1 00:00:00,800 --> 00:00:05,400 Speaker 1: Welcome to Prognosis. I'm Laura Carlson. It's day two hundred 2 00:00:05,440 --> 00:00:09,639 Speaker 1: and thirty seven since coronavirus was declared a global pandemic. 3 00:00:10,680 --> 00:00:14,840 Speaker 1: Today's main story. The risk of COVID nineteen transmission is 4 00:00:14,960 --> 00:00:19,600 Speaker 1: high on college campuses, where students live in close quarters 5 00:00:19,640 --> 00:00:24,320 Speaker 1: and may avoid following social distancing rules. But one upstate 6 00:00:24,400 --> 00:00:29,560 Speaker 1: New York University has stayed open and managed to control 7 00:00:29,800 --> 00:00:34,760 Speaker 1: its COVID cases. But first, here's what happened in Virus 8 00:00:34,800 --> 00:00:43,680 Speaker 1: News Today. Infections in the US increased by one point 9 00:00:43,760 --> 00:00:47,919 Speaker 1: three percent on Friday, with Iowa, North Dakota, Michigan, and 10 00:00:47,960 --> 00:00:53,120 Speaker 1: Colorado seeing the biggest single day rises. That's according to 11 00:00:53,240 --> 00:00:58,480 Speaker 1: data compiled by Johns Hopkins University and Bloomberg News. Yesterday, 12 00:00:58,800 --> 00:01:02,480 Speaker 1: new cases passed a hundred and twenty six thousand, a 13 00:01:02,520 --> 00:01:07,320 Speaker 1: global record for a single nation. Johnson and Johnson is 14 00:01:07,319 --> 00:01:10,640 Speaker 1: about to start clinical trials of its COVID nineteen vaccine 15 00:01:10,680 --> 00:01:14,680 Speaker 1: in South Africa after getting regulatory approval, according to the 16 00:01:14,720 --> 00:01:19,319 Speaker 1: co chair of the study in the country. Meanwhile, scientists 17 00:01:19,400 --> 00:01:23,600 Speaker 1: monitoring wastewater in one region of the country detected spikes 18 00:01:23,800 --> 00:01:28,080 Speaker 1: of the coronavirus in the last three weeks. The government 19 00:01:28,160 --> 00:01:31,720 Speaker 1: is concerned that a lack of compliance with health guidelines 20 00:01:32,280 --> 00:01:37,720 Speaker 1: may trigger a second wave. Finally, France posted a record 21 00:01:37,800 --> 00:01:41,319 Speaker 1: number of new virus cases as the nation's health minister, 22 00:01:41,440 --> 00:01:45,160 Speaker 1: Olivier Veron warned that a violent second wave of the 23 00:01:45,240 --> 00:01:50,360 Speaker 1: illness is sweeping the country. He said virus patients now 24 00:01:50,400 --> 00:01:54,800 Speaker 1: occupy more than eighty five percent of French hospitals initial 25 00:01:54,920 --> 00:01:59,720 Speaker 1: intensive care facilities. Europe is battling a new surge in 26 00:01:59,760 --> 00:02:03,840 Speaker 1: the IRS, with France starting a second lockdown just last 27 00:02:03,880 --> 00:02:13,360 Speaker 1: week and now for today's main story, Cornell University in 28 00:02:13,480 --> 00:02:17,960 Speaker 1: upstate New York welcomed around twenty four thousand people back 29 00:02:18,000 --> 00:02:22,080 Speaker 1: to campus this fall. The idea of students packed into 30 00:02:22,120 --> 00:02:27,320 Speaker 1: dorms and mingling in classrooms made many people nervous, But 31 00:02:27,600 --> 00:02:32,079 Speaker 1: while outbreaks have plagued colleges across the country, Cornell has 32 00:02:32,120 --> 00:02:36,440 Speaker 1: managed to keep a lid on its COVID cases. In fact, 33 00:02:36,720 --> 00:02:40,399 Speaker 1: the college's test positivity rate has been among the lowest 34 00:02:40,639 --> 00:02:44,560 Speaker 1: of any college or university in the country doing large 35 00:02:44,600 --> 00:02:49,160 Speaker 1: scale testing. I spoke with reporter and a court, an 36 00:02:49,200 --> 00:02:53,120 Speaker 1: alumna of Cornell about how the school has done it. 37 00:02:57,320 --> 00:03:00,640 Speaker 1: You know the story with so