276 00:15:33,760 --> 00:15:38,480 Speaker 1: for the invention of pandemic planning. So I was moving 277 00:15:38,520 --> 00:15:43,240 Speaker 1: through the world last March, and the Wolverine say, you've 278 00:15:43,240 --> 00:15:45,440 Speaker 1: got to meet this woman named Charity Dean, who's number 279 00:15:45,440 --> 00:15:48,200 Speaker 1: two in the Health Department California. If anybody's gonna save 280 00:15:48,240 --> 00:15:52,200 Speaker 1: if us, it's her and another character I wrote about 281 00:15:52,200 --> 00:15:55,920 Speaker 1: in the Fifth Risk, who was Obama's chief data scientist 282 00:15:56,400 --> 00:15:59,720 Speaker 1: named d J. Patel, called me up and said, I've 283 00:15:59,760 --> 00:16:01,680 Speaker 1: just I'm from trying to help the state of California, 284 00:16:01,680 --> 00:16:03,440 Speaker 1: and You've got to meet this woman named Charity Dean. 285 00:16:04,280 --> 00:16:07,080 Speaker 1: And so I wrote a note finally to the Governor 286 00:16:07,120 --> 00:16:09,200 Speaker 1: of California. To the government of California, said I want 287 00:16:09,200 --> 00:16:10,920 Speaker 1: to meet this woman named Charity Dean, and they said, no, 288 00:16:11,000 --> 00:16:13,000 Speaker 1: you can't. She didn't want to talk to you. So 289 00:16:13,240 --> 00:16:15,320 Speaker 1: it took me about four weeks to get her private 290 00:16:15,320 --> 00:16:19,880 Speaker 1: cell number, and she said they're they're lying and and 291 00:16:19,880 --> 00:16:22,800 Speaker 1: and to figure out that, yeah, she's She kind of 292 00:16:22,880 --> 00:16:25,000 Speaker 1: unifies the story and she's the character I want to 293 00:16:25,000 --> 00:16:28,600 Speaker 1: build the book around. And the wolverine who ends up 294 00:16:28,600 --> 00:16:32,640 Speaker 1: being the main character from the tribe is Carter Measure, 295 00:16:33,080 --> 00:16:36,720 Speaker 1: and he is this savant but what was so interesting 296 00:16:36,760 --> 00:16:38,640 Speaker 1: to me about him is at heart, what he was 297 00:16:39,080 --> 00:16:41,640 Speaker 1: is a a critical care doctor who, as he said, 298 00:16:41,640 --> 00:16:43,040 Speaker 1: he has a d h D or a d D 299 00:16:43,200 --> 00:16:46,000 Speaker 1: or something exampled. I can't focus unless he has a 300 00:16:46,080 --> 00:16:48,760 Speaker 1: kind of life or death problem. And he discovered his 301 00:16:48,800 --> 00:16:51,880 Speaker 1: calling in the I c U, where people were living 302 00:16:51,920 --> 00:16:56,160 Speaker 1: and dying based on his, you know, decisions, and he 303 00:16:56,200 --> 00:16:58,560 Speaker 1: had hyper focus in the I c U. And he 304 00:16:58,640 --> 00:17:02,720 Speaker 1: was just really gifted at at and through kind of 305 00:17:02,720 --> 00:17:05,800 Speaker 1: a series of accidents, he keeps being pulled up by 306 00:17:05,840 --> 00:17:10,520 Speaker 1: the society by a string to deal with versions of 307 00:17:11,200 --> 00:17:14,920 Speaker 1: like crises life or death crisis, but at the institutional level. 308 00:17:15,200 --> 00:17:18,720 Speaker 1: First he's asked to run a giant VA hospital that's 309 00:17:18,720 --> 00:17:22,000 Speaker 1: in a total state of crisis because he's obviously really competent, 310 00:17:22,040 --> 00:17:24,879 Speaker 1: they think, and he frames it is like, the patient 311 00:17:24,960 --> 00:17:27,159 Speaker 1: is now my hospital. Then he gets pulled up to 312 00:17:27,240 --> 00:17:29,840 Speaker 1: run a whole chain of hospitals and the patient is 313 00:17:29,880 --> 00:17:33,080 Speaker 1: the is this all these hospitals And I've got to 314 00:17:33,080 --> 00:17:35,240 Speaker 1: prevent them from making the mistakes that end up causing 315 00:17:35,320 --> 00:17:38,320 Speaker 1: us all this these problems, And kind of by accident, 316 00:17:38,560 --> 00:17:41,040 Speaker 1: he's pulled into the Bush White House to figure out 317 00:17:41,040 --> 00:17:44,119 Speaker 1: how to save the society from a pandemic. And he 318 00:17:44,720 --> 00:17:48,040 Speaker 1: had this this incredible ability to come at a problem 319 00:17:48,040 --> 00:17:50,680 Speaker 1: in a really weird way and think about a new 320 00:17:50,800 --> 00:17:54,879 Speaker 1: kind of solution. And then Joe Ici, who is this 321 00:17:54,960 --> 00:17:58,480 Speaker 1: biochemist at UCSF who is the most badass virus enter 322 00:17:58,520 --> 00:18:01,080 Speaker 1: on the planet, and he's serving like in the James 323 00:18:01,119 --> 00:18:05,040 Speaker 1: Bond movie. He's cute. He creates all the gadgets he 324 00:18:05,160 --> 00:18:08,119 Speaker 1: used to go kill the bad guys. I do identify 325 00:18:08,280 --> 00:18:11,840 Speaker 1: with Q, but I'd like to put it towards infectious 326 00:18:11,880 --> 00:18:14,920 Speaker 1: disease rather than you know, hiding machine guns and cars. 327 00:18:16,240 --> 00:18:19,240 Speaker 1: My name is Joseph Desi. I'm a professor in biochemistry 328 00:18:19,280 --> 00:18:22,480 Speaker 1: and biophysics at the University of California, San Francisco, and 329 00:18:22,600 --> 00:18:24,960 Speaker 1: I'm the co president of the chan Zuckerberg bio Hub. 330 00:18:26,240 --> 00:18:30,120 Speaker 1: I first met Michael Lewis in two thousand and sixteen. 331 00:18:30,760 --> 00:18:33,320 Speaker 1: Five years ago, I published a book called flash Boys. 332 00:18:33,880 --> 00:18:36,359 Speaker 1: I was a big Michael Lewis fan, having read a 333 00:18:36,440 --> 00:18:39,560 Speaker 1: number of his books. I think Flashboys is probably one 334 00:18:39,560 --> 00:18:42,399 Speaker 1: of my favorites. A money manager in San Francisco who 335 00:18:42,480 --> 00:18:44,399 Speaker 1: liked the book wanted to go to dinner, and I 336 00:18:44,480 --> 00:18:46,920 Speaker 1: said sure. It turns out the reason he wants to 337 00:18:46,960 --> 00:18:49,159 Speaker 1: go to dinner is to say I have the character 338 00:18:49,240 --> 00:18:52,960 Speaker 1: for your next book. His name is Joe Esi. I thought, 339 00:18:53,280 --> 00:18:55,960 Speaker 1: all right, I'll go have a lunch with JODORESI. I 340 00:18:56,080 --> 00:18:58,320 Speaker 1: invited him over to the Chance Like Work bio Hub, 