1 00:00:00,240 --> 00:00:02,480 Speaker 1: Hi, this is newt twenty twenty is going to be 2 00:00:02,520 --> 00:00:05,160 Speaker 1: one of the most extraordinary election years of our lifetime. 3 00:00:05,360 --> 00:00:07,560 Speaker 1: I want to invite you to join my Inner Circle 4 00:00:07,920 --> 00:00:10,280 Speaker 1: as we discuss each twist and turn in the race 5 00:00:10,320 --> 00:00:13,640 Speaker 1: and my members only Inner Circle Club. You will receive 6 00:00:13,760 --> 00:00:18,960 Speaker 1: special flash briefings, online events, and members only audio reports 7 00:00:18,960 --> 00:00:21,599 Speaker 1: from me and my team. Here's a special offer to 8 00:00:21,640 --> 00:00:24,880 Speaker 1: my podcast listeners. If you joined the Inner Circle today 9 00:00:24,920 --> 00:00:27,760 Speaker 1: at Newtcenter Circle dot com and sign up for a 10 00:00:27,800 --> 00:00:30,720 Speaker 1: one or two year membership, I'll send you a free 11 00:00:30,960 --> 00:00:34,760 Speaker 1: personally autographed copy of my book Jettisburg and a VIP 12 00:00:35,000 --> 00:00:39,000 Speaker 1: fast pass to my live events. Join my Inner Circle 13 00:00:39,080 --> 00:00:43,800 Speaker 1: today at Newtsinner Circle dot com. Use the code free 14 00:00:43,840 --> 00:00:47,600 Speaker 1: book at checkout. Sign up today at Newts Inner Circle 15 00:00:47,680 --> 00:00:52,680 Speaker 1: dot com Code free Book. This offer ends January thirty first. 16 00:00:59,000 --> 00:01:02,360 Speaker 1: On this episode The Newts World, we first heard about 17 00:01:02,360 --> 00:01:05,560 Speaker 1: the coronavirus three weeks ago, and we've been watching the 18 00:01:05,600 --> 00:01:09,800 Speaker 1: global death toll ever since. As China continues its national 19 00:01:09,880 --> 00:01:13,959 Speaker 1: quarantine walking down whole cities, other countries around the globe 20 00:01:13,959 --> 00:01:17,759 Speaker 1: worry if they could be next. The question remains, are 21 00:01:17,800 --> 00:01:21,200 Speaker 1: we facing the next global pandemic? As you'll hear in 22 00:01:21,240 --> 00:01:24,759 Speaker 1: this episode, we just don't know yet. At the time 23 00:01:24,760 --> 00:01:28,200 Speaker 1: I recorded this episode, there were twelve cases of coronavirus 24 00:01:28,240 --> 00:01:30,760 Speaker 1: in the United States, and the death toll in China, 25 00:01:31,080 --> 00:01:34,119 Speaker 1: where the disease started is at five hundred and sixty 26 00:01:34,160 --> 00:01:38,600 Speaker 1: three and continuing to increase. We'll look at the epidemiology 27 00:01:38,959 --> 00:01:43,040 Speaker 1: of the coronavirus and explain what we as Americans should 28 00:01:43,080 --> 00:01:47,080 Speaker 1: be concerned about. I'm pleased to welcome my guests, doctor 29 00:01:47,120 --> 00:01:50,320 Speaker 1: Anthony Fauci, the director of the National Institute of Aology 30 00:01:50,520 --> 00:01:53,640 Speaker 1: and Infectious Diseases at the National Institutes of Health, and 31 00:01:54,400 --> 00:01:58,800 Speaker 1: doctor Peter Dassik, president of the Eco Health Alliance and 32 00:01:59,000 --> 00:02:11,120 Speaker 1: a Disease ecolled Doctor Anthony Faushy, director of the nationals 33 00:02:11,200 --> 00:02:14,640 Speaker 1: Toute of Allergy and Infectious Diseases at the Nationalist to 34 00:02:14,720 --> 00:02:18,480 Speaker 1: Its Health. Let's talk about what we're going through with 35 00:02:18,680 --> 00:02:22,359 Speaker 1: coronavirus and what your sense is about the scale of 36 00:02:22,400 --> 00:02:27,320 Speaker 1: the challenge and the concerns you have. You know, it's 37 00:02:27,320 --> 00:02:32,040 Speaker 1: a moving target, it's evolving. It is clearly a very 38 00:02:32,160 --> 00:02:37,119 Speaker 1: serious problem in China. It could be and turn out 39 00:02:37,160 --> 00:02:41,640 Speaker 1: to be a very serious problem for the world in 40 00:02:41,760 --> 00:02:47,000 Speaker 1: that it has the makings and the capability of evolving 41 00:02:47,120 --> 00:02:51,520 Speaker 1: into a global pandemic, But it's evolving in the sense 42 00:02:51,680 --> 00:02:55,080 Speaker 1: of we know a lot about it now than we 43 00:02:55,160 --> 00:02:58,040 Speaker 1: did a month ago, but there's still a lot about 44 00:02:58,080 --> 00:03:00,840 Speaker 1: it that we don't know. What do we know? We 45 00:03:00,960 --> 00:03:04,520 Speaker 1: know it is a virus of the coronavirus family, the 46 00:03:04,639 --> 00:03:09,040 Speaker 1: same virus that gave us the Stars outbreak in two 47 00:03:09,080 --> 00:03:13,760 Speaker 1: thousand and two and the Mayor's Middle East Respiratory syndrome 48 00:03:14,400 --> 00:03:18,760 Speaker 1: in two thousand and twelve. It's similar in some respects 49 00:03:18,800 --> 00:03:23,040 Speaker 1: and different. It's different in that it spreads more easily 50 00:03:23,080 --> 00:03:28,280 Speaker 1: and rapidly. It also has a situation where the mortality 51 00:03:28,400 --> 00:03:32,600 Speaker 1: rate now is about two percent when you look at 52 00:03:32,639 --> 00:03:35,280 Speaker 1: all of the people in China, because there's not much 53 00:03:35,720 --> 00:03:41,160 Speaker 1: infections outside of China. There really are only about twenty 54 00:03:41,320 --> 00:03:48,120 Speaker 1: six countries that have cases that are almost exclusively travel 55 00:03:48,200 --> 00:03:53,320 Speaker 1: related cases with some secondary transmissions to people who are 56 00:03:53,320 --> 00:03:59,440 Speaker 1: close contacts. So with two percent mortality is compared to 57 00:03:59,680 --> 00:04:03,360 Speaker 1: SAW which has a nine to ten percent mortality, compared 58 00:04:03,400 --> 00:04:06,360 Speaker 1: to mayors, which has a thirty six percent mortality. But 59 00:04:06,480 --> 00:04:12,000 Speaker 1: if you compare it to other respiratory diseases, seasonal flu 60 00:04:12,320 --> 00:04:17,200 Speaker 1: which imposes a great disease burden and death throughout the world. 61 00:04:17,839 --> 00:04:20,880 Speaker 1: In the United States, there are anywhere from thirty thousand 62 00:04:20,920 --> 00:04:24,760 Speaker 1: to seventy nine thousand deaths from flu each year and 63 00:04:24,960 --> 00:04:30,360 Speaker 1: hundreds of thousands of hospitalizations. We have a situation where 64 00:04:30,640 --> 00:04:34,640 Speaker 1: the death rate is only point one percent. Pandemic flu 65 00:04:34,760 --> 00:04:38,320 Speaker 1: of nineteen sixty eight was about point eight to one, 66 00:04:38,400 --> 00:04:43,320 Speaker 1: and the real terrible flu in nineteen eighteen, the famous 67 00:04:43,960 --> 00:04:47,039 Speaker 1: Spanish flu which kills fifty to one hundred million people, 68 00:04:47,880 --> 00:04:51,560 Speaker 1: that had a death rate of about two percent. Now, 69 00:04:51,680 --> 00:04:54,120 Speaker 1: I do not believe Newt that the death rate in 70 00:04:54,160 --> 00:04:57,359 Speaker 1: this disease is going to stay at two percent. I 71 00:04:57,400 --> 00:04:59,920 Speaker 1: think it's going to be less because as the disease 72 00:05:00,600 --> 00:05:04,560 Speaker 1: spreads more, you get more people who are minimally symptomatic 73 00:05:05,120 --> 00:05:10,320 Speaker 1: or asymptomatic, so the denominator of the calculation becomes much 74 00:05:10,520 --> 00:05:14,600 Speaker 1: much bigger. So as of last night, there were twenty 75 00:05:14,600 --> 00:05:18,839 Speaker 1: eight thousand cases reported and about five hundred and fifty 76 00:05:18,960 --> 00:05:23,839 Speaker 1: or so deaths, which gives you a two percent death rate. However, 77 00:05:23,880 --> 00:05:27,599 Speaker 1: if you count all of the people who are either 78 00:05:27,839 --> 00:05:32,720 Speaker 1: asymptomatic or minimally symptomatic, the denominator increases and that goes 79 00:05:32,760 --> 00:05:36,880 Speaker 1: down The critical issue that really is evolving now is 80 00:05:36,960 --> 00:05:41,640 Speaker 1: the draconian actions that have been taken both by the Chinese, 81 00:05:41,680 --> 00:05:46,799 Speaker 1: where they've cut off fifty million people, preventing travel by train, 82 00:05:46,960 --> 00:05:50,359 Speaker 1: by air, by ferry in and out of cities like 83 00:05:50,640 --> 00:05:55,040 Speaker 1: Wuhan which has eleven million people, and other countries which 84 00:05:55,040 --> 00:05:58,839 Speaker 1: are to a greater or lesser degree closing their borders, 85 00:05:58,839 --> 00:06:03,000 Speaker 1: and the United States, which has done the unprecedented move 86 00:06:03,760 --> 00:06:09,840 Speaker 1: of doing a temporary type of travel restriction from China. 87 00:06:10,080 --> 00:06:16,719 Speaker 1: In general, those kinds of moves have potentially unintended negative consequences, 88 00:06:17,360 --> 00:06:20,120 Speaker 1: but the purpose of doing that I think has some 89 00:06:20,279 --> 00:06:24,440 Speaker 1: logic to it new in that these kinds of restrictions 90 00:06:25,080 --> 00:06:29,440 Speaker 1: tend to not stop the ultimate spread of an outbreak, 91 00:06:29,480 --> 00:06:33,159 Speaker 1: but to slow it down from getting into a particular country. 