WEBVTT 00:00:03.675 --> 00:00:07.166 Hello, I'm Chris Anderson. Welcome to The TED Interview. 00:00:07.190 --> 00:00:10.825 We're gearing up for season four with some extraordinary guests, 00:00:10.849 --> 00:00:14.319 but I don't want to wait for that for today's episode, 00:00:14.343 --> 00:00:17.263 because we're in the middle of a pandemic, 00:00:17.287 --> 00:00:20.642 and there's a guest I really wanted to talk to now. NOTE Paragraph 00:00:21.514 --> 00:00:23.593 He is Adam Kucharski, 00:00:23.617 --> 00:00:26.053 an infectious diseases scientist 00:00:26.077 --> 00:00:29.466 who focuses on the mathematical modeling of pandemics. 00:00:29.990 --> 00:00:31.316 He's an associate professor 00:00:31.340 --> 00:00:33.901 at the London School of Hygiene and Tropical Medicine 00:00:33.925 --> 00:00:35.266 and a TED Fellow. NOTE Paragraph 00:00:35.290 --> 00:00:37.391 (Music) NOTE Paragraph 00:00:37.415 --> 00:00:39.813 (TED Talk) Adam Kucharski: So what kind of behavior 00:00:39.837 --> 00:00:41.598 is actually important for epidemics? 00:00:41.622 --> 00:00:45.260 Conversations, close physical contacts? 00:00:45.284 --> 00:00:47.815 What sort of data should we be collecting 00:00:47.839 --> 00:00:49.022 before an outbreak 00:00:49.046 --> 00:00:51.580 if we want to predict how infection might spread? 00:00:52.268 --> 00:00:56.426 To find out, our team built a mathematical model ... NOTE Paragraph 00:00:56.450 --> 00:00:59.331 Chris Anderson: When it comes to figuring out what to make of 00:00:59.355 --> 00:01:01.785 this pandemic, known technically as COVID-19, 00:01:01.809 --> 00:01:04.760 and informally as just the coronavirus, 00:01:04.784 --> 00:01:07.681 I find his thinking unbelievably helpful. 00:01:07.705 --> 00:01:10.054 And I'm excited to dive into it with you. 00:01:10.467 --> 00:01:12.483 A special callout to my friends on Twitter 00:01:12.507 --> 00:01:14.824 who offered up many suggestions for questions. 00:01:14.848 --> 00:01:18.022 I know this topic is on everyone's mind right now. 00:01:18.046 --> 00:01:19.998 And what I hope this episode does 00:01:20.022 --> 00:01:22.346 is give us all a more nuanced way 00:01:22.370 --> 00:01:26.085 of thinking about how this pandemic has unfolded so far, 00:01:26.109 --> 00:01:27.847 what might be to come 00:01:27.871 --> 00:01:30.499 and what we all collectively can do about it. 00:01:31.212 --> 00:01:32.405 Let's dive in. NOTE Paragraph 00:01:32.429 --> 00:01:33.579 (Music) NOTE Paragraph 00:01:37.777 --> 00:01:39.792 Adam, welcome to the TED Interview. NOTE Paragraph 00:01:39.816 --> 00:01:41.499 Adam Kucharski: Thank you. NOTE Paragraph 00:01:41.523 --> 00:01:44.840 CA: So let's just start with a couple of basics. 00:01:44.864 --> 00:01:48.341 A lot of skeptical people's response -- 00:01:48.365 --> 00:01:51.309 certainly over the last few weeks, maybe less so now -- 00:01:51.333 --> 00:01:53.929 has been, "Oh, come on, this isn't such a big deal, 00:01:53.953 --> 00:01:56.487 there's a relatively tiny number of cases. 00:01:56.511 --> 00:01:58.903 Compare it to the flu, compare it to anything else. 00:01:58.927 --> 00:02:01.014 There are much bigger problems in the world. 00:02:01.038 --> 00:02:04.378 Why are we making such a fuss about this?" 00:02:04.847 --> 00:02:08.475 And I guess the answer to that fuss is that it comes down to the mathematics. 00:02:08.499 --> 00:02:12.481 We're talking about the mathematics of exponential growth, 00:02:12.505 --> 00:02:13.871 fundamentally, right? NOTE Paragraph 00:02:13.895 --> 00:02:15.045 AK: Exactly. 00:02:15.069 --> 00:02:19.903 And there's a number that we use to get a sense of how easy things spread 00:02:19.927 --> 00:02:22.364 and the level of transmission we're dealing with. 00:02:22.864 --> 00:02:24.661 We call that the reproduction number, 00:02:24.685 --> 00:02:26.122 and conceptually, it's just, 00:02:26.146 --> 00:02:27.873 for each case you have, on average, 00:02:27.897 --> 00:02:29.589 how many others are they infecting? 00:02:29.613 --> 00:02:32.625 And that gives you a sense of how much is this scaling, 00:02:32.649 --> 00:02:34.649 how much this growth is going to look like. 00:02:34.673 --> 00:02:37.875 For coronavirus, we're now seeing, across multiple countries, 00:02:37.899 --> 00:02:41.354 we're seeing each person on average giving it to two or three more. NOTE Paragraph 00:02:42.518 --> 00:02:44.129 CA: So that reproduction number, 00:02:44.153 --> 00:02:48.377 the first thing to understand is that any number above one 00:02:48.401 --> 00:02:50.768 means that this thing is going to grow. 00:02:50.792 --> 00:02:54.880 Any number below one means it's going to diminish. NOTE Paragraph 00:02:55.507 --> 00:02:57.501 AK: Exactly -- if you have it above one, 00:02:57.525 --> 00:02:59.593 then each group of people infected 00:02:59.617 --> 00:03:02.626 are going to be generating more infection than there was before. 00:03:02.650 --> 00:03:04.585 And you will see the exponential effect, 00:03:04.609 --> 00:03:07.920 so if it's two, you will be doubling every round of infection, 00:03:07.944 --> 00:03:09.109 and if it's below one, 00:03:09.133 --> 00:03:12.229 you're going to get something that's going to decline, on average. NOTE Paragraph 00:03:12.602 --> 00:03:14.201 CA: So that number two or higher, 00:03:14.225 --> 00:03:17.514 I think everyone here is maybe familiar with the famous story 00:03:17.538 --> 00:03:19.779 of the chessboard and the grains of rice, 00:03:19.803 --> 00:03:24.316 and if you double the number of grains for every square of the chessboard, 00:03:24.340 --> 00:03:27.712 for the first 10 or 15 squares nothing much happens, 00:03:27.736 --> 00:03:30.403 but by the time you've got to the 64th square, 00:03:30.427 --> 00:03:33.828 you suddenly have tons of rice for every individual on the planet. NOTE Paragraph 00:03:33.852 --> 00:03:34.905 (Laughs) NOTE Paragraph 00:03:34.929 --> 00:03:38.010 Exponential growth is an incredible thing. 00:03:38.034 --> 00:03:39.375 And the small numbers now 00:03:39.399 --> 00:03:42.032 are really not what you should be paying attention to -- 00:03:42.056 --> 00:03:45.397 you should be paying attention to the models of what could be to come. NOTE Paragraph 00:03:45.982 --> 00:03:47.133 AK: Exactly. 00:03:47.157 --> 00:03:49.514 Obviously, if you continue the exponential growth, 00:03:49.538 --> 00:03:51.618 you do sometimes get these incredibly large, 00:03:51.642 --> 00:03:53.205 maybe implausibly large numbers. 00:03:53.229 --> 00:03:55.592 But even looking at a timescale of say, a month, 00:03:55.616 --> 00:03:57.378 if the reproduction number is three, 00:03:57.402 --> 00:03:59.442 each person is infecting three on average. 00:03:59.466 --> 00:04:02.903 The gap between these rounds of infection is about five days. 00:04:02.927 --> 00:04:05.188 So if you imagine that you've got one case now, 00:04:05.212 --> 00:04:09.386 that's, kind of, six of these five-day steps in a month. 00:04:09.410 --> 00:04:10.776 So by the end of that month, 00:04:10.800 --> 00:04:12.958 that one person could have generated, 00:04:12.982 --> 00:04:15.712 I think it works out at about 729 cases. 00:04:15.736 --> 00:04:17.291 So even in a month, 00:04:17.315 --> 00:04:19.578 just the scale of this thing can really shoot up 00:04:19.602 --> 00:04:21.135 if it's not controlled. NOTE Paragraph 00:04:22.236 --> 00:04:23.400 CA: And so certainly, 00:04:23.424 --> 00:04:26.495 that seems to be happening on most numbers that you look at now, 00:04:26.519 --> 00:04:29.399 certainly where the virus is in the early stages 00:04:29.423 --> 00:04:31.447 of entering a country. 