341 00:18:58,359 --> 00:19:02,160 Speaker 1: which is a nonprofit research institute affiliated with UC Staff, Stanford, 342 00:19:02,200 --> 00:19:04,960 Speaker 1: and Berkeley. It was like sort of indifferent to whether 343 00:19:05,119 --> 00:19:06,480 Speaker 1: he was a character in one of my books. He 344 00:19:06,600 --> 00:19:08,919 Speaker 1: just like that, that's cool, I'll meet this off. Um. 345 00:19:09,520 --> 00:19:13,000 Speaker 1: He was electrical, I mean electric. I've kind of pitched 346 00:19:13,040 --> 00:19:16,600 Speaker 1: this idea of of talking about infectious disease work and 347 00:19:16,720 --> 00:19:20,680 Speaker 1: things like that, and he seemed mildly interested, but you know, 348 00:19:20,920 --> 00:19:23,760 Speaker 1: not really that. I thought, God, I wish I knew 349 00:19:23,800 --> 00:19:26,280 Speaker 1: something about science. I wish I didn't get a d 350 00:19:26,480 --> 00:19:30,160 Speaker 1: in biology myself more year in high school, because someone 351 00:19:30,200 --> 00:19:32,679 Speaker 1: should write a book about this. Gaw. I mean, he's unbelievable. 352 00:19:32,960 --> 00:19:36,040 Speaker 1: He was like doing things like hunting down pandemics and snakes, 353 00:19:36,520 --> 00:19:39,399 Speaker 1: like find finding a virus that was wiping out parents. 354 00:19:39,800 --> 00:19:42,520 Speaker 1: He was. He was finding rare bugs that were killing 355 00:19:42,600 --> 00:19:46,040 Speaker 1: people in mysterious ways. He was, And I just thought, yeah, 356 00:19:46,240 --> 00:19:48,440 Speaker 1: I want to know more about this, but I didn't. 357 00:19:48,440 --> 00:19:50,360 Speaker 1: I felt that I didn't have a reason to write 358 00:19:50,359 --> 00:19:53,520 Speaker 1: about him until this happened. That was the last I 359 00:19:53,600 --> 00:19:56,760 Speaker 1: saw of him until you know, the pandemic hit and 360 00:19:56,840 --> 00:19:59,680 Speaker 1: then suddenly he got a lot more interested in infectious 361 00:19:59,720 --> 00:20:01,879 Speaker 1: disease easy and then I called him and he was 362 00:20:01,960 --> 00:20:03,760 Speaker 1: turned out shirt off. He's smack in the middle of it. 363 00:20:05,560 --> 00:20:08,720 Speaker 1: The Chance Luckerberg biohob as I mentioned, is a nonprofit 364 00:20:08,840 --> 00:20:11,919 Speaker 1: research institute of five ones. The three affiliate with UCSF 365 00:20:12,000 --> 00:20:15,600 Speaker 1: Stanford and Berkeley, and we're a research institute that is 366 00:20:15,680 --> 00:20:19,240 Speaker 1: dedicated to some basic science and the study of infectious 367 00:20:19,280 --> 00:20:23,400 Speaker 1: diseases in particular. And so for example, we were working 368 00:20:23,640 --> 00:20:28,199 Speaker 1: on a system for early detection of emerging pathogens worldwide, 369 00:20:28,280 --> 00:20:31,639 Speaker 1: especially in low and middle income countries, and we were 370 00:20:31,720 --> 00:20:36,000 Speaker 1: working on spinning up a number of these pathogen monitoring 371 00:20:36,119 --> 00:20:40,960 Speaker 1: sites in numerous countries like Bangladesh and Cambodia and Nepal, 372 00:20:41,520 --> 00:20:44,720 Speaker 1: Pakistan and many other places, with the idea that we 373 00:20:44,920 --> 00:20:49,760 Speaker 1: needed an early warning radar and early detection network that 374 00:20:49,880 --> 00:20:54,200 Speaker 1: would help us know when something new is coming our way. 375 00:20:55,000 --> 00:20:58,760 Speaker 1: So I was helping Cambodia get set up in January. 376 00:21:00,160 --> 00:21:04,159 Speaker 1: On my trip back from Cambodia through China, compared to 377 00:21:04,320 --> 00:21:07,879 Speaker 1: when I came through China into Cambodia only about ten 378 00:21:08,000 --> 00:21:11,840 Speaker 1: days prior, there was a much heightened level of security, 379 00:21:12,640 --> 00:21:15,239 Speaker 1: and not the security of you know, um X ray 380 00:21:15,359 --> 00:21:18,200 Speaker 1: machines looking for you know, things in luggage. It was 381 00:21:18,280 --> 00:21:21,680 Speaker 1: security around people. So they were big, these big, you know, 382 00:21:22,040 --> 00:21:24,359 Speaker 1: glass and acrylic boxes that you stood in and it 383 00:21:24,520 --> 00:21:27,440 Speaker 1: monitored your fever. It was a temperature sensor with a 384 00:21:27,520 --> 00:21:29,800 Speaker 1: video monitor, and there was a lot of security personnel 385 00:21:30,359 --> 00:21:31,879 Speaker 1: and everybody had to go in there and kind of 386 00:21:31,960 --> 00:21:34,359 Speaker 1: stand one at a time, and it was, you know, 387 00:21:34,720 --> 00:21:37,320 Speaker 1: a level, a heightened level that just wasn't there ten 388 00:21:37,400 --> 00:21:43,840 Speaker 1: days earlier. And that different said to me, Okay, something's 389 00:21:43,880 --> 00:21:46,920 Speaker 1: going on. It's probably a bigger deal than we thought. 390 00:21:47,720 --> 00:21:50,119 Speaker 1: But did we have much more information than that, No, 391 00:21:50,520 --> 00:21:53,000 Speaker 1: we didn't really know. Alls I could tell is that 392 00:21:53,119 --> 00:21:57,119 Speaker 1: the feeling inside the airport, the security level and the 393 00:21:57,320 --> 00:22:03,880 Speaker 1: tenseness there, it was just something you could feel. February 394 00:22:03,880 --> 00:22:06,000 Speaker 1: of the first cases really came in here. And then, 395 00:22:06,440 --> 00:22:09,840 Speaker 1: you know, the thing that really became apparent to us 396 00:22:10,160 --> 00:22:17,000 Speaker 1: was in early March, it became completely obvious that are 397 00:22:17,119 --> 00:22:21,760 Speaker 1: testing capacity in the United States and the commercial providers 398 00:22:21,800 --> 00:22:25,640 Speaker 1: and big labs were ill suited to carry the load 399 00:22:25,720 --> 00:22:29,440 Speaker 1: that was coming. There was a tidal wave coming and 400 00:22:31,200 --> 00:22:36,840 Speaker 1: nobody had the higher ground. Everybody was going to be flooded, 401 00:22:40,040 --> 00:22:43,080 Speaker 1: and when tests were being sent out to commercial providers, 402 00:22:43,160 --> 00:22:46,240 Speaker 1: they weren't coming back for ten or fourteen days, which 403 00:22:46,320 --> 00:22:49,560 Speaker 1: is unacceptable because the window is, you know, now you 404 00:22:49,680 --> 00:22:52,120 Speaker 1: need to have an answer in less than twenty four hours. 