many colleges and universities 38 00:03:00,680 --> 00:03:04,160 Speaker 1: around the US for the full term has either been 39 00:03:04,240 --> 00:03:08,520 Speaker 1: one of online or distance learning, and many of the 40 00:03:08,520 --> 00:03:12,480 Speaker 1: stories we even have heard about students on campus has 41 00:03:12,520 --> 00:03:16,079 Speaker 1: been pretty negative news UM with outbreaks and the spread 42 00:03:16,120 --> 00:03:20,280 Speaker 1: of COVID, but not Cornell. And I was wondering if 43 00:03:20,280 --> 00:03:24,320 Speaker 1: you might just unpack what what happened at Cornell to 44 00:03:24,480 --> 00:03:28,520 Speaker 1: make it this success story. Yeah, so I would know. 45 00:03:28,919 --> 00:03:31,840 Speaker 1: Cornell isn't the only school that has been able to 46 00:03:31,919 --> 00:03:35,360 Speaker 1: keep cases very low, but it's what's significant is what 47 00:03:35,440 --> 00:03:38,480 Speaker 1: a big school it is. Cornell reopened its campus about 48 00:03:38,520 --> 00:03:44,080 Speaker 1: two thousand people in the late summer, and really what 49 00:03:44,120 --> 00:03:47,080 Speaker 1: they did was kind of take all the public health 50 00:03:47,160 --> 00:03:51,280 Speaker 1: measures that are recommended, and in fact, they say that 51 00:03:51,320 --> 00:03:53,720 Speaker 1: their experience is a testament to the fact that the 52 00:03:53,720 --> 00:03:56,720 Speaker 1: things that we've been talking to about throughout this whole pandemic, 53 00:03:56,800 --> 00:03:59,480 Speaker 1: from you know, frequent testing all the way to to 54 00:03:59,640 --> 00:04:04,280 Speaker 1: mask wearing and handwashing that they work. Most significant about 55 00:04:04,320 --> 00:04:07,480 Speaker 1: what Cornell did, I would say is that frequent testing. 56 00:04:08,280 --> 00:04:12,200 Speaker 1: They're testing about thirty five thousand students, faculty and staff 57 00:04:12,200 --> 00:04:15,800 Speaker 1: a week. Undergrads are tested as frequently as twice a week. 58 00:04:16,400 --> 00:04:18,800 Speaker 1: Uh and that they say that has helped them find 59 00:04:18,920 --> 00:04:22,520 Speaker 1: these people who could be you know, asymptomatic silent spreaders 60 00:04:22,520 --> 00:04:25,080 Speaker 1: of the virus and and really tamped down on that 61 00:04:25,120 --> 00:04:29,400 Speaker 1: spread and you know, isolate people and prevent further infections 62 00:04:29,440 --> 00:04:33,080 Speaker 1: on campus. Another thing that they really cite for their 63 00:04:33,120 --> 00:04:36,200 Speaker 1: success has been sort of a souped up version of 64 00:04:36,200 --> 00:04:40,080 Speaker 1: of contact tracing. They do something called that they call 65 00:04:40,320 --> 00:04:43,800 Speaker 1: adaptive testing, which is instead of sort of adhering to 66 00:04:43,839 --> 00:04:46,520 Speaker 1: the strict definition of a of a contact. You know, 67 00:04:46,920 --> 00:04:49,440 Speaker 1: there are different definitions for contact tracing, but in New 68 00:04:49,520 --> 00:04:53,039 Speaker 1: York State, it's someone who's been within six ft of 69 00:04:53,120 --> 00:04:56,520 Speaker 1: someone who had a confirmed COVID nineteen infection for about 70 00:04:56,560 --> 00:04:59,360 Speaker 1: ten minutes. So they did something a little bit more 71 00:04:59,400 --> 00:05:02,320 Speaker 1: expanse of They did do contact tracing, but they also 72 00:05:02,400 --> 00:05:05,080 Speaker 1: did this thing where they looked at people who might 73 00:05:05,120 --> 00:05:09,279 Speaker 1: have been exposed but weren't technically close contact. So if 74 00:05:09,279 --> 00:05:11,839 Speaker 1: you're living on a dorm floor and you turn out 75 00:05:11,839 --> 00:05:14,840 Speaker 1: to have COVID nineteen, they might test everyone