1 00:00:00,080 --> 00:00:02,480 Speaker 1: Hi, this is new due to the virus. I'm recording 2 00:00:02,560 --> 00:00:05,440 Speaker 1: from home, so you may notice a difference in audio 3 00:00:05,559 --> 00:00:13,240 Speaker 1: quality on this episode of News World. I recently read 4 00:00:13,280 --> 00:00:17,960 Speaker 1: a fascinating article in Nature entitled How Iceland Hammered COVID 5 00:00:18,000 --> 00:00:21,400 Speaker 1: with science. It details how Iceland, the island country with 6 00:00:21,480 --> 00:00:24,759 Speaker 1: the population of three hundred and sixty five thousand, was 7 00:00:24,800 --> 00:00:29,160 Speaker 1: able to test their population trace cases, enforce public health measures, 8 00:00:29,320 --> 00:00:31,639 Speaker 1: and reduce their COVID numbers to the point where they 9 00:00:31,640 --> 00:00:35,360 Speaker 1: could reopen their country for tourism, which contributes so greatly 10 00:00:35,640 --> 00:00:38,760 Speaker 1: to their economy. I started to wonder, how could the 11 00:00:38,840 --> 00:00:41,400 Speaker 1: United States apply some are all of the learnings from 12 00:00:41,440 --> 00:00:46,280 Speaker 1: the Iceland experience to help fight COVID. Here. Decogenetics, a 13 00:00:46,360 --> 00:00:49,879 Speaker 1: global leader in analyzing and understanding the human genome, has 14 00:00:49,920 --> 00:00:54,560 Speaker 1: played a crucial role in shaping Iceland's COVID strategy, working 15 00:00:54,640 --> 00:00:57,920 Speaker 1: hand in hand with Iceland's Director of Health, the government 16 00:00:57,960 --> 00:01:02,240 Speaker 1: agency that oversees how care services. Here it tell us 17 00:01:02,320 --> 00:01:06,600 Speaker 1: the story of Iceland's code approach is doctor Terry Stephenson, 18 00:01:06,880 --> 00:01:10,640 Speaker 1: who is the founder and CEO of Deco Genetics in Iceland. 19 00:01:22,200 --> 00:01:26,039 Speaker 1: I want to start if I could doctor Stephenson and 20 00:01:26,200 --> 00:01:29,360 Speaker 1: ask you what care you into all this? I mean, 21 00:01:29,400 --> 00:01:32,679 Speaker 1: you're sitting in Iceland and you follow an interesting track 22 00:01:33,160 --> 00:01:37,480 Speaker 1: that clue wasn't planned that this could act. This was 23 00:01:37,600 --> 00:01:42,240 Speaker 1: not something that was planned in advance. But basically when 24 00:01:42,440 --> 00:01:46,600 Speaker 1: the news of COVID nineteen made it to Iceland, it 25 00:01:47,319 --> 00:01:49,800 Speaker 1: was clear to us that this was all handsome, that 26 00:01:50,040 --> 00:01:52,720 Speaker 1: kind of a moment. So when you're living in a 27 00:01:52,760 --> 00:01:57,680 Speaker 1: small community where the distance between people is relatively small, 28 00:01:58,520 --> 00:02:02,960 Speaker 1: it is so much easier to find a way to contribute, 29 00:02:03,680 --> 00:02:06,160 Speaker 1: and that is what we did. We knew that the island, 30 00:02:06,160 --> 00:02:10,000 Speaker 1: the calcure system was not equipped to test as much 31 00:02:10,040 --> 00:02:14,160 Speaker 1: as needed, and we are Decode are extremely well equipped, 32 00:02:14,280 --> 00:02:19,120 Speaker 1: with incredible number of extremely talented young people who are 33 00:02:19,160 --> 00:02:23,200 Speaker 1: basically almost trained for doing this. And I'd argue that 34 00:02:23,880 --> 00:02:29,359 Speaker 1: basically our twenty five years of work looking for variance 35 00:02:29,440 --> 00:02:32,600 Speaker 1: in the human genome that affect the risk of common 36 00:02:32,680 --> 00:02:37,280 Speaker 1: diseases was almost just a preparation for dealing with something 37 00:02:37,680 --> 00:02:42,520 Speaker 1: like COVID nineteen. The beauty of the small community is 38 00:02:42,560 --> 00:02:45,079 Speaker 1: that I could just pick up the phone. I found them, 39 00:02:45,720 --> 00:02:48,480 Speaker 1: the Prime Minister of Iceland, and I told them We're 40 00:02:48,480 --> 00:02:50,000 Speaker 1: going to come in and we are going to help. 41 00:02:50,720 --> 00:02:54,720 Speaker 1: And it's not just that we organize testing of our 42 00:02:54,800 --> 00:02:59,600 Speaker 1: very last percentage of the Iceland depopulation. We sequenced the 43 00:02:59,720 --> 00:03:03,760 Speaker 1: gene all the virus from every person in facted, which 44 00:03:03,800 --> 00:03:05,799 Speaker 1: is the only place in the world that did that. 45 00:03:06,480 --> 00:03:09,840 Speaker 1: And why was it important to sequence the virus because 46 00:03:09,880 --> 00:03:13,400 Speaker 1: by looking at the combination of mutations in the virus, 47 00:03:13,600 --> 00:03:17,560 Speaker 1: we could determine where from the virus came. For example, 48 00:03:17,600 --> 00:03:20,760 Speaker 1: we could determine that, yes, in the beginning, the virus 49 00:03:20,800 --> 00:03:24,000 Speaker 1: came mostly from the ski slopes of Austria and Italy, 50 00:03:24,560 --> 00:03:27,280 Speaker 1: but gradually more and more of the virus started to 51 00:03:27,320 --> 00:03:30,720 Speaker 1: come from Great Britain, and once the virus was in 52 00:03:30,760 --> 00:03:35,720 Speaker 1: the country, we could determine who in facted whom. For exam, believe, 53 00:03:35,920 --> 00:03:39,480 Speaker 1: if Peter was supposed to have infected John, Peter and 54 00:03:39,560 --> 00:03:43,040 Speaker 1: John had to have the same