405 00:22:52,240 --> 00:22:54,440 Speaker 1: These days, we want an answer in fifteen minutes, not 406 00:22:54,560 --> 00:22:57,479 Speaker 1: twenty four hours. At that time, I would have been 407 00:22:57,520 --> 00:23:01,160 Speaker 1: throwed with twenty four hours. And so you know, at 408 00:23:01,359 --> 00:23:04,000 Speaker 1: at the chance, like bio Hub, we have this ability 409 00:23:04,080 --> 00:23:06,760 Speaker 1: to be nimble, to change what we're doing and turn 410 00:23:06,800 --> 00:23:09,760 Speaker 1: on a dime, and we really felt that it was 411 00:23:09,800 --> 00:23:12,480 Speaker 1: going to be necessary to get into the game. We're 412 00:23:12,480 --> 00:23:15,960 Speaker 1: a bunch of molecular biologists were study infectious disease. If 413 00:23:16,040 --> 00:23:19,440 Speaker 1: we can't participate in this fight, what fight can we fight? In? 414 00:23:21,240 --> 00:23:23,600 Speaker 1: This goal of setting up a clinical lab as fast 415 00:23:23,680 --> 00:23:25,960 Speaker 1: as we could, it really took everything that we had. 416 00:23:27,040 --> 00:23:29,920 Speaker 1: We begged and borrowed every piece of equipment we could 417 00:23:29,920 --> 00:23:32,920 Speaker 1: get across the research campus. And luckily here at you CSF, 418 00:23:33,040 --> 00:23:38,119 Speaker 1: we have a tremendous workforce of incredibly trained pH d 419 00:23:38,359 --> 00:23:42,480 Speaker 1: s in virology and molecular biology and infectious disease, and 420 00:23:42,640 --> 00:23:44,840 Speaker 1: so I was able to draw on over a hundred 421 00:23:44,880 --> 00:23:48,280 Speaker 1: and seventy five volunteers. There were you know that are 422 00:23:48,320 --> 00:23:51,959 Speaker 1: all PhD level volunteers. To show up and put their 423 00:23:52,040 --> 00:23:55,280 Speaker 1: skills to use. Everybody wanted to get into the fight, 424 00:23:56,200 --> 00:23:59,000 Speaker 1: and so they brought their skills, They brought their re agents, 425 00:23:59,080 --> 00:24:01,920 Speaker 1: they brought their rope oots, they brought their time. We 426 00:24:02,040 --> 00:24:07,320 Speaker 1: built a clinical testing lab starting on March twelve, and 427 00:24:07,800 --> 00:24:09,879 Speaker 1: we had it up and running returned our first clinical 428 00:24:09,960 --> 00:24:12,240 Speaker 1: result on March twentieth. So it took us eight days 429 00:24:12,320 --> 00:24:15,080 Speaker 1: to set up the entire lab and get clinical testing 430 00:24:15,160 --> 00:24:18,400 Speaker 1: for COVID down. And then we just rolled it out 431 00:24:18,520 --> 00:24:23,800 Speaker 1: to essentially all the counties in California. And so when 432 00:24:23,840 --> 00:24:27,480 Speaker 1: we initially did outreach and sort of hey, local counties, 433 00:24:27,840 --> 00:24:29,760 Speaker 1: we know you're not getting your test back for seven 434 00:24:29,880 --> 00:24:32,280 Speaker 1: or ten days, we could do it way faster and 435 00:24:32,760 --> 00:24:36,080 Speaker 1: by the way, we'll do it for free. Uh. And 436 00:24:36,520 --> 00:24:38,560 Speaker 1: we didn't really get that much of a response, and 437 00:24:38,640 --> 00:24:42,000 Speaker 1: we didn't really understand why. And I think Priscilla put 438 00:24:42,080 --> 00:24:45,359 Speaker 1: it really well. Actually, she said, you know, a lot 439 00:24:45,440 --> 00:24:48,520 Speaker 1: of departments of public health don't know how to ask 440 00:24:48,680 --> 00:24:52,760 Speaker 1: for something because they've never been given anything. And it's true. 441 00:24:52,880 --> 00:24:56,280 Speaker 1: When we worked with our our local county department and 442 00:24:56,359 --> 00:24:59,400 Speaker 1: health offices, you know, in different counties around the Bay Area, 443 00:24:59,520 --> 00:25:02,720 Speaker 1: we found owned that there's a great disparity in different 444 00:25:03,119 --> 00:25:07,200 Speaker 1: public offices. Some had some decent resources, others had almost nothing. 445 00:25:07,720 --> 00:25:11,040 Speaker 1: And it's from years of neglect of our public health system. Frankly, 446 00:25:11,640 --> 00:25:14,720 Speaker 1: and I think the pandemic has taught us that we 447 00:25:14,840 --> 00:25:19,800 Speaker 1: need to reinforce and rebuild those public health institutions so 448 00:25:19,960 --> 00:25:24,480 Speaker 1: that this doesn't happen again. Uh and um, I hope 449 00:25:24,840 --> 00:25:28,160 Speaker 1: that this crisis spurs us to actions so that does 450 00:25:28,240 --> 00:25:32,000 Speaker 1: occur now. Luckily, we were able to reach out to 451 00:25:32,280 --> 00:25:37,320 Speaker 1: our public health directors across the state. Actually, Priscilla Chant 452 00:25:37,320 --> 00:25:40,320 Speaker 1: actually had a conference call and she invited everybody onto 453 00:25:40,359 --> 00:25:42,800 Speaker 1: the call from all the different counties and said, hey, 454 00:25:42,880 --> 00:25:45,440 Speaker 1: what's not to like about free testing? And they got it, 455 00:25:45,600 --> 00:25:47,879 Speaker 1: and they finally got it. It sticks some talking to you, 456 00:25:48,200 --> 00:25:50,200 Speaker 1: and then it took off, and of course we did it, 457 00:25:50,320 --> 00:25:53,000 Speaker 1: you know more, we did, you know, thousands and thousands 458 00:25:53,040 --> 00:25:55,440 Speaker 1: and thousands of tests until the state was able to 459 00:25:55,520 --> 00:25:58,800 Speaker 1: bring up its own mass testing sort of systems, and 460 00:25:59,119 --> 00:26:02,880 Speaker 1: direct Emagine to testing also came online, which also made 461 00:26:02,920 --> 00:26:06,320 Speaker 1: things much faster and easier. And so once those came online, 462 00:26:06,560 --> 00:26:09,560 Speaker 1: we're able to sort of ramp down the clinical testing. 