92 00:06:33,960 --> 00:06:38,720 Speaker 1: So if we could slow this down enough until it 93 00:06:38,800 --> 00:06:42,720 Speaker 1: actually turns the corner itself on the basis of what 94 00:06:42,760 --> 00:06:45,800 Speaker 1: the Chinese are doing to try and contain it, on 95 00:06:45,839 --> 00:06:48,760 Speaker 1: the basis of as you get into the spring weather 96 00:06:48,960 --> 00:06:54,000 Speaker 1: with warmth, coronaviruses tend not to spread very well at all, 97 00:06:55,200 --> 00:06:58,279 Speaker 1: same as flu, and the reason why you have a 98 00:06:58,320 --> 00:07:01,720 Speaker 1: peak flu season in January and February, and yet by 99 00:07:01,760 --> 00:07:05,040 Speaker 1: March and April it goes down. So we're playing this 100 00:07:05,160 --> 00:07:09,320 Speaker 1: interesting strategy of trying to keep the lid on things 101 00:07:10,000 --> 00:07:14,160 Speaker 1: until it actually turns itself around. At the same time, 102 00:07:14,960 --> 00:07:19,720 Speaker 1: we are very actively trying to develop a vaccine, and 103 00:07:19,800 --> 00:07:21,800 Speaker 1: we're going to do something new that I wouldn't say 104 00:07:21,800 --> 00:07:24,960 Speaker 1: it would surprise you, but I think you'll be impressed 105 00:07:25,120 --> 00:07:29,560 Speaker 1: that the fastest we've ever gotten into a vaccine from 106 00:07:29,560 --> 00:07:33,120 Speaker 1: the time we have made the sequence of the virus 107 00:07:33,200 --> 00:07:37,840 Speaker 1: known was with Zeka. We did it in about four months. Previously, 108 00:07:38,240 --> 00:07:40,320 Speaker 1: it took a year or two or more to go 109 00:07:40,440 --> 00:07:44,040 Speaker 1: from getting the virus to even getting a vaccine into 110 00:07:44,080 --> 00:07:48,680 Speaker 1: a phase one safety trial. We're projecting that from the 111 00:07:48,720 --> 00:07:51,760 Speaker 1: time we got the sequence, which was about two and 112 00:07:51,760 --> 00:07:54,760 Speaker 1: a half three weeks ago, that we will be in 113 00:07:54,760 --> 00:07:58,840 Speaker 1: a phase one trial within about two months. That will 114 00:07:58,880 --> 00:08:02,880 Speaker 1: take about three months to get safety data and imenogenicity, 115 00:08:02,920 --> 00:08:05,239 Speaker 1: and then you go into phase two, which would probably 116 00:08:05,280 --> 00:08:09,400 Speaker 1: take another six to eight months. So even with emergency 117 00:08:09,520 --> 00:08:13,440 Speaker 1: use authorization if we're successful, we're not going to have 118 00:08:13,440 --> 00:08:16,400 Speaker 1: a vaccine for at least a year and probably more. 119 00:08:17,040 --> 00:08:21,120 Speaker 1: Having said that, that is the fastest anyone has ever 120 00:08:21,200 --> 00:08:25,640 Speaker 1: gone from knowing the sequence of a virus and getting 121 00:08:25,640 --> 00:08:29,400 Speaker 1: a vaccine into a human trial. But it also tells 122 00:08:29,480 --> 00:08:32,679 Speaker 1: us that between now and then, the tools that we 123 00:08:32,760 --> 00:08:38,600 Speaker 1: have are classic public health tools of identification, isolation, and 124 00:08:38,760 --> 00:08:43,679 Speaker 1: contact tracing. What has been the breakthrough that's accelerating all this? 125 00:08:43,840 --> 00:08:46,640 Speaker 1: I mean, how much it goes back to basic research 126 00:08:46,720 --> 00:08:52,480 Speaker 1: and DNA and developing capacity for gene analysis that comes 127 00:08:52,520 --> 00:08:55,120 Speaker 1: out of basic science, and how much of it comes 128 00:08:55,160 --> 00:08:59,600 Speaker 1: from other kinds of breakthroughs. Well, I would say ultimately, 129 00:09:00,960 --> 00:09:05,640 Speaker 1: singer prints of basic science are on everything that I'm 130 00:09:05,679 --> 00:09:09,760 Speaker 1: talking about. Let me give you just one example, when 131 00:09:10,080 --> 00:09:16,600 Speaker 1: the virus was isolated very quickly in China and the 132 00:09:16,679 --> 00:09:21,760 Speaker 1: sequence was put on a public database. Just having the 133 00:09:21,840 --> 00:09:26,200 Speaker 1: ability to sequence a virus in a couple of days 134 00:09:26,280 --> 00:09:29,320 Speaker 1: as opposed to a year the way it used to be, 135 00:09:29,880 --> 00:09:35,719 Speaker 1: basic science brought us there. The CDC took that sequence 136 00:09:35,800 --> 00:09:40,839 Speaker 1: and was able to make a PCR based diagnostic literally 137 00:09:41,440 --> 00:09:46,880 Speaker 1: within a week. They've quality controlled it and yesterday knew. 138 00:09:47,160 --> 00:09:53,760 Speaker 1: The FDA did an emergency use authorization to ship those 139 00:09:53,880 --> 00:09:57,400 Speaker 1: kits to one hundred and ninety state and local health 140 00:09:57,400 --> 00:10:01,560 Speaker 1: authorities throughout the United States, so that we can do 141 00:10:01,640 --> 00:10:05,680 Speaker 1: the kind of testing as Americans get air of Act 142 00:10:06,320 --> 00:10:10,080 Speaker 1: out of Wuhan. The Chinese are doing the same thing, 143 00:10:12,000 --> 00:10:16,800 Speaker 1: but also superimposed upon that is. The other thing that 144 00:10:16,880 --> 00:10:21,240 Speaker 1: I believe you're alluding to is the classic nineteenth and 145 00:10:21,320 --> 00:10:28,040 Speaker 1: twentieth century public health measures of observation, identification, isolation, and 146 00:10:28,160 --> 00:10:33,160 Speaker 1: contact tracing. So science has its fingerprints on everything. Because 147 00:10:33,200 --> 00:10:35,760 Speaker 1: we could not do the diagnostics, We could not even 148 00:10:35,840 --> 00:10:40,640 Speaker 1: think about a vaccine. We couldn't do drug screening nor 149 00:10:40,760 --> 00:10:43,720 Speaker 1: targeted drug development. None of that would be able to 150 00:10:43,760 --> 00:10:48,120 Speaker 1: be done without science. I'm sort of appalled at the 151 00:10:48,200 --> 00:10:51,520 Speaker 1: way that the Chinese government has responded, and I don't 152 00:10:51,600 --> 00:10:57,120 Speaker 1: understand how you can quarantine entire cities. We are trying 153 00:10:57,679 --> 00:11:04,880 Speaker 1: to get our epidemiologists and scientist who, before this coronavirus situation, 154 00:11:05,520 --> 00:11:11,040 Speaker 1: had long been collaborating with our Chinese scientific colleagues. There's 155 00:11:11,040 --> 00:11:15,520 Speaker 1: a big difference between the Chinese scientific colleagues and Chinese 156 00:11:15,840 --> 00:11:19,400 Speaker 1: political officials. We want to go over there not only 157 00:11:19,480 --> 00:11:23,719 Speaker 1: help them, but actually take a look at what's going on. 158 00:11:24,440 --> 00:11:27,839 Speaker 1: When SARS came about in two thousand and two, it 159 00:11:27,960 --> 00:11:32,920 Speaker 1: was revealed after examination and everyone agrees that they were 160 00:11:32,960 --> 00:11:37,480 Speaker 1: egregiously non transparent and letting the world know what was 161 00:11:37,520 --> 00:11:40,600 Speaker 1: going on in China for at least a couple of months, 162 00:11:40,640 --> 00:11:43,680 Speaker 1: and by that time the horse was out of the barn. 163 00:11:44,720 --> 00:11:50,880 Speaker 1: They have been much more transparent now, we think, But 164 00:11:50,920 --> 00:11:54,000 Speaker 1: one of the things they did again that's wrong. In 165 00:11:54,040 --> 00:11:58,000 Speaker 1: the first few weeks of the outbreak, they were telling 166 00:11:58,360 --> 00:12:02,920 Speaker 1: the Chinese people that this was just an animal to 167 00:12:03,080 --> 00:12:07,000 Speaker 1: human infection, which I think originally it was, but they 168 00:12:07,000 --> 00:12:11,839 Speaker 1: were saying there's no human to human transmission at the time. 169 00:12:11,880 --> 00:12:14,840 Speaker 1: They were saying that it was clear that there was 170 00:12:14,920 --> 00:12:18,719 Speaker 1: infection in early December which was being spread underneath the 171 00:12:18,840 --> 00:12:24,920 Speaker 1: radar screen, and the population was not alerted to the danger, 172 00:12:25,160 --> 00:12:30,360 Speaker 1: and things were being done like attending festivals of forty 173 00:12:30,360 --> 00:12:35,839 Speaker 1: thousand people the more instead of socially distancing themselves so 174 00:12:35,880 --> 00:12:38,880 Speaker 1: that they don't spread. So that kind of lack of 175 00:12:38,920 --> 00:12:42,440 Speaker 1: transparency even in this has been a problem. Getting to 176 00:12:42,559 --> 00:12:48,680 Speaker 1: your question about essentially locking down tens of millions of people, 177 00:12:49,480 --> 00:12:53,200 Speaker 1: I believe they feel that since the horse is a 178 00:12:53,240 --> 00:12:56,240 Speaker 1: bit out of the barn here, in order to prevent 179 00:12:57,040 --> 00:13:01,400 Speaker 1: the total spread of infection out of Wuhan, which clearly 180 00:13:01,600 --> 00:13:05,160 Speaker 1: is the epicenter the city of Wuhan in the province 181 00:13:05,320 --> 00:13:08,880 Speaker 1: of Oubay. They feel that if they do that, which 182 00:13:08,920 --> 00:13:14,600 Speaker 1: is unprecedented, they may prevent the further spread. You