1 00:00:04,280 --> 00:00:09,719 Speaker 1: Welcome to Prognosis. I'm Laura Carlson. It's day one, twelve 2 00:00:10,080 --> 00:00:14,720 Speaker 1: since coronavirus was declared a global pandemic. Our main story. 3 00:00:15,960 --> 00:00:18,960 Speaker 1: Even as the infection rates surges around the United States, 4 00:00:19,560 --> 00:00:22,520 Speaker 1: some have pointed to lower death rates as proof that 5 00:00:22,640 --> 00:00:26,040 Speaker 1: this stage of the outbreak isn't as bad as it seems. 6 00:00:27,200 --> 00:00:29,840 Speaker 1: But a close look at the numbers shows it may 7 00:00:29,880 --> 00:00:34,120 Speaker 1: be too early to declare that fatalities are really declining. 8 00:00:35,320 --> 00:00:47,920 Speaker 1: But first, here's what happened in virus news today. As 9 00:00:47,960 --> 00:00:52,400 Speaker 1: the alarming coronavirus surge continues in dozens of U S states, 10 00:00:52,880 --> 00:00:56,920 Speaker 1: New York City postponed a planned return to indoor dining 11 00:00:57,000 --> 00:01:02,800 Speaker 1: next week. Mayor Build a Blasio side rising cases in Florida, California, 12 00:01:02,920 --> 00:01:08,120 Speaker 1: and Texas after some of those states reopened restaurants. The 13 00:01:08,200 --> 00:01:11,560 Speaker 1: city had planned to allow restaurants to have a limited 14 00:01:11,640 --> 00:01:17,080 Speaker 1: number of available tables indoors starting this Sunday. Instead, it 15 00:01:17,120 --> 00:01:22,280 Speaker 1: will now help restaurants expand operations outdoors on sidewalks and 16 00:01:22,400 --> 00:01:27,240 Speaker 1: in curbside parking spaces. He said. Some large US companies 17 00:01:27,280 --> 00:01:31,360 Speaker 1: are also reevaluating their plans to ramp up normal operations. 18 00:01:32,120 --> 00:01:34,760 Speaker 1: Google is pushing back a plan to reopen its u 19 00:01:34,880 --> 00:01:38,920 Speaker 1: S offices. In a memo to employees, the company said 20 00:01:39,160 --> 00:01:44,240 Speaker 1: all US offices will remain closed until September seven, at 21 00:01:44,280 --> 00:01:50,160 Speaker 1: the earliest. An experimental coronavirus vaccine is showing promise. In 22 00:01:50,200 --> 00:01:54,720 Speaker 1: an early trial, fiser and bio n text treatment has 23 00:01:54,760 --> 00:01:58,760 Speaker 1: been shown to be safe. It also successfully prompted patients 24 00:01:58,880 --> 00:02:03,520 Speaker 1: to produce and bodies against the virus that has kept 25 00:02:03,520 --> 00:02:05,480 Speaker 1: it at the front of the pack in the race 26 00:02:05,560 --> 00:02:11,120 Speaker 1: to develop a vaccine. Finally, Europe may be starting to 27 00:02:11,160 --> 00:02:16,600 Speaker 1: see a tenuous economic recovery following months of coronavirus shutdowns, 28 00:02:17,280 --> 00:02:21,679 Speaker 1: but the road ahead will be long. European Central Bank 29 00:02:21,760 --> 00:02:25,560 Speaker 1: President Christine Lagarde renewed her warning at a United Nations 30 00:02:25,600 --> 00:02:30,200 Speaker 1: event that the hardest times are yet to come. She 31 00:02:30,360 --> 00:02:34,840 Speaker 1: said the recovery would be uncertain and uneven, and would 32 00:02:34,960 --> 00:02:39,320 Speaker 1: lead to arise in inequality and unemployment that will leave 33 00:02:39,360 --> 00:02:50,400 Speaker 1: the most vulnerable in difficult conditions. And now for our 34 00:02:50,440 --> 00:02:55,920 Speaker 1: main story, the coronavirus continues it's terrifying rampage of large 35 00:02:55,919 --> 00:02:59,519 Speaker 1: swaths of the country, but the Trump administration has made 36 00:02:59,520 --> 00:03:03,080 Speaker 1: a point of mentioning that even while cases are rising 37 00:03:03,800 --> 00:03:09,280 Speaker 1: deaths are declining. That disconnect is Trump says, proof that 38 00:03:09,320 --> 00:03:14,760 Speaker 1: the COVID nineteen pandemic is under control. But the mismatch 39 00:03:14,840 --> 00:03:18,200 Speaker 1: could be an anomaly caused by quirks in how death 40 00:03:18,360 --> 00:03:22,320 Speaker 1: data is collected and reported. It could also be that 41 00:03:22,360 --> 00:03:25,000 Speaker 1: a greater number of younger people are catching the virus 42 00:03:25,600 --> 00:03:30,120 Speaker 1: not necessarily assigned. The coronavirus is becoming less lethal or 43 00:03:30,320 --> 00:03:34,960 Speaker 1: easier to treat. Robert Langre and Emma Court report that 44 00:03:35,160 --> 00:03:38,120 Speaker 1: medical experts say it's too soon to know for sure 45 00:03:38,600 --> 00:03:46,520 Speaker 1: that deaths are still declining in recent days. In recent 46 00:03:46,560 --> 00:03:49,800 Speaker 1: weeks here in the US, we have been seeing case 47 00:03:49,880 --> 00:03:53,960 Speaker 1: counts rise pretty much across the board, particularly in the 48 00:03:54,000 --> 00:03:56,600 Speaker 1: sun belt in the South and the West. And yet 49 00:03:56,800 --> 00:04:00,240 Speaker 1: one interesting thing about these developments we've been seeing is 50 00:04:00,280 --> 00:04:05,240 Speaker 1: that even as the case counts rise, the corresponding mortality rate, 51 00:04:05,320 --> 00:04:07,960 Speaker 1: the death rate does not seem to be climbing with 52 00:04:08,000 --> 00:04:11,440 Speaker 1: the same rates. And I was wondering if you could 53 00:04:11,520 --> 00:04:15,640 Speaker 1: unpack that for us, what are we seeing here? One 54 00:04:15,680 --> 00:04:17,640 Speaker 1: thing to be really aware of it is sort of 55 00:04:17,680 --> 00:04:20,440 Speaker 1: that that death rates in this for COVID are kind 56 00:04:20,440 --> 00:04:24,000 Speaker 1: of the ultimate lacking indicator. We don't really know yet 57 00:04:24,080 --> 00:04:25,680 Speaker 1: what the death rate is going to be for this 58 00:04:26,040 --> 00:04:28,760 Speaker 1: current rise in case counts. And that's because some of 59 00:04:28,839 --> 00:04:31,560 Speaker 1: the cases in the States are reported rather quickly. But 60 00:04:31,680 --> 00:04:33,640 Speaker 1: you know, deaths really do take a while to come 61 00:04:33,880 --> 00:04:37,960 Speaker 1: roll in. Once you diagnose with COVID, even a bad case, 62 00:04:38,000 --> 00:04:40,080 Speaker 1: it may take the people that do die, it may take, 63 00:04:40,120 --> 00:04:42,320 Speaker 1: you know, two or three weeks for them to die, 64 00:04:42,680 --> 00:04:45,719 Speaker 1: if you're going to die. And then these these death 65 00:04:45,800 --> 00:04:48,880 Speaker 1: numbers that come in, they aren't the deaths that occurred yesterday. 66 00:04:48,920 --> 00:04:52,560 Speaker 1: These are deaths that may have been occurred a week 67 00:04:52,640 --> 00:04:54,720 Speaker 1: or two weeks or even three weeks ago. That that is, 68 00:04:54,880 --> 00:04:58,119 Speaker 1: after once someone dies, it can take a while days, 69 00:04:58,240 --> 00:05:02,039 Speaker 1: even weeks or dr filling the death certificate, turn it 70 00:05:02,040 --> 00:05:05,479 Speaker 1: in for the state authorities to kind of adjudicate and 71 00:05:05,560 --> 00:05:08,680 Speaker 1: verify it, and then reported out to two people so 72 00:05:09,279 --> 00:05:10,800 Speaker 1: to the rest of the world. To some of these 73 00:05:11,080 --> 00:05:14,160 Speaker 1: these death numbers coming are quite you know, quite delayed, 74 00:05:14,200 --> 00:05:17,360 Speaker 1: and it just takes several weeks corresponding to the cases 75 00:05:17,400 --> 00:05:19,680 Speaker 1: we're still seeing now. Is the first thing to be 76 00:05:19,800 --> 00:05:22,160 Speaker 1: very aware of. We don't really know yet, you know, 77 00:05:22,240 --> 00:05:24,600 Speaker 1: what the death rate is going to be for this 78 00:05:24,960 --> 00:05:29,320 Speaker 1: current wave of cases. But there are several reasons also 79 00:05:29,480 --> 00:05:32,840 Speaker 1: to believe to suspect that the death rate, you know, 80 00:05:32,960 --> 00:05:36,800 Speaker 1: when we have the numbers will actually be lower. We're 81 00:05:36,839 --> 00:05:40,479 Speaker 1: now six months into this into this pandemic. I mean, 82 00:05:40,600 --> 00:05:42,960 Speaker 1: is it a question with regards to the death rates 83 00:05:43,040 --> 00:05:48,679 Speaker 1: that were simply treating COVID nineteen more successfully. For months, 84 00:05:48,720 --> 00:05:51,160 Speaker 1: medical providers have been you know, learning about how to 85 00:05:51,200 --> 00:05:53,880 Speaker 1: treat this virus, sharing best practices. And I think the 86 00:05:53,880 --> 00:05:56,520 Speaker 1: answer is yes. You know, we still don't have all 87 00:05:56,560 --> 00:05:59,760 Speaker 1: the information we'd like to have. Doctors still don't have 88 00:06:00,120 --> 00:06:03,080 Speaker 1: like a you know, a perfect treatment for this condition. 89 00:06:03,120 --> 00:06:06,480 Speaker 1: We definitely don't have any vaccines right now, except experimental 90 00:06:06,520 --> 00:06:09,320 Speaker 1: ones that are still being tested. You know, It's true 91 00:06:09,320 --> 00:06:11,960 Speaker 1: that we've learned a lot and doctors have better practices 92 00:06:12,000 --> 00:06:14,360 Speaker 1: now and um, and you know, I think we are 93 00:06:14,440 --> 00:06:17,440 Speaker 1: seeing that payoff. But it's not totally clear how all 94 00:06:17,480 --> 00:06:19,520 Speaker 1: of these factors break down in terms of what we're 95 00:06:19,520 --> 00:06:22,599 Speaker 1: seeing right We think, you know, the death rate lagging 96 00:06:22,640 --> 00:06:26,239 Speaker 1: maybe one factor. Another factor is this friend towards younger patients, 97 00:06:26,279 --> 00:06:29,919 Speaker 1: you know, better treatments. Another potential factor is maybe the 98 00:06:29,960 --> 00:06:32,839 Speaker 1: virus is just not transmitting as well in the summer. 99 00:06:32,920 --> 00:06:36,280 Speaker 1: You know, it was sort of hypothesized that the summer 100 00:06:36,920 --> 00:06:41,640 Speaker 1: might make for less virus transmission because that hot air, 101 00:06:41,760 --> 00:06:44,599 Speaker 1: you know, pushing the virus kind of down out out 102 00:06:44,600 --> 00:06:47,080 Speaker 1: of kind of the path of transmission. But you know, 103 00:06:47,120 --> 00:06:49,640 Speaker 1: it's not clear that that's happening. But it's possible that 104 00:06:49,680 --> 00:06:52,200 Speaker 1: perhaps a weaker form of the virus is being transmitted 105 00:06:52,200 --> 00:06:54,479 Speaker 1: people aren't getting as sick. There's also been a pretty 106 00:06:54,520 --> 00:06:57,760 Speaker 1: high profile theory that the virus is getting sort of 107 00:06:57,839 --> 00:07:01,280 Speaker 1: weaker in and of itself as it applicates around the world, 108 00:07:01,320 --> 00:07:04,799 Speaker 1: and that's been pretty roundly criticized. It's not totally clear 109 00:07:05,200 --> 00:07:09,240 Speaker 1: that's what's happening, but there's a variety of explanations here. 110 00:07:09,360 --> 00:07:13,320 Speaker 1: We just we just don't really know. Unfortunately, it does 111 00:07:13,360 --> 00:07:17,040 Speaker 1: seem to be a lot more complicated or perhaps even 112 00:07:17,080 --> 00:07:21,240 Speaker 1: a lengthy process in recording the death count. And I 113 00:07:21,280 --> 00:07:23,040 Speaker 1: was wondering if maybe you could go into some of 114 00:07:23,040 --> 00:07:27,760 Speaker 1: the different kinds of factors that go into potentially delaying 115 00:07:28,360 --> 00:07:32,360 Speaker 1: the recording of a death due to COVID nineteen. If 116 00:07:32,360 --> 00:07:34,400 Speaker 1: you look a few days ago, there's a huge spike 117 00:07:34,440 --> 00:07:36,680 Speaker 1: of death just like three or four days ago, and 118 00:07:36,760 --> 00:07:39,400 Speaker 1: almost all of that was new to New Jersey suddenly 119 00:07:39,400 --> 00:07:43,760 Speaker 1: adding probable COVID nineteen deaths and we're in its account before. 