463 00:26:09,960 --> 00:26:14,639 Speaker 1: But simultaneously, we were always ramping up the sequencing, and 464 00:26:14,800 --> 00:26:17,840 Speaker 1: of course variance and sequencing only got super popular in 465 00:26:17,960 --> 00:26:22,440 Speaker 1: round December. But we've been sequencing since April, not just 466 00:26:22,560 --> 00:26:25,919 Speaker 1: for variance, but for using the data for actionable intervention 467 00:26:26,000 --> 00:26:29,200 Speaker 1: at the public health level. And the way that works 468 00:26:29,280 --> 00:26:33,000 Speaker 1: is this, we can sequence the positive samples and we 469 00:26:33,080 --> 00:26:37,560 Speaker 1: can understand which genomes are related. Since the virus makes 470 00:26:37,680 --> 00:26:41,000 Speaker 1: mistakes in itself as it copies itself and transmits from 471 00:26:41,040 --> 00:26:43,920 Speaker 1: one person to the other, it creates basically a little 472 00:26:44,000 --> 00:26:49,160 Speaker 1: breadcrumb trail in which you can track back which infections 473 00:26:49,200 --> 00:26:53,159 Speaker 1: were related to who. When we were working with some 474 00:26:53,280 --> 00:26:57,160 Speaker 1: of our public health officials and counties, UM I remember 475 00:26:57,760 --> 00:27:02,879 Speaker 1: um one reporter asking the the official, Hey, if you 476 00:27:02,920 --> 00:27:05,720 Speaker 1: can have anything today right now, you know what would 477 00:27:05,720 --> 00:27:09,159 Speaker 1: it be? A shiny new testing machine? Uh? You know, 478 00:27:09,240 --> 00:27:10,960 Speaker 1: a mobile van? Wan? What what do we what do 479 00:27:11,000 --> 00:27:12,639 Speaker 1: you need right now? What could it be? And the 480 00:27:12,840 --> 00:27:18,680 Speaker 1: Department of Health official said information that's more valuable than anything. 481 00:27:19,320 --> 00:27:22,159 Speaker 1: Where is the virus coming in? Are there new introductions 482 00:27:22,200 --> 00:27:25,800 Speaker 1: to my city or is there continuing forward spread among 483 00:27:25,880 --> 00:27:29,879 Speaker 1: a certain community? Where can I cut the transmission change short? 484 00:27:30,280 --> 00:27:33,040 Speaker 1: What is my next action that it's going to save lives, 485 00:27:34,520 --> 00:27:37,080 Speaker 1: and that's how we can put genomic epidemiology to work. 486 00:27:40,359 --> 00:27:43,240 Speaker 1: It's been a wild roller coaster ride. It's been very 487 00:27:43,320 --> 00:27:47,160 Speaker 1: tense and very exciting, but also stressful at the same time. 488 00:27:47,960 --> 00:27:52,960 Speaker 1: I learned lessons about how how our public health system works. 489 00:27:53,000 --> 00:27:56,959 Speaker 1: I learned lessons about disease transmission that I didn't fully appreciate, 490 00:27:57,480 --> 00:28:03,440 Speaker 1: and the potential for pandemic spread in asymptomatic individuals. The 491 00:28:03,560 --> 00:28:06,400 Speaker 1: basic biology of this virus will be studying for decades 492 00:28:06,520 --> 00:28:09,680 Speaker 1: to come. We still don't fundamentally understand the biology of that. 493 00:28:10,320 --> 00:28:13,160 Speaker 1: It has been wonderful to see the miracle the MR 494 00:28:13,200 --> 00:28:16,720 Speaker 1: and A vaccines from both Visor Maderna in particular. Those 495 00:28:16,840 --> 00:28:21,520 Speaker 1: have been incredible innovations that I was initially skeptical of, 496 00:28:21,760 --> 00:28:25,399 Speaker 1: but it has done really well and I think we 497 00:28:25,440 --> 00:28:26,840 Speaker 1: can all see the light at the end of the 498 00:28:26,880 --> 00:28:30,000 Speaker 1: tunnel now. So you know, the other thing that I 499 00:28:30,160 --> 00:28:35,040 Speaker 1: learned is that in these situations, there's no points for hesitation. 500 00:28:35,480 --> 00:28:37,960 Speaker 1: You have to act and act quickly, and sometimes it's 501 00:28:38,000 --> 00:28:41,280 Speaker 1: not going to be the right move, but the inaction, 502 00:28:41,400 --> 00:28:45,240 Speaker 1: the waiting for more data, is potentially more damaging over 503 00:28:45,280 --> 00:28:50,480 Speaker 1: the long run than not doing something. We're going to 504 00:28:50,560 --> 00:28:52,720 Speaker 1: take a short break, but when we come back. Michael 505 00:28:52,800 --> 00:28:56,320 Speaker 1: Lewis on how to handle what some experts are calling 506 00:28:56,800 --> 00:29:08,200 Speaker 1: the age of pandemics. Talk about the notion, Michael, of premonition, 507 00:29:08,400 --> 00:29:11,840 Speaker 1: the fact that these folks have this essential trait that 508 00:29:12,080 --> 00:29:17,080 Speaker 1: enabled them to sense that something catastrophic was was on 509 00:29:17,240 --> 00:29:20,000 Speaker 1: the horizon and to act on the impulse. I mean, 510 00:29:20,120 --> 00:29:22,959 Speaker 1: what did these three people have in common? What did 511 00:29:23,040 --> 00:29:26,320 Speaker 1: you learn from them? Well, all three of them. Once 512 00:29:26,360 --> 00:29:29,960 Speaker 1: you're living in the world of you know, biochemical events. 513 00:29:30,000 --> 00:29:32,080 Speaker 1: Once you're once you're spending a lot of time thinking 514 00:29:32,080 --> 00:29:36,360 Speaker 1: about how various viruses mutate, might change, and how broken 515 00:29:36,400 --> 00:29:39,440 Speaker 1: our relationship with nature is so that things are leaping 516 00:29:39,480 --> 00:29:42,600 Speaker 1: from animals to people more often. When you're really looking 517 00:29:42,640 --> 00:29:44,280 Speaker 1: at that close. It really isn't a matter of if 518 00:29:44,360 --> 00:29:48,760 Speaker 1: the wind right that that they they became all of them, 519 00:29:48,800 --> 00:29:51,120 Speaker 1: And there are different ways and for different reasons became 520 00:29:51,160 --> 00:29:54,240 Speaker 1: convinced that the risk of pandemic was higher than say, 521 00:29:54,320 --> 00:29:57,240 Speaker 1: what I thought it was. But the whole premonition notion 522 00:29:57,360 --> 00:30:00,800 Speaker 1: is is an interesting one because car a measure was 523 00:30:01,640 --> 00:30:05,200 Speaker 1: among his gifts was his ability to figure out very 524 00:30:05,360 --> 00:30:08,360 Speaker 1: very quickly what's happening in the beginning of a pandemic, 525 00:30:08,880 --> 00:30:12,880 Speaker 1: and so he's January twenty. He has a very accurate 526 00:30:12,960 --> 00:30:17,560 Speaker 1: read on the