know, 183 00:13:14,760 --> 00:13:17,080 Speaker 1: normally you would say, wow, that's something that is really 184 00:13:17,160 --> 00:13:21,640 Speaker 1: draconian and shouldn't have been done. In general, that's correct, 185 00:13:22,120 --> 00:13:26,400 Speaker 1: but I think they're faced with such an unusual, unprecedented 186 00:13:26,480 --> 00:13:30,520 Speaker 1: situation that I really hesitate to be critical of that 187 00:13:30,600 --> 00:13:33,320 Speaker 1: right now, because I don't think they have many other 188 00:13:33,440 --> 00:13:38,080 Speaker 1: choices since they have such a terrible, unprecedented problem right now. 189 00:13:38,880 --> 00:13:41,720 Speaker 1: I just saw some pictures this morning where they literally 190 00:13:42,280 --> 00:13:46,120 Speaker 1: have piled dirt up to block roads so you can't 191 00:13:46,320 --> 00:13:49,000 Speaker 1: just drive out of the city. But at least in 192 00:13:48,960 --> 00:13:51,880 Speaker 1: the case, that means they got to find a way 193 00:13:52,400 --> 00:13:55,160 Speaker 1: to get food into there. I mean, as you know, 194 00:13:55,320 --> 00:13:59,240 Speaker 1: even dealing with relatively small population, when you are trying 195 00:13:59,280 --> 00:14:04,080 Speaker 1: to deal with a by quarantine, it's very complicated. How 196 00:14:04,120 --> 00:14:06,319 Speaker 1: do you feed and take care of eleven million people 197 00:14:06,640 --> 00:14:11,000 Speaker 1: without in the process having a functionally broken down the quarantine, 198 00:14:11,400 --> 00:14:13,640 Speaker 1: even if it's technically still in place, because you have 199 00:14:13,720 --> 00:14:16,360 Speaker 1: to have people moving around the city or people will 200 00:14:16,360 --> 00:14:19,920 Speaker 1: starve to death. Newt You're absolutely correct, and that is 201 00:14:20,000 --> 00:14:26,000 Speaker 1: clearly one of the well recognized collateral type of negative 202 00:14:26,520 --> 00:14:30,560 Speaker 1: impact that one can have. With that, the Chinese are 203 00:14:30,600 --> 00:14:34,280 Speaker 1: saying that they are able to get supplies and food 204 00:14:34,400 --> 00:14:38,720 Speaker 1: and other necessities to the people that are there. They're 205 00:14:38,760 --> 00:14:42,360 Speaker 1: doing some amazing things. The fact that they have put 206 00:14:42,440 --> 00:14:47,080 Speaker 1: up a thousand dead hospital in like a week, which 207 00:14:47,160 --> 00:14:51,680 Speaker 1: is beyond imagination to be able to do that. So 208 00:14:52,320 --> 00:14:54,760 Speaker 1: I don't know, since we're not there, what they're doing, 209 00:14:54,920 --> 00:15:01,400 Speaker 1: but they're saying that despite these rather strict limitations on 210 00:15:01,440 --> 00:15:05,640 Speaker 1: travel where they shut down an entire city, they're saying 211 00:15:05,680 --> 00:15:11,360 Speaker 1: that they actually can get supplies and necessities to these people. Hopefully, 212 00:15:11,400 --> 00:15:13,600 Speaker 1: when we get over there, and I hope we do 213 00:15:13,680 --> 00:15:16,480 Speaker 1: get over there soon, we'll be able to see for 214 00:15:16,520 --> 00:15:19,600 Speaker 1: ourselves and perhaps help them, but also learn from them. 215 00:15:19,800 --> 00:15:22,560 Speaker 1: Were they more open during SARS or was it a 216 00:15:22,600 --> 00:15:26,880 Speaker 1: similar pattern of being very cautious about opening up to 217 00:15:26,920 --> 00:15:30,320 Speaker 1: the world and what they're doing. In the beginning of SARS, 218 00:15:30,360 --> 00:15:34,400 Speaker 1: they were quite non transparent, and I think that's one 219 00:15:34,400 --> 00:15:38,840 Speaker 1: of the reasons why the outbreak took off. Once the 220 00:15:38,880 --> 00:15:42,280 Speaker 1: world knew what was going on and SARS spread from 221 00:15:42,320 --> 00:15:47,240 Speaker 1: Guangdong Province to Hong Kong and then the massive infection 222 00:15:47,320 --> 00:15:50,000 Speaker 1: about more than nineteen people who then got on planes 223 00:15:50,040 --> 00:15:53,640 Speaker 1: and whe elsewhere. Then it didn't make any difference how 224 00:15:53,680 --> 00:15:55,800 Speaker 1: transparent they were because it was in the rest of 225 00:15:55,800 --> 00:15:59,080 Speaker 1: the world. But in the beginning of the SARS epidemic 226 00:15:59,160 --> 00:16:04,160 Speaker 1: they clearly when transparent. Coming up, we'll discuss the source 227 00:16:04,280 --> 00:16:23,600 Speaker 1: of the coronavirus. Well, I'd like you to talk about briefly, 228 00:16:23,720 --> 00:16:26,200 Speaker 1: is you have this pattern in China, whether it's the 229 00:16:26,240 --> 00:16:30,480 Speaker 1: bird flu or as stars, or it's the African swine flu. 230 00:16:30,960 --> 00:16:34,040 Speaker 1: And now with coronavirus, you seem to have a pattern 231 00:16:34,080 --> 00:16:38,160 Speaker 1: of animal to human transmission that doesn't seem to exist 232 00:16:38,280 --> 00:16:42,520 Speaker 1: much anywhere else. How do you analyze that. The one 233 00:16:42,520 --> 00:16:45,000 Speaker 1: thing we have to be careful that this gets interpreted 234 00:16:45,040 --> 00:16:49,240 Speaker 1: as blaming of the Chinese. It isn't. It's a situation. 235 00:16:49,360 --> 00:16:55,160 Speaker 1: If you look at evidence influenza the interface, and I've 236 00:16:55,200 --> 00:16:58,120 Speaker 1: done that myself when I've gone to the Far East, 237 00:16:58,240 --> 00:17:03,480 Speaker 1: including China, you see that you have pigs next to ducks, 238 00:17:03,520 --> 00:17:07,399 Speaker 1: next to chickens, next to people. And that's the worst 239 00:17:07,440 --> 00:17:13,400 Speaker 1: possible scenario that you have for influenza jumping species from 240 00:17:13,440 --> 00:17:17,320 Speaker 1: an animal reservoir or a human the wet markets that 241 00:17:17,520 --> 00:17:22,679 Speaker 1: have exotic animals in them. You're not talking about a 242 00:17:22,680 --> 00:17:25,440 Speaker 1: big chicken farm, You're not talking about raising pigs. You're 243 00:17:25,480 --> 00:17:30,080 Speaker 1: talking about getting exotic animals from the wild who we 244 00:17:30,280 --> 00:17:35,280 Speaker 1: know from genetic screening that these animals have reservoirs for 245 00:17:35,400 --> 00:17:40,879 Speaker 1: viruses that are fundamentally animal viruses, but they can evolve 246 00:17:41,160 --> 00:17:46,280 Speaker 1: and adapt themselves to humans. So to your point, you 247 00:17:46,320 --> 00:17:49,000 Speaker 1: could say to yourself, wait a minute, why don't we 248 00:17:49,080 --> 00:17:53,840 Speaker 1: just stop that and somehow revamp it so you don't 249 00:17:53,920 --> 00:17:58,800 Speaker 1: have this interface in a manner and under circumstances that 250 00:17:58,840 --> 00:18:03,120 Speaker 1: could lead to the jumping of species from an animal 251 00:18:03,200 --> 00:18:07,919 Speaker 1: reservoir with human. But the fact is, the customs and 252 00:18:08,560 --> 00:18:12,320 Speaker 1: the traditions and things that people have done for centuries 253 00:18:13,280 --> 00:18:18,400 Speaker 1: are so ingrained in the population that the Chinese authorities 254 00:18:18,400 --> 00:18:21,520 Speaker 1: and the Chinese people have found it very difficult to 255 00:18:21,560 --> 00:18:24,119 Speaker 1: make those kinds of changes. But I think they really 256 00:18:24,160 --> 00:18:29,880 Speaker 1: need to take another fresh look at that because just 257 00:18:30,200 --> 00:18:36,640 Speaker 1: with pars and mares and now coronavirus, it's clear that 258 00:18:36,680 --> 00:18:42,440 Speaker 1: when you have a close interface between certain animal situations 259 00:18:42,480 --> 00:18:46,440 Speaker 1: and humans, there's a risk of an outbreak that could 260 00:18:46,440 --> 00:18:49,760 Speaker 1: have serious consequences. I don't know if you have had 261 00:18:49,760 --> 00:18:52,840 Speaker 1: access to enough information from the Chinese, but as you know, 262 00:18:52,960 --> 00:18:57,640 Speaker 1: there's a sort of urban legend that there's a biological 263 00:18:57,680 --> 00:19:01,960 Speaker 1: warfare center in Wuhan and that the coronavirus escape from that. 264 00:19:02,400 --> 00:19:06,479 Speaker 1: Did you have any sense of where it probably came from. Well, 265 00:19:06,520 --> 00:19:09,560 Speaker 1: I think ultimately we know that these things come from 266 00:19:09,600 --> 00:19:13,959 Speaker 1: an animal reservoir. I've heard these conspiracy theories, and like 267 00:19:14,000 --> 00:19:18,119 Speaker 1: all conspiracy theories new they just conspiracy theories. Is it 268 00:19:18,240 --> 00:19:21,600 Speaker 1: impossible that that could have happened. I don't think I 269 00:19:21,680 --> 00:19:25,000 Speaker 1: can say that it's not impossible. But I think if 270 00:19:25,040 --> 00:19:28,919 Speaker 1: you examine all of the isolates and look at the 271 00:19:29,000 --> 00:19:35,200 Speaker 1: very detailed pattern or map of their molecular structure, you 272 00:19:35,240 --> 00:19:38,359 Speaker 1: may get more insight as to whether it was a 273 00:19:38,520 --> 00:19:44,720 Speaker 1: natural direct jump, whether it percolated in another species from 274 00:19:44,760 --> 00:19:48,960 Speaker 1: the bat to whatever, a civic cat or some other animal, 275 00:19:49,640 --> 00:19:53,320 Speaker 1: and then jump species into humans. I think the more 276 00:19:53,400 --> 00:19:57,840 Speaker 1: you examine isolates and the more we get information, will 277 00:19:57,920 --> 00:20:01,919 Speaker 1: be able to clarify the evolutionary origin of the virus. 