00:04:31.471 --> 00:04:32.649 You've given a model 00:04:32.673 --> 00:04:38.029 whereby we can much more clearly understand this reproduction number, 00:04:38.053 --> 00:04:41.820 because it seems to me this is almost like the core to how we think of the virus 00:04:41.844 --> 00:04:46.434 and how we respond to it and how much we should fear it, almost. 00:04:46.458 --> 00:04:48.006 And in your thinking, 00:04:48.030 --> 00:04:50.895 you sort of break it down into four components, 00:04:50.919 --> 00:04:54.355 which you call DOTS: 00:04:54.379 --> 00:04:57.029 Duration, Opportunities, 00:04:57.053 --> 00:04:59.069 Transmission probability 00:04:59.093 --> 00:05:00.292 and Susceptibility. 00:05:00.316 --> 00:05:02.425 And I think it would be really helpful, Adam, 00:05:02.449 --> 00:05:04.299 for you to just explain each of these, 00:05:04.323 --> 00:05:07.260 because it's quite a simple equation 00:05:07.284 --> 00:05:11.520 that links those four things to the actual reproduction number. 00:05:11.544 --> 00:05:13.154 So talk about them in turn. 00:05:13.178 --> 00:05:14.662 Duration, what does that mean? NOTE Paragraph 00:05:14.686 --> 00:05:18.364 AK: Duration measures how long someone is infectious for. 00:05:18.742 --> 00:05:19.917 If, for example, 00:05:19.941 --> 00:05:23.780 intuitively, if someone is infectious for a longer period of time, 00:05:23.804 --> 00:05:25.966 say, twice as long as someone else, 00:05:25.990 --> 00:05:27.723 then that's twice the length 00:05:27.747 --> 00:05:30.127 that they've got to be spreading infection. NOTE Paragraph 00:05:30.981 --> 00:05:35.821 CA: And what is the duration number for this virus, 00:05:35.845 --> 00:05:39.901 compared with, say, flu or with other pathogens? NOTE Paragraph 00:05:40.439 --> 00:05:41.808 AK: It depends a little bit 00:05:41.832 --> 00:05:43.855 on what happens when people are infectious, 00:05:43.879 --> 00:05:47.459 if they're being isolated very quickly, that shortens that period of time, 00:05:47.483 --> 00:05:49.749 but potentially, we're looking at around a week 00:05:49.773 --> 00:05:54.090 people are effectively infectious before they might be isolated in hospital. NOTE Paragraph 00:05:54.844 --> 00:05:58.741 CA: And during that week, they may not even be showing symptoms 00:05:58.765 --> 00:06:00.965 for that full week either, right? 00:06:01.395 --> 00:06:05.220 So someone gets infected, there's an incubation period. 00:06:05.680 --> 00:06:08.569 There's a period some way into that incubation period 00:06:08.593 --> 00:06:11.141 where they start being infectious, 00:06:11.165 --> 00:06:14.645 and there may be a period after that, where they start to show symptoms, 00:06:14.669 --> 00:06:17.425 and it's not clear, quite, how those dates align. 00:06:17.449 --> 00:06:18.600 Is that right? NOTE Paragraph 00:06:18.624 --> 00:06:20.561 AK: No, we're getting more information. 00:06:20.585 --> 00:06:24.799 One of the signals we see in data 00:06:24.823 --> 00:06:27.851 that suggest that you may have that early transmission going on 00:06:27.875 --> 00:06:31.893 is when you have this delay from one infection to the next. 00:06:32.349 --> 00:06:34.621 So that seems to be around five days. 00:06:35.191 --> 00:06:37.835 That incubation period, the time for symptoms to appear, 00:06:37.859 --> 00:06:39.483 is also about five days. 00:06:39.507 --> 00:06:41.311 So if you imagine that most people 00:06:41.335 --> 00:06:44.811 are only infecting others when they're symptomatic, 00:06:44.835 --> 00:06:46.422 you'd have that incubation period 00:06:46.446 --> 00:06:49.506 and then you'd have some more time when they're infecting others. 00:06:49.530 --> 00:06:51.848 So the fact that those values seem to be similar, 00:06:51.872 --> 00:06:53.948 suggesting that some people are transmitting 00:06:53.972 --> 00:06:57.808 either very early on or potentially before they're showing clear symptoms. NOTE Paragraph 00:06:58.397 --> 00:07:01.881 CA: So almost implies that on average, 00:07:01.905 --> 00:07:03.649 people are infecting others 00:07:03.673 --> 00:07:06.910 as much before they show symptoms as after. NOTE Paragraph 00:07:07.403 --> 00:07:08.569 AK: Potentially. 00:07:08.593 --> 00:07:10.348 Obviously these are early data sets, 00:07:10.372 --> 00:07:13.348 but I think there's good evidence that a fair number of people, 00:07:13.372 --> 00:07:15.966 either before they're showing clear symptoms 00:07:15.990 --> 00:07:19.421 or maybe they're not showing the kind of very distinctive fever and cough 00:07:19.429 --> 00:07:21.924 but they're feeling unwell and they're shedding virus 00:07:21.938 --> 00:07:23.205 during that period. NOTE Paragraph 00:07:23.625 --> 00:07:28.341 CA: And does that make it quite different from the flu, for example? NOTE Paragraph 00:07:29.421 --> 00:07:32.016 AK: It makes it actually similar to flu in that regard. 00:07:32.040 --> 00:07:34.541 One of the reasons pandemic flu is so hard to control 00:07:34.565 --> 00:07:36.389 and so feared as a threat 00:07:36.413 --> 00:07:40.738 is because so much transmission happens before people are severely ill. 00:07:40.762 --> 00:07:44.149 And that means that by the time you identify these cases, 00:07:44.173 --> 00:07:47.251 they've probably actually spread it to a number of other people. NOTE Paragraph 00:07:47.275 --> 00:07:49.522 CA: Yeah, so this is the trickery of the thing, 00:07:49.546 --> 00:07:54.497 and why it's so hard to do anything about it. 00:07:54.521 --> 00:07:56.387 It is ahead of us all the time, 00:07:56.411 --> 00:08:00.166 and you can't just pay attention to how someone feels 00:08:00.190 --> 00:08:01.410 or what they're doing. 00:08:01.434 --> 00:08:03.426 I mean, how does that happen, by the way? 00:08:03.450 --> 00:08:05.323 How does someone infect someone else 00:08:05.347 --> 00:08:08.109 before they're even showing symptoms themselves, 00:08:08.133 --> 00:08:11.752 because classically, we think of, you know, the person sneezing 00:08:11.776 --> 00:08:14.895 and droplets go through the air and someone else breathes them in 00:08:14.919 --> 00:08:16.546 and that's how infection happens. 00:08:16.570 --> 00:08:20.760 What is actually going on for infection pre-symptoms? NOTE Paragraph 00:08:21.950 --> 00:08:24.529 AK: So the level of transmission we see with this virus 00:08:24.553 --> 00:08:26.673 isn't what we see, for example, with measles, 00:08:26.697 --> 00:08:29.029 where someone sneezes and a lot of virus gets out 00:08:29.053 --> 00:08:32.005 and potentially lots of susceptible people can get exposed. 00:08:32.029 --> 00:08:34.159 So potentially, it could be quite early on 00:08:34.183 --> 00:08:36.292 that even if someone has quite mild symptoms, 00:08:36.316 --> 00:08:37.530 maybe a bit of a cough, 00:08:37.554 --> 00:08:39.720 that's enough for some virus to be getting out 00:08:39.744 --> 00:08:40.917 and particularly, 00:08:40.941 --> 00:08:42.481 some of the work that we've done 00:08:42.505 --> 00:08:44.520 trying to look at sort of close gatherings, 00:08:44.544 --> 00:08:45.871 so very tight-knit meals, 00:08:45.895 --> 00:08:47.784 there was an example in a ski chalet -- 00:08:47.808 --> 00:08:50.868 and even in those situations, you might have someone mildly ill, 00:08:50.892 --> 00:08:53.799 but enough virus is getting out and somehow exposing others, 00:08:53.823 --> 00:08:55.823 we're still trying to work out exactly how, 00:08:55.847 --> 00:08:58.315 but there's enough there to cause some infection. NOTE Paragraph 00:08:58.958 --> 00:09:03.125 CA: But if someone's mildly ill, don't they still have symptoms? 