lethality and transmissibility of the virus in Wuhan, 527 00:30:17,880 --> 00:30:20,200 Speaker 1: and he knows it's coming here. So if he had 528 00:30:20,240 --> 00:30:22,600 Speaker 1: been in charge, as there's every possibility he would have 529 00:30:22,600 --> 00:30:25,360 Speaker 1: been in charge, just wasn't um, we would have started acting, 530 00:30:25,560 --> 00:30:27,760 Speaker 1: you know, two months before we did, and he would 531 00:30:27,800 --> 00:30:30,320 Speaker 1: tell you, you've got to get it. You've got to 532 00:30:30,400 --> 00:30:34,640 Speaker 1: have this sort of like clairvoyance because by the time 533 00:30:34,720 --> 00:30:38,320 Speaker 1: you see the virus, you know in action. By the 534 00:30:38,400 --> 00:30:41,160 Speaker 1: time you see the first death, you're looking at the 535 00:30:41,240 --> 00:30:44,160 Speaker 1: equivalent of starlight. You're looking at something an infection that 536 00:30:44,280 --> 00:30:47,200 Speaker 1: took place maybe five weeks ago, and in those five 537 00:30:47,280 --> 00:30:51,320 Speaker 1: weeks that virus has multiplied exponentially. So if you wait 538 00:30:51,440 --> 00:30:54,280 Speaker 1: till the death, you've got so many cases in your community. 539 00:30:54,400 --> 00:30:57,680 Speaker 1: You can't you can't manage it. You need to anticipate it. 540 00:30:58,280 --> 00:31:01,160 Speaker 1: Charity is the one who got a mystical on me 541 00:31:01,240 --> 00:31:04,480 Speaker 1: about this, and that Charity Dean, she was the only 542 00:31:04,520 --> 00:31:08,000 Speaker 1: one who's actually stopping disease on the ground, and she 543 00:31:08,240 --> 00:31:10,080 Speaker 1: found that she had to kind of use that she 544 00:31:10,160 --> 00:31:11,840 Speaker 1: had to smell it. I mean it was like it 545 00:31:11,960 --> 00:31:15,239 Speaker 1: was like jungle instincts with her, and she I'll tell 546 00:31:15,280 --> 00:31:17,840 Speaker 1: a story that sent a chilled down my spot. It 547 00:31:18,000 --> 00:31:20,320 Speaker 1: was not not long after I met her. I had 548 00:31:20,360 --> 00:31:22,880 Speaker 1: been interviewing her something and she mentioned to me, I 549 00:31:22,960 --> 00:31:24,880 Speaker 1: don't know why that every year she made her New 550 00:31:24,960 --> 00:31:27,120 Speaker 1: Year's resolutions, but she made them on her birthday, which 551 00:31:27,160 --> 00:31:30,160 Speaker 1: was December twenty, and she scribbled them down on the 552 00:31:30,240 --> 00:31:34,040 Speaker 1: back of her grandmother's photograph, her dead grandmother who she adored. 553 00:31:34,720 --> 00:31:38,000 Speaker 1: And one day, sometime after we had met, I said, 554 00:31:38,480 --> 00:31:40,520 Speaker 1: I think to get to know you better, it would 555 00:31:40,560 --> 00:31:42,240 Speaker 1: really help me if you just let me wander around 556 00:31:42,280 --> 00:31:43,680 Speaker 1: your house a bit, because there were a lot of 557 00:31:43,800 --> 00:31:46,640 Speaker 1: like very personal touches in the house. And she went 558 00:31:46,720 --> 00:31:48,240 Speaker 1: out back with her kids and she left me to 559 00:31:48,320 --> 00:31:51,480 Speaker 1: wander the house. I get to her bedroom and her 560 00:31:51,600 --> 00:31:55,000 Speaker 1: grandmother's photograph is beside her bed, and I think she said, 561 00:31:55,000 --> 00:31:56,600 Speaker 1: I could look at anything, So I pull it off 562 00:31:56,640 --> 00:31:59,400 Speaker 1: the wall and it's got all her New Year's resolutions, 563 00:31:59,440 --> 00:32:02,920 Speaker 1: her birthday resolutions going back for like twelve years. They 564 00:32:02,960 --> 00:32:06,440 Speaker 1: are all of the sort that I make, like learn Spanish, 565 00:32:06,880 --> 00:32:10,040 Speaker 1: or or like go to Africa, or they're all resident, 566 00:32:10,040 --> 00:32:12,440 Speaker 1: they're all kind of like what you're gonna do? Until 567 00:32:12,520 --> 00:32:17,120 Speaker 1: two thousand and nineteen, and in December two thousand and nineteen, 568 00:32:17,480 --> 00:32:20,800 Speaker 1: her first resolution is something very personal, and number two 569 00:32:21,000 --> 00:32:25,360 Speaker 1: it says it has started. And now this is this, 570 00:32:25,480 --> 00:32:27,960 Speaker 1: This is before anybody would have known that there was 571 00:32:28,520 --> 00:32:31,800 Speaker 1: a virus in Upan. And this is a woman who's 572 00:32:31,840 --> 00:32:34,280 Speaker 1: been waiting her whole life for the pandemic. There's nothing 573 00:32:34,440 --> 00:32:37,320 Speaker 1: like that on anywhere on this And I call her 574 00:32:37,400 --> 00:32:39,240 Speaker 1: up I said, I said, like, what is this? And 575 00:32:39,320 --> 00:32:41,760 Speaker 1: she said, yeah, yeah. I had this vision in my 576 00:32:41,880 --> 00:32:45,600 Speaker 1: head of this giant tsunami washing over America and I thought, 577 00:32:45,960 --> 00:32:48,600 Speaker 1: something's coming. Now I don't know what it is. I'm 578 00:32:48,640 --> 00:32:51,920 Speaker 1: on red alert. And she'd written this down and I thought, 579 00:32:52,800 --> 00:32:55,600 Speaker 1: you know, I can't explain it. She couldn't explain it. 580 00:32:56,040 --> 00:32:58,200 Speaker 1: She didn't make a big deal of it. But it 581 00:32:58,320 --> 00:33:00,760 Speaker 1: was sort of like you sometimes when you're an expert 582 00:33:00,800 --> 00:33:03,880 Speaker 1: in something, when you do something so often you don't 583 00:33:03,960 --> 00:33:06,680 Speaker 1: know why you know what you know. And something had 584 00:33:06,760 --> 00:33:09,400 Speaker 1: bothered her and it was that instinct. She says she 585 00:33:09,440 --> 00:33:11,640 Speaker 1: had learned to trust because if she didn't trust it. 586 00:33:11,720 --> 00:33:14,240 Speaker 1: She didn't have a tool for dealing with disease because 587 00:33:14,280 --> 00:33:18,040 Speaker 1: you need that instinct that is freaky but maybe not 588 00:33:18,320 --> 00:33:21,840 Speaker 1: as freaky but also freaky. Is an interview that you 589 00:33:22,000 --> 00:33:26,120 Speaker 1: gave to The Guardian in December of two thousand nineteen, Michael, 590 00:33:26,280 --> 00:33:29,320 Speaker 1: and you say, for people to suddenly start to value 591 00:33:29,400 --> 00:33:31,760 Speaker 1: what good government does, I think there will have to 592 00:33:31,840 --> 00:33:34,240 Speaker 1: be something that threatens a lot of people at once. 593 00:33:34,760 --> 00:33:37,800 Speaker 1: The problem with a wildfire in California or a hurricane 594 00:33:37,840 --> 00:33:40,280 Speaker 1: in Florida is that for most people it is happening 595 00:33:40,360 --> 00:33:43,400 Speaker 1: to someone else. I think a pandemic might do it. 596 00:33:43,680 --> 00:33:47,520 Speaker 1: Something that could affect millions of people indiscriminately and from 597 00:33:47,560 --> 00:33:50,920 Speaker 1: which you could not insulate yourself even if you were rich. 598 00:33:51,480 --> 00:33:54,720 Speaker 1: I think that might do it. Okay, do doo doo 599 00:33:54,760 --> 00:33:58,000 Speaker 1: doo doo doo doo doo. That wasn't December of two 600 00:33:58,080 --> 00:34:01,360 Speaker 1: thousand nineteen. Yeah, but I didn't know anything. So it's 601 00:34:01,520 --> 00:34:06,400 Speaker 1: it's um. Charity's performance is more impressive than mine, I 602 00:34:06,440 --> 00:34:08,960 Speaker 1: would say, but I would say this in my I 603 00:34:09,280 --> 00:34:13,400 Speaker 1: want to like par settlement because here's what I was thinking, 604 00:34:13,760 --> 00:34:16,560 Speaker 1: and how different it is from what happened. It wasn't 605 00:34:17,120 --> 00:34:19,279 Speaker 1: It's not true that you couldn't insulate yourself from this. 606 00:34:19,880 --> 00:34:22,200 Speaker 1: Rich people have been able to insulate themselves from this. 607 00:34:22,320 --> 00:34:25,839 Speaker 1: There's been a few exceptions, but the price has fallen vary. 608 00:34:25,960 --> 00:34:29,440 Speaker 1: The cost has fallen very unevenly on the society, so 609 00:34:29,680 --> 00:34:33,080 Speaker 1: that my pandemic is very different from the pandemic of 610 00:34:33,239 --> 00:34:38,640 Speaker 1: a migrant worker in California and or some someone who 611 00:34:38,719 --> 00:34:42,279 Speaker 1: can't afford not to work from home. And so the 612 00:34:42,520 --> 00:34:44,640 Speaker 1: politics of it weren't what I thought it was going 613 00:34:44,719 --> 00:34:48,440 Speaker 1: to be because enough people could escape and tell a 614 00:34:48,560 --> 00:34:52,520 Speaker 1: story about how it's a hoax, it's not really that serious, 615 00:34:52,760 --> 00:34:56,920 Speaker 1: all that stuff. As six hundred thousand Americans die, the 616 00:34:57,280 --> 00:35:00,400 Speaker 1: biff that it gave to the society wasn't quite as 617 00:35:00,480 --> 00:35:03,960 Speaker 1: direct as I imagined it would be. However, I do 618 00:35:04,120 --> 00:35:07,480 Speaker 1: think that is what's happening. I think that the bidens 619 00:35:07,560 --> 00:35:09,120 Speaker 1: being able to get it, will get away with stuff. 620 00:35:09,360 --> 00:35:13,480 Speaker 1: There's more full throated like defense of government going on 621 00:35:13,640 --> 00:35:17,200 Speaker 1: now than than than ever happened in the Obama administration. 622 00:35:17,760 --> 00:35:20,320 Speaker 1: And because you I think that there's there's more of 623 00:35:20,360 --> 00:35:23,200 Speaker 1: a market for the for the idea like, yeah, we 624 00:35:23,360 --> 00:35:26,200 Speaker 1: screwed up, We screwed up because our government was screwed 625 00:35:26,280 --> 00:35:29,600 Speaker 1: up enough people would see that that it's it's had 626 00:35:29,719 --> 00:35:33,120 Speaker 1: some effects. So I was wrong that a pandemic was 627 00:35:33,160 --> 00:35:35,960 Speaker 1: completely going to completely fix this. A pandemic had a 628 00:35:36,000 --> 00:35:39,080 Speaker 1: slightly different effect than I thought. But in that direction, 629 00:35:40,040 --> 00:35:42,800 Speaker 1: did any of these scientists try to cut through the 630 00:35:42,880 --> 00:35:47,160 Speaker 1: government bureaucracy and sound the alarm since they're the people 631 00:35:47,320 --> 00:35:50,160 Speaker 1: you wish were in charge when this all was happening, 632 00:35:50,280 --> 00:35:53,279 Speaker 1: and what happened to them when they tried, Oh my god, 633 00:35:54,200 --> 00:35:57,279 Speaker 1: well let's start a car mession. Since he wrote the 634 00:35:57,320 --> 00:36:01,680 Speaker 1: pandemic plan, the White House neglected. So at the beginning 635 00:36:01,680 --> 00:36:04,640 Speaker 1: of the Trump administration, there were some characters you would 636 00:36:04,640 --> 00:36:07,520 Speaker 1: not have expected to be there because they had associations 637 00:36:07,560 --> 00:36:10,040 Speaker 1: with previous administrations. I guess there were so many jobs 638 00:36:10,080 --> 00:36:12,640 Speaker 1: to feel that some people slipt through, And one of 639 00:36:12,719 --> 00:36:15,319 Speaker 1: them was Tom Bosster, who had been on the been 640 00:36:15,360 --> 00:36:18,440 Speaker 1: on the National security in the Bush administration, and he 641 00:36:18,520 --> 00:36:21,560 Speaker 1: had watched Carter Measure and his partner in crime, Richard Hatchett, 642 00:36:21,600 --> 00:36:23,600 Speaker 1: cook up this plan and was so in awe of 643 00:36:23,680 --> 00:36:27,640 Speaker 1: him that when he got there in two thousand and seventeen, 644 00:36:28,280 --> 00:36:29,960 Speaker 1: one of his first calls was to them and say, 645 00:36:29,960 --> 00:36:32,120 Speaker 1: I want to badge you into the White House right now, 646 00:36:32,480 --> 00:36:34,560 Speaker 1: because if there's a pandemic, you guys are coming to 647 00:36:34,680 --> 00:36:37,719 Speaker 1: run it now. When John Bolton was brought into the 648 00:36:37,760 --> 00:36:40,960 Speaker 1: Trump White House, he fired Boston and at that moment 649 00:36:41,080 --> 00:36:45,880 Speaker 1: the actual link with past knowledge was severed. However, everybody, 650 00:36:46,239 --> 00:36:48,480 Speaker 1: the people there are people in the know, like Tony Fauci, 651 00:36:48,920 --> 00:36:53,360 Speaker 1: know who Carter Measure is. And Carter started writing these emails, 652 00:36:53,640 --> 00:36:57,120 Speaker 1: they called him the Red Dawn emails that had a 653 00:36:57,239 --> 00:37:00,440 Speaker 1: bigger and bigger following, and it was read. I mean, 654 00:37:00,560 --> 00:37:02,360 Speaker 1: you know, it was read by the Surgeon General, it 655 00:37:02,480 --> 00:37:04,440 Speaker 1: was read by people in the f d A, it 656 00:37:04,520 --> 00:37:06,800 Speaker 1: was read by people in the CDC. And he knew that. 657 00:37:07,040 --> 00:37:09,280 Speaker 1: And so he was trying with that, use that bullhorn 658 00:37:09,400 --> 00:37:12,720 Speaker 1: to get them to do stuff. So but we're crazy 659 00:37:12,840 --> 00:37:14,759 Speaker 1: doing it. I mean, he couldn't believe. Carter is a 660 00:37:14,840 --> 00:37:18,440 Speaker 1: hard person to upset. He couldn't believe how long it 661 00:37:18,560 --> 00:37:21,080 Speaker 1: took for them to acknowledge there was any kind of threat. 