120 00:07:44,120 --> 00:07:46,160 Speaker 1: And those weren't deaths that occurred in the last few days. 121 00:07:46,200 --> 00:07:48,640 Speaker 1: There was their deaths that went way back this you know, 122 00:07:48,760 --> 00:07:52,560 Speaker 1: county of deak Is a is. It just takes a 123 00:07:52,600 --> 00:07:55,400 Speaker 1: while for the death to roll in. Often, for example, 124 00:07:55,840 --> 00:07:59,600 Speaker 1: in Arizona, one of the researchers of follows Is showed 125 00:07:59,680 --> 00:08:02,960 Speaker 1: me when some of the deaths occurred. And so for 126 00:08:03,080 --> 00:08:06,720 Speaker 1: the deaths reported in the weekending June fourteenth in Arizona 127 00:08:06,760 --> 00:08:09,200 Speaker 1: due to COVID, So it turns out only half of 128 00:08:09,240 --> 00:08:12,000 Speaker 1: those deaths reported that week we're from that week, and 129 00:08:12,080 --> 00:08:15,040 Speaker 1: fully fifty were from two or three or even more 130 00:08:15,280 --> 00:08:17,960 Speaker 1: weeks before. That's when they actually happens. That that's an 131 00:08:18,000 --> 00:08:20,920 Speaker 1: example just how the lag can be. And that's from 132 00:08:20,960 --> 00:08:24,240 Speaker 1: when the death actually happens to whether it's reported as 133 00:08:24,280 --> 00:08:26,240 Speaker 1: a death due to COVID. That doesn't even count the 134 00:08:26,320 --> 00:08:29,000 Speaker 1: fact that you know, you get sick, you got a 135 00:08:29,080 --> 00:08:31,080 Speaker 1: case so to take, you know, and it takes two 136 00:08:31,160 --> 00:08:33,120 Speaker 1: to three weeks for that to play out, and you 137 00:08:33,280 --> 00:08:37,400 Speaker 1: either to get better or not. Deaths lag not just 138 00:08:37,520 --> 00:08:41,800 Speaker 1: because It takes time when someone gets COVID to die, um, 139 00:08:42,200 --> 00:08:44,560 Speaker 1: you know, from the disease, to succumb to the disease. 140 00:08:44,679 --> 00:08:47,960 Speaker 1: But but then afterwards there's these official processes that takes 141 00:08:48,000 --> 00:08:49,800 Speaker 1: some time. Right. It takes time for you know, the 142 00:08:49,880 --> 00:08:52,920 Speaker 1: health officials to adjudicate the death. It takes time, you know, 143 00:08:53,000 --> 00:08:56,079 Speaker 1: doctors have to decide did this person die of COVID nineteen. 144 00:08:56,120 --> 00:08:58,360 Speaker 1: You know, if they you know, had COVID nineteen and 145 00:08:58,440 --> 00:09:01,560 Speaker 1: then seemed to recover a little bit and then ended 146 00:09:01,679 --> 00:09:03,800 Speaker 1: up dying, you know, was that a death from COVID 147 00:09:03,880 --> 00:09:06,520 Speaker 1: nineteen or not? There there are some questions about you know, 148 00:09:06,559 --> 00:09:09,520 Speaker 1: the squish nous of of these subjects, right, And during 149 00:09:09,559 --> 00:09:12,360 Speaker 1: this time, everyone wants to rely on the data, right. 