00:09:03.149 --> 00:09:07.886 Isn't there evidence that even before they know that they're ill, 00:09:07.910 --> 00:09:11.942 something is going on? 00:09:11.966 --> 00:09:14.062 There was a German paper published this week 00:09:14.086 --> 00:09:18.073 that seemed to suggest that even really early on, 00:09:18.097 --> 00:09:20.968 you take a swab from the back of someone's throat 00:09:20.992 --> 00:09:24.268 and they have hundreds of thousands of these viruses 00:09:24.292 --> 00:09:26.301 already reproducing there. 00:09:26.325 --> 00:09:30.172 Like, can someone just literally just be breathing normally 00:09:30.196 --> 00:09:33.466 and there is some transmission of virus out into the air 00:09:33.490 --> 00:09:35.081 that they don't even know about 00:09:35.105 --> 00:09:36.969 and is either infecting people directly 00:09:36.993 --> 00:09:39.002 or settling on surfaces, is that possible? NOTE Paragraph 00:09:39.026 --> 00:09:41.335 AK: I think that's what we're trying to pin down, 00:09:41.359 --> 00:09:42.546 how much that [unclear]. 00:09:42.570 --> 00:09:43.743 As you said, 00:09:43.767 --> 00:09:46.482 there's evidence that you can have people without symptoms 00:09:46.506 --> 00:09:48.450 and you can get virus out their throats. 00:09:48.474 --> 00:09:51.434 And so certainly there's potential that it can be breathed out, 00:09:51.458 --> 00:09:54.804 but is that a fairly rare event for that actual transmission to happen, 00:09:54.828 --> 00:09:58.384 or are we potentially seeing more infections occur through that route? 00:09:58.408 --> 00:10:00.779 So it's really early data, 00:10:00.803 --> 00:10:02.676 and I think it's a piece of the puzzle, 00:10:02.700 --> 00:10:04.910 but we're trying to work out where that fits in 00:10:04.934 --> 00:10:08.388 with what we know about the kind of other transmission events we've seen. NOTE Paragraph 00:10:08.412 --> 00:10:13.649 CA: Alright, so, duration is the duration of the period of infectiousness. 00:10:13.673 --> 00:10:18.291 We think is five to six days, is that what I heard you say? NOTE Paragraph 00:10:18.315 --> 00:10:19.772 AK: Potentially around a week, 00:10:19.796 --> 00:10:23.026 depending on exactly what happens to people when they're infectious. NOTE Paragraph 00:10:23.050 --> 00:10:25.971 CA: And there are cases of people testing positive 00:10:25.995 --> 00:10:28.726 way, way later, after they've got infected. 00:10:29.384 --> 00:10:32.447 That may be true, but they are probably not as infectious then. 00:10:32.471 --> 00:10:35.161 Is that basically right, that's the way to think of this? NOTE Paragraph 00:10:35.185 --> 00:10:37.003 AK: I think that's our working theory, 00:10:37.027 --> 00:10:39.408 that a lot of that infection is happening early on. 00:10:39.432 --> 00:10:42.050 And we see that for a number of respiratory infections, 00:10:42.074 --> 00:10:44.349 that when people obviously become severely ill, 00:10:44.373 --> 00:10:45.912 their behavior is very different 00:10:45.936 --> 00:10:49.188 to when they may be walking around and going about their normal day. NOTE Paragraph 00:10:49.908 --> 00:10:52.827 CA: And so again, comparing that D number to other cases, 00:10:52.851 --> 00:10:54.042 like the flu, 00:10:54.066 --> 00:10:55.534 is flu similar? 00:10:55.558 --> 00:10:57.608 What's the D number for flu? NOTE Paragraph 00:10:58.414 --> 00:11:01.463 AK: So for flu, it's probably slightly shorter 00:11:01.487 --> 00:11:04.776 in terms of the period that people are actively infectious. 00:11:04.800 --> 00:11:07.249 I mean, for flu, it's a very quick turnover 00:11:07.273 --> 00:11:09.054 from one case to the next, actually. 00:11:09.078 --> 00:11:11.514 Even a matter of about three days, potentially, 00:11:11.538 --> 00:11:13.995 from one infection to the person that they infect. 00:11:14.852 --> 00:11:17.958 And then at the other end of the scale, you get things like STDs, 00:11:17.982 --> 00:11:20.678 where that duration could be several months, potentially. NOTE Paragraph 00:11:21.228 --> 00:11:22.379 CA: Right. 00:11:22.403 --> 00:11:26.958 OK, really nothing that unusual so far, in terms of this particular virus. 00:11:26.982 --> 00:11:29.791 Let's look at the O, opportunity. 00:11:29.815 --> 00:11:30.973 What is that? NOTE Paragraph 00:11:30.997 --> 00:11:34.437 AK: So opportunity is a measure of how many chances 00:11:34.461 --> 00:11:37.217 the virus has to spread through interactions 00:11:37.241 --> 00:11:38.709 while someone is infectious. 00:11:38.733 --> 00:11:41.058 So typically, it's a measure of social behavior. 00:11:41.646 --> 00:11:45.014 On average, how many social contacts do people make 00:11:45.038 --> 00:11:48.529 that create opportunities for transmission while they're infectious. NOTE Paragraph 00:11:48.553 --> 00:11:53.696 CA: So it's how many people have you got close enough to 00:11:53.720 --> 00:11:56.095 during a day, during a given day, 00:11:56.119 --> 00:11:58.063 to have a chance of infecting them. 00:11:58.087 --> 00:12:00.990 And that number could be, 00:12:01.014 --> 00:12:04.611 if people aren't taking precautions in a normal, sort of, urban setting, 00:12:04.635 --> 00:12:07.155 I mean, that could run into the hundreds, presumably? NOTE Paragraph 00:12:07.179 --> 00:12:08.751 AK: Potentially, for some people. 00:12:08.775 --> 00:12:11.734 We've done a number of studies looking at that in recent years, 00:12:11.758 --> 00:12:13.992 and the average, in terms of physical contacts, 00:12:14.016 --> 00:12:15.452 is about five people per day. 00:12:15.476 --> 00:12:17.633 Most people will have conversation or contacts 00:12:17.657 --> 00:12:19.007 generally with about 10, 15, 00:12:19.031 --> 00:12:20.195 but obviously, 00:12:20.219 --> 00:12:22.518 between cultures, we see quite a lot of variation 00:12:22.542 --> 00:12:25.101 in the level of physical greetings that might happen. NOTE Paragraph 00:12:25.125 --> 00:12:29.710 CA: And presumably, that number again is no different for this virus 00:12:29.734 --> 00:12:30.900 than for any other. 00:12:30.924 --> 00:12:34.367 I mean, that's just a feature of the lives that we live. NOTE Paragraph 00:12:35.280 --> 00:12:37.049 AK: I think for this one, 00:12:37.073 --> 00:12:39.438 if it's driven through these kind of interactions, 00:12:39.462 --> 00:12:42.367 and we've seen for flu, for other respiratory infections, 00:12:42.391 --> 00:12:46.316 those kinds of fairly close contacts and everyday physical interactions 00:12:46.340 --> 00:12:49.435 seem to be the ones that are important for transmission. NOTE Paragraph 00:12:49.459 --> 00:12:51.650 CA: Perhaps there is one difference. 00:12:51.674 --> 00:12:56.400 The fact that if you're infectious pre-symptoms, 00:12:56.424 --> 00:12:59.790 perhaps that means that actually, there are more opportunities here. 00:12:59.814 --> 00:13:02.784 This is part of the virus's genius, as it were, 00:13:02.808 --> 00:13:06.609 that by not letting on that it's inside someone, 00:13:06.633 --> 00:13:09.976 people continue to interact and go to work 00:13:10.000 --> 00:13:11.777 and take the subway and so forth, 00:13:11.801 --> 00:13:13.729 not even knowing that they're sick. NOTE Paragraph 00:13:13.753 --> 00:13:14.916 AK: Exactly. 00:13:14.940 --> 00:13:16.293 And for something like flu, 00:13:16.317 --> 00:13:20.276 you see when people get ill, clearly, their social contacts drop off. 00:13:20.300 --> 00:13:23.283 So to have a virus that can be infectious 00:13:23.307 --> 00:13:26.149 while people are going around their everyday lives, 00:13:26.173 --> 00:13:28.712 really gives it an advantage in terms of transmission. NOTE Paragraph 00:13:28.736 --> 00:13:29.903 CA: In your modeling, 00:13:29.927 --> 00:13:34.755 do you actually have this opportunities number higher than for flu? NOTE Paragraph 00:13:35.406 --> 00:13:39.940 AK: So for the moment, we're kind of using similar values, 00:13:39.964 --> 00:13:43.023 so we're trying to look at, for example, 00:13:43.047 --> 00:13:45.450 physical contacts within different populations. 