662 00:37:21,640 --> 00:37:25,800 Speaker 1: But so yes, he tried. He got the CDC itself, 663 00:37:25,880 --> 00:37:27,640 Speaker 1: even though he lives in Atlanta. Didn't want to see 664 00:37:27,719 --> 00:37:33,440 Speaker 1: him in the flesh Um the second person charity Deane 665 00:37:33,880 --> 00:37:37,480 Speaker 1: number two in the state of California. She sees with 666 00:37:37,640 --> 00:37:41,120 Speaker 1: Carter sees bid January this thing, but she's primed. It 667 00:37:41,200 --> 00:37:44,520 Speaker 1: has started. Uh that this thing in Wuhan is um. 668 00:37:44,800 --> 00:37:47,440 Speaker 1: This is serious. You don't well people inside their homes 669 00:37:47,480 --> 00:37:49,960 Speaker 1: to die if you're if you've got a mild outbreak 670 00:37:50,600 --> 00:37:54,280 Speaker 1: and um. And she started to try to sound the alarm. 671 00:37:55,520 --> 00:37:59,239 Speaker 1: Her boss, uh Redder, the riot at, said you're not 672 00:37:59,280 --> 00:38:02,080 Speaker 1: allowed to use the word pandemic. You're scaring people. You're 673 00:38:02,120 --> 00:38:04,480 Speaker 1: not allowed to do that exponential math on the whiteboard 674 00:38:04,520 --> 00:38:06,920 Speaker 1: showing the twenty million in California are gonna get infected 675 00:38:06,960 --> 00:38:09,840 Speaker 1: unless we mitigate this thing. She was shut down. She 676 00:38:10,000 --> 00:38:13,319 Speaker 1: was told go in your box and stay there. You're 677 00:38:13,360 --> 00:38:16,759 Speaker 1: not welcome at any meetings on the subject uh for 678 00:38:16,960 --> 00:38:22,120 Speaker 1: two and something months. So she got shut down. Joe 679 00:38:22,200 --> 00:38:24,840 Speaker 1: Does is in a slightly different position. He's at a nonprofit. 680 00:38:24,920 --> 00:38:27,320 Speaker 1: He's running the Chance Zuckerberg bio Hub, which is a 681 00:38:27,400 --> 00:38:30,560 Speaker 1: couple of enterprise that was funded with Mark Zuckerberg's money. 682 00:38:30,680 --> 00:38:33,400 Speaker 1: But when his wife's his wife is a pediatrician, it 683 00:38:33,520 --> 00:38:36,800 Speaker 1: was her interest to try to eliminate disease by the 684 00:38:36,880 --> 00:38:40,560 Speaker 1: end of the twenty one century. He's got resources. He, 685 00:38:41,880 --> 00:38:44,719 Speaker 1: to his shock, realizes that, my god, we're not even 686 00:38:44,760 --> 00:38:47,200 Speaker 1: have a test to do in the in the United States. 687 00:38:47,520 --> 00:38:50,320 Speaker 1: He turns the bio hub into it into the fastest, 688 00:38:50,400 --> 00:38:54,440 Speaker 1: biggest COVID testing lab in this area, maybe in the 689 00:38:54,480 --> 00:38:57,520 Speaker 1: country at one point, and starts to try to give 690 00:38:57,560 --> 00:39:02,600 Speaker 1: away free, free COVID testing and finds incredibly that as 691 00:39:02,880 --> 00:39:06,440 Speaker 1: starved as we are of COVID testing, that the system 692 00:39:06,600 --> 00:39:10,359 Speaker 1: is not equipped to take free stuff to take his help. 693 00:39:10,920 --> 00:39:14,919 Speaker 1: So local public health officers say, we don't have test 694 00:39:14,960 --> 00:39:17,719 Speaker 1: tubes are swabs to administer the test. He provides them 695 00:39:17,760 --> 00:39:20,800 Speaker 1: with that, we don't have fax machines to receive receive 696 00:39:20,920 --> 00:39:23,279 Speaker 1: the results. He provides them with that. I mean that 697 00:39:23,600 --> 00:39:27,200 Speaker 1: over and over. He's got to resource these public institutions 698 00:39:27,840 --> 00:39:30,960 Speaker 1: in order to get sort of receive his help. And Joe, 699 00:39:31,160 --> 00:39:32,840 Speaker 1: who had never heard of the public I mean, he 700 00:39:32,920 --> 00:39:34,480 Speaker 1: heard of it, but he didn't know anything about the 701 00:39:34,520 --> 00:39:37,239 Speaker 1: public health system until he starts to try to help it, 702 00:39:38,320 --> 00:39:43,640 Speaker 1: sees just how ossified, how corroded, how inapt and incapable 703 00:39:43,840 --> 00:39:45,879 Speaker 1: the system is, even though it's filled with like people 704 00:39:45,920 --> 00:39:49,600 Speaker 1: he admires, they just don't have the tools. Um, so 705 00:39:49,920 --> 00:39:52,239 Speaker 1: each of them. I mean, you just add the question 706 00:39:52,360 --> 00:39:53,839 Speaker 1: just asked me got to the heart of the story 707 00:39:53,880 --> 00:39:56,239 Speaker 1: of why. What interested me about the story? I have 708 00:39:56,440 --> 00:40:01,400 Speaker 1: these extraordinary characters trying to having to do extraordinary things 709 00:40:02,000 --> 00:40:03,960 Speaker 1: because the system that should have taken care of it 710 00:40:04,080 --> 00:40:08,720 Speaker 1: was broken, And the way they flounder about and tried 711 00:40:08,840 --> 00:40:13,239 Speaker 1: to try to operate inside the broken system is sort 712 00:40:13,280 --> 00:40:16,800 Speaker 1: of a portrait of the system. And it's the system 713 00:40:16,920 --> 00:40:20,640 Speaker 1: that is the endgame in the story. It's like, we 714 00:40:20,800 --> 00:40:23,560 Speaker 1: can't have this, like we we're not gonna survive if 715 00:40:23,560 --> 00:40:26,479 Speaker 1: our systems look like this, and these people are telling 716 00:40:26,600 --> 00:40:30,920 Speaker 1: us how how it looks, and so what's the solution? 