1 00:00:02,920 --> 00:00:07,800 Speaker 1: Welcome to Prognosis. I'm Laura Carlson. It's day three and 2 00:00:07,960 --> 00:00:13,680 Speaker 1: nineteen since coronavirus was declared a global pandemic. Today's main story. 3 00:00:14,640 --> 00:00:18,840 Speaker 1: Despite plenty of resources, the US is way behind the 4 00:00:18,960 --> 00:00:23,959 Speaker 1: UK and other countries when it comes to identifying dangerous 5 00:00:24,000 --> 00:00:30,320 Speaker 1: new variants of the coronavirus, and that has serious implications 6 00:00:30,360 --> 00:00:36,199 Speaker 1: for fighting the pandemic. But first, here's what happened in 7 00:00:36,320 --> 00:00:50,080 Speaker 1: virus news today. Snafi made an unusual deal to produce 8 00:00:50,280 --> 00:00:54,840 Speaker 1: millions of doses of the Fighter and bio Ntech coronavirus vaccine. 9 00:00:55,960 --> 00:00:58,760 Speaker 1: The French drugmaker set in a statement today it will 10 00:00:58,800 --> 00:01:02,680 Speaker 1: give bio n Tech access to a production facility in Frankfurt, 11 00:01:02,880 --> 00:01:06,959 Speaker 1: which will start to deliver doses this summer. The deal 12 00:01:07,080 --> 00:01:12,319 Speaker 1: will produce more than one million doses for the European Union. 13 00:01:13,560 --> 00:01:17,560 Speaker 1: Sanafi's own effort to develop a COVID vaccine has stumbled. 14 00:01:18,400 --> 00:01:20,960 Speaker 1: The deal with bio n Tech allows Europe to make 15 00:01:21,080 --> 00:01:24,639 Speaker 1: up for some of the loss. The pact also raised 16 00:01:24,640 --> 00:01:28,679 Speaker 1: hopes that more pharma giants would throw their manufacturing and 17 00:01:28,760 --> 00:01:33,880 Speaker 1: distribution weight behind the few coronavirus shots that have proved effective. 18 00:01:35,520 --> 00:01:39,839 Speaker 1: A standoff between the EU and drugmaker Astra Zenica over 19 00:01:39,959 --> 00:01:45,919 Speaker 1: vaccine delivery delays turned from bitter to chaotic on Wednesday, 20 00:01:45,959 --> 00:01:49,280 Speaker 1: with the two sides disagreeing over whether a call to 21 00:01:49,400 --> 00:01:55,040 Speaker 1: discuss drug delivery would take place. Later, both confirmed that 22 00:01:55,120 --> 00:01:59,200 Speaker 1: talks will in fact resume as planned. It was just 23 00:01:59,240 --> 00:02:02,520 Speaker 1: the latest in a series of clashes between the EU 24 00:02:02,600 --> 00:02:08,680 Speaker 1: and the drugmaker. Finally, the Biden administration said it intends 25 00:02:08,720 --> 00:02:14,200 Speaker 1: to increase orders for the two approved vaccines by the 26 00:02:14,320 --> 00:02:18,840 Speaker 1: US government will order one hundred million more doses each 27 00:02:19,240 --> 00:02:24,440 Speaker 1: of Fiser and Moderna's coronavirus vaccines. It will also speed 28 00:02:24,520 --> 00:02:33,480 Speaker 1: up shipments to states, at least temporarily. And now for 29 00:02:33,560 --> 00:02:38,800 Speaker 1: today's main story, the US is struggling to monitor COVID 30 00:02:38,880 --> 00:02:42,799 Speaker 1: nineteen variants, a key part of watching for the emergence 31 00:02:42,880 --> 00:02:47,920 Speaker 1: of dangerous mutations that might spread quickly, evade vaccines, or 32 00:02:48,120 --> 00:02:54,120 Speaker 1: kill more infected people. Currently, the US ranks thirty second 33 00:02:54,200 --> 00:02:56,360 Speaker 1: in the world for the number of tests it's done 34 00:02:56,480 --> 00:03:02,200 Speaker 1: to detect mutations per one thousand good cases. I spoke 35 00:03:02,240 --> 00:03:06,000 Speaker 1: to health reporter Kristin V. Brown, who reports that other 36 00:03:06,080 --> 00:03:12,200 Speaker 1: countries like the UK have established robust nationwide surveillance programs 37 00:03:12,360 --> 00:03:17,200 Speaker 1: to identify new covid genomes and track the spread of 38 00:03:17,240 --> 00:03:30,000 Speaker 1: existing ones. The emergence of specific variants of COVID nineteen 39 00:03:30,200 --> 00:03:33,919 