00:13:45.474 --> 00:13:47.879 But what we are doing is scaling the risk. 00:13:47.903 --> 00:13:50.212 So that's coming on to the T term. 00:13:50.236 --> 00:13:52.474 So that between each contact, 00:13:52.498 --> 00:13:55.347 what's the risk that a transmission event will occur. NOTE Paragraph 00:13:55.371 --> 00:13:57.620 CA: Alright, so let's go on to this next number, 00:13:57.644 --> 00:14:00.299 the T, transmission probability. 00:14:00.323 --> 00:14:01.982 How do you define that? NOTE Paragraph 00:14:02.006 --> 00:14:04.609 AK: So this measures the chance 00:14:04.633 --> 00:14:07.212 that, essentially, the virus will get across 00:14:07.236 --> 00:14:10.110 during a particular opportunity or a particular interaction. 00:14:10.134 --> 00:14:13.120 So you may well have a conversation with somebody, 00:14:13.144 --> 00:14:16.573 but actually, you don't cough or you don't sneeze 00:14:16.597 --> 00:14:19.295 or for some reason, the virus doesn't actually get across 00:14:19.319 --> 00:14:20.969 and expose the other person. 00:14:20.993 --> 00:14:23.794 And so, for this virus, as I mentioned, 00:14:23.818 --> 00:14:25.929 say people are having 10 conversations a day, 00:14:25.953 --> 00:14:28.810 but we're not seeing infected people infect 10 others a day. 00:14:28.834 --> 00:14:31.254 So it suggests that not all of those opportunities 00:14:31.278 --> 00:14:33.710 are actually resulting in the virus getting across. NOTE Paragraph 00:14:34.540 --> 00:14:38.921 CA: But people say that this is an infectious virus. 00:14:38.945 --> 00:14:42.452 Like, what is that transmission probability number, 00:14:42.476 --> 00:14:44.407 again, compared with, say, the flu? NOTE Paragraph 00:14:44.858 --> 00:14:48.617 AK: So, we did some analysis looking at these very close gatherings. 00:14:48.641 --> 00:14:51.061 We looked at about 10 different case studies, 00:14:51.085 --> 00:14:54.889 and we found that about a third of the contacts in those settings 00:14:54.913 --> 00:14:56.764 subsequently got infected 00:14:56.788 --> 00:14:59.145 in these early stages, when people weren't aware. 00:14:59.169 --> 00:15:01.440 So if you had these, kind of, big group meals, 00:15:01.464 --> 00:15:05.177 potentially, each contact had about, a kind of, one in three chance 00:15:05.201 --> 00:15:06.558 of getting exposed. 00:15:06.582 --> 00:15:10.189 For seasonal flu, that tends to be slightly lower, 00:15:10.213 --> 00:15:12.323 even within households and close settings, 00:15:12.347 --> 00:15:14.482 you don't necessarily get values that high. 00:15:14.506 --> 00:15:18.366 And even for something like SARS, those values have, kind of -- 00:15:18.390 --> 00:15:21.700 the risk per interaction you had 00:15:21.724 --> 00:15:24.466 was lower than what we seem to be getting for coronavirus. 00:15:24.490 --> 00:15:25.934 Which intuitively makes sense, 00:15:25.958 --> 00:15:28.120 there must be a higher risk per interaction 00:15:28.144 --> 00:15:30.096 if this thing is spreading so easily. NOTE Paragraph 00:15:30.120 --> 00:15:31.270 CA: Hm. 00:15:32.350 --> 00:15:35.904 OK, and then the fourth letter of DOTS 00:15:35.928 --> 00:15:38.482 is S for susceptibility. 00:15:39.873 --> 00:15:41.045 What's that? NOTE Paragraph 00:15:41.069 --> 00:15:45.591 AK: So that is a measure of the proportion of the population who are susceptible. 00:15:45.615 --> 00:15:48.170 If you imagine you have this interaction with someone, 00:15:48.194 --> 00:15:50.381 the virus gets across, it exposes them, 00:15:50.405 --> 00:15:52.350 but some people may have been vaccinated 00:15:52.374 --> 00:15:54.175 or otherwise have some immunity 00:15:54.199 --> 00:15:55.992 and not develop infection themselves 00:15:56.016 --> 00:15:57.776 and not be infectious to others. 00:15:57.800 --> 00:16:01.291 So we've got to account for this potential proportion of people 00:16:01.315 --> 00:16:04.382 who are not actually going to turn into cases themselves. NOTE Paragraph 00:16:06.371 --> 00:16:11.701 CA: And obviously, there's no vaccine yet for this coronavirus, 00:16:11.725 --> 00:16:16.312 nor is anyone, at least initially, immune, as far as we know. 00:16:16.336 --> 00:16:20.360 So are you modeling that susceptibility number pretty high, 00:16:20.384 --> 00:16:22.097 is that part of the issue here? NOTE Paragraph 00:16:22.121 --> 00:16:23.728 AK: Yeah, I think the evidence 00:16:23.752 --> 00:16:26.577 is that this is going to fully susceptible populations, 00:16:26.601 --> 00:16:29.141 and even in areas, for example, like China, 00:16:29.165 --> 00:16:31.093 where there's been a lot of transmission 00:16:31.117 --> 00:16:33.268 but there's been very strong control measures, 00:16:33.292 --> 00:16:35.339 we estimated that up to the end of January, 00:16:35.363 --> 00:16:38.115 probably about 95 percent of Wuhan are still susceptible. 00:16:38.139 --> 00:16:39.816 So there's been a lot of infection, 00:16:39.840 --> 00:16:43.056 but it hasn't really taken much of that component, 00:16:43.080 --> 00:16:46.096 of the DOTS, of those four things that drive transmission. NOTE Paragraph 00:16:47.359 --> 00:16:49.371 CA: And so the way the mathematics works, 00:16:49.395 --> 00:16:55.219 I have to confess, amidst the stress of this whole situation, 00:16:55.243 --> 00:16:58.387 the nerd in me kind of loves the elegance of the mathematics here, 00:16:58.411 --> 00:17:00.822 because I'd never really thought about it this way, 00:17:00.846 --> 00:17:03.546 but you basically just multiply those numbers together 00:17:03.570 --> 00:17:05.509 to get the reproduction number. 00:17:05.533 --> 00:17:06.684 Is that right? NOTE Paragraph 00:17:06.708 --> 00:17:07.890 AK: Exactly, yeah, 00:17:07.914 --> 00:17:10.843 you almost take the path of the infection during transmission 00:17:10.867 --> 00:17:12.374 as you multiply those together, 00:17:12.398 --> 00:17:14.541 and that gives you the number for that virus. NOTE Paragraph 00:17:14.565 --> 00:17:17.781 CA: And so there's just a total logic to that. 00:17:17.805 --> 00:17:20.567 It's the number of days, duration that you're infectious, 00:17:20.591 --> 00:17:23.432 it's the number of people you're seeing on average 00:17:23.456 --> 00:17:26.058 during those days that you have a chance to infect. 00:17:27.188 --> 00:17:32.180 Then you multiply that by the transmission probability, 00:17:32.204 --> 00:17:34.880 is virus getting into them, essentially, 00:17:34.904 --> 00:17:36.752 that's what you mean by crossing over. 00:17:36.776 --> 00:17:38.863 And then by the susceptibility number. 00:17:38.887 --> 00:17:41.948 By the way, what do you think the susceptibility probability is 00:17:41.972 --> 00:17:43.312 for this case? NOTE Paragraph 00:17:43.796 --> 00:17:47.050 AK: I think we have to assume that it's near 100 percent 00:17:47.074 --> 00:17:49.110 in terms of spread, yeah. NOTE Paragraph 00:17:50.133 --> 00:17:52.434 CA: Alright, you multiply those numbers together, 00:17:52.458 --> 00:17:57.454 and right now, it looks like, for this coronavirus, 00:17:57.478 --> 00:18:02.228 that you say two to three is the most plausible current number, 00:18:02.530 --> 00:18:04.663 which implies very rapid growth. NOTE Paragraph 00:18:05.141 --> 00:18:06.308 AK: Exactly. 