combination of mutations, and 55 00:03:43,120 --> 00:03:45,680 Speaker 1: the reason we knew that it was Peter who in 56 00:03:45,720 --> 00:03:50,040 Speaker 1: facted John is that John had one additional mutation in 57 00:03:50,080 --> 00:03:53,120 Speaker 1: addition to Peter, so it could not happen Peter infected 58 00:03:53,200 --> 00:03:57,240 Speaker 1: John and all cancer tricks like that we could use 59 00:03:57,760 --> 00:04:00,240 Speaker 1: to help in mapping the spread to the virus. In 60 00:04:00,280 --> 00:04:05,000 Speaker 1: the country, help with a tracking other contacts, and basically 61 00:04:05,360 --> 00:04:10,000 Speaker 1: it worked perfectly and very quickly. After we started our 62 00:04:10,080 --> 00:04:15,480 Speaker 1: work on screening widely sequence survivors, track the contacts, etc. 63 00:04:16,320 --> 00:04:19,520 Speaker 1: We started to put the picture together right of scientific 64 00:04:19,600 --> 00:04:22,680 Speaker 1: papers to publish, to inform the rest of the world 65 00:04:22,800 --> 00:04:25,039 Speaker 1: on the vein in which we've been doing this. You 66 00:04:25,120 --> 00:04:29,279 Speaker 1: had a quarter century where you had been living out 67 00:04:29,279 --> 00:04:32,719 Speaker 1: a dream, you'd raise the money to make the dream impossible. 68 00:04:33,200 --> 00:04:36,680 Speaker 1: You've then done the work and pull together the teams. 69 00:04:36,800 --> 00:04:40,680 Speaker 1: I mean, Iceland was extraordinarily fortunate. And if you had 70 00:04:40,720 --> 00:04:43,760 Speaker 1: not been in Iceland, they wouldn't have had the capacity 71 00:04:43,760 --> 00:04:47,080 Speaker 1: to do what you did. Nude, It doesn't matter what 72 00:04:47,200 --> 00:04:52,040 Speaker 1: it is, it is always in the end individuals who 73 00:04:52,360 --> 00:04:57,279 Speaker 1: make a difference. It is the initiative of the individual 74 00:04:57,400 --> 00:05:00,799 Speaker 1: and then the individual who brings together team. And I 75 00:05:00,839 --> 00:05:04,719 Speaker 1: was fortunate as I was professor at Harvard, I got 76 00:05:04,760 --> 00:05:09,479 Speaker 1: this idea of starting a large population genetics initiative in Iceland. 77 00:05:10,120 --> 00:05:13,440 Speaker 1: So I left Harvard, came to Iceland, and I started 78 00:05:13,480 --> 00:05:16,640 Speaker 1: it from scratch. When I came to Iceland, there was 79 00:05:16,720 --> 00:05:19,680 Speaker 1: no tradition, there was no know how, there was no 80 00:05:19,760 --> 00:05:25,480 Speaker 1: experience in doing biomedical research like this, but it is astonishing. 81 00:05:25,560 --> 00:05:29,920 Speaker 1: I recruit almost solely people from Iceland, and there is 82 00:05:29,960 --> 00:05:34,520 Speaker 1: an astonishing collection or people who work here. But you 83 00:05:34,640 --> 00:05:37,360 Speaker 1: recruit in a very different way from the way in 84 00:05:37,400 --> 00:05:41,400 Speaker 1: which you recruit in America, because everyone you recruit into 85 00:05:41,440 --> 00:05:44,600 Speaker 1: a company like this in Iceland is a special purpose instrument. 86 00:05:45,200 --> 00:05:47,800 Speaker 1: You do not expect the people who come in to 87 00:05:47,880 --> 00:05:50,960 Speaker 1: be able to do everything, but you expect them to 88 00:05:51,000 --> 00:05:54,679 Speaker 1: be extremely good at something. And when you put together 89 00:05:55,040 --> 00:05:59,400 Speaker 1: basically a collas or a patch work like that, and 90 00:05:59,480 --> 00:06:04,200 Speaker 1: you with something that is absolutely spectacular. So I would 91 00:06:04,240 --> 00:06:08,080 Speaker 1: pitch the team. I have had a decode against any 92 00:06:08,480 --> 00:06:12,000 Speaker 1: university in the world when it comes to human genetics, 93 00:06:12,040 --> 00:06:16,120 Speaker 1: and these people were extremely eager to participate. So when 94 00:06:16,120 --> 00:06:19,880 Speaker 1: we started to screen in the beginning of March, basically 95 00:06:20,200 --> 00:06:25,680 Speaker 1: people worked here eighteen twenty hours day. No one complained, 96 00:06:26,000 --> 00:06:28,719 Speaker 1: No one asked, you know, when can we go home? 97 00:06:29,160 --> 00:06:32,440 Speaker 1: No one asked whether it was a Saturday or Sunday. 98 00:06:32,480 --> 00:06:37,520 Speaker 1: But everyone put the shoulder to the wheel and enjoyed it. 99 00:06:37,520 --> 00:06:41,520 Speaker 1: It was a difficult period, it was great fun. All right, 100 00:06:42,200 --> 00:06:45,640 Speaker 1: what percent of the population of Iceland do you now 101 00:06:45,680 --> 00:06:51,839 Speaker 1: have genetic data? For we have insight into the genetics 102 00:06:51,920 --> 00:06:55,400 Speaker 1: of every person living here. We have sequenced the whole 103 00:06:55,480 --> 00:06:58,960 Speaker 1: demon of a very last percentage of the population. We 104 00:06:59,040 --> 00:07:02,560 Speaker 1: have geno time using so called dinner type in ship 105 00:07:03,240 --> 00:07:06,400 Speaker 1: of about sixty percent of the population, and we can 106 00:07:06,480 --> 00:07:10,640 Speaker 1: infer there awful of about the genome of the rest 107 00:07:10,680 --> 00:07:14,720 Speaker 1: of the population. And this has allowed us to lead 108 00:07:14,720 --> 00:07:19,240 Speaker 1: to world in this population genetics that we're doing, and 109 00:07:19,440 --> 00:07:23,120 Speaker 1: you will find all over the world sort of replications 110 00:07:23,120 --> 00:07:25,280 Speaker 1: of what we have done. The UK buy a bank 111 00:07:26,200 --> 00:07:48,520 Speaker 1: is a British establishment. I think it's fascinating. You're sitting 112 00:07:48,560 --> 00:07:52,960 Speaker 1: at Harvard, you are already a well published expert researcher. 