717 00:40:31,000 --> 00:40:33,319 Speaker 1: I know, Dr Fauci told me we're living in an 718 00:40:33,440 --> 00:40:37,759 Speaker 1: age of pandemics, um, And I think you can talk 719 00:40:37,840 --> 00:40:43,239 Speaker 1: about any existential threat, not just a coronavirus, but anything 720 00:40:43,680 --> 00:40:47,680 Speaker 1: that the current systems or structure of government is not 721 00:40:47,920 --> 00:40:51,839 Speaker 1: capable of handling. So do you think there were real 722 00:40:52,040 --> 00:40:55,680 Speaker 1: lessons learned from this? Will things change or are you 723 00:40:55,880 --> 00:40:59,640 Speaker 1: fearful that it will remain as ossified as ever? I 724 00:40:59,719 --> 00:41:03,520 Speaker 1: act seemed prett hopeful. Uh and I'm pretty hopeful because 725 00:41:03,680 --> 00:41:07,120 Speaker 1: even though this country has this bizarre movement to declare 726 00:41:07,160 --> 00:41:10,040 Speaker 1: the whole thing a hoax, enough people's lives have been 727 00:41:10,080 --> 00:41:13,840 Speaker 1: disrupted and touched, and there's enough evidence from outside of 728 00:41:13,920 --> 00:41:17,120 Speaker 1: America just how awful it could be. But doesn't it 729 00:41:17,200 --> 00:41:21,279 Speaker 1: freak you out, Michael, that like Republican men refused to 730 00:41:21,320 --> 00:41:24,719 Speaker 1: be vaccinated. I mean, it's so crazy. You know, we're 731 00:41:24,920 --> 00:41:28,200 Speaker 1: we are, We're a byproduct of a long period of 732 00:41:28,400 --> 00:41:31,320 Speaker 1: basic prosperity and peace that we're we have the luxury 733 00:41:31,360 --> 00:41:35,160 Speaker 1: of being idiots that we won't survive if we're that way, 734 00:41:35,239 --> 00:41:37,879 Speaker 1: And I think that the more more existential the risk, 735 00:41:38,440 --> 00:41:42,200 Speaker 1: the quicker the society will respond and fix itself. I 736 00:41:42,239 --> 00:41:43,880 Speaker 1: think we have, Like I guess, I guess I think 737 00:41:44,040 --> 00:41:47,360 Speaker 1: about the country, it has a bizarre ability to bounce 738 00:41:47,400 --> 00:41:50,719 Speaker 1: in all kinds of directions and change. It's a very 739 00:41:50,920 --> 00:41:54,359 Speaker 1: changeable society. It's a young society in a way, uh, 740 00:41:54,960 --> 00:41:58,600 Speaker 1: and so as much weirdness as there is now, I 741 00:41:58,680 --> 00:42:01,759 Speaker 1: could see it bounce in a complete different direction. Yes, 742 00:42:01,880 --> 00:42:04,080 Speaker 1: we'll have always have some people who won't get vaccinated, 743 00:42:04,640 --> 00:42:07,600 Speaker 1: but I'm not terrified for our future. I actually think 744 00:42:07,920 --> 00:42:10,239 Speaker 1: these people you know this is our field. Here's an 745 00:42:10,280 --> 00:42:13,759 Speaker 1: analogy that that describes how I feel. We had this 746 00:42:13,880 --> 00:42:16,920 Speaker 1: team that just we had a catastrophic season. We had 747 00:42:16,960 --> 00:42:19,600 Speaker 1: all these resources and we just stuck it up. We 748 00:42:19,760 --> 00:42:22,759 Speaker 1: lost all our games. You asked me to go in 749 00:42:22,880 --> 00:42:25,960 Speaker 1: and evaluate the situation. Is maybe a person who might 750 00:42:26,000 --> 00:42:29,399 Speaker 1: be the next coach. If I walked in and I thought, Wow, 751 00:42:29,600 --> 00:42:32,320 Speaker 1: this team does suck. I don't want to be I 752 00:42:32,360 --> 00:42:34,440 Speaker 1: don't want to coach this team. There's a reason they 753 00:42:34,480 --> 00:42:37,239 Speaker 1: lost all these games. You know, I wouldn't take the job. 754 00:42:37,960 --> 00:42:40,399 Speaker 1: But I walk into this team and I write about 755 00:42:40,480 --> 00:42:43,279 Speaker 1: the team, and I see such talent. It's like, this 756 00:42:43,440 --> 00:42:45,960 Speaker 1: is an incredibly talented team. This is like the most 757 00:42:46,040 --> 00:42:48,960 Speaker 1: talented team. It's like giving me the Golden State Warriors 758 00:42:49,000 --> 00:42:51,400 Speaker 1: from three years ago and somehow they used to having 759 00:42:51,400 --> 00:42:53,839 Speaker 1: to lose all these games. Yeah, I'll take this job. 760 00:42:54,040 --> 00:42:56,320 Speaker 1: I can fix this because talent that it's hard to 761 00:42:56,560 --> 00:42:58,480 Speaker 1: you know, you know you got the talent, it just 762 00:42:58,600 --> 00:43:01,600 Speaker 1: needs to be organized. So the fact that we have 763 00:43:01,880 --> 00:43:04,879 Speaker 1: these resources, and I don't mean just material resources, these 764 00:43:04,920 --> 00:43:10,839 Speaker 1: inner resources, I think it's very hopeful. A huge thank 765 00:43:10,960 --> 00:43:13,920 Speaker 1: you to Michael Lewis and to Dr Joe Deresi of 766 00:43:14,000 --> 00:43:17,960 Speaker 1: the University of California's San Francisco and the chan Zuckerberg 767 00:43:18,080 --> 00:43:21,880 Speaker 1: bio Hub. Michael's new book is called The Premonition of 768 00:43:22,000 --> 00:43:29,120 Speaker 1: Pandemic Story and it's out now. Next Question with Katie 769 00:43:29,160 --> 00:43:31,680 Speaker 1: Kurik is a production of I Heart Media and Katie 770 00:43:31,719 --> 00:43:35,400 Speaker 1: Kurk Media. The executive producers are me, Katie Curic, and 771 00:43:35,600 --> 00:43:40,560 Speaker 1: Courtney Litz. The supervising producer is Lauren Hansen. Associate producers 772 00:43:40,760 --> 00:43:45,200 Speaker 1: Derek Clements, Adrianna Fassio, and Emily Pinto. The show is 773 00:43:45,400 --> 00:43:49,120 Speaker 1: edited and mixed by Derrick Clements. For more information about 774 00:43:49,160 --> 00:43:52,080 Speaker 1: today's episode, or to sign up for my morning newsletter, 775 00:43:52,160 --> 00:43:54,960 Speaker 1: wake Up Call, go to Katie Couric dot com. You 776 00:43:55,040 --> 00:43:57,680 Speaker 1: can also find me at Katie Curic, on Instagram and 777 00:43:57,880 --> 00:44:01,239 Speaker 1: all my social media channels. For more podcasts from I 778 00:44:01,400 --> 00:44:05,239 Speaker 1: Heart Radio, visit the I Heart Radio app, Apple Podcasts, 779 00:44:05,560 --> 00:44:07,760 Speaker 1: or wherever you listen to your favorite shows.