278 00:20:02,000 --> 00:20:05,120 Speaker 1: But right now, I think the things you're hearing are 279 00:20:05,160 --> 00:20:09,520 Speaker 1: still in the realm of conspiracy theories without any scientific 280 00:20:09,600 --> 00:20:14,200 Speaker 1: basis for it. The most dangerous viruses seem to come 281 00:20:14,240 --> 00:20:19,120 Speaker 1: out of animal populations, largely in Western Africa, and we 282 00:20:19,160 --> 00:20:22,320 Speaker 1: respond to them very aggressively because their mortality rates are 283 00:20:22,359 --> 00:20:25,840 Speaker 1: so high. Is that just a part of the same 284 00:20:26,720 --> 00:20:28,960 Speaker 1: pattern in your mind that you're seeing in terms of 285 00:20:29,359 --> 00:20:33,080 Speaker 1: species jumping to humans, or there's something different about the 286 00:20:33,119 --> 00:20:36,720 Speaker 1: West Africa and why are they such higher mortality rates 287 00:20:37,800 --> 00:20:42,040 Speaker 1: the jumping of species, there's a common denominata. It is 288 00:20:42,160 --> 00:20:46,800 Speaker 1: manifested in a different way in Far Eastern countries than 289 00:20:46,800 --> 00:20:51,240 Speaker 1: it is in Africa. But the common denominata is two things. 290 00:20:51,280 --> 00:20:56,040 Speaker 1: The way I look at it, it's the interface in 291 00:20:56,080 --> 00:21:03,120 Speaker 1: a somewhat unusual way between the animal population and the 292 00:21:03,280 --> 00:21:08,280 Speaker 1: human population. That could be deliberately. Having people who are 293 00:21:08,320 --> 00:21:13,280 Speaker 1: in the agricultural raising of chickens and pigs in the 294 00:21:13,359 --> 00:21:16,960 Speaker 1: Far East, where you have these animals that can serve 295 00:21:17,000 --> 00:21:22,400 Speaker 1: as a mixing vessel or a reservoir, you essentially, by 296 00:21:22,400 --> 00:21:29,359 Speaker 1: odds alone, allow viruses to jump species to humans in Africa. 297 00:21:29,600 --> 00:21:33,760 Speaker 1: A great example of that is the emergence of HIV, 298 00:21:33,960 --> 00:21:39,480 Speaker 1: which was fundamentally a virus of non human primates, particularly chimpanzees, 299 00:21:40,200 --> 00:21:45,399 Speaker 1: which because of an unusual interface of butchering these for 300 00:21:45,560 --> 00:21:49,040 Speaker 1: what we call bush meat. That there was the jumping 301 00:21:49,040 --> 00:21:53,680 Speaker 1: of species from the chimp or another non human primate 302 00:21:54,240 --> 00:21:59,280 Speaker 1: to a human, which then spread throughout the human population. 303 00:22:00,320 --> 00:22:05,399 Speaker 1: The bottleneck of that new is how well a virus 304 00:22:05,560 --> 00:22:10,280 Speaker 1: adapts itself to being able to replicate in humans. More 305 00:22:10,440 --> 00:22:16,840 Speaker 1: often than not, there are one os where some virus 306 00:22:17,160 --> 00:22:20,560 Speaker 1: be at H five and one flu, H seven and 307 00:22:20,800 --> 00:22:25,080 Speaker 1: nine flu, or what have you, jumps let's say from 308 00:22:25,080 --> 00:22:30,960 Speaker 1: a chicken to a human, replicates in that human and 309 00:22:31,119 --> 00:22:33,520 Speaker 1: has a high mortality. And I'll get back to high 310 00:22:33,600 --> 00:22:39,040 Speaker 1: mortality in a minute. What happens is unless that virus 311 00:22:39,400 --> 00:22:47,240 Speaker 1: mutates enough to adapt itself to efficient replication in the humans, 312 00:22:47,400 --> 00:22:51,240 Speaker 1: you're not going to have an outbreak of any consequence. 313 00:22:51,480 --> 00:22:54,600 Speaker 1: It'll be one oss the way we've seen with H 314 00:22:54,680 --> 00:22:58,200 Speaker 1: five N one and H seven and nine. Every once 315 00:22:58,240 --> 00:23:01,480 Speaker 1: in a while, it isn't a and off. That's what 316 00:23:01,640 --> 00:23:05,400 Speaker 1: we saw in two thousand and nine with the swine flu, 317 00:23:06,240 --> 00:23:11,720 Speaker 1: which originated somewhere around southern California and northern Mexico, where 318 00:23:11,880 --> 00:23:16,119 Speaker 1: the virus jumped from a pig to a human, but 319 00:23:16,240 --> 00:23:20,760 Speaker 1: it did it with the necessary mutations to allow it 320 00:23:20,800 --> 00:23:26,640 Speaker 1: to adapt itself for very efficient spread in humans. So 321 00:23:26,760 --> 00:23:31,399 Speaker 1: you contrast that jump species with the chicken to human 322 00:23:31,640 --> 00:23:36,359 Speaker 1: which went nowhere. So the interesting thing that seems to 323 00:23:36,400 --> 00:23:41,920 Speaker 1: be another common denominator is that when these viruses first 324 00:23:42,040 --> 00:23:46,959 Speaker 1: jump species, they either have a high degree of mortality 325 00:23:48,119 --> 00:23:52,919 Speaker 1: or a high degree of transmissibility. The higher the transmissibility, 326 00:23:53,640 --> 00:23:58,920 Speaker 1: the less the mortality. We're seeing exactly that with the 327 00:23:58,920 --> 00:24:06,480 Speaker 1: new coronavirus. With stars, the virus is not very adaptable 328 00:24:06,600 --> 00:24:10,960 Speaker 1: in the sense of massive transmission from human to human, 329 00:24:11,520 --> 00:24:13,959 Speaker 1: and the mortality is quite high. It's nine to ten. 330 00:24:15,359 --> 00:24:19,280 Speaker 1: With the coronavirus, it's much much better adapted to humans 331 00:24:20,000 --> 00:24:24,560 Speaker 1: than stars, and the mortality is much less. That doesn't 332 00:24:24,840 --> 00:24:29,240 Speaker 1: happen every single time, but it is absolutely more the 333 00:24:29,400 --> 00:24:33,400 Speaker 1: rule than the exception that as you adapt yourself as 334 00:24:33,440 --> 00:24:38,720 Speaker 1: a virus to better transmissibility, you're less lethal. Given that 335 00:24:39,160 --> 00:24:42,800 Speaker 1: there's already a relatively low mortallyrate, I mean, how concerns 336 00:24:42,800 --> 00:24:47,040 Speaker 1: should Americans be about coronavirus spreading in the US. I 337 00:24:47,119 --> 00:24:52,359 Speaker 1: think we're as of today, we're about twelve cases right well, 338 00:24:52,920 --> 00:24:57,159 Speaker 1: right now, the risk is relatively low in fact, that 339 00:24:57,200 --> 00:24:59,439 Speaker 1: would take the relatively out and say the risk is 340 00:24:59,480 --> 00:25:05,280 Speaker 1: low for Americans. That's the good news. The somewhat concerning 341 00:25:05,280 --> 00:25:08,960 Speaker 1: news is that this could change because this is a 342 00:25:08,960 --> 00:25:13,720 Speaker 1: moving target. It's an evolving situation. We have been very 343 00:25:13,760 --> 00:25:18,600 Speaker 1: fortunate that the cases that came in travel related have 344 00:25:18,720 --> 00:25:24,439 Speaker 1: been able to be addressed appropriately and successfully by identification, isolation, 345 00:25:24,480 --> 00:25:28,760 Speaker 1: and contact tracing. But if we have a broader global 346 00:25:28,880 --> 00:25:33,320 Speaker 1: outbreak where there are cases that aren't giving the kind 347 00:25:33,320 --> 00:25:38,960 Speaker 1: of sustained transmission in multiple different countries besides China, right now, 348 00:25:39,080 --> 00:25:43,960 Speaker 1: China is the only place where the sustained transmission. There 349 00:25:44,000 --> 00:25:49,160 Speaker 1: have been about thirty countries that have travel related cases, 350 00:25:49,800 --> 00:25:54,120 Speaker 1: and twenty five of those there are human to human transmissibility, 351 00:25:54,119 --> 00:25:58,960 Speaker 1: but in none of them are really sustained transmissibility, which 352 00:25:59,000 --> 00:26:03,520 Speaker 1: is the reason why technically the WHO is not calling 353 00:26:03,560 --> 00:26:09,720 Speaker 1: this a global pandemic. But once there's sustained transmission in 354 00:26:09,840 --> 00:26:14,160 Speaker 1: multiple countries throughout the world, then you're dealing with a 355 00:26:14,240 --> 00:26:17,159 Speaker 1: real pandemic, and then it becomes a threat to the 356 00:26:17,160 --> 00:26:21,359 Speaker 1: American people. But right now that is a low risk, 357 00:26:21,760 --> 00:26:23,600 Speaker 1: but we have to keep an eye out on it 358 00:26:23,680 --> 00:26:27,520 Speaker 1: and take it extremely seriously. Do you think that the 359 00:26:27,560 --> 00:26:31,440 Speaker 1: process of bringing Americans home from China and in some 360 00:26:31,480 --> 00:26:35,399 Speaker 1: cases quarantining people who have some symptoms, do you think 361 00:26:35,480 --> 00:26:38,600 Speaker 1: that's an appropriate response at the stage, I do knute. 