113 00:07:53,720 --> 00:07:57,440 Speaker 1: You have a big idea that's sort of theoretical, and 114 00:07:57,640 --> 00:08:00,160 Speaker 1: you're not really go back home twice some more. Is 115 00:08:00,240 --> 00:08:04,480 Speaker 1: probably the right sized population, and because of its unique 116 00:08:04,560 --> 00:08:10,240 Speaker 1: genetic history of being almost overwhelmingly believable Indinavia, you have 117 00:08:10,280 --> 00:08:14,120 Speaker 1: a unique population. But you then go off and decide 118 00:08:14,200 --> 00:08:17,080 Speaker 1: that to get this done right, you've got to get 119 00:08:17,120 --> 00:08:21,040 Speaker 1: private capital, because you wouldn't be able to say momentum 120 00:08:21,120 --> 00:08:23,160 Speaker 1: if you had to go from grant to grant to grant, 121 00:08:23,480 --> 00:08:26,400 Speaker 1: and you actually go out to raise the capital. That's 122 00:08:26,400 --> 00:08:28,480 Speaker 1: pretty amazing. How did you do that? Mean? What was 123 00:08:28,480 --> 00:08:31,960 Speaker 1: the core of your sales pitch? You see, I took 124 00:08:32,000 --> 00:08:38,199 Speaker 1: advantage of one of the unique features of American society, 125 00:08:38,280 --> 00:08:42,720 Speaker 1: which is the venture capital vote. And basically, when capital 126 00:08:42,840 --> 00:08:46,560 Speaker 1: is still almost solely an American sport, it's very little 127 00:08:46,600 --> 00:08:49,920 Speaker 1: of real venture capital in Europe, for example. So I 128 00:08:50,000 --> 00:08:53,680 Speaker 1: basically put together a story. The story had told most 129 00:08:53,720 --> 00:08:55,559 Speaker 1: that I'm going to go to Iceland. I'm going to 130 00:08:55,679 --> 00:08:58,920 Speaker 1: do something that no one has done before, which says 131 00:08:58,960 --> 00:09:01,160 Speaker 1: that I'm going to gather are a very large amount 132 00:09:01,200 --> 00:09:04,480 Speaker 1: of data on one population, and I'm going to gather 133 00:09:04,600 --> 00:09:08,480 Speaker 1: these data independent of the questions I might ask of 134 00:09:08,520 --> 00:09:12,280 Speaker 1: the data later. Because once you begin to collect data 135 00:09:12,760 --> 00:09:16,800 Speaker 1: based on your preconceived ideas as to what you might 136 00:09:16,920 --> 00:09:20,040 Speaker 1: want to discover or the questions you might want to ask, 137 00:09:20,520 --> 00:09:24,440 Speaker 1: you begin to generate biases in your data. All right, 138 00:09:24,960 --> 00:09:27,440 Speaker 1: So I said, I'm going to gather very large amount 139 00:09:27,480 --> 00:09:31,920 Speaker 1: of data on the same population, mostly independent of questions 140 00:09:31,920 --> 00:09:35,319 Speaker 1: I might ask, and the population, in addition to being 141 00:09:35,600 --> 00:09:39,760 Speaker 1: of the right size, has what is called a founder effect. 142 00:09:39,760 --> 00:09:42,679 Speaker 1: The founder effect is rooted in the fact that there 143 00:09:42,800 --> 00:09:46,120 Speaker 1: is a relatively small number of ancestors that I can't 144 00:09:46,160 --> 00:09:50,240 Speaker 1: for a fairly large percentage of the current population. So 145 00:09:50,400 --> 00:09:53,440 Speaker 1: if there is a rare mutation in the founders, it 146 00:09:53,600 --> 00:09:58,600 Speaker 1: becomes relatively common and the later population. And I told 147 00:09:58,679 --> 00:10:01,720 Speaker 1: him I will go there and I will do human 148 00:10:01,760 --> 00:10:04,960 Speaker 1: genetics like it has never been done before. And the 149 00:10:05,040 --> 00:10:07,360 Speaker 1: fact of the matter is that we have all right 150 00:10:08,320 --> 00:10:12,400 Speaker 1: on this barren left rock in the North Atlantic. We 151 00:10:12,640 --> 00:10:16,640 Speaker 1: put up an operation that has been out competing the 152 00:10:16,840 --> 00:10:21,800 Speaker 1: big universities in your wonderful country. So I'm very proud 153 00:10:21,800 --> 00:10:24,640 Speaker 1: of that. I'm proud of having started it from scratch 154 00:10:25,440 --> 00:10:28,280 Speaker 1: and it has worked nicely. But let me correct one thing. 155 00:10:29,520 --> 00:10:34,520 Speaker 1: You see, we are not just or Scandinavian origin. There's 156 00:10:34,559 --> 00:10:38,120 Speaker 1: a book called Book or Settlement that says that Iceland 157 00:10:38,160 --> 00:10:42,679 Speaker 1: was settled by Norwegian vikings who stopped by in Ireland 158 00:10:42,720 --> 00:10:45,840 Speaker 1: and picked up slaves. And we did a very large 159 00:10:46,360 --> 00:10:51,160 Speaker 1: genetic anthropology study, and we used the by chromosome as 160 00:10:51,240 --> 00:10:55,040 Speaker 1: marker of paternal lineage. I am to use the mitochondria, 161 00:10:55,679 --> 00:10:57,920 Speaker 1: which are the energy stations of the cell, as a 162 00:10:58,000 --> 00:11:01,520 Speaker 1: marker of maternal lineage because they are passed from mother 163 00:11:01,679 --> 00:11:05,280 Speaker 1: to