Speaker 1: have been known for a while now, and obviously scientists 40 00:03:33,960 --> 00:03:38,000 Speaker 1: always knew they were a possibility. But let's talk a 41 00:03:38,240 --> 00:03:41,960 Speaker 1: bit about what mutations of viruses can do. How do 42 00:03:42,040 --> 00:03:46,200 Speaker 1: they impact how infectious of viruses? And you know, the 43 00:03:46,240 --> 00:03:50,760 Speaker 1: big question, will they impact the efficacy of a COVID 44 00:03:50,840 --> 00:03:56,960 Speaker 1: nineteen vaccine? So viruses muta It's just something that viruses do, 45 00:03:57,200 --> 00:04:00,000 Speaker 1: you know. That's why the flu vaccine is a different 46 00:04:00,040 --> 00:04:02,640 Speaker 1: shot every year. So it might seem like a kind 47 00:04:02,680 --> 00:04:06,280 Speaker 1: of arcane thing, right, Why does this variant that it's 48 00:04:06,320 --> 00:04:09,119 Speaker 1: just a little bit different from another version of COVID 49 00:04:09,200 --> 00:04:12,800 Speaker 1: nineteen matter? But it actually could potentially matter a lot 50 00:04:13,280 --> 00:04:17,719 Speaker 1: depending on what the mutation in the virus is. So 51 00:04:17,960 --> 00:04:22,440 Speaker 1: the current mutations that hob scientists concerned have to do 52 00:04:22,520 --> 00:04:25,719 Speaker 1: with the way the virus actually gets into a person's body, 53 00:04:25,960 --> 00:04:30,120 Speaker 1: and that is why they believe that these variants might 54 00:04:30,160 --> 00:04:34,440 Speaker 1: be more contagious. But that could also potentially interfere with 55 00:04:34,680 --> 00:04:38,920 Speaker 1: therapies that are being developed um or vaccines. Right, there's 56 00:04:38,920 --> 00:04:42,480 Speaker 1: a big question right now, about whether these emerging variants 57 00:04:42,600 --> 00:04:46,200 Speaker 1: might interfere with the efficacy of the vaccines that we're developing. 58 00:04:46,680 --> 00:04:50,240 Speaker 1: And so you know what has specifically the US been 59 00:04:50,279 --> 00:04:56,640 Speaker 1: doing to track, identify, or even sequence these known variants 60 00:04:56,640 --> 00:05:01,080 Speaker 1: of COVID nineteen. So you brought up sequencing. How you 61 00:05:01,120 --> 00:05:05,200 Speaker 1: detect these variants is through genetic sequencing, Right. You have 62 00:05:05,360 --> 00:05:09,560 Speaker 1: to be taking samples from patients and you know, running 63 00:05:09,600 --> 00:05:13,960 Speaker 1: them through this machine that can decode the viruses genome 64 00:05:14,520 --> 00:05:20,360 Speaker 1: and tell you, okay, is this virus significantly different from 65 00:05:20,600 --> 00:05:24,680 Speaker 1: other ones that we know are commonly circulating in the population. 66 00:05:25,200 --> 00:05:30,240 Speaker 1: So the UK and many other countries have established really 67 00:05:30,279 --> 00:05:34,440 Speaker 1: really robust genetic surveillance programs to sort of be on 68 00:05:34,560 --> 00:05:37,840 Speaker 1: the hunt for this. The US does have a program, 69 00:05:38,040 --> 00:05:41,800 Speaker 1: but it is not as robust as many other nations. 70 00:05:42,080 --> 00:05:44,480 Speaker 1: At the time that we're talking, the US, I believe, 71 00:05:44,560 --> 00:05:46,839 Speaker 1: ranks thirty second in the world for the number of 72 00:05:46,880 --> 00:05:51,599 Speaker 1: sequences is completing per thousand COVID cases. And that's behind, 73 00:05:52,000 --> 00:05:54,560 Speaker 1: you know, countries like the UK and Iceland that are 74 00:05:54,600 --> 00:05:57,839 Speaker 1: really known for their genomic capabilities, but it's also behind 75 00:05:57,920 --> 00:06:01,400 Speaker 1: countries that you don't really think of as leaders in 76 00:06:01,400 --> 00:06:07,000 Speaker 1: that space. Like Latvia and Senegal. And so you know, 77 00:06:07,040 --> 00:06:10,320 Speaker 1: we know that about two hundred thousand people in the 78 00:06:10,400 --> 00:06:13,800 Speaker 1: US are testing