00:18:06.332 --> 00:18:07.878 In these uncontrolled outbreaks, 00:18:07.902 --> 00:18:10.488 we're seeing now a number of countries in this stage -- 00:18:10.522 --> 00:18:13.533 you are going to get this really rapid growth occurring. NOTE Paragraph 00:18:13.804 --> 00:18:18.638 CA: And so how does that two to three compare with flu? 00:18:18.662 --> 00:18:22.217 And I guess, there's seasonal flu, 00:18:22.241 --> 00:18:23.942 in the winter, when it's spreading, 00:18:23.966 --> 00:18:28.244 and at other times during the year drops well below one 00:18:28.268 --> 00:18:30.403 as a reproduction number, right? 00:18:30.427 --> 00:18:33.093 But what is it during seasonal flu time? NOTE Paragraph 00:18:33.831 --> 00:18:36.045 AK: During the early stage when it's taking off 00:18:36.069 --> 00:18:37.596 at the start of the flu season, 00:18:37.620 --> 00:18:41.736 it's probably, we reckon, somewhere between about maybe 1.2, 1.4. 00:18:41.760 --> 00:18:43.706 So it's not incredibly transmissible, 00:18:43.730 --> 00:18:47.735 if you imagine you do have some immunity in your population from vaccination 00:18:47.759 --> 00:18:48.949 and from other things. 00:18:48.973 --> 00:18:50.560 So it can spread, it's above one, 00:18:50.584 --> 00:18:54.139 but it's not taking off, necessarily, as quickly as the coronavirus is. NOTE Paragraph 00:18:55.020 --> 00:18:58.268 CA: So I want to come back to two of those elements, 00:18:58.292 --> 00:19:00.856 specifically opportunity and transmission probability, 00:19:00.880 --> 00:19:05.553 because those seem to have the most chance to actually do something 00:19:05.577 --> 00:19:07.387 about this infection rate. 00:19:07.411 --> 00:19:08.561 Before we go there, 00:19:08.585 --> 00:19:10.927 let's talk about another key number on this, 00:19:10.951 --> 00:19:13.910 which is the fatality rate. 00:19:13.934 --> 00:19:15.609 First of all, could you define -- 00:19:15.633 --> 00:19:18.410 I think there's two different versions of the fatality rate 00:19:18.434 --> 00:19:20.442 that maybe confuse people. 00:19:20.466 --> 00:19:22.466 Could you define them? NOTE Paragraph 00:19:22.490 --> 00:19:26.584 AK: So the one that we often talk about is what's known as the case fatality rate, 00:19:26.608 --> 00:19:30.482 and that's of the proportion who show up with symptoms as cases, 00:19:30.506 --> 00:19:33.559 what proportion of those will subsequently be fatal. 00:19:34.177 --> 00:19:36.313 And we also sometimes talk about what's known 00:19:36.337 --> 00:19:37.829 as the infection fatality rate, 00:19:37.853 --> 00:19:39.789 which is, of everyone who gets infected, 00:19:39.813 --> 00:19:41.027 regardless of symptoms, 00:19:41.051 --> 00:19:43.736 how many of those infections will subsequently be fatal. 00:19:43.760 --> 00:19:45.866 But most of the values we see kicking around 00:19:45.890 --> 00:19:49.032 are the case fatality rate, or the CFR, as it's sometimes known. NOTE Paragraph 00:19:49.963 --> 00:19:54.032 CA: And so what is that fatality rate for this virus, 00:19:54.056 --> 00:19:57.264 and again, how does that compare with other pathogens? NOTE Paragraph 00:19:57.668 --> 00:20:00.482 AK: So there's a few numbers that have been bouncing around. 00:20:00.506 --> 00:20:04.189 One of the challenges in real time is you often don't see all of your cases, 00:20:04.213 --> 00:20:06.688 you have people symptomatic not being reported. 00:20:06.712 --> 00:20:07.871 You also have a delay. 00:20:07.895 --> 00:20:09.236 If you imagine, for example, 00:20:09.260 --> 00:20:11.815 100 people turn up to a hospital with coronavirus 00:20:11.839 --> 00:20:13.307 and none have died yet, 00:20:13.331 --> 00:20:15.680 that doesn't imply that the fatality rate is zero, 00:20:15.704 --> 00:20:18.569 because you've got to wait to see what might happen to them. 00:20:18.593 --> 00:20:21.482 So when you adjust for that underreporting and delays, 00:20:21.506 --> 00:20:24.601 best estimate for the case fatality is about one percent. 00:20:24.625 --> 00:20:26.729 So about one percent of people with symptoms, 00:20:26.753 --> 00:20:28.133 on average, 00:20:28.157 --> 00:20:29.403 those outcomes are fatal. 00:20:29.427 --> 00:20:32.282 And that's probably about 10 times worse than seasonal flu. NOTE Paragraph 00:20:33.514 --> 00:20:37.174 CA: Yeah, so that's a scary comparison right there, 00:20:37.198 --> 00:20:40.351 given how many people die of flu. 00:20:40.375 --> 00:20:44.844 So when the World Health Organization mentioned a higher number, 00:20:44.868 --> 00:20:47.608 a little while back, of 3.4 percent, 00:20:47.632 --> 00:20:50.331 they were criticized a bit for that. 00:20:50.355 --> 00:20:54.102 Explain why that might have been misleading 00:20:54.126 --> 00:20:57.173 and how to think about it and adjust for that. NOTE Paragraph 00:20:57.197 --> 00:21:00.300 AK: It's incredibly common that people look at these raw numbers, 00:21:00.324 --> 00:21:03.238 they say, "How many deaths are there so far, how many cases," 00:21:03.262 --> 00:21:04.633 and they look at that ratio, 00:21:04.657 --> 00:21:08.141 and even a couple of weeks ago, that number produced a two percent value. 00:21:08.165 --> 00:21:10.791 But if you imagine you have this delay effect, 00:21:10.815 --> 00:21:13.061 then even if you stop all your cases, 00:21:13.085 --> 00:21:15.918 you will still have these kind of fatal outcomes over time, 00:21:15.942 --> 00:21:17.688 so that number will creep up. 00:21:17.712 --> 00:21:21.617 This has occurred in every epidemic from pandemic flu to Ebola, 00:21:21.641 --> 00:21:23.228 we see this again and again. 00:21:23.252 --> 00:21:26.982 And I made the point to a number of people that this number is going to go up, 00:21:27.006 --> 00:21:28.536 because as China's cases slow, 00:21:28.560 --> 00:21:30.220 it will look like it's increasing, 00:21:30.244 --> 00:21:32.694 and that's just kind of a statistical quirk. 00:21:32.718 --> 00:21:35.131 There's nothing really kind of, behind a change, 00:21:35.155 --> 00:21:37.638 there's no mutations or anything going on. NOTE Paragraph 00:21:38.972 --> 00:21:41.940 CA: If I have this right, there are two effects going on. 00:21:41.964 --> 00:21:45.056 One is that the number of fatalities 00:21:45.080 --> 00:21:47.618 from the existing caseload will rise, 00:21:47.642 --> 00:21:51.634 which actually would boost that 3.4 even higher. 00:21:51.658 --> 00:21:55.482 But then you have to offset that against the fact that, apparently, 00:21:55.506 --> 00:21:58.093 huge numbers of cases have just gone undetected 00:21:58.117 --> 00:21:59.579 and that we haven't, 00:21:59.603 --> 00:22:02.025 due to bad testing, 00:22:02.049 --> 00:22:04.589 that the number of fatalities don't -- 00:22:04.613 --> 00:22:07.956 they probably reflect a much larger number of early cases. 00:22:07.980 --> 00:22:09.151 Is that it? NOTE Paragraph 00:22:09.175 --> 00:22:10.349 AK: Exactly. 00:22:10.373 --> 00:22:12.445 So you have one thing pulling the number up 00:22:12.469 --> 00:22:13.926 and one thing pulling it down. 00:22:13.950 --> 00:22:16.243 And it means that on these kind of early values, 00:22:16.267 --> 00:22:18.284 if you actually just adjust for the delay 00:22:18.308 --> 00:22:20.411 and don't think about these unreported cases, 00:22:20.435 --> 00:22:22.873 you start getting really very scary numbers indeed. 00:22:22.897 --> 00:22:24.882 You get up to 20, 30 percent potentially, 00:22:24.906 --> 00:22:26.206 which really doesn't align 00:22:26.230 --> 00:22:29.191 with what we know about this virus in general. NOTE Paragraph 00:22:29.542 --> 00:22:30.874 CA: Alright. 