362 00:26:38,640 --> 00:26:41,639 Speaker 1: It was a difficult decision because you don't like to 363 00:26:41,680 --> 00:26:45,400 Speaker 1: do those things unless it's necessary, because sometimes it can 364 00:26:45,640 --> 00:26:49,280 Speaker 1: instill fear in people, they tend to panic, or it 365 00:26:49,400 --> 00:26:52,560 Speaker 1: also encroaches on some of the liberties of people. But 366 00:26:52,720 --> 00:26:55,760 Speaker 1: sometimes you have to make that choice. The people who 367 00:26:55,760 --> 00:26:58,640 Speaker 1: are being quarantined are not people who are sick. Those 368 00:26:58,680 --> 00:27:01,840 Speaker 1: are people who were in an area at high risk 369 00:27:02,320 --> 00:27:07,000 Speaker 1: and if they were in Wuhan over the past fourteen days, 370 00:27:07,040 --> 00:27:10,960 Speaker 1: they have to get quarantine when they come in for 371 00:27:11,119 --> 00:27:15,960 Speaker 1: the fourteen day incubation period, and that is institutional quarantine. 372 00:27:16,480 --> 00:27:20,400 Speaker 1: If they are an American citizen and coming from any 373 00:27:20,440 --> 00:27:25,120 Speaker 1: other part of China besides Wuhan and come into the country, 374 00:27:25,800 --> 00:27:29,440 Speaker 1: they have the same restriction over the fourteen day period, 375 00:27:29,440 --> 00:27:32,920 Speaker 1: but they can do that in a voluntary self isolation. 376 00:27:33,640 --> 00:27:37,600 Speaker 1: The institutional quarantine is only if you come from Wuhan, 377 00:27:37,760 --> 00:27:41,399 Speaker 1: but if you get symptoms, it goes from quarantine to 378 00:27:41,560 --> 00:27:46,119 Speaker 1: actually true isolation and treatment. So the quarantine mostly is 379 00:27:46,119 --> 00:27:49,520 Speaker 1: to let people run out the incubation period so that 380 00:27:49,560 --> 00:27:52,159 Speaker 1: they can then be released and go into society. I 381 00:27:52,280 --> 00:27:55,680 Speaker 1: just strength four days in Korea and Soul and observed 382 00:27:55,720 --> 00:27:58,320 Speaker 1: a couple of things. About eighty or eighty five percent 383 00:27:58,320 --> 00:28:01,120 Speaker 1: of the people in the airport we're wearing mans. And 384 00:28:01,920 --> 00:28:05,840 Speaker 1: in walking into a one high end hotel, every person 385 00:28:05,880 --> 00:28:09,160 Speaker 1: and walked in, they had this device that would instantly 386 00:28:09,240 --> 00:28:12,200 Speaker 1: check your temperature. They put it up against your wrist 387 00:28:12,800 --> 00:28:15,639 Speaker 1: and they were checking every single person to see if 388 00:28:15,640 --> 00:28:19,000 Speaker 1: they had a raised temperature. In reports of the coming 389 00:28:19,000 --> 00:28:23,320 Speaker 1: out of China, fever is the most common manifestation of 390 00:28:23,440 --> 00:28:27,960 Speaker 1: the people who were recognized as being ill. In reports 391 00:28:28,000 --> 00:28:30,760 Speaker 1: coming out of China, about ninety eight of them had fever, 392 00:28:31,280 --> 00:28:35,760 Speaker 1: so fever was a good indication. It's quite debatable about masks. 393 00:28:36,359 --> 00:28:39,080 Speaker 1: Masks some more to prevent people who are infected from 394 00:28:39,120 --> 00:28:42,800 Speaker 1: infecting other people. The mask that you buy in a 395 00:28:42,880 --> 00:28:48,400 Speaker 1: drug store would be not particularly efficient in keeping out virus, 396 00:28:49,000 --> 00:28:52,480 Speaker 1: and that's the reason why we do not recommend people 397 00:28:52,600 --> 00:28:57,120 Speaker 1: wearing masks. Yet it makes some people feel more comforted, 398 00:28:57,600 --> 00:29:01,200 Speaker 1: and perhaps it can have some slight amodity effect, but 399 00:29:01,320 --> 00:29:07,080 Speaker 1: it isn't a primary effective barrier against transmission. So taking 400 00:29:07,080 --> 00:29:11,640 Speaker 1: the temperature and then questioning and doing a good exam 401 00:29:12,400 --> 00:29:17,520 Speaker 1: and potentially isolating people who with temperatures obviously the public 402 00:29:17,520 --> 00:29:20,720 Speaker 1: health measure to do, but there's a lot of concern 403 00:29:20,800 --> 00:29:25,800 Speaker 1: and debate and disagreement about masks. Listen, I really appreciate 404 00:29:26,280 --> 00:29:28,880 Speaker 1: you're taking this kind of time. You are truly a 405 00:29:29,040 --> 00:29:33,400 Speaker 1: national treasurer. You're total impact of your career is astonishing. 406 00:29:33,800 --> 00:29:37,120 Speaker 1: I don't know if anybody who's dealt with more potentially 407 00:29:37,160 --> 00:29:40,800 Speaker 1: disastrous problems than you have, but I feel like we've 408 00:29:40,800 --> 00:29:43,720 Speaker 1: really come a long way, both in our ability to 409 00:29:43,800 --> 00:29:46,960 Speaker 1: understand diseases and in our ability at the public health 410 00:29:47,040 --> 00:29:50,640 Speaker 1: side to respond to them, and pretty dramatically rapid time 411 00:29:51,080 --> 00:29:53,560 Speaker 1: compared to thirty or forty years ago. And a good 412 00:29:53,600 --> 00:29:56,040 Speaker 1: piece of that is due to your work. Well, thank 413 00:29:56,080 --> 00:29:58,640 Speaker 1: you for those kind words and knew what I appreciate them. 414 00:29:58,680 --> 00:30:01,400 Speaker 1: There's a lot of people for involved in helping us 415 00:30:01,400 --> 00:30:04,960 Speaker 1: with this. Thank you. Doctor Anthony Faucer has been the 416 00:30:05,040 --> 00:30:08,600 Speaker 1: Director of the National Institute of Allergy and Infectious Diseases 417 00:30:08,920 --> 00:30:12,120 Speaker 1: at the National Institute's of Health since nineteen eighty four. 418 00:30:12,640 --> 00:30:14,960 Speaker 1: Here how he got his start in his field at 419 00:30:15,000 --> 00:30:18,800 Speaker 1: New Center Circle dot com. It's a subscription service where 420 00:30:18,840 --> 00:30:21,840 Speaker 1: I offer insights in commentary on the issues that matter 421 00:30:21,880 --> 00:30:27,960 Speaker 1: to me. Most joined today at New Center Circle dot com. Next, 422 00:30:28,360 --> 00:30:38,720 Speaker 1: how deadly is the coronavirus? Hi? This is newt twenty 423 00:30:38,880 --> 00:30:40,600 Speaker 1: twenty is going to be one of the most extraordinary 424 00:30:40,640 --> 00:30:43,520 Speaker 1: election years of our lifetime. I want to invite you 425 00:30:43,600 --> 00:30:46,880 Speaker 1: to join my Inner Circle as we discuss each twist 426 00:30:46,920 --> 00:30:49,960 Speaker 1: and turn in the presidential race. In my members only 427 00:30:50,240 --> 00:30:55,440 Speaker 1: Inner Circle Club. You will receive special flash briefings, online events, 428 00:30:55,880 --> 00:30:59,200 Speaker 1: and members only audio reports from me and my team. 429 00:30:59,280 --> 00:31:01,960 Speaker 1: Here is a special shall offer for my podcast listeners. 430 00:31:02,720 --> 00:31:05,280 Speaker 1: Join my Inner Circle today at New Center Circle dot 431 00:31:05,280 --> 00:31:08,240 Speaker 1: com slash Podcast, and if you sign up for a 432 00:31:08,280 --> 00:31:11,160 Speaker 1: one or two year membership, you'll get ten percent off 433 00:31:11,200 --> 00:31:14,959 Speaker 1: your membership price and a VIP fast pass to my 434 00:31:15,040 --> 00:31:19,200 Speaker 1: live events. Join my Inner Circle today at newt Center 435 00:31:19,240 --> 00:31:23,520 Speaker 1: Circle dot com slash Podcast use the Code podcast at 436 00:31:23,560 --> 00:31:27,080 Speaker 1: check out. Sign up today at New Center Circle dot 437 00:31:27,080 --> 00:31:31,560 Speaker 1: com Slash Podcast and use the Code podcast hurry. This 438 00:31:31,800 --> 00:31:44,280 Speaker 1: offtware expires February fourteenth. Doctor Peter Dawson, You've got very 439 00:31:44,280 --> 00:31:47,959 Speaker 1: engaged in this whole question of public health and how 440 00:31:47,960 --> 00:31:49,960 Speaker 1: do we deal with it? Can you explain what the 441 00:31:50,000 --> 00:31:53,520 Speaker 1: eco Health Alliance is. What we do at eco Health 442 00:31:53,680 --> 00:31:57,720 Speaker 1: is we look at the connection between these viruses that 443 00:31:57,720 --> 00:32:00,920 Speaker 1: are emerging and affecting public health and what is underlying that. 444 00:32:01,280 --> 00:32:04,040 Speaker 1: And it turns out, and there's a bunch of research 445 00:32:04,080 --> 00:32:06,600 Speaker 1: that we've done, but it turns out that almost all 446 00:32:06,600 --> 00:32:12,320 Speaker 1: emerging disease are linked to some underlying drivers, some cause 447 00:32:12,400 --> 00:32:16,560 Speaker 1: that's related to people. It's things like travel and trade 448 00:32:16,560 --> 00:32:19,560 Speaker 1: and building roads into forests around the world. We have 449 00:32:19,600 --> 00:32:23,080 Speaker 1: this unprecedented population growth. We're doing things on the planet 450 00:32:23,080 --> 00:32:25,560 Speaker 1: that we never used to do. We're building roads into 451 00:32:25,600 --> 00:32:28,160 Speaker 1: the remotest forests and what we do is we've come 452 00:32:28,200 --> 00:32:31,160 Speaker 1: into contact with wildlife species and pick up their viruses. 