positive for COVID nineteen every single week, 79 00:06:14,320 --> 00:06:18,960 Speaker 1: But are these tests being used to track or as 80 00:06:19,000 --> 00:06:24,200 Speaker 1: you mentioned, sequence these COVID variants. This week, the CDC 81 00:06:24,400 --> 00:06:28,440 Speaker 1: told me that the US is sequencing about three thousand 82 00:06:29,160 --> 00:06:33,240 Speaker 1: COVID nineteen samples every week. To put things in perspective, 83 00:06:33,480 --> 00:06:37,640 Speaker 1: right now, the UK is sequencing about ten percent of 84 00:06:37,680 --> 00:06:41,599 Speaker 1: its COVID cases and that number, that three thousand number, 85 00:06:41,680 --> 00:06:45,680 Speaker 1: puts the US at less than point five. So we 86 00:06:45,760 --> 00:06:50,200 Speaker 1: are not sequencing very much of the virus at all. 87 00:06:50,600 --> 00:06:53,960 Speaker 1: And I mean, scientists have said that this effectively leaves 88 00:06:54,080 --> 00:06:58,120 Speaker 1: us flying blind. We do not know what mutations of 89 00:06:58,160 --> 00:07:00,960 Speaker 1: the virus might be out there are that pose a 90 00:07:01,040 --> 00:07:05,440 Speaker 1: threat to to US and to our pandemic response. I mean, 91 00:07:05,560 --> 00:07:09,120 Speaker 1: is this something that we're seeing in the US because 92 00:07:09,440 --> 00:07:12,520 Speaker 1: of say a lack of interest on the federal level. 93 00:07:12,760 --> 00:07:15,000 Speaker 1: What's some of the reasons here that the US is 94 00:07:15,000 --> 00:07:19,520 Speaker 1: is so lagging in this regard. It's kind of complicated 95 00:07:19,840 --> 00:07:25,200 Speaker 1: why the US has not had a robust sequencing program. So, 96 00:07:25,600 --> 00:07:28,560 Speaker 1: like many things in this pandemic, the nature of our 97 00:07:28,600 --> 00:07:31,560 Speaker 1: country has mean this a bit more complicated. Right, we 98 00:07:31,640 --> 00:07:35,480 Speaker 1: have fifty different states. Things happen at federal level, at 99 00:07:35,520 --> 00:07:38,920 Speaker 1: state level, local level, and that's what we've we've seen 100 00:07:39,040 --> 00:07:44,920 Speaker 1: with sequencing efforts. It's happening at a constellation of public labs, 101 00:07:45,000 --> 00:07:49,559 Speaker 1: of private labs, of academic labs, and there's not really 102 00:07:49,600 --> 00:07:53,800 Speaker 1: a national program that connects all these things. So if 103 00:07:53,840 --> 00:07:56,320 Speaker 1: you're a lab that wants to contribute to this effort, 104 00:07:56,440 --> 00:07:59,040 Speaker 1: you have to figure out how do you get patient samples? 105 00:07:59,160 --> 00:08:03,800 Speaker 1: You know, Script Research Institute, for example, they told me 106 00:08:03,880 --> 00:08:06,560 Speaker 1: that they were able to get their program to do 107 00:08:06,640 --> 00:08:09,360 Speaker 1: this work up and running because they already had a 108 00:08:09,360 --> 00:08:13,720 Speaker 1: good relationship with the local health authorities, with the Sandy County. 109 00:08:13,840 --> 00:08:16,360 Speaker 1: So it's a little bit of serendipity that has allowed 110 00:08:16,400 --> 00:08:20,880 Speaker 1: these operations to to get up and running. And the 111 00:08:21,160 --> 00:08:24,400 Speaker 1: lack of a national program that sets up protocols like 112 00:08:24,440 --> 00:08:27,760 Speaker 1: where do you get the samples, how do you uh, 113 00:08:27,800 --> 00:08:31,000 Speaker 1: what format does the data come in? All of that 114 00:08:31,040 --> 00:08:34,400 Speaker 1: has made it harder to have a robust national effort 115 00:08:34,400 --> 00:08:38,240 Speaker 1: in the US. And as we see the first days 116 00:08:38,440 --> 00:08:42,280 Speaker 1: of the Biden administration, is this something that the administration 117 00:08:42,320 --> 00:08:46,160 Speaker 1: has prioritized that we'll be seeing more sequencing going forward. 