00:22:31.621 --> 00:22:33.137 There's a lot more data in now. 00:22:33.161 --> 00:22:36.781 From your point of view, you think the likely fatality rate, 00:22:36.805 --> 00:22:41.503 at least in the earlier stage of an infection, 00:22:41.527 --> 00:22:43.687 is about two percent? NOTE Paragraph 00:22:44.330 --> 00:22:45.481 AK: I think overall, 00:22:45.505 --> 00:22:48.806 I think we can put something probably in the 0.5 to two percent range, 00:22:48.830 --> 00:22:51.644 and that's on a number of different data sets. 00:22:51.668 --> 00:22:53.668 And that's for people who are symptomatic. 00:22:53.692 --> 00:22:56.736 I think on average, one percent is a good number to work with. NOTE Paragraph 00:22:56.760 --> 00:22:58.301 CA: OK, one percent, 00:22:58.325 --> 00:23:01.370 So flu is often quoted as a tenth of a percent, 00:23:01.394 --> 00:23:06.513 so it's five to 10 times or more more dangerous than flu. 00:23:06.537 --> 00:23:10.006 And that danger is not symmetric across age groups, 00:23:10.030 --> 00:23:11.395 as is well known. 00:23:11.419 --> 00:23:14.466 It primarily affects the elderly. NOTE Paragraph 00:23:14.490 --> 00:23:16.815 AK: Yeah, we've seen that one percent on average, 00:23:16.839 --> 00:23:19.458 but once you start getting into the over 60s, over 70s, 00:23:19.482 --> 00:23:21.323 that number really starts to shoot up. 00:23:21.347 --> 00:23:24.109 I mean, we're estimating potentially in these older groups, 00:23:24.133 --> 00:23:28.879 you're looking at maybe five, 10 percent fatality. 00:23:29.243 --> 00:23:31.013 And then of course, on top of that, 00:23:31.037 --> 00:23:33.656 you've got to add what are going to be the severe cases 00:23:33.680 --> 00:23:35.950 and people are going to require hospitalization. 00:23:35.974 --> 00:23:38.853 And those risks get very large in the older groups indeed. NOTE Paragraph 00:23:41.193 --> 00:23:43.296 CA: Adam, put these numbers together for us. 00:23:43.320 --> 00:23:44.470 In your models, 00:23:44.494 --> 00:23:49.407 if you put together a reproduction rate of two to three 00:23:49.431 --> 00:23:53.548 and a fatality rate of 0.5 percent to one percent 00:23:53.572 --> 00:23:56.062 and you run the simulation, 00:23:56.086 --> 00:23:57.620 what does it look like? NOTE Paragraph 00:23:58.699 --> 00:24:01.517 AK: So if you have this uncontrolled transmission, 00:24:01.541 --> 00:24:04.030 and you have this reproduction number of two or three 00:24:04.054 --> 00:24:05.783 and you don't do anything about it, 00:24:05.807 --> 00:24:07.480 the only way the outbreak ends 00:24:07.504 --> 00:24:11.289 is enough people get it and immunity builds up 00:24:11.313 --> 00:24:15.400 and the outbreak kind of ends on its own. 00:24:15.424 --> 00:24:16.587 And in that case, 00:24:16.611 --> 00:24:19.861 you would expect very large numbers of the population to be infected. 00:24:19.885 --> 00:24:21.449 It's what we see, for example, 00:24:21.473 --> 00:24:24.019 with many other uncontained outbreaks, 00:24:24.043 --> 00:24:26.355 that it essentially burns through the population, 00:24:26.379 --> 00:24:27.856 you get large numbers infected 00:24:27.880 --> 00:24:30.869 and with this kind of fatality rate and hospitalization rate, 00:24:30.893 --> 00:24:35.022 that would really be hugely damaging if that were to occur. 00:24:35.046 --> 00:24:37.252 Certainly at the country level, we're seeing -- 00:24:37.276 --> 00:24:39.133 Italy is a good example at the moment, 00:24:39.157 --> 00:24:41.918 that if you have that early transmission that's undetected, 00:24:41.936 --> 00:24:43.069 that rapid growth, 00:24:43.069 --> 00:24:47.260 you very quickly get to a situation where your health systems are overwhelmed. 00:24:47.284 --> 00:24:50.895 I think one of the nastiest aspects of this virus 00:24:50.919 --> 00:24:55.002 is that because you have the delay between infection and symptoms 00:24:55.026 --> 00:24:57.279 and people showing up in health care, 00:24:57.303 --> 00:24:59.145 if your health system is overwhelmed, 00:24:59.169 --> 00:25:00.382 even on that day, 00:25:00.406 --> 00:25:02.430 if you completely stop transmission, 00:25:02.454 --> 00:25:05.328 you've got all of these people who have already been exposed, 00:25:05.352 --> 00:25:08.260 so you're still going to have cases and severe cases appearing 00:25:08.284 --> 00:25:10.180 for maybe another couple of weeks. 00:25:10.204 --> 00:25:13.149 So it's really this huge accumulation of infection and burden 00:25:13.173 --> 00:25:16.144 that's coming through the system on your population. NOTE Paragraph 00:25:17.497 --> 00:25:19.561 CA: So there's another key number, actually, 00:25:19.585 --> 00:25:24.098 is how does the total case number 00:25:24.122 --> 00:25:27.791 compare to the capacity of a country's health system 00:25:27.815 --> 00:25:30.219 to process that number of cases. 00:25:30.846 --> 00:25:33.014 Presumably that issue makes a huge difference 00:25:33.038 --> 00:25:34.235 to the fatality rate, 00:25:34.259 --> 00:25:37.037 the difference between people coming in with severe illness 00:25:37.061 --> 00:25:40.410 and a health system that's able to respond and one that's overwhelmed. 00:25:40.434 --> 00:25:43.363 The fatality rate is going to be very different at that point. NOTE Paragraph 00:25:43.387 --> 00:25:45.141 AK: If someone requires an ICU bed, 00:25:45.165 --> 00:25:47.816 that's a couple of weeks they're going to require it for 00:25:47.840 --> 00:25:50.331 and you've got more cases coming through the system, 00:25:50.355 --> 00:25:52.045 so it very quickly gets very tough. NOTE Paragraph 00:25:52.069 --> 00:25:54.942 CA: So talk about the difference between containment 00:25:54.966 --> 00:25:56.529 and mitigation. 00:25:56.553 --> 00:25:59.895 These are different terms that we're hearing a lot about. 00:25:59.919 --> 00:26:06.110 In the early stages of the virus, governments are focused on containment. 00:26:06.134 --> 00:26:07.737 What does that mean? NOTE Paragraph 00:26:07.761 --> 00:26:11.467 AK: Containment is this idea that you can focus your effort on control 00:26:11.491 --> 00:26:13.737 very much on the cases and their contacts. 00:26:13.761 --> 00:26:16.467 So you're not causing disruption to the wider population, 00:26:16.491 --> 00:26:19.167 you have a case that comes in, you isolate them, 00:26:19.191 --> 00:26:21.459 you work out who they've come into contact with, 00:26:21.483 --> 00:26:24.550 who's potentially these opportunities for exposure 00:26:24.574 --> 00:26:26.537 and then you can follow up those people, 00:26:26.561 --> 00:26:30.133 maybe quarantine them to make sure that no further transmission happens. 00:26:30.157 --> 00:26:32.680 So it's a very focused, targeted method, 00:26:32.704 --> 00:26:35.304 and for SARS, it worked remarkably well. 00:26:35.982 --> 00:26:37.823 But I think for this infection, 00:26:37.847 --> 00:26:41.397 because some cases are going to be missed or undetected, 00:26:41.421 --> 00:26:44.627 you've really got to be capturing a large chunk of people at risk. 00:26:44.651 --> 00:26:46.153 If a few slip through the net, 00:26:46.177 --> 00:26:48.356 potentially, you're going to get an outbreak. NOTE Paragraph 00:26:48.380 --> 00:26:49.749 CA: Are there any countries 00:26:49.773 --> 00:26:51.855 that have been able to employ this strategy 00:26:51.879 --> 00:26:55.188 and effectively contain the virus? NOTE Paragraph 00:26:55.212 --> 00:26:58.760 AK: So Singapore have been doing a really remarkable job of this 00:26:58.784 --> 00:27:00.324 for the last six weeks or so. 00:27:00.744 --> 00:27:03.157 So as well as some wider measures, 00:27:03.181 --> 00:27:04.903 they've been working incredibly hard 00:27:04.927 --> 00:27:07.482 to trace people who have come into contact. 