offspin and he showed that in current day Iceland 164 00:11:05,400 --> 00:11:08,319 Speaker 1: is seventy five percent of the Y chromosome on Norwegian 165 00:11:09,080 --> 00:11:13,640 Speaker 1: sixty five percent of the Martel Contria Celtic. So Iceland 166 00:11:13,760 --> 00:11:17,520 Speaker 1: was settled by Norwegian boys went to Great Britain, picked 167 00:11:17,559 --> 00:11:20,520 Speaker 1: up women and went up to Iceland and settled down. 168 00:11:21,080 --> 00:11:24,080 Speaker 1: And there is no mention in the book of Settlement 169 00:11:24,240 --> 00:11:27,240 Speaker 1: whether the women came with mutual consent or not. But 170 00:11:27,440 --> 00:11:32,040 Speaker 1: they went up to Iceland. And it's interesting because we 171 00:11:32,080 --> 00:11:36,360 Speaker 1: started in Iceland to write books substantially sooner than elsewhere 172 00:11:36,360 --> 00:11:39,840 Speaker 1: in Scandinavia. So we probably brought with us, where the 173 00:11:39,920 --> 00:11:45,440 Speaker 1: women brought with them substantial amount of their Celtic culture, 174 00:11:46,160 --> 00:11:49,560 Speaker 1: the culture of the storytellers, all right, So we are 175 00:11:49,600 --> 00:11:55,240 Speaker 1: grateful for that vision scouts. So you're now telling me 176 00:11:55,280 --> 00:11:58,440 Speaker 1: I may well have relatives scattered all across Iceland. Yes, 177 00:11:59,200 --> 00:12:04,439 Speaker 1: and actually there are many things in your past news 178 00:12:04,600 --> 00:12:09,400 Speaker 1: that indicate that you would tap in a reasonable team 179 00:12:09,480 --> 00:12:13,000 Speaker 1: members during the time of the vikings. Yes, I think 180 00:12:13,000 --> 00:12:18,800 Speaker 1: that's right. I can see that. It's even more complex. 181 00:12:19,320 --> 00:12:21,760 Speaker 1: Then we went to skulls from the time of the 182 00:12:21,800 --> 00:12:26,320 Speaker 1: settlement of Iceland, all right. We isolated DNA from the 183 00:12:26,360 --> 00:12:28,640 Speaker 1: skulls of the settlement, and we looked at the same 184 00:12:28,720 --> 00:12:33,760 Speaker 1: genetic markers, and then we compared that to these markers 185 00:12:33,760 --> 00:12:38,200 Speaker 1: in current day Islanders versus current day Norwegians and current 186 00:12:38,240 --> 00:12:42,800 Speaker 1: day Bridge. And the amazing thing is that these genetic 187 00:12:42,880 --> 00:12:45,559 Speaker 1: markers from the time of the settlement from the skulls 188 00:12:46,320 --> 00:12:49,640 Speaker 1: have not changed. They are the same in Great Britain 189 00:12:49,679 --> 00:12:53,000 Speaker 1: today and the same in Norway today, but they are 190 00:12:53,080 --> 00:12:57,080 Speaker 1: different in Iceland. So over these thousand years we have 191 00:12:57,320 --> 00:13:00,839 Speaker 1: changed more than the Bridge, in spite to the fact 192 00:13:00,840 --> 00:13:04,640 Speaker 1: that we were isolated, or actually because we were isolated, 193 00:13:05,200 --> 00:13:08,120 Speaker 1: because we have gone through so many population bottom acts. 194 00:13:08,480 --> 00:13:11,440 Speaker 1: And when you go through a population bottom act, there's 195 00:13:11,440 --> 00:13:15,040 Speaker 1: a phenomenon that is called drift that takes place because 196 00:13:15,080 --> 00:13:19,080 Speaker 1: the chromosomes are shorted into the sperms and the eggs 197 00:13:19,120 --> 00:13:21,520 Speaker 1: in a random manner. And yet there is a tight 198 00:13:21,600 --> 00:13:26,320 Speaker 1: bottom act, you will lose genetic diversity. So living in 199 00:13:26,360 --> 00:13:30,400 Speaker 1: Iceland in this harsh nature or light for thousand to 200 00:13:30,440 --> 00:13:34,880 Speaker 1: eleven hundred years has changed out genetics more than the 201 00:13:34,960 --> 00:13:37,240 Speaker 1: genetics have changed in the Bridge. In spite to the 202 00:13:37,280 --> 00:13:40,160 Speaker 1: fact that there has been a continuous stream or people 203 00:13:40,200 --> 00:13:44,360 Speaker 1: coming through that that's an interesting aspect how the environment 204 00:13:45,080 --> 00:13:48,160 Speaker 1: is constantly changing us. I have to tell you one 205 00:13:48,200 --> 00:13:50,679 Speaker 1: quick story that I think that's exactly you're thinking. That 206 00:13:50,840 --> 00:13:54,080 Speaker 1: you can correct if you go to the American Museum 207 00:13:54,080 --> 00:13:57,400 Speaker 1: of Natural History. They have a huge hall that is 208 00:13:57,440 --> 00:14:00,280 Speaker 1: the Birds of the South Pacific that was called elected 209 00:14:00,320 --> 00:14:02,959 Speaker 1: in the twenties and thirties by great ornithologists named BIB. 210 00:14:03,640 --> 00:14:06,600 Speaker 1: When we ended up in a war with Japan, we 211 00:14:06,760 --> 00:14:11,880 Speaker 1: discovered that the only maps available for that region had 212 00:14:11,920 --> 00:14:15,720 Speaker 1: been gathered in the twenties and thirties by the ornithologists 213 00:14:15,760 --> 00:14:19,640 Speaker 1: for the purpose of tracking the bird populations. And so 214 00:14:19,760 --> 00:14:22,960 Speaker 1: here you had a basic research tool that nobody had 215 00:14:23,000 --> 00:14:26,240 Speaker 1: any idea would be useful in terms of dealing with 216 00:14:26,440 --> 00:14:29,080 Speaker 1: World War two, but it was sitting there and they 217 00:14:29,120 --> 00:14:31,800 Speaker 1: were able to borrow it and use it. I think 218 00:14:31,800 --> 00:14:35,680 Speaker 1: there's a huge argument for basic research that then makes 219 00:14:35,720 --> 00:14:40,720 Speaker 1: possible later on an amazing array of applied research. But 220 00:14:40,800 --> 00:14:42,800 Speaker 1: if you go in the opposite direction, you can't go 221 00:14:42,880 --> 00:14:46,400 Speaker 1: from applied to creating a model of basic research. Does 222 00:14:46,400 --> 00:14:49,480 Speaker 1: that make sense? It makes a lot of sense. And 223 00:14:49,600 --> 00:14:53,600 Speaker 1: basically because to be hot order the data be hot. 224 00:14:54,200 --> 00:14:57,400 Speaker 1: When the adverteming came because we have developed all the 225 00:14:57,560 --> 00:15:01,520 Speaker 1: software systems to menace exactly this type of data. This 226 00:15:01,720 --> 00:15:06,000 Speaker 1: offer systems to analyze exactly this data. Because we had 227 00:15:06,040 --> 00:15:09,040 Speaker 1: it tall then to do this, we could dive into it. 228 00:15:09,360 --> 00:15:12,480 Speaker 1: And basically, three days after we had decided we were 229 00:15:12,520 --> 00:15:16,000 Speaker 1: going to pitch in, we were screening for twenty four 230 00:15:16,040 --> 00:15:19,360 Speaker 1: hours a day. If we had not been doing what 231 00:15:19,520 --> 00:15:22,040 Speaker 1: we had done for the past twenty five years, there 232 00:15:22,120 --> 00:15:24,760 Speaker 1: is not a snowball chance that this could have been 233 00:15:24,760 --> 00:15:28,160 Speaker 1: done in Iceland. One of the things that I feel 234 00:15:28,240 --> 00:15:32,320 Speaker 1: compelled to say is that one of the reasons we 235 00:15:32,440 --> 00:15:36,560 Speaker 1: did well is that this is a very cohesive society 236 00:15:37,280 --> 00:15:41,400 Speaker 1: where an awful lot to what we do is rooted 237 00:15:41,600 --> 00:15:44,800 Speaker 1: in this fondness that we have for each other. That 238 00:15:44,880 --> 00:15:48,800 Speaker 1: we are used to help each other when things go wrong. 239 00:15:49,520 --> 00:15:53,800 Speaker 1: And I think that the societal cohesiveness is a fundamental 240 00:15:53,880 --> 00:15:58,000 Speaker 1: reason that he did so well with this epidemic. People 241 00:15:58,280 --> 00:16:01,480 Speaker 1: did abide by the rules, the measure that we put 242 00:16:01,520 --> 00:16:05,120 Speaker 1: in place to contain the epidemic, they will followed by everyone. 243 00:16:06,320 --> 00:16:09,200 Speaker 1: And I think that is arsiable that this nation that 244 00:16:09,360 --> 00:16:14,480 Speaker 1: is usually failure unruly when a crisis comes, we turn 245 00:16:14,520 --> 00:16:19,520 Speaker 1: our backs together I have a lot of interest invested 246 00:16:19,640 --> 00:16:22,360 Speaker 1: in the United States of America. I have a daughter 247 00:16:23,000 --> 00:16:26,960 Speaker 1: and three grandson who live in America are Americans. So 248 00:16:27,080 --> 00:16:30,880 Speaker 1: I really want this last country of yours to do well, 249 00:16:31,080 --> 00:16:35,480 Speaker 1: and it has been going through tumultuous times, right, that's right. 250 00:16:35,720 --> 00:16:38,720 Speaker 1: You know you see a certain parallelism. I think if 251 00:16:38,760 --> 00:16:43,000 Speaker 1: you look at Korea and Japan and Taiwan and Singapore, 252 00:16:43,680 --> 00:16:47,440 Speaker 1: that there are cultures lead them to a more immediate 253 00:16:48,040 --> 00:16:52,400 Speaker 1: adaptation to crisis mentality, and they were all able to 254 00:16:52,440 --> 00:16:57,080 Speaker 1: get people to change their behavior much much faster than weekend. Also, 255 00:16:57,120 --> 00:17:02,760 Speaker 1: the messages in your country versial mixed. Yes, let's put 256 00:17:02,800 --> 00:17:06,800 Speaker 1: it this way. I think that your former precedent would 257 00:17:06,880 --> 00:17:09,480 Speaker 1: have done much better if he had listened to scientists. 258 00:17:10,320 --> 00:17:13,360 Speaker 1: I think that's right. I mean, I think that the 259 00:17:13,480 --> 00:17:16,280 Speaker 1: challenge you have is and even among the public health 260 00:17:16,840 --> 00:17:20,040 Speaker 1: was constant in fighting. You're an earlier point that when 261 00:17:20,040 --> 00:17:23,560 Speaker 1: you're threatening seventy five thousousand people, you can have an 262 00:17:23,600 --> 00:17:27,720 Speaker 1: intimacy at the senior levels where people can actually be practical. 263 00:17:28,600 --> 00:17:31,159 Speaker 1: We have probably more than that number of people in 264 00:17:31,200 --> 00:17:37,240 Speaker 1: our public health crecy. That's a huge problem for us 265 00:17:37,359 --> 00:17:41,000 Speaker 1: right now. We've grown beyond our ability to be competent. Yeah, 266 00:17:41,080 --> 00:17:47,720 Speaker 1: but that's true. But in biology, just like in physics, etc. 267 00:17:48,200 --> 00:17:52,840 Speaker 1: There are some things that are indisputable a lot. And 268 00:17:53,000 --> 00:17:57,400 Speaker 1: when it comes to the containment of an epidemic, there 269 00:17:57,440 --> 00:18:02,880 Speaker 1: are certain basic factors that you basically should do and 270 00:18:02,960 --> 00:18:07,240 Speaker 1: they weren't done in the stays, unfortunately, And it is 271 00:18:07,240 --> 00:18:10,560 Speaker 1: so shad because of this enormous potential. What we know 272 00:18:10,920 --> 00:18:13,320 Speaker 1: in the rest of the world and it comes to 273 00:18:13,480 --> 00:18:17,680 Speaker 1: containing and everything looks like this we learned from Americans, 274 00:18:17,840 --> 00:18:20,399 Speaker 1: all right, and then we sit there the rest of 275 00:18:20,440 --> 00:18:41,240 Speaker 1: the world and what's you screw this ude for Americans? 