453 00:32:31,600 --> 00:32:33,560 Speaker 1: What we do at eco Health is look at the 454 00:32:33,680 --> 00:32:38,760 Speaker 1: relationship between people and animals and the environment and how 455 00:32:38,800 --> 00:32:41,000 Speaker 1: that leads to pandemics and we try and do something 456 00:32:41,000 --> 00:32:43,239 Speaker 1: about it. You know, we do the science and then 457 00:32:43,240 --> 00:32:45,640 Speaker 1: we get on the ground in these places. And we've 458 00:32:45,640 --> 00:32:48,440 Speaker 1: been working in China for fifteen years and we say, 459 00:32:48,600 --> 00:32:50,880 Speaker 1: what is it that people doing that's building a risk 460 00:32:50,960 --> 00:32:54,080 Speaker 1: for them to pick up new diseases that When those 461 00:32:54,080 --> 00:32:58,560 Speaker 1: diseases happen, they always gravitate to the US, Europe, the 462 00:32:58,600 --> 00:33:01,120 Speaker 1: countries that travel a lot. If we can deal with 463 00:33:01,160 --> 00:33:04,720 Speaker 1: it there, we can stop it getting here. So when 464 00:33:04,760 --> 00:33:08,560 Speaker 1: you look at what's happened with coronavirus, what's your sense 465 00:33:08,560 --> 00:33:11,720 Speaker 1: of how the Chinese have responded so far? Well, if 466 00:33:11,720 --> 00:33:14,040 Speaker 1: you compare it to what they did with size orders 467 00:33:14,040 --> 00:33:17,640 Speaker 1: of magnitude better, China is a very interesting country to me, 468 00:33:18,080 --> 00:33:20,320 Speaker 1: And when you're on the ground working with scientists, it's 469 00:33:20,400 --> 00:33:23,880 Speaker 1: completely open and collaborative, just like working with US scientists. 470 00:33:24,280 --> 00:33:26,800 Speaker 1: How they just want to do interesting work and publish 471 00:33:26,840 --> 00:33:29,840 Speaker 1: it and make a name for themselves. But of course, 472 00:33:29,880 --> 00:33:33,200 Speaker 1: at the same time that there's an authoritarian government that 473 00:33:33,320 --> 00:33:36,400 Speaker 1: can move extremely quickly to close things down and to 474 00:33:36,560 --> 00:33:40,080 Speaker 1: change policy. So what we've seen is those two things 475 00:33:40,160 --> 00:33:43,400 Speaker 1: plane out. We've seen scientists at the very beginning of 476 00:33:43,400 --> 00:33:48,400 Speaker 1: this outbreak finding the virus quickly within two weeks, sequencing 477 00:33:48,440 --> 00:33:51,520 Speaker 1: the whole genome of the virus, and publishing it on 478 00:33:51,560 --> 00:33:53,840 Speaker 1: the web. That would never have happened twenty years ago. 479 00:33:54,280 --> 00:33:57,480 Speaker 1: The reason that's really important is because if we get 480 00:33:57,480 --> 00:34:01,800 Speaker 1: that genetic sequence around the world, can then design dynostic 481 00:34:01,880 --> 00:34:04,680 Speaker 1: tests to start testing people coming into the country. So 482 00:34:04,720 --> 00:34:07,120 Speaker 1: that was a very good move. Then you've got the 483 00:34:07,240 --> 00:34:10,799 Speaker 1: government coming in and doing what I think actually very 484 00:34:10,880 --> 00:34:16,360 Speaker 1: bold public health measures like blocking travel within China during 485 00:34:16,480 --> 00:34:19,839 Speaker 1: their lunar New Year. I thought that was just such 486 00:34:19,880 --> 00:34:23,920 Speaker 1: a strong move, but of course that's China. They have 487 00:34:24,160 --> 00:34:26,120 Speaker 1: the capacity to do it and the people will go 488 00:34:26,160 --> 00:34:31,480 Speaker 1: along with that. To some extent, the coronavirus probably came 489 00:34:31,640 --> 00:34:36,480 Speaker 1: from one of the food markets, although there is a 490 00:34:36,520 --> 00:34:42,920 Speaker 1: sort of secondary rumor that there's a biological weapons laboratory 491 00:34:42,920 --> 00:34:46,120 Speaker 1: in Wuhan and it may have come from there. There's 492 00:34:46,160 --> 00:34:49,520 Speaker 1: a year's sense there's almost certain that it came from 493 00:34:49,560 --> 00:34:53,000 Speaker 1: an animal to human transmission. All the evidence says that 494 00:34:53,000 --> 00:34:55,759 Speaker 1: that's what happened. I mean again, it's not as exciting 495 00:34:55,840 --> 00:35:00,839 Speaker 1: as the movie release of a bioweapon, but the real 496 00:35:00,920 --> 00:35:04,680 Speaker 1: bio terras Now there is nature. We've got wildlife carrying. 497 00:35:04,719 --> 00:35:09,000 Speaker 1: We estimate one point seven million unknown viruses in mammals alone, 498 00:35:09,600 --> 00:35:12,000 Speaker 1: about half a million to eight hundred thousand dollars can 499 00:35:12,000 --> 00:35:13,880 Speaker 1: probably infect us. We don't know what they are, we 500 00:35:13,920 --> 00:35:16,560 Speaker 1: don't know where they are. It turns out that bats 501 00:35:16,560 --> 00:35:20,439 Speaker 1: in China and all across Southeast Asia carry a whole 502 00:35:20,440 --> 00:35:24,480 Speaker 1: host of probably pretty risky viruses. We've been out there 503 00:35:24,600 --> 00:35:27,279 Speaker 1: discovering these new viruses. We've found five hundred of them 504 00:35:27,320 --> 00:35:31,279 Speaker 1: so far, including the closest relative to this one. It 505 00:35:31,320 --> 00:35:33,640 Speaker 1: looks to me and to most scientists like it's a 506 00:35:33,680 --> 00:35:37,160 Speaker 1: bat virus that gone into people either in a market 507 00:35:37,280 --> 00:35:41,040 Speaker 1: or in rural China and just unfortunately has the capacity 508 00:35:41,080 --> 00:35:45,880 Speaker 1: to spread. We surveyed people in southwest China and found 509 00:35:46,480 --> 00:35:49,320 Speaker 1: two to three percent of them had antibodies to bat viruses. 510 00:35:49,360 --> 00:35:53,120 Speaker 1: They were exposed as a matter of course of everyday 511 00:35:53,160 --> 00:35:56,120 Speaker 1: life in a very low level. But if you multiply 512 00:35:56,239 --> 00:36:01,200 Speaker 1: that by one point three billion people by who intimately 513 00:36:01,640 --> 00:36:04,520 Speaker 1: connect to wildlife through eating them and butchering them, you 514 00:36:04,600 --> 00:36:06,640 Speaker 1: get a high risk and eventually this thing is going 515 00:36:06,680 --> 00:36:11,040 Speaker 1: to happen. Is the bat genome so similar to ours 516 00:36:11,239 --> 00:36:14,480 Speaker 1: that that's a major reason why it's able to be 517 00:36:14,560 --> 00:36:17,960 Speaker 1: such a carrier and have such a leaper ross to humans. 518 00:36:18,520 --> 00:36:21,879 Speaker 1: That's a really good question. We know that HIV has 519 00:36:22,040 --> 00:36:25,239 Speaker 1: a relationship with a chimpanzee virus, and we think that 520 00:36:25,280 --> 00:36:29,200 Speaker 1: it probably came from chimpanzees. Chimpanzees are famously ninety nine 521 00:36:29,640 --> 00:36:33,200 Speaker 1: percent similar to us. Bats are less similar, but if 522 00:36:33,200 --> 00:36:36,759 Speaker 1: you look at the surface proteins of the cells, they 523 00:36:36,800 --> 00:36:39,640 Speaker 1: have a receptor that these viruses can bind to, and 524 00:36:39,719 --> 00:36:42,880 Speaker 1: it's very similar to the one that we have. Surprisingly, 525 00:36:42,920 --> 00:36:46,560 Speaker 1: bats are fairly close to us evolutionarily enough for their 526 00:36:46,640 --> 00:36:49,360 Speaker 1: viruses to sometimes be able to bind. And what we 527 00:36:49,440 --> 00:36:52,000 Speaker 1: look at when we find a new virus in bats, 528 00:36:52,560 --> 00:36:56,560 Speaker 1: we sequence the genes of the protein that binds to 529 00:36:56,600 --> 00:36:58,640 Speaker 1: the cells and we say it, does that look like 530 00:36:58,680 --> 00:37:03,520 Speaker 1: it could get into people? One can? So how seriously 531 00:37:03,560 --> 00:37:06,759 Speaker 1: do you take the coronavirus given what looks like a 532 00:37:06,840 --> 00:37:10,840 Speaker 1: relatively low fatality rate, at least so far, I'm pretty 533 00:37:10,840 --> 00:37:14,600 Speaker 1: optimistic about it, and optimism based on fact. Your point 534 00:37:14,680 --> 00:37:17,320 Speaker 1: is right. The mortality rate is low. It's two percent. 