on that 76 00:05:14,839 --> 00:05:17,760 Speaker 1: floor because you're all sharing a bathroom. If you're on 77 00:05:17,800 --> 00:05:21,080 Speaker 1: a hockey team, maybe you weren't technically within six ft 78 00:05:21,080 --> 00:05:23,640 Speaker 1: of someone for ten minutes, but you know, you're likely 79 00:05:23,720 --> 00:05:26,279 Speaker 1: spending time around them and maybe you could be infected, 80 00:05:26,320 --> 00:05:28,920 Speaker 1: so maybe you test the whole hockey team. So they say, 81 00:05:28,960 --> 00:05:30,880 Speaker 1: this is something that kind of goes above and beyond 82 00:05:30,880 --> 00:05:33,960 Speaker 1: the call of duty and you know, help them basically 83 00:05:34,360 --> 00:05:38,040 Speaker 1: locked down the chains of transmission on campus. I was 84 00:05:38,080 --> 00:05:41,559 Speaker 1: wondering if you might go into just actually how low 85 00:05:41,920 --> 00:05:45,760 Speaker 1: the infection rate has been on campus. And I mean, 86 00:05:45,800 --> 00:05:50,279 Speaker 1: among those few infections that Cornell has seen, where are 87 00:05:50,400 --> 00:05:53,839 Speaker 1: we seeing transmission coming from. Is this something that students 88 00:05:53,880 --> 00:05:56,840 Speaker 1: are being exposed in the classroom or or is it 89 00:05:56,880 --> 00:06:01,040 Speaker 1: coming really from somewhere else. Just to start off with, 90 00:06:01,200 --> 00:06:04,520 Speaker 1: I just pulled up Cornell's COVID dashboard and right now 91 00:06:04,520 --> 00:06:08,320 Speaker 1: their positivity rate is point zero four percent, so you know, 92 00:06:08,360 --> 00:06:12,080 Speaker 1: point zero four percent of their test return positive. That's 93 00:06:12,080 --> 00:06:14,120 Speaker 1: really good. And in a recent week, a couple of 94 00:06:14,120 --> 00:06:16,760 Speaker 1: weeks ago, it was actually as low as point zero 95 00:06:16,880 --> 00:06:19,200 Speaker 1: zero six percent, So they were joking that they would 96 00:06:19,200 --> 00:06:22,200 Speaker 1: have to add another, you know, decimal place to the 97 00:06:22,600 --> 00:06:25,680 Speaker 1: online dashboard. Um, it was so low. You know, if 98 00:06:25,680 --> 00:06:28,520 Speaker 1: you look at how many cases they've had since they reopened, 99 00:06:28,839 --> 00:06:31,560 Speaker 1: it's been about hundred and seventy one cases from mid 100 00:06:31,600 --> 00:06:38,360 Speaker 1: August to basically now through November four. That's really significant 101 00:06:38,360 --> 00:06:40,839 Speaker 1: because that is very low, and they do have a 102 00:06:40,880 --> 00:06:44,400 Speaker 1: lot of people, you know, thousand people on campus. You know, 103 00:06:44,520 --> 00:06:46,960 Speaker 1: things didn't look like they were going to go quite 104 00:06:47,000 --> 00:06:49,919 Speaker 1: this way when I first started my reporting, though, you know, 105 00:06:49,920 --> 00:06:52,559 Speaker 1: I talked to a lot of people in August before 106 00:06:52,640 --> 00:06:57,839 Speaker 1: campus reopened, and the plan was constantly changing. There was 107 00:06:57,920 --> 00:07:01,640 Speaker 1: a lot of anxiety among people in the unity, you know, students, 108 00:07:01,680 --> 00:07:05,280 Speaker 1: their parents, faculty members, because it looked like a big 109 00:07:05,400 --> 00:07:08,240 Speaker 1: risk that Cornell was taking. They were bringing all these 110 00:07:08,279 --> 00:07:11,200 Speaker 1: people to upstate New York, you know, at the time 111 00:07:11,240 --> 00:07:14,680 Speaker 1: had been very much untouched by COVID nineteen. It was 112 00:07:14,840 --> 00:07:17,000 Speaker 1: very you know, rates were very low, and so it 113 00:07:17,000 --> 00:07:20,760 Speaker 1: seemed like things could go pretty awry. And in fact, 114 00:07:20,920 --> 00:07:23,520 Speaker 1: you know, as students were coming back to campus, there 115 00:07:23,720 --> 00:07:27,760 Speaker 1: was an early cluster of cases on campus that really 116 00:07:27,880 --> 00:07:29,880 Speaker 1: raised a lot of alarm bells, you know, which was 117 00:07:29,920 --> 00:07:34,520 Speaker 1: actually tied to student athletes socializing without the proper you know, 118 00:07:34,600 --> 00:07:39,160 Speaker 1: social distancing and mask wearing. Um but you know, Cornell 119 00:07:39,240 --> 00:07:44,640 Speaker 1: again really credits this aggressive testing and and contact tracing 120 00:07:44,680 --> 00:07:48,000 Speaker 1: to helping kind of stand that chain of transmission. And 121 00:07:48,040 --> 00:07:50,480 Speaker 1: in fact, you know, they did a lot of interesting 122 00:07:50,560 --> 00:07:54,760 Speaker 1: modeling around how infection good spread around campus, really plotting 123 00:07:54,760 --> 00:07:56,680 Speaker 1: out a lot of different scenarios. That's actually how they 124 00:07:56,760 --> 00:07:59,400 Speaker 1: ended up doing so much testing. They realized they needed 125 00:07:59,440 --> 00:08:02,280 Speaker 1: to in order to keep infection low, and they set 126 00:08:02,280 --> 00:08:05,320 Speaker 1: out a couple of different scenarios for how you know, 127 00:08:05,640 --> 00:08:09,520 Speaker 1: infections could spread. And the actual cases on campus have 128 00:08:09,560 --> 00:08:13,480 Speaker 1: actually stayed so low that they've been far lower than 129 00:08:13,520 --> 00:08:16,400 Speaker 1: even the most optimistic scenario, which I think is is 130 00:08:16,760 --> 00:08:21,440 Speaker 1: really a testament to to what they've done. And you know, 131 00:08:21,520 --> 00:08:25,160 Speaker 1: you've mentioned a lot of this plan, um, and and 132 00:08:25,160 --> 00:08:29,120 Speaker 1: perhaps their success does revolve around the amount of testing 133 00:08:29,200 --> 00:08:32,920 Speaker 1: that's going on, and and that's quite a significant amount 134 00:08:33,120 --> 00:08:37,360 Speaker 1: of testing. I was just curious how is the university 135 00:08:37,400 --> 00:08:42,640 Speaker 1: handling this this amount of regular testing. Cornell actually set 136 00:08:42,760 --> 00:08:45,719 Speaker 1: up a new lab in its veterinary school to do 137 00:08:45,880 --> 00:08:49,880 Speaker 1: human testing. Interestingly, a number of colleges and universities have 138 00:08:49,960 --> 00:08:52,960 Speaker 1: actually done this because um, this mode of you know, 139 00:08:53,000 --> 00:08:56,480 Speaker 1: the common mode of COVID nineteen testing is is something 140 00:08:56,520 --> 00:08:59,839 Speaker 1: called polymaries chain reaction tests, and they're actually often you 141 00:09:00,080 --> 00:09:03,040 Speaker 1: to look for disease and animals UM. The big thing 142 00:09:03,080 --> 00:09:05,520 Speaker 1: that they did, and other colleges have done this too, 143 00:09:05,600 --> 00:09:08,679 Speaker 1: is that they did something called pooling, where you put 144 00:09:09,200 --> 00:09:13,079 Speaker 1: multiple samples together um and process them at the same time. 145 00:09:13,440 --> 00:09:15,960 Speaker 1: This is something that works actually best when you don't 146 00:09:15,960 --> 00:09:18,440 Speaker 1: have a lot of infection on campus, as Cornell has. 147 00:09:19,000 --> 00:09:21,280 Speaker 1: You know, it's important to note that this has been 148 00:09:21,320 --> 00:09:24,000 Speaker 1: a big push for Cornell, and they're running their lab 149 00:09:24,040 --> 00:09:28,800 Speaker 1: you know, practically seven and and it's been difficult. You know, 150 00:09:28,840 --> 00:09:31,800 Speaker 1: they set up all these centers around campus for people 151 00:09:31,840 --> 00:09:33,600 Speaker 