276 00:18:41,520 --> 00:18:44,439 Speaker 1: Would you walk us through from the very beginning of 277 00:18:44,480 --> 00:18:46,879 Speaker 1: the discovering that there was a pandemic, what were the 278 00:18:46,920 --> 00:18:50,679 Speaker 1: steps that Iceland talk and sequence that enabled them to 279 00:18:50,840 --> 00:18:54,640 Speaker 1: have such a dramatically better containment strategy. First of all, 280 00:18:54,680 --> 00:18:56,960 Speaker 1: we are an island in the middle of the Atlantic, 281 00:18:57,400 --> 00:19:02,440 Speaker 1: don't forget that. But when we learned of the emerging 282 00:19:02,520 --> 00:19:07,240 Speaker 1: epidemic coming out to China, we started to screen for 283 00:19:07,400 --> 00:19:10,440 Speaker 1: the virus more than a month before the first case 284 00:19:10,560 --> 00:19:15,840 Speaker 1: was diagnosed, So we started to screen. We anticipated that 285 00:19:15,960 --> 00:19:19,680 Speaker 1: this would come. Then when the cases started to pile 286 00:19:19,760 --> 00:19:23,600 Speaker 1: in from the ski slopes of Austria and Italy. Decode 287 00:19:24,400 --> 00:19:28,240 Speaker 1: started to screen and we put our entire company on 288 00:19:28,320 --> 00:19:31,360 Speaker 1: the screening. And keep in mind we are owned by Anjen, 289 00:19:32,000 --> 00:19:36,199 Speaker 1: an American corporation. And I just phoned the CEO of 290 00:19:36,320 --> 00:19:39,199 Speaker 1: Bungyin and I got his permission. You know it's not 291 00:19:39,240 --> 00:19:42,000 Speaker 1: correct a sentiment email and I got back an email 292 00:19:42,080 --> 00:19:45,560 Speaker 1: that's set. Do whatever you can to have the government 293 00:19:45,640 --> 00:19:49,560 Speaker 1: dealing with this. And this entire time since the arrival 294 00:19:49,600 --> 00:19:53,840 Speaker 1: of the epidemic, we have been using resources are Deco 295 00:19:53,920 --> 00:19:58,920 Speaker 1: genetics that come from Anjen. No questions asked to how 296 00:19:59,080 --> 00:20:01,840 Speaker 1: to contain the epidemic in Iceland, and for that time 297 00:20:01,920 --> 00:20:08,360 Speaker 1: extremely grateful through even their very capitalistic big cooperations. At 298 00:20:08,359 --> 00:20:12,239 Speaker 1: a moment like this, they rise and show what they 299 00:20:12,240 --> 00:20:16,960 Speaker 1: are made of. Alight. It is interesting that in attempts 300 00:20:16,960 --> 00:20:21,320 Speaker 1: to develop vaccines and medicines to treat this disease, the 301 00:20:21,440 --> 00:20:24,440 Speaker 1: pharmashould gal industry, which is usually looked up on as 302 00:20:24,440 --> 00:20:28,640 Speaker 1: the bad guys, have been extraordinarily noble. They have tirted 303 00:20:28,680 --> 00:20:32,520 Speaker 1: backs together, they have been helping each other, and they 304 00:20:32,560 --> 00:20:36,200 Speaker 1: have plots not to use these vaccines for these medicines 305 00:20:36,240 --> 00:20:40,440 Speaker 1: they are making, not to use them to get extraordinarily 306 00:20:41,040 --> 00:20:44,080 Speaker 1: a profit from it, but to distribute it at a 307 00:20:44,080 --> 00:20:46,679 Speaker 1: low price. And I think that is wonderful. That is 308 00:20:46,720 --> 00:20:51,640 Speaker 1: the nice sight of their pharmashoold gal industry. So when 309 00:20:51,640 --> 00:20:55,640 Speaker 1: you began the tracing and the testing, it was un 310 00:20:55,720 --> 00:20:57,960 Speaker 1: a point where you closed the entire society down to 311 00:20:58,080 --> 00:21:02,200 Speaker 1: isolate it. No, we never closed to society down. When 312 00:21:02,200 --> 00:21:05,960 Speaker 1: we started to screen, when the cases started to sort 313 00:21:06,000 --> 00:21:09,080 Speaker 1: of pilot, what we did is that we closed the 314 00:21:09,200 --> 00:21:12,520 Speaker 1: orchestral halls, the movie theaters, We kept all of the 315 00:21:12,600 --> 00:21:17,040 Speaker 1: stores open. We kept the elementary schools open, but we 316 00:21:17,160 --> 00:21:21,320 Speaker 1: closed to universities and the higher schools of education. We 317 00:21:21,480 --> 00:21:26,440 Speaker 1: insisted on two meters social distancing. We were very focused 318 00:21:26,520 --> 00:21:30,880 Speaker 1: on having people washed their hands, etc. And we had 319 00:21:31,000 --> 00:21:35,919 Speaker 1: extraordinarily competent team during the contact tracing. And it is 320 00:21:35,960 --> 00:21:41,440 Speaker 1: interesting that their contact tracing in Iceland was run by 321 00:21:41,480 --> 00:21:45,280 Speaker 1: the police department all right, and they did an extraordinary 322 00:21:45,359 --> 00:21:50,480 Speaker 1: job of it was spectacularly well done. We allowed the 323 00:21:50,680 --> 00:21:54,920 Speaker 1: use of an app on cellular phones that allowed sort 324 00:21:54,920 --> 00:21:58,639 Speaker 1: of the determine who had been closed to someone else 325 00:21:59,520 --> 00:22:02,840 Speaker 1: was in fact did and the enemy used our viral 326 00:22:02,920 --> 00:22:07,359 Speaker 1: sequencing data to determine the way and the direction in 327 00:22:07,440 --> 00:22:11,119 Speaker 1: which the virus spread. With the app and the contact tracing, 328 00:22:11,800 --> 00:22:18,200 Speaker 1: you were able to pursue a policy of selective isolation. Yes, 329 00:22:18,440 --> 00:22:23,320 Speaker 1: rather than the whole society. You're absolutely correct. By using science, 330 00:22:23,400 --> 00:22:28,280 Speaker 1: we could use selective isolation around closing down the society. 