535 00:37:17,520 --> 00:37:20,439 Speaker 1: Probably may even drop as we find that more people 536 00:37:20,520 --> 00:37:24,560 Speaker 1: got mild infections we just didn't know about them. Secondly, yes, 537 00:37:24,640 --> 00:37:27,200 Speaker 1: this thing's spread out of China, and we've got cases 538 00:37:27,200 --> 00:37:29,800 Speaker 1: here in the States and all around Europe and other countries, 539 00:37:30,360 --> 00:37:34,480 Speaker 1: but those are controlled pretty well and we're not seeing 540 00:37:34,880 --> 00:37:39,200 Speaker 1: human to human transmission in countries outside China. That's a 541 00:37:39,239 --> 00:37:41,799 Speaker 1: good thing. If that starts to happen, and we see 542 00:37:41,840 --> 00:37:44,880 Speaker 1: that travelers come into a country seed and new epidemic, 543 00:37:45,280 --> 00:37:47,120 Speaker 1: then you've got a real problem. I mean, I do 544 00:37:47,200 --> 00:37:48,600 Speaker 1: worry a bit when I look at the map of 545 00:37:48,600 --> 00:37:52,480 Speaker 1: where this virus is. Africa and Latin America are just blank, 546 00:37:53,080 --> 00:37:54,920 Speaker 1: and I just don't buy that. I think that there 547 00:37:54,920 --> 00:37:58,920 Speaker 1: are probably people who have traveled to African countries from 548 00:37:59,000 --> 00:38:01,759 Speaker 1: China who are infected and we're just not caught yet. 549 00:38:01,840 --> 00:38:04,960 Speaker 1: So we may see a few little clusters here and there, 550 00:38:05,000 --> 00:38:08,680 Speaker 1: but I think that in two three months this will 551 00:38:08,719 --> 00:38:10,960 Speaker 1: be on the way out, and I expect that in 552 00:38:11,000 --> 00:38:12,840 Speaker 1: a year we won't be able to find this virus 553 00:38:12,840 --> 00:38:16,720 Speaker 1: and people anymore. Around the world, we keep having waves 554 00:38:16,719 --> 00:38:21,600 Speaker 1: of virus is coming, Avian virus stars. They currently have 555 00:38:21,640 --> 00:38:25,120 Speaker 1: a huge problem with the African swine flu, which has 556 00:38:25,160 --> 00:38:28,800 Speaker 1: just decimated their pig heard. Is all of this a 557 00:38:28,880 --> 00:38:33,400 Speaker 1: function of these markets where there's so many different kinds 558 00:38:33,400 --> 00:38:37,400 Speaker 1: of animals brought together, people therefore have a greater range 559 00:38:37,440 --> 00:38:40,399 Speaker 1: of options to pick up diseases. Yeah, I think that's 560 00:38:40,400 --> 00:38:42,160 Speaker 1: a big part of it. But there's a couple of 561 00:38:42,160 --> 00:38:46,000 Speaker 1: other things too. We actually did analysis of every single 562 00:38:46,000 --> 00:38:48,240 Speaker 1: emerging disease that we've ever come across on the planet 563 00:38:48,239 --> 00:38:51,200 Speaker 1: and said, well, where are they coming from and what's 564 00:38:51,280 --> 00:38:53,760 Speaker 1: driving it? And it turns out there are certain regions 565 00:38:53,800 --> 00:38:56,320 Speaker 1: where these things tend to come from. Satie Stage is 566 00:38:56,360 --> 00:38:59,280 Speaker 1: one of them. Central and West Africa and Latin America 567 00:38:59,440 --> 00:39:03,560 Speaker 1: hotspots too. The reason that they have all these issues 568 00:39:03,640 --> 00:39:05,479 Speaker 1: is that we've got a lot of wildlife in those places, 569 00:39:05,560 --> 00:39:09,000 Speaker 1: a lot of wildlife diversity, and they carry their own viruses. 570 00:39:09,480 --> 00:39:11,560 Speaker 1: The more wildlife you've got, the more species, the more 571 00:39:11,600 --> 00:39:14,120 Speaker 1: viruses you've got. There's a lot of people in all 572 00:39:14,120 --> 00:39:18,200 Speaker 1: of these countries. They're developing countries rapidly, building road and infrastructure. 573 00:39:19,000 --> 00:39:21,960 Speaker 1: They're still eating bush meat. China is right in the 574 00:39:22,040 --> 00:39:24,440 Speaker 1: middle of the Southeast Asia hotspot. It's got all of 575 00:39:24,480 --> 00:39:28,239 Speaker 1: this dense population, even in rural areas, and all of 576 00:39:28,280 --> 00:39:35,360 Speaker 1: them are still in very very traditional things like eating snakes, bamboo, rats, primates, bats. 577 00:39:35,880 --> 00:39:38,640 Speaker 1: We meet people who eat bats in rural China and 578 00:39:38,680 --> 00:39:41,439 Speaker 1: they do it for medicinal purposes and they say they're 579 00:39:41,520 --> 00:39:44,239 Speaker 1: very tasty. In medieval times, it wouldn't have been a 580 00:39:44,239 --> 00:39:46,360 Speaker 1: big deal. A couple of people may have been infected 581 00:39:46,360 --> 00:39:48,719 Speaker 1: and the virus would go away. But when we're so 582 00:39:48,920 --> 00:39:52,480 Speaker 1: connected on the planet now and China is extremely connected, 583 00:39:53,040 --> 00:39:55,680 Speaker 1: these viruses are going to spread, and that's the problem 584 00:39:55,680 --> 00:39:59,680 Speaker 1: we've got. The worst diseases we see are diseases that 585 00:40:00,320 --> 00:40:04,440 Speaker 1: get into people and don't cause illness for a few weeks. 586 00:40:04,440 --> 00:40:07,480 Speaker 1: This new coronavirus in the early stages of the outbreak, 587 00:40:07,520 --> 00:40:09,200 Speaker 1: there are plenty of people who got this we don't 588 00:40:09,280 --> 00:40:12,040 Speaker 1: yet know about, who just thought they had a cold 589 00:40:12,320 --> 00:40:16,320 Speaker 1: or pneumonia. In the more elderly patients it gets very severe, 590 00:40:16,640 --> 00:40:19,160 Speaker 1: but if a young person probably didn't even go into 591 00:40:19,160 --> 00:40:22,279 Speaker 1: the clinic. Those are the worst diseases because you have 592 00:40:22,320 --> 00:40:25,280 Speaker 1: these hidden cases that are wandering around in the community 593 00:40:25,320 --> 00:40:28,360 Speaker 1: infecting other people. And I think what's really good is 594 00:40:28,400 --> 00:40:31,680 Speaker 1: that scientists got the virus quickly, and now there is 595 00:40:31,719 --> 00:40:34,839 Speaker 1: some really good tests, so if someone comes into an 596 00:40:34,840 --> 00:40:38,680 Speaker 1: airport with pneumonia, you can very quickly find out whether 597 00:40:38,680 --> 00:40:42,359 Speaker 1: they're infected with this virus or not. In the long run, 598 00:40:42,440 --> 00:40:46,120 Speaker 1: what would you say as success between stars and now 599 00:40:46,760 --> 00:40:49,399 Speaker 1: we've been working in China for fifteen years, in one 600 00:40:49,400 --> 00:40:53,480 Speaker 1: of the many countries working tracking these viruses, finding new viruses, 601 00:40:53,680 --> 00:40:56,239 Speaker 1: raising the flag and saying these are a risk The 602 00:40:56,360 --> 00:41:00,839 Speaker 1: problem really is big picture things didn't change, things like 603 00:41:00,880 --> 00:41:04,759 Speaker 1: the wildlife trade, which still goes on, things like access 604 00:41:04,840 --> 00:41:08,240 Speaker 1: to backcaves. If we know backcast carry viruses, why people 605 00:41:08,280 --> 00:41:11,600 Speaker 1: still walking in those things, why people still hunting them. 606 00:41:11,640 --> 00:41:14,480 Speaker 1: If we know that communities are being exposed, let's get 607 00:41:14,520 --> 00:41:17,759 Speaker 1: into those communities teach them how to avoid the risk 608 00:41:17,840 --> 00:41:22,040 Speaker 1: of getting infected. We're treating pandemics in the wrong way. 609 00:41:22,040 --> 00:41:24,359 Speaker 1: And I think about terrorism ninety eleven was a wake 610 00:41:24,440 --> 00:41:27,480 Speaker 1: up call. We don't wait for a terrorist attack and 611 00:41:27,560 --> 00:41:30,239 Speaker 1: then mop up afterwards. We get out there and we 612 00:41:30,280 --> 00:41:33,080 Speaker 1: find out where the terrorist cells are hiding. We listen 613 00:41:33,160 --> 00:41:35,120 Speaker 1: to what they're doing, and we hear the rumors of 614 00:41:35,200 --> 00:41:38,759 Speaker 1: an attack, and we send in the drones. With a pandemic, 615 00:41:39,280 --> 00:41:41,200 Speaker 1: we just wait for it to happen and hope we're 616 00:41:41,200 --> 00:41:43,799 Speaker 1: going to get vaccines. That's the wrong approach, and I 617 00:41:43,800 --> 00:41:46,920 Speaker 1: think we need to treat these pandemics as just then. 618 00:41:46,960 --> 00:41:49,879 Speaker 1: It strings it risk to people and the way we 619 00:41:49,960 --> 00:41:52,239 Speaker 1: do business on the planet, and let's do with that 620 00:41:52,400 --> 00:41:54,319 Speaker 1: risk in a mature way. Let's get ready for it, 621 00:41:54,400 --> 00:41:57,560 Speaker 1: let's prevent it. Let's find ou where all these viruses are. 622 00:41:57,960 --> 00:42:01,120 Speaker 1: Let's get into those hotspots and all the infrastructure to 623 00:42:01,160 --> 00:42:04,160 Speaker 1: protect people. Let's teach people how to avoid it, and 624 00:42:04,239 --> 00:42:07,280 Speaker 1: let's get rid of activities that are going to produce 625 00:42:07,360 --> 00:42:11,360 Speaker 1: the next pandemic like the wildlife trade, push me hunting, 626 00:42:11,680 --> 00:42:15,320 Speaker 1: or at least monitor it and test people and find 627 00:42:15,320 --> 00:42:18,640 Speaker 1: them at the very early stages. Would your reaction to 628 00:42:18,800 --> 00:42:23,280 Speaker 1: China quarantining an entire city. We have colleagues in China 629 00:42:23,320 --> 00:42:25,040 Speaker 1: who went home to see the family for the year. 630 00:42:25,080 --> 00:42:28,040 Speaker 1: They can't get back. I live in New York and 631 00:42:28,120 --> 00:42:29,919 Speaker 1: work in the city, and I just wonder what would 632 00:42:29,920 --> 00:42:32,759 Speaker 1: happen if the mayor New York said, sorry, guys, you 633 00:42:32,800 --> 00:42:37,000 Speaker 1: can't leave your stuck. You have real problems. But China 634 00:42:37,120 --> 00:42:40,200 Speaker 1: is different, and people in China, I think, first of all, 635 00:42:40,239 --> 00:42:43,200 Speaker 1: they understand that they live in a very dense population 636 00:42:43,760 --> 00:42:46,080 Speaker 1: and they know that at