1: to get their samples collected. You know, it's a it's 152 00:09:33,600 --> 00:09:36,480 Speaker 1: a nasal swab, and it's something that you know, took 153 00:09:36,559 --> 00:09:39,120 Speaker 1: up a lot of their resources, but also you know 154 00:09:39,559 --> 00:09:42,200 Speaker 1: a lot of participation from the community to go in 155 00:09:42,240 --> 00:09:47,160 Speaker 1: and get tested so frequently. And you've raised a really 156 00:09:47,400 --> 00:09:51,280 Speaker 1: important point. I think that many other colleges and universities 157 00:09:51,600 --> 00:09:55,760 Speaker 1: might be looking to Cornell's policy because, I mean, in 158 00:09:56,120 --> 00:09:59,920 Speaker 1: all honesty, Cornell has been able to welcome students back, 159 00:10:00,040 --> 00:10:03,360 Speaker 1: They've been able to collect, particularly from the financial angle 160 00:10:03,760 --> 00:10:07,160 Speaker 1: room and board rents from the students that are back 161 00:10:07,240 --> 00:10:11,640 Speaker 1: on campus. Is this something that perhaps other college campuses 162 00:10:11,679 --> 00:10:14,960 Speaker 1: other universities can look to Cornell as perhaps a model 163 00:10:15,040 --> 00:10:19,440 Speaker 1: for how they can apply this policy on their own campuses. 164 00:10:20,280 --> 00:10:23,960 Speaker 1: You know, a lot of cynics and skeptics when colleges 165 00:10:24,040 --> 00:10:27,200 Speaker 1: said that they were going to reopen, pointed to the 166 00:10:27,240 --> 00:10:30,560 Speaker 1: fact that college has had a real financial incentive to reopen. 167 00:10:30,679 --> 00:10:33,760 Speaker 1: You know, it's hard to justify charging a lot of 168 00:10:33,760 --> 00:10:36,760 Speaker 1: tuition when your students are basically, you know, at home, 169 00:10:37,240 --> 00:10:41,520 Speaker 1: living with their parents, you know, taking classes online. I 170 00:10:41,559 --> 00:10:46,120 Speaker 1: think for Cornell what's important to note is that they 171 00:10:46,120 --> 00:10:49,320 Speaker 1: did have advantages and they and they acknowledge those advantages. 172 00:10:49,520 --> 00:10:52,000 Speaker 1: You know, from the fact that Ithaca is a pretty 173 00:10:52,040 --> 00:10:55,800 Speaker 1: remote location. Ithaca when you're driving up is really a 174 00:10:55,840 --> 00:10:59,600 Speaker 1: lot of cows and fields. So you know, that's an 175 00:10:59,600 --> 00:11:02,040 Speaker 1: advance Didge because you don't have a lot of people 176 00:11:02,080 --> 00:11:04,240 Speaker 1: coming and going from other places where they can bring 177 00:11:04,280 --> 00:11:07,640 Speaker 1: the virus. Although Cornell has had people bring the virus 178 00:11:07,760 --> 00:11:10,240 Speaker 1: that way to campus and they've found it using that testing. 179 00:11:11,240 --> 00:11:14,080 Speaker 1: And there are other advantages just conferred by their you know, 180 00:11:14,160 --> 00:11:18,880 Speaker 1: financial and scientific resources that are important to note and 181 00:11:18,880 --> 00:11:22,559 Speaker 1: and again might be hard for other schools to replicate, 182 00:11:22,720 --> 00:11:27,440 Speaker 1: particularly if they don't you know, have these kinds of resources. 183 00:11:29,800 --> 00:11:33,200 Speaker 1: And I mean here we are. It's early November, but 184 00:11:33,520 --> 00:11:36,480 Speaker 1: the end of the fall semester is in sight. Students 185 00:11:36,480 --> 00:11:39,280 Speaker 1: are about to leave to to go on holiday, to 186 00:11:39,360 --> 00:11:42,400 Speaker 1: go back to their family and friends all over the 187 00:11:42,520 --> 00:11:46,679 Speaker 1: US and the world. Is this going to affect Cornell's 188 00:11:46,679 --> 00:11:51,600 Speaker 1: plan for the spring or is this fall scenario what 189 00:11:51,679 --> 00:11:55,000 Speaker 1: Cornell is expecting to adopt in the spring. Yeah, Cornell 190 00:11:55,120 --> 00:11:58,320 Speaker 1: is planning US spring semester, you know in person. You know, 191 00:11:58,320 --> 00:12:00,720 Speaker 1: they're hoping to bring even more students back this time, 192 00:12:01,160 --> 00:12:04,800 Speaker 1: hoping to do more classes in person um and they 193 00:12:04,840 --> 00:12:07,280 Speaker 1: have a lot more time to plan now than they 194 00:12:07,679 --> 00:12:10,680 Speaker 1: did last time. A lot of things were really quickly 195 00:12:10,800 --> 00:12:14,200 Speaker 1: changing right before the semester began um, including you know, 196 00:12:14,280 --> 00:12:16,800 Speaker 1: a lot of students were coming from states that had 197 00:12:16,800 --> 00:12:18,839 Speaker 1: been put on New York State's quarantine list, and so 198 00:12:19,040 --> 00:12:22,800 Speaker 1: that made it very difficult logistically for everyone to come back. 199 00:12:23,360 --> 00:12:25,720 Speaker 1: I think it's important to think about also how things 200 00:12:25,800 --> 00:12:29,000 Speaker 1: will be different in the spring semester. You know, they're 201 00:12:29,040 --> 00:12:32,480 Speaker 1: planning on starting classes in February. You know, the weather 202 00:12:32,559 --> 00:12:36,160 Speaker 1: in February and Ithaca can be quite cold, and as 203 00:12:36,200 --> 00:12:38,920 Speaker 1: we all know, winter could be a real time of 204 00:12:38,960 --> 00:12:43,120 Speaker 1: spreading COVID because of those cold temperatures, bringing people to 205 00:12:43,200 --> 00:12:45,480 Speaker 1: gather inside more where they could you know, are more 206 00:12:45,520 --> 00:12:48,280 Speaker 1: likely also to spread the virus. So you know, it's 207 00:12:48,280 --> 00:12:50,920 Speaker 1: going to bring a new slate of challenges for Cornell. 208 00:12:51,000 --> 00:12:54,360 Speaker 1: And in fact, right now the university is already seeing 209 00:12:54,720 --> 00:12:58,959 Speaker 1: um infection rates in surrounding communities on the rise. And 210 00:12:59,360 --> 00:13:01,800 Speaker 1: so it kind of went from the situation where the 211 00:13:01,880 --> 00:13:07,200 Speaker 1: community was worried about Cornell bringing COVID to their backyards 212 00:13:07,320 --> 00:13:10,840 Speaker 1: and now Cornell is is starting to warily look at 213 00:13:10,840 --> 00:13:13,480 Speaker 1: the community and say, maybe people are going to get sick, 214 00:13:13,600 --> 00:13:15,920 Speaker 1: you know, in our surrounding areas, and they've they've started 215 00:13:15,960 --> 00:13:25,760 Speaker 1: to see some of that already. That was Emma Corp. 216 00:13:26,200 --> 00:13:28,640 Speaker 1: And that's it for our show today. For coverage of 217 00:13:28,679 --> 00:13:31,440 Speaker 1: the outbreak from one and twenty bureaus around the world, 218 00:13:31,880 --> 00:13:36,680 Speaker 1: visit Bloomberg dot com slash coronavirus and if you like 219 00:13:36,760 --> 00:13:39,200 Speaker 1: the show, please leave us a review and a rating 220 00:13:39,440 --> 00:13:42,880 Speaker 1: on Apple Podcasts or Spotify. It's the best way to 221 00:13:42,920 --> 00:13:47,680 Speaker 1: help more listeners find our global reporting. The Prognosis Daily 222 00:13:47,760 --> 00:13:51,840 Speaker 1: edition is produced by Topha Foreheads, Jordan gas Pure, Magnus 223 00:13:51,840 --> 00:13:56,640 Speaker 1: Henrickson and me Laura Carlson. Today's main story was reported 224 00:13:56,640 --> 00:14:01,439 Speaker 1: by Emma Corp. Original music by Leo sidrin Our. Editors 225 00:14:01,480 --> 00:14:06,160 Speaker 1: are Rick Shine and Francesco Levi. Francesca Levi is Bloomberg's 226 00:14:06,160 --> 00:14:08,760 Speaker 1: head of podcasts. Thanks for listening.