150 00:09:12,400 --> 00:09:14,520 Speaker 1: They put all this trust in the numbers that are 151 00:09:14,559 --> 00:09:16,079 Speaker 1: coming out of the states and the numbers that we 152 00:09:16,120 --> 00:09:19,439 Speaker 1: see about testing on the federal level too. But you know, 153 00:09:19,640 --> 00:09:25,480 Speaker 1: importantly this data is not infallible, right, I mean, especially 154 00:09:25,520 --> 00:09:27,120 Speaker 1: when you think about the fact that you know, in 155 00:09:27,280 --> 00:09:30,160 Speaker 1: terms of diagnoses, the only cases that we know we 156 00:09:30,240 --> 00:09:32,720 Speaker 1: only know about cases that actually get diagnosed. We only 157 00:09:32,760 --> 00:09:35,800 Speaker 1: know about people who test positive because they got a test. 158 00:09:35,880 --> 00:09:38,520 Speaker 1: There are likely many more people who are not getting 159 00:09:38,559 --> 00:09:41,000 Speaker 1: tested for these symptoms, for instance. So you know, these 160 00:09:41,040 --> 00:09:43,400 Speaker 1: are official counts, but that's important to remember. These are 161 00:09:43,480 --> 00:09:46,120 Speaker 1: the official numbers, right and there are probably a lot 162 00:09:46,160 --> 00:09:49,480 Speaker 1: of numbers that aren't getting captured in these data even now. 163 00:09:49,840 --> 00:09:52,199 Speaker 1: So I think that's also important when you think about deaths. 164 00:09:52,280 --> 00:09:54,559 Speaker 1: You know, there has been some back and forth even 165 00:09:54,640 --> 00:09:56,839 Speaker 1: earlier in the pandemic about whether all of the death 166 00:09:56,920 --> 00:09:59,600 Speaker 1: from COVID nineteen were actually being counted, you know, as 167 00:09:59,640 --> 00:10:01,959 Speaker 1: health to partments got overwhelmed and things like that. So 168 00:10:02,400 --> 00:10:04,319 Speaker 1: these are the official numbers, but do they tell the 169 00:10:04,520 --> 00:10:07,920 Speaker 1: complete and full and completely thorough story, Like we probably 170 00:10:08,000 --> 00:10:10,600 Speaker 1: won't know that for some time, you know, if at all. 171 00:10:11,320 --> 00:10:14,000 Speaker 1: What should we be looking at or taking away from 172 00:10:14,040 --> 00:10:16,280 Speaker 1: the numbers as they stand right now, and what should 173 00:10:16,320 --> 00:10:19,280 Speaker 1: we be preparing for. You know, we don't know exactly 174 00:10:19,360 --> 00:10:21,720 Speaker 1: what's going to happen in two or three weeks from now, 175 00:10:21,760 --> 00:10:23,760 Speaker 1: and that would be very very interesting to watch because 176 00:10:23,960 --> 00:10:27,679 Speaker 1: we do have in some of these southern states increased hospitalizations, 177 00:10:28,120 --> 00:10:30,079 Speaker 1: increased numbers of people in I c u s. You know, 178 00:10:30,200 --> 00:10:33,720 Speaker 1: what does that translate into. So some of the research 179 00:10:33,760 --> 00:10:35,880 Speaker 1: we talked to in Arizona said that what they would 180 00:10:35,880 --> 00:10:39,120 Speaker 1: expect might be, you know, leveling off of this decline 181 00:10:39,160 --> 00:10:41,760 Speaker 1: in depths and you know, somewhat at an increase again, 182 00:10:42,120 --> 00:10:44,079 Speaker 1: you know, and maybe not a huge spike like we 183 00:10:44,160 --> 00:10:46,320 Speaker 1: had before in April when the in New York, when 184 00:10:46,400 --> 00:10:49,359 Speaker 1: this disease is totally new, when we were kind of unprepared. 185 00:10:49,520 --> 00:10:52,000 Speaker 1: Hospitals are better prepared and there are some treatments and 186 00:10:52,040 --> 00:10:54,679 Speaker 1: they have some better strategies. So be very very interesting, 187 00:10:54,720 --> 00:10:56,719 Speaker 1: you know, to watch. And then I have four or 188 00:10:56,760 --> 00:10:59,079 Speaker 1: five or six weeks from now, the deaths, you know, 189 00:10:59,200 --> 00:11:02,840 Speaker 1: haven't gone up at all, and despite lots of people 190 00:11:02,880 --> 00:11:04,679 Speaker 1: in the hospital of I see you, that will be 191 00:11:04,720 --> 00:11:07,520 Speaker 1: an indication you know, we've gotten there's something's changed a 192 00:11:07,559 --> 00:11:10,559 Speaker 1: little about the the the virus, or you've gotten better 193 00:11:10,760 --> 00:11:13,240 Speaker 1: treating it, or somehow you know, we've kept