risk from pandemics. They've had 637 00:42:46,080 --> 00:42:50,480 Speaker 1: them before, bird flu stars, so that's one thing, so 638 00:42:50,560 --> 00:42:54,120 Speaker 1: they're ready for this sort of control measure. Secondly, they're 639 00:42:54,200 --> 00:42:57,719 Speaker 1: used to a government that puts in place restrictions that 640 00:42:57,760 --> 00:43:00,560 Speaker 1: we wouldn't accept in the West. I think for the 641 00:43:00,600 --> 00:43:03,319 Speaker 1: Chinese population, they're just going to live through this. The 642 00:43:03,400 --> 00:43:04,719 Speaker 1: virus is going to go away and they're going to 643 00:43:04,760 --> 00:43:08,759 Speaker 1: be happy. From a disease prevention point of view, international 644 00:43:08,800 --> 00:43:12,319 Speaker 1: travel bands are that effect if the best thing you 645 00:43:12,360 --> 00:43:16,120 Speaker 1: can do is to test people when they arrived, find 646 00:43:16,160 --> 00:43:18,680 Speaker 1: the cases and get them in hospital and treat them 647 00:43:18,760 --> 00:43:23,000 Speaker 1: in good quarantine measure locking down a city is a 648 00:43:23,000 --> 00:43:25,920 Speaker 1: pretty harsh measure that often doesn't work. And the reason 649 00:43:25,960 --> 00:43:28,799 Speaker 1: that there's a problem with that is people try and 650 00:43:29,160 --> 00:43:33,560 Speaker 1: dodge the regulations and they'll hide the symptoms to move. 651 00:43:33,600 --> 00:43:36,360 Speaker 1: We saw that in the US. Remember the Bowler patient 652 00:43:36,960 --> 00:43:39,160 Speaker 1: who came back and went to hospital with a fever 653 00:43:39,520 --> 00:43:41,839 Speaker 1: and they said, had you been to Africa? And they 654 00:43:41,880 --> 00:43:44,200 Speaker 1: said no, and in turns out they had and they 655 00:43:44,200 --> 00:43:48,600 Speaker 1: actually affected a nurse. People do deceptive things, so bands 656 00:43:48,600 --> 00:43:51,160 Speaker 1: are often ineffective. But when you've got a city like 657 00:43:51,239 --> 00:43:55,440 Speaker 1: we're hang with sixteen thousand cases, that harsh measure may 658 00:43:55,480 --> 00:43:59,560 Speaker 1: actually do some goodness sense. They can't quite imagine if 659 00:43:59,560 --> 00:44:03,440 Speaker 1: they have to sustained very long, how you keep an 660 00:44:03,560 --> 00:44:07,680 Speaker 1: entire city quarantined. Well, it's not sustainable. China can probably 661 00:44:07,680 --> 00:44:09,520 Speaker 1: do it better than most contrast, because they've got the 662 00:44:09,600 --> 00:44:12,600 Speaker 1: logistics and supply chain and they'll bring in the army 663 00:44:13,200 --> 00:44:14,960 Speaker 1: but look what happened in a bowl that there was 664 00:44:15,000 --> 00:44:18,600 Speaker 1: some towns, cities in West Africa that people did this 665 00:44:18,680 --> 00:44:20,719 Speaker 1: in The police blocked out the town. There were so 666 00:44:20,719 --> 00:44:24,239 Speaker 1: many bowler cases. There were riots on the street, and 667 00:44:24,360 --> 00:44:27,240 Speaker 1: what a riot does. You've got a national security problem 668 00:44:27,440 --> 00:44:31,840 Speaker 1: with a raging infection as well. That's a recipe for disaster. 669 00:44:32,520 --> 00:44:35,680 Speaker 1: It's not a sustainable strategy. But I think that the 670 00:44:35,760 --> 00:44:40,439 Speaker 1: equation that President shi Jimpeng is working with is this 671 00:44:40,560 --> 00:44:43,400 Speaker 1: virus will be over within a few weeks and then 672 00:44:43,440 --> 00:44:46,239 Speaker 1: we can loosen the regulations. I think that's true, and 673 00:44:46,320 --> 00:44:49,640 Speaker 1: I hope it happens. There's a gamble there that this 674 00:44:49,840 --> 00:44:53,279 Speaker 1: is a very short run crisis. I think it's a 675 00:44:53,280 --> 00:44:55,920 Speaker 1: fair gamble, to be honestly. We're looking at this now, 676 00:44:55,960 --> 00:44:59,319 Speaker 1: we're five and a half, six weeks in. It's not 677 00:44:59,480 --> 00:45:03,960 Speaker 1: reached hundreds of thousands of cases. The mortality rate is 678 00:45:04,000 --> 00:45:07,600 Speaker 1: staying low. We're not seeing human to human transmission in 679 00:45:07,600 --> 00:45:11,319 Speaker 1: a big way outside China. It'll wait another couple of weeks. 680 00:45:11,360 --> 00:45:13,600 Speaker 1: It will continue to rise, but eventually it's got a 681 00:45:13,680 --> 00:45:16,759 Speaker 1: peak and then we're going to see caseloads drop. One 682 00:45:16,760 --> 00:45:19,120 Speaker 1: of the problems is people get out for a long time, 683 00:45:19,200 --> 00:45:22,360 Speaker 1: and that's going to keep the case load high. But 684 00:45:22,520 --> 00:45:25,400 Speaker 1: I think within two three months we'll be at the 685 00:45:25,400 --> 00:45:28,160 Speaker 1: back end of this my hunches. You are right. I've 686 00:45:28,320 --> 00:45:32,920 Speaker 1: had a feeling all along the mortality rate wasn't anything 687 00:45:33,000 --> 00:45:36,680 Speaker 1: like you'd experience, and that the rate of transmission human 688 00:45:36,680 --> 00:45:39,879 Speaker 1: to human was so low. Our travel as the way 689 00:45:39,920 --> 00:45:42,239 Speaker 1: that these viruses are going to get around, and if 690 00:45:42,280 --> 00:45:46,000 Speaker 1: we can target those ports get ready for it, we 691 00:45:46,040 --> 00:45:48,680 Speaker 1: can do a lot to stop these outbreaks spreading. And 692 00:45:48,800 --> 00:45:51,880 Speaker 1: I think in this case, the speed of the worldwide 693 00:45:51,880 --> 00:45:56,880 Speaker 1: response has been pretty amazing. To see China releasing information 694 00:45:56,880 --> 00:46:00,760 Speaker 1: at this level is amazing to see who declare an 695 00:46:00,800 --> 00:46:04,520 Speaker 1: emergency is really good. This is a real emergency because 696 00:46:04,520 --> 00:46:08,400 Speaker 1: it's global at this point. But my concern is, do 697 00:46:08,520 --> 00:46:12,359 Speaker 1: we really have to wait until a thousand people die 698 00:46:12,480 --> 00:46:15,839 Speaker 1: before we start dealing with these pandemics as a real 699 00:46:15,880 --> 00:46:18,960 Speaker 1: problem and getting ready for them before they emerge A 700 00:46:19,080 --> 00:46:23,200 Speaker 1: true pandemic, a true black Swan event, would break down 701 00:46:23,280 --> 00:46:26,400 Speaker 1: all of the security measures we've got in place, because 702 00:46:26,960 --> 00:46:30,160 Speaker 1: your frontline responders are going to get sick. They're probably 703 00:46:30,200 --> 00:46:33,240 Speaker 1: going to get sick first, so all of those measures 704 00:46:33,239 --> 00:46:35,680 Speaker 1: are going to disappear early on, and it's going to 705 00:46:35,719 --> 00:46:40,719 Speaker 1: be security issues and riots. Pandemics have that capacity. The 706 00:46:40,880 --> 00:46:43,360 Speaker 1: security people in the US know that. The now that 707 00:46:43,520 --> 00:46:46,959 Speaker 1: in China they're doing things to get ready. But let's 708 00:46:47,040 --> 00:46:49,120 Speaker 1: get really ahead of the curve. Let's find out where 709 00:46:49,160 --> 00:46:52,040 Speaker 1: these things come from, and let's work to stop them 710 00:46:52,080 --> 00:46:54,640 Speaker 1: emerging in the first place. That's our mission. Well, I 711 00:46:54,760 --> 00:46:59,040 Speaker 1: really appreciate your sharing with us. I really appreciate you 712 00:46:59,160 --> 00:47:01,680 Speaker 1: talking about this new and taking the big picture look 713 00:47:01,719 --> 00:47:07,640 Speaker 1: as you always do. Thank you to my guests, doctor 714 00:47:07,680 --> 00:47:11,840 Speaker 1: Anthony Fauci and doctor Peter Does. You can read more 715 00:47:12,120 --> 00:47:17,280 Speaker 1: about the coronavirus on our show page at newtsworld dot com. 716 00:47:17,480 --> 00:47:21,200 Speaker 1: Newtsworld is produced by Westwood One. Our executive producer is 717 00:47:21,239 --> 00:47:25,320 Speaker 1: Debbie Myers and our producer is Garnsey Slump. Our editor 718 00:47:25,400 --> 00:47:29,640 Speaker 1: is Robert Borowski, and our researcher is Rachel Peterson. Our 719 00:47:29,640 --> 00:47:33,279 Speaker 1: guest booker is Tamara Coleman. The artwork for the show 720 00:47:33,360 --> 00:47:37,040 Speaker 1: was created by Steve Penny. The music was composed by 721 00:47:37,120 --> 00:47:40,399 Speaker 1: Joey Selby. Special thanks to the team at Gingwich three 722 00:47:40,520 --> 00:47:46,440 Speaker 1: sixty and Westwood One's John Wardock and Robert Mathers. Please 723 00:47:46,480 --> 00:47:50,560 Speaker 1: email me with your comments at newt at newtsworld dot com. 724 00:47:50,600 --> 00:47:53,080 Speaker 1: If you've been enjoying Newtsworld, I hope you'll go to 725 00:47:53,080 --> 00:47:57,040 Speaker 1: Apple Podcast and both rate us with five stars and 726 00:47:57,160 --> 00:47:59,719 Speaker 1: give us a review so others can learn what it's 727 00:47:59,760 --> 00:48:11,920 Speaker 1: all about. I'm new Kangridge. This is news World, the 728 00:48:12,000 --> 00:48:14,200 Speaker 1: Westwood One podcast Network