00:27:08.117 --> 00:27:09.585 Looking at CCTV, 00:27:09.609 --> 00:27:12.569 going through to find out which taxi someone might have gotten, 00:27:12.593 --> 00:27:13.767 who might be at risk -- 00:27:13.791 --> 00:27:15.450 really, really thorough follow-up. 00:27:15.474 --> 00:27:18.656 And for about six weeks, that has kept a lid on transmission. NOTE Paragraph 00:27:19.355 --> 00:27:20.529 CA: So that's amazing. 00:27:20.553 --> 00:27:22.974 So someone comes into the country, 00:27:22.998 --> 00:27:24.553 they test positive -- 00:27:24.577 --> 00:27:27.133 they go to work, and with a massive team, 00:27:27.157 --> 00:27:29.268 and trace everything 00:27:29.292 --> 00:27:31.133 to the level of actually saying, 00:27:31.157 --> 00:27:33.157 "Oh, you don't know what taxi you went in? 00:27:33.181 --> 00:27:34.664 Let us find that out for you." 00:27:34.688 --> 00:27:36.926 And presumably, when they find the taxi driver, 00:27:36.950 --> 00:27:40.344 they then have to try and figure out everyone else who was in that taxi? NOTE Paragraph 00:27:40.368 --> 00:27:43.463 AK: So they will focus on close contacts of people most at risk, 00:27:43.487 --> 00:27:47.327 but they're really minimizing the chance that anyone slips through the net. NOTE Paragraph 00:27:47.925 --> 00:27:51.680 CA: But even in Singapore, if I'm not mistaken, 00:27:51.704 --> 00:27:54.054 numbers started to trend back down to zero, 00:27:54.078 --> 00:27:56.522 but I think recently, they've picked up again a bit. 00:27:56.546 --> 00:27:58.435 It's still unclear 00:27:58.459 --> 00:28:01.617 whether they will actually be able to sustain containment. NOTE Paragraph 00:28:01.641 --> 00:28:02.801 AK: Exactly. 00:28:02.825 --> 00:28:05.029 If we talk in terms of the reproduction number, 00:28:05.053 --> 00:28:07.443 we saw it dipped to maybe 0.8, 0.9, 00:28:07.467 --> 00:28:09.402 so under that crucial value of one. 00:28:10.201 --> 00:28:11.550 But in the last week or two, 00:28:11.550 --> 00:28:14.876 it does seem to be ticking up and they're getting more cases appearing. 00:28:14.900 --> 00:28:16.138 I think a lot of it is, 00:28:16.162 --> 00:28:18.130 even if they are containing it, 00:28:18.154 --> 00:28:20.065 the world is experiencing outbreaks 00:28:20.089 --> 00:28:22.157 and just keeps throwing sparks of infection, 00:28:22.181 --> 00:28:23.760 and it becomes harder and harder 00:28:23.784 --> 00:28:26.522 with that level of intensive effort to stamp them all out. NOTE Paragraph 00:28:26.546 --> 00:28:32.349 (Music) NOTE Paragraph 00:28:47.712 --> 00:28:49.578 CA: In the case of this virus, 00:28:49.602 --> 00:28:52.688 you know, there was warning to most countries in the world 00:28:52.712 --> 00:28:54.172 that this thing was happening. 00:28:54.196 --> 00:28:58.380 The news out of China very quickly became very bleak, 00:28:58.404 --> 00:29:01.118 and people had time to prepare. 00:29:01.142 --> 00:29:05.630 I mean, what would ideal preparation look like 00:29:05.654 --> 00:29:07.805 if you know that something like this is coming 00:29:07.829 --> 00:29:09.832 and you know that there's a lot on the line 00:29:09.856 --> 00:29:12.807 if you can successfully contain it before it really escapes? NOTE Paragraph 00:29:13.291 --> 00:29:16.022 AK: I think two things would make a really big difference. 00:29:16.046 --> 00:29:20.767 One is having as thorough a follow-up and detection as possible. 00:29:20.791 --> 00:29:22.416 We've done some modeling analyses, 00:29:22.440 --> 00:29:25.529 looking at how effective that kind of early containment is. 00:29:25.553 --> 00:29:29.671 And it can be, if you're identifying maybe 70 or 80 percent 00:29:29.695 --> 00:29:32.799 of the people who might have come into contact. 00:29:32.823 --> 00:29:36.348 But if you're not detecting those cases coming in, 00:29:36.372 --> 00:29:38.368 if you're not detecting their contacts -- 00:29:38.392 --> 00:29:41.948 and a lot of the early focus, for example, was on travel history to China, 00:29:41.972 --> 00:29:44.669 and then it became clear that the situation was changing, 00:29:44.693 --> 00:29:47.852 but because you were relying on that as your definition of a case, 00:29:47.876 --> 00:29:50.860 it meant a lot of maybe other cases that matched the definition 00:29:50.884 --> 00:29:52.051 weren't being tested 00:29:52.075 --> 00:29:54.617 because they didn't seem to be potentially at risk. NOTE Paragraph 00:29:54.641 --> 00:29:59.227 CA: So I mean, if you know that early detection is key to this, 00:29:59.251 --> 00:30:01.131 an essential early measure, I guess, 00:30:01.155 --> 00:30:06.268 would be to rapidly ensure that you had enough tests available 00:30:06.292 --> 00:30:07.990 and where needed, 00:30:08.014 --> 00:30:09.783 so that you could respond, 00:30:09.807 --> 00:30:13.720 be ready to swing into action as soon as someone was detected, 00:30:13.744 --> 00:30:19.029 you then have to very quickly, I guess, test their contacts and so forth, 00:30:19.053 --> 00:30:21.910 to have a chance of keeping this under control. NOTE Paragraph 00:30:21.934 --> 00:30:23.220 AK: Exactly. 00:30:23.244 --> 00:30:26.410 In my line of work, we say there's value in a negative test, 00:30:26.434 --> 00:30:29.760 because it shows that you're looking for something and it's not there. 00:30:29.784 --> 00:30:33.283 And so I think having small numbers of people tested 00:30:33.307 --> 00:30:36.315 doesn't give you confidence that you're not missing infections, 00:30:36.339 --> 00:30:39.308 whereas if you are doing really thorough follow-up on contacts, 00:30:39.332 --> 00:30:41.316 we've seen countries even like Korea now, 00:30:41.340 --> 00:30:42.901 huge numbers of people tested. 00:30:42.925 --> 00:30:45.013 So although there are still cases appearing, 00:30:45.037 --> 00:30:46.426 it gives them more confidence 00:30:46.450 --> 00:30:49.241 that they have some sense of where those infections are. NOTE Paragraph 00:30:49.265 --> 00:30:51.963 CA: I mean, you're in the UK right now, 00:30:51.987 --> 00:30:54.767 I'm in the US. 00:30:54.791 --> 00:30:58.368 How likely is it that the UK is going to be able to contain, 00:30:58.392 --> 00:31:02.194 how likely is it that the US is going to be able to contain this? NOTE Paragraph 00:31:03.162 --> 00:31:06.625 AK: I think it's pretty unlikely in both cases. 00:31:06.649 --> 00:31:10.051 I think the UK is going to have to introduce some additional measures. 00:31:10.075 --> 00:31:12.410 I think when that happens obviously depends a bit 00:31:12.434 --> 00:31:13.656 on the current situation, 00:31:13.680 --> 00:31:16.013 but we've tested almost 30,000 people now. 00:31:17.403 --> 00:31:21.735 Frankly, I think the US may well be moving beyond that point, 00:31:21.759 --> 00:31:24.688 given how much evidence of extensive transmission that has, 00:31:24.712 --> 00:31:27.808 and I think without clear ideas of how much infection there is 00:31:27.832 --> 00:31:30.103 and that level of testing, 00:31:30.127 --> 00:31:33.516 it's quite hard to actually see what the picture currently is in the US. NOTE Paragraph 00:31:35.308 --> 00:31:39.028 CA: I mean, I definitely don't want to get too political about this, 00:31:39.052 --> 00:31:40.894 but I mean, does this strike you as -- 00:31:40.918 --> 00:31:43.441 you just said that the UK has tested 30,000 people -- 00:31:43.465 --> 00:31:45.964 the US is five or six times bigger 00:31:45.988 --> 00:31:49.181 and I think the total number of tests here is five or six thousand, 00:31:49.205 --> 00:31:50.458 or it was a few days ago. 00:31:50.482 --> 00:31:52.673 Does that strike you as bizarre? 