331 00:22:28,359 --> 00:22:32,399 Speaker 1: And we put those in fact it in isolation, and 332 00:22:32,800 --> 00:22:35,760 Speaker 1: we put their contacts in a two week quarantine, and 333 00:22:35,840 --> 00:22:39,399 Speaker 1: those who were diagnosed were capt in isolation until they 334 00:22:39,440 --> 00:22:43,600 Speaker 1: had been asymptomatic for a week. Now, as I understand, 335 00:22:43,680 --> 00:22:46,480 Speaker 1: I saw a brief article to day you actually as 336 00:22:46,480 --> 00:22:50,720 Speaker 1: a country made the decision to reopen tourism, and I 337 00:22:50,760 --> 00:22:53,080 Speaker 1: saw some note you'd had people from like forty six 338 00:22:53,080 --> 00:22:56,760 Speaker 1: countries have come through. How are you able to do that? 339 00:22:57,200 --> 00:22:59,760 Speaker 1: We did that by screening people when they came in. 340 00:23:00,760 --> 00:23:06,240 Speaker 1: But unfortunately screaming ones is not sufficient. So basically on 341 00:23:06,320 --> 00:23:10,399 Speaker 1: the nineteens who August, we had to implement a different 342 00:23:10,400 --> 00:23:14,280 Speaker 1: system where people who came into the country was screened 343 00:23:14,320 --> 00:23:16,919 Speaker 1: when they came in. We're put in five day quarantine 344 00:23:16,960 --> 00:23:21,679 Speaker 1: and then screened again. And now that the epidemic is 345 00:23:21,720 --> 00:23:25,679 Speaker 1: searching in all of the country surrounders. The number of 346 00:23:25,720 --> 00:23:29,000 Speaker 1: cases has been increasing in Great Britain and Germany all 347 00:23:29,040 --> 00:23:34,160 Speaker 1: over the place. That basically having the borders of Iceland 348 00:23:34,280 --> 00:23:38,800 Speaker 1: controlled by double screening, separated by a quarantine is the 349 00:23:38,840 --> 00:23:42,080 Speaker 1: reason that you yesterday, I think we had two cases 350 00:23:42,160 --> 00:23:47,440 Speaker 1: or something like that week a boy monitoring our borders closely. 351 00:23:48,200 --> 00:23:52,840 Speaker 1: We are managing to have a reasonably normal life in Iceland. 352 00:23:53,440 --> 00:23:55,720 Speaker 1: Would it take two big a ramp up for a 353 00:23:55,800 --> 00:23:59,840 Speaker 1: country's like a Great Britain or a Germany to blilpply 354 00:24:00,119 --> 00:24:03,800 Speaker 1: your model? It's complicated. For Germany, it is complicated because 355 00:24:03,840 --> 00:24:07,719 Speaker 1: they are surrounded by other countries where the boarders that 356 00:24:07,760 --> 00:24:12,000 Speaker 1: are not particularly well watched. Great Britain certainly could do it. 357 00:24:12,840 --> 00:24:16,000 Speaker 1: Great Britain hasn't done much better than the United States, 358 00:24:16,600 --> 00:24:19,640 Speaker 1: which is another interesting thing with all of these spectatul 359 00:24:20,400 --> 00:24:24,560 Speaker 1: academic institutions. They haven't done any better, all right, And 360 00:24:24,720 --> 00:24:27,360 Speaker 1: in spite of the National Health Service and all of that, 361 00:24:27,400 --> 00:24:32,199 Speaker 1: they haven't done particularly well. Did you expect everyone in 362 00:24:32,280 --> 00:24:36,359 Speaker 1: Iceland to get the vaccination? We had a part of 363 00:24:36,400 --> 00:24:40,199 Speaker 1: this pact that includes the European Union, that is, you know, 364 00:24:40,400 --> 00:24:45,520 Speaker 1: buying vaccine and distributing vaccine, and it is happening very slowly. 365 00:24:46,800 --> 00:24:52,200 Speaker 1: Feiser is behind schedule and delivering vaccine Astrosenny case behind schedule. 366 00:24:52,960 --> 00:24:54,840 Speaker 1: My guess is that we are not going to be 367 00:24:54,880 --> 00:24:59,080 Speaker 1: done with vaccinating our country until you know, late next 368 00:24:59,080 --> 00:25:02,240 Speaker 1: four and the same is going to apply to most 369 00:25:02,280 --> 00:25:05,280 Speaker 1: countries in Europe. The United States is going to be 370 00:25:05,320 --> 00:25:07,119 Speaker 1: a little bit ahead. They are probably going to be 371 00:25:07,160 --> 00:25:11,359 Speaker 1: two to three months ahead of us, if you can 372 00:25:11,600 --> 00:25:15,919 Speaker 1: take the numbers that people are throwing around seriously. And 373 00:25:16,080 --> 00:25:18,000 Speaker 1: one of the things that we will have to deal 374 00:25:18,040 --> 00:25:22,600 Speaker 1: with now once this year it is over, is the 375 00:25:22,640 --> 00:25:26,480 Speaker 1: fact that these western parts of the world, these rich countries, 376 00:25:27,040 --> 00:25:30,680 Speaker 1: have border up over nine all of their vaccine produced. 