it out 194 00:11:13,400 --> 00:11:15,439 Speaker 1: of the older, most vulnerable people. One of those you 195 00:11:15,520 --> 00:11:18,599 Speaker 1: know three things. I think also an important part of 196 00:11:18,679 --> 00:11:21,199 Speaker 1: this is to understand the different kinds of data and 197 00:11:21,320 --> 00:11:24,480 Speaker 1: how they trickle in, right, I mean, public health officials 198 00:11:24,800 --> 00:11:27,559 Speaker 1: can't wait for deaths to spike to take action to 199 00:11:27,640 --> 00:11:30,360 Speaker 1: control an outbreak, right, they have to start relying on 200 00:11:30,520 --> 00:11:35,199 Speaker 1: earlier forms of data like case counts and especially hospitalizations. 201 00:11:35,480 --> 00:11:37,800 Speaker 1: The problem is the earliest data that we have coming 202 00:11:37,840 --> 00:11:40,520 Speaker 1: in our case counts, and that doesn't present the fullest 203 00:11:40,600 --> 00:11:43,959 Speaker 1: possible picture of an outbreak, but it is the earliest 204 00:11:44,000 --> 00:11:46,280 Speaker 1: indicator we have. And an expert I spoke with at 205 00:11:46,320 --> 00:11:49,160 Speaker 1: Johns Hopkins put this really well. He said, Basically, you know, 206 00:11:49,240 --> 00:11:51,760 Speaker 1: a couple of weeks ago when the case cases were 207 00:11:51,800 --> 00:11:54,640 Speaker 1: spiking in some of these states like Arizona and Texas 208 00:11:54,679 --> 00:11:56,880 Speaker 1: and Florida, which we now know, you know, are having 209 00:11:57,200 --> 00:11:59,920 Speaker 1: problems in terms of the outbreak in their communities. He's 210 00:12:00,200 --> 00:12:02,319 Speaker 1: you know, this is early data in terms of the 211 00:12:02,440 --> 00:12:05,520 Speaker 1: case counts rising, but it's important to act on early 212 00:12:05,679 --> 00:12:08,680 Speaker 1: data because by the time you get more thorough data, 213 00:12:08,800 --> 00:12:12,000 Speaker 1: more final data, you get hospitalization spiking, you get death 214 00:12:12,120 --> 00:12:15,200 Speaker 1: god forbid spiking. You know, that may be too late, 215 00:12:15,520 --> 00:12:19,719 Speaker 1: and I think that sensitivity towards the mechanism of these 216 00:12:19,800 --> 00:12:22,520 Speaker 1: numbers is important for public health officials to be eyeing. 217 00:12:22,600 --> 00:12:25,360 Speaker 1: You know, waiting for the deaths to rise is not 218 00:12:25,920 --> 00:12:29,280 Speaker 1: the most productive tack here. Right by the time deaths rise, 219 00:12:29,520 --> 00:12:32,920 Speaker 1: you maybe four or five weeks behind something that's happening 220 00:12:33,240 --> 00:12:41,839 Speaker 1: in a state or a local area. That was Robert 221 00:12:41,920 --> 00:12:44,920 Speaker 1: Lang and Emma Cord. And that's it for our show today. 222 00:12:45,679 --> 00:12:49,040 Speaker 1: For coverage of the outbreak from one bureaus around the world, 223 00:12:49,559 --> 00:12:54,079 Speaker 1: visit Bloomberg dot com slash Coronavirus and if you like 224 00:12:54,240 --> 00:12:57,000 Speaker 1: the show, please leave us a review and a rating 225 00:12:57,200 --> 00:13:00,559 Speaker 1: on Apple Podcasts or Spotify. It's the best way to 226 00:13:00,640 --> 00:13:05,600 Speaker 1: help more listeners find our global reporting. The Prognosis Daily 227 00:13:05,760 --> 00:13:09,120 Speaker 1: edition is produced by Top for foreheads Jordan gas Pure, 228 00:13:09,559 --> 00:13:14,400 Speaker 1: Magnus Hendrickson and me Laura Carlson. Today's main story was 229 00:13:14,480 --> 00:13:18,679 Speaker 1: reported by Robert Langrath and Emma Court. Original music by 230 00:13:18,800 --> 00:13:23,120 Speaker 1: Leo Sidran. Our editors are Rick Shine and Francesco Levi. 231 00:13:24,000 --> 00:13:28,440 Speaker 1: Francesco Levi is Bloomberg's head of podcasts. Thanks for listening.