00:31:52.697 --> 00:31:56.644 I don't understand, honestly, how that happened in an educated country 00:31:56.668 --> 00:31:59.460 that has so much knowledge about infectious diseases. NOTE Paragraph 00:32:00.173 --> 00:32:01.340 AK: It does, 00:32:01.364 --> 00:32:04.542 and I think there's obviously a number of factors playing in there, 00:32:04.566 --> 00:32:05.891 logistics and so on, 00:32:05.915 --> 00:32:08.109 but there has been that period of warning 00:32:08.133 --> 00:32:10.212 that this is a threat and this is coming in. 00:32:10.236 --> 00:32:13.561 And I think countries need to make sure that they've got the capacity 00:32:13.585 --> 00:32:16.697 to really do as much detection as they can in those early stages, 00:32:16.721 --> 00:32:18.871 because that's where you're going to catch it 00:32:18.895 --> 00:32:22.450 and that's where you're going to have a better chance of containing it. NOTE Paragraph 00:32:22.474 --> 00:32:24.752 CA: OK, so if you fail to contain, 00:32:24.776 --> 00:32:28.090 then you have to move to some kind of mitigation strategy. 00:32:28.114 --> 00:32:31.495 So what comes into play there? 00:32:31.519 --> 00:32:34.574 And I think I almost want to bring that back 00:32:34.598 --> 00:32:38.419 to two of your DOTS factors, 00:32:38.443 --> 00:32:41.443 opportunity and transmission probability, 00:32:41.467 --> 00:32:43.720 because it seems like the virus is what it is, 00:32:43.744 --> 00:32:46.506 the actual duration when someone is potentially infectious, 00:32:46.530 --> 00:32:47.764 we can't do much about. 00:32:47.788 --> 00:32:49.879 The susceptibility side, 00:32:49.903 --> 00:32:52.505 we can't do much about until there's a vaccine. 00:32:52.529 --> 00:32:54.760 We could maybe talk about that in a bit. 00:32:54.784 --> 00:32:58.451 But the middle two of opportunity and transmission probability, 00:32:58.475 --> 00:32:59.871 we can do something about. 00:32:59.895 --> 00:33:03.418 Do you want to maybe talk about those in turn, 00:33:03.442 --> 00:33:04.665 of what that looks like, 00:33:04.689 --> 00:33:09.273 how would you build a mitigation strategy? 00:33:09.297 --> 00:33:11.623 I mean, first of all, thinking about opportunity, 00:33:11.647 --> 00:33:13.781 how do you reduce the number of opportunities 00:33:13.805 --> 00:33:15.072 to pass on the bug? NOTE Paragraph 00:33:15.885 --> 00:33:17.643 AK: And so I think in that respect, 00:33:17.667 --> 00:33:21.328 it would be about massive changes in our social interactions. 00:33:21.352 --> 00:33:23.877 And if you think in terms of the reproduction number 00:33:23.901 --> 00:33:26.068 of being about two or three, 00:33:26.092 --> 00:33:27.473 to get that number below one, 00:33:27.497 --> 00:33:30.763 you've really got to cut some aspect of that transmission 00:33:30.787 --> 00:33:32.192 in half or in two-thirds 00:33:32.216 --> 00:33:33.620 to get that below one. 00:33:34.017 --> 00:33:35.747 And so that would require, 00:33:35.771 --> 00:33:38.128 of the opportunities that could spread the virus, 00:33:38.152 --> 00:33:40.101 so these kind of close contacts, 00:33:40.125 --> 00:33:42.379 everybody in the population, on average, 00:33:42.403 --> 00:33:45.323 will be needing to reduce those interactions 00:33:45.347 --> 00:33:47.966 potentially by two-thirds to bring it under control. 00:33:47.990 --> 00:33:50.704 That might be through working from home, 00:33:50.728 --> 00:33:52.735 from changing lifestyle 00:33:52.759 --> 00:33:56.102 and kind of where you go in crowded places and dinners. 00:33:56.653 --> 00:33:59.490 And of course, these measures, things like school closures, 00:33:59.514 --> 00:34:01.577 and other things that just attempt to reduce 00:34:01.601 --> 00:34:03.386 the social mixing of a population. NOTE Paragraph 00:34:03.712 --> 00:34:06.513 CA: Well, actually, talk to me more about school closures, 00:34:06.537 --> 00:34:08.934 because that, if I remember, 00:34:08.958 --> 00:34:15.307 often in past pandemics has been cited as an absolutely key measure, 00:34:15.331 --> 00:34:18.597 that schools represent this sort of coming together of people, 00:34:18.621 --> 00:34:21.454 children are often -- 00:34:21.478 --> 00:34:23.601 certainly when it comes to flu and colds -- 00:34:23.615 --> 00:34:25.425 they're carriers. 00:34:25.569 --> 00:34:27.188 But on this case, 00:34:27.212 --> 00:34:31.093 children don't seem to be getting sick from this particular virus, 00:34:31.117 --> 00:34:33.958 or at least very few of them are. 00:34:34.371 --> 00:34:39.301 Do we know whether they can still be infectious? 00:34:39.325 --> 00:34:41.896 They can be the unintended carriers of it. 00:34:41.920 --> 00:34:45.342 Or actually, is there evidence that school closures 00:34:45.366 --> 00:34:48.659 may not be as important in this instance as it is in others? NOTE Paragraph 00:34:49.093 --> 00:34:51.156 AK: So that point on what role children play 00:34:51.180 --> 00:34:52.339 is a crucial one, 00:34:52.363 --> 00:34:54.680 and there's still not a good evidence base there. 00:34:54.704 --> 00:34:56.942 From following up of contacts of cases, 00:34:56.966 --> 00:34:59.617 there's now evidence that children are getting infected, 00:34:59.641 --> 00:35:01.974 so when you're testing, they are getting exposed, 00:35:01.998 --> 00:35:05.629 it's not that somehow they're just not getting the infection at all, 00:35:05.653 --> 00:35:09.117 but as you said, they're not showing symptoms in the same way. 00:35:09.141 --> 00:35:11.445 And particularly for flu, 00:35:11.469 --> 00:35:14.201 when we see the implications of school closures, 00:35:14.225 --> 00:35:17.120 even in the UK in 2009 during swine flu, 00:35:17.144 --> 00:35:19.954 there was a dip in the outbreak during the school holidays, 00:35:19.978 --> 00:35:21.883 you could see it on the epidemic curve, 00:35:21.907 --> 00:35:25.319 it kind of comes back down in the summer and goes back up in the autumn. 00:35:25.343 --> 00:35:28.403 But of course, in 2009, there was some immunity in older groups. 00:35:28.427 --> 00:35:31.537 That kind of shifted more the transmission into the younger ones. 00:35:31.561 --> 00:35:34.832 So I think it's really something we're trying to work to understand. 00:35:34.856 --> 00:35:37.733 Obviously, it will reduce interactions, with school closures, 00:35:37.757 --> 00:35:39.749 but then there's knock-on social effects, 00:35:39.773 --> 00:35:41.876 there's potential knock-on changes in mixing, 00:35:41.900 --> 00:35:45.743 maybe grandparents and their role, in terms of alternative carers 00:35:45.767 --> 00:35:47.109 if parents have to work. 00:35:47.133 --> 00:35:50.720 So I think there's a lot of pieces that need to be considered. NOTE Paragraph 00:35:52.101 --> 00:35:56.865 CA: I mean, based on all of the different pieces of evidence you've seen, 00:35:56.889 --> 00:35:58.166 if it were down to you, 00:35:58.190 --> 00:36:01.579 would you be recommending that most countries at this point 00:36:01.603 --> 00:36:05.878 do look hard at extensive school closures as a precautionary measure, 00:36:05.902 --> 00:36:09.458 that it's just worth it to do that 00:36:09.482 --> 00:36:14.504 as a sort of painful two, three, four, five-month strategy? 00:36:14.528 --> 00:36:16.163 What would you recommend? NOTE Paragraph 00:36:16.187 --> 00:36:17.505 AK: I think the key thing, 00:36:17.529 --> 00:36:20.684 given the age distribution of risk and the severity in older groups 00:36:20.708 --> 00:36:25.489 is reduce interactions that bring the infection into those groups. 00:36:25.513 --> 00:36:28.975 And then amongst everyone else, reduce interactions as much as possible. 00:36:28.999 --> 00:36:30.602 I think the key thing is 00:36:30.626 --> 00:36:34.473 we've got so much of the disease burden in the kind of 60-plus group 00:36:34.497 --> 00:36:37.990 that it's not just about everyone trying to avoid 00:36:38.014 --> 00:36:39.180 everyone's interactions, 00:36:39.204 --