377 00:25:31,280 --> 00:25:34,119 Speaker 1: So we are going to have the Third World, you know, 378 00:25:34,320 --> 00:25:37,560 Speaker 1: devastated by disease for a long time after we have 379 00:25:37,680 --> 00:25:41,520 Speaker 1: come out of this. In many ways, it is incredibly 380 00:25:42,240 --> 00:25:48,400 Speaker 1: undesirable to have so unequitable distribution of vaccine, even if 381 00:25:48,440 --> 00:25:53,080 Speaker 1: you're only focusing on our attempts to put this virus 382 00:25:53,119 --> 00:25:58,280 Speaker 1: to rest. To have a large population pocket where the 383 00:25:58,440 --> 00:26:01,320 Speaker 1: disease is rampant is going to make it much more 384 00:26:01,359 --> 00:26:05,439 Speaker 1: complicated to bring it under control. Do you worry that 385 00:26:05,520 --> 00:26:09,639 Speaker 1: the mutations that were starting to see that one of 386 00:26:09,680 --> 00:26:12,320 Speaker 1: them could break out in a way that would make 387 00:26:12,440 --> 00:26:17,000 Speaker 1: the current vaccines irrelevant because they simply wouldn't be susceptible 388 00:26:17,040 --> 00:26:23,199 Speaker 1: to it. I'm not particularly concerned about these mutations. There 389 00:26:23,320 --> 00:26:26,399 Speaker 1: is an incredible number of mutations. The virus has in 390 00:26:26,400 --> 00:26:29,040 Speaker 1: facted almost one hundred million people, so it has had 391 00:26:29,080 --> 00:26:33,359 Speaker 1: so enormous opportunity to mutate. And even though people say 392 00:26:33,440 --> 00:26:37,240 Speaker 1: that the British verse and other virus is more infectious 393 00:26:37,400 --> 00:26:41,480 Speaker 1: than most of it, it is possibly correct, but it 394 00:26:41,640 --> 00:26:46,680 Speaker 1: isn't dramatically more infectious, and exactly the same methods that 395 00:26:46,920 --> 00:26:49,679 Speaker 1: I used to contain the spread to the virus in 396 00:26:49,800 --> 00:26:54,679 Speaker 1: general apply to their British version. We have had bunch 397 00:26:54,720 --> 00:26:58,240 Speaker 1: of individuals in fact it with the British virus. One 398 00:26:58,280 --> 00:27:01,680 Speaker 1: of the things that happens very often when a virus 399 00:27:01,840 --> 00:27:05,640 Speaker 1: like these mutates to become more infectious is that at 400 00:27:05,640 --> 00:27:09,560 Speaker 1: the same time it becomes less harmful, because it serves 401 00:27:09,600 --> 00:27:12,520 Speaker 1: the interest of the virus to have the people who 402 00:27:12,520 --> 00:27:15,800 Speaker 1: are infected as healthy as possible so they can move 403 00:27:15,840 --> 00:27:19,560 Speaker 1: around then spread the virus. But there are those who 404 00:27:19,600 --> 00:27:23,359 Speaker 1: insist that the British form is a little bit more dangerous. 405 00:27:23,400 --> 00:27:26,199 Speaker 1: But these are the differences of degree, not of nature. 406 00:27:26,800 --> 00:27:30,480 Speaker 1: And then the question is is the South African valiant 407 00:27:30,560 --> 00:27:35,560 Speaker 1: going to escape the protection from the vaccine, And there 408 00:27:35,640 --> 00:27:39,320 Speaker 1: is very little data supporting that it may be a 409 00:27:39,320 --> 00:27:43,840 Speaker 1: little bit less protected by their moderna vaccine than the 410 00:27:43,960 --> 00:27:47,679 Speaker 1: usual form of the virus, but not dramatically. So we 411 00:27:47,760 --> 00:27:52,080 Speaker 1: will contain this virus with vaccines. And even if one 412 00:27:52,160 --> 00:27:56,160 Speaker 1: form would escape, it takes these companies today extraordinarily shure 413 00:27:56,240 --> 00:27:59,480 Speaker 1: time to develop a new vaccine, So I don't buy 414 00:27:59,520 --> 00:28:02,280 Speaker 1: the nose that we will have. This value is around 415 00:28:02,480 --> 00:28:04,879 Speaker 1: for a long time and this will be sason or 416 00:28:05,000 --> 00:28:08,720 Speaker 1: what taver we're going to get out for this. On 417 00:28:08,960 --> 00:28:12,000 Speaker 1: that cheerful note, I'm going to thank you. This has 418 00:28:12,040 --> 00:28:18,840 Speaker 1: been wonderful, great conversation. Thank you, Thank you to my 419 00:28:18,920 --> 00:28:22,360 Speaker 1: guest doctor Carry Stephenson. You can read more about how 420 00:28:22,400 --> 00:28:27,159 Speaker 1: Iceland conquered COVID on our show page at newtsworld dot com. 421 00:28:27,320 --> 00:28:31,640 Speaker 1: Newtsworld is produced by Gingwish three sixty and iHeartMedia. Our 422 00:28:31,720 --> 00:28:36,159 Speaker 1: executive producer is Debbie Myers, our producer is Guardzi Sloan, 423 00:28:36,520 --> 00:28:39,920 Speaker 1: and our researcher is Rachel Peterson. The artwork for the 424 00:28:39,960 --> 00:28:44,040 Speaker 1: show was created by Steve Fenman. Special thanks to the 425 00:28:44,040 --> 00:28:47,280 Speaker 1: team at gingwis thweet sixty. If you've been to enjoy Newtsworld, 426 00:28:47,600 --> 00:28:50,480 Speaker 1: I hope you'll go to Apple Podcasts and both rate 427 00:28:50,560 --> 00:28:53,840 Speaker 1: us with five stars and give us a review so 428 00:28:53,920 --> 00:28:56,640 Speaker 1: others can learn what it's all about. It Right now, 429 00:28:56,960 --> 00:28:59,600 Speaker 1: listeners at newts World can sign up for my three 430 00:28:59,600 --> 00:29:04,600 Speaker 1: free weekly columns at Gingwich three sixty dot com slash newsletter. 431 00:29:04,960 --> 00:29:07,080 Speaker 1: I'm new Gingwich. This is newswork.