118 00:08:47,040 --> 00:08:51,760 Speaker 1: So the Biden administration has said that it plans to 119 00:08:51,880 --> 00:08:56,520 Speaker 1: prioritize this. It plans to up the number of samples 120 00:08:56,559 --> 00:09:00,559 Speaker 1: that are getting sequenced every week, But we haven't seen 121 00:09:00,760 --> 00:09:04,360 Speaker 1: any concrete plans discussed yet. And I think it's going 122 00:09:04,400 --> 00:09:06,680 Speaker 1: to be a really big challenge because, as I mentioned, 123 00:09:06,720 --> 00:09:11,840 Speaker 1: it is a constellation of efforts that are public, private, local, 124 00:09:12,400 --> 00:09:17,480 Speaker 1: uh statewide that are is doing this sequencing, and you 125 00:09:17,520 --> 00:09:19,760 Speaker 1: have to figure out a system that can connect all 126 00:09:19,760 --> 00:09:21,800 Speaker 1: of those things, and that will be a kind of 127 00:09:21,840 --> 00:09:26,240 Speaker 1: gargantuan task. What are some of the additional benefits or 128 00:09:26,280 --> 00:09:29,800 Speaker 1: the importance to this genetic sequencing, I mean specifically for 129 00:09:30,160 --> 00:09:35,880 Speaker 1: other diseases beyond COVID nineteen. One thing that this pandemic 130 00:09:35,960 --> 00:09:39,360 Speaker 1: has shown that I think is actually really sort of 131 00:09:39,559 --> 00:09:45,160 Speaker 1: awesome is that sequencing can be a really powerful tool. Right. 132 00:09:45,760 --> 00:09:48,280 Speaker 1: We saw very early in the pandemic. I believe it 133 00:09:48,320 --> 00:09:52,520 Speaker 1: was in January we saw the first full genome of 134 00:09:52,520 --> 00:09:57,400 Speaker 1: this virus published That allowed us to very quickly demonstrate 135 00:09:57,800 --> 00:10:01,000 Speaker 1: how this virus had moved around the world, you know, 136 00:10:01,040 --> 00:10:03,760 Speaker 1: what countries that had traveled from, and that allowed us 137 00:10:03,800 --> 00:10:08,760 Speaker 1: to create policies that helped make our response more more 138 00:10:08,840 --> 00:10:14,079 Speaker 1: intelligent and more efficient. Right, And I think that going forward, 139 00:10:14,840 --> 00:10:18,360 Speaker 1: that same idea can be applied to many things. It 140 00:10:18,400 --> 00:10:23,400 Speaker 1: can help us more intelligently respond to superbugs. It could 141 00:10:23,440 --> 00:10:27,960 Speaker 1: help us respond to other future emerging zoonotic threats like 142 00:10:28,200 --> 00:10:32,040 Speaker 1: COVID nineteen. It can help us to detect people are 143 00:10:32,040 --> 00:10:35,400 Speaker 1: concerned about bio terror. It could help us detect potential 144 00:10:35,400 --> 00:10:40,040 Speaker 1: bio terror threats too. So I mean, this technology is 145 00:10:40,520 --> 00:10:45,800 Speaker 1: really important and has great potential to help us respond 146 00:10:46,400 --> 00:10:56,000 Speaker 1: to future threats to our national security. That was Kristin V. 147 00:10:56,120 --> 00:10:59,120 Speaker 1: Brown And that's it for our show today. For coverage 148 00:10:59,160 --> 00:11:02,000 Speaker 1: of the outbreak for one and twenty bureaus around the world, 149 00:11:02,400 --> 00:11:06,880 Speaker 1: visit Bloomberg dot com slash Coronavirus and if you like 150 00:11:07,000 --> 00:11:09,480 Speaker 1: the show, please leave us a review and a rating 151 00:11:09,679 --> 00:11:13,080 Speaker 1: on Apple Podcasts or Spotify. It's the best way to 152 00:11:13,080 --> 00:11:17,480 Speaker 1: help more listeners find our global reporting. The Prognosis Daily 153 00:11:17,600 --> 00:11:21,520 Speaker 1: edition is produced by top foreheads Magnus Henrickson and me 154 00:11:21,960 --> 00:11:26,480 Speaker 1: Laura Carlson. Today's main story was reported by Kristin V. Brown. 155 00:11:27,320 --> 00:11:31,440 Speaker 1: Original music by Leo Sedrin. Our editors are Rick Shine 156 00:11:31,440 --> 00:11:36,080 Speaker 1: and Francesco Levi. Francesco Levi is Bloomberg's out of podcasts. 157 00:11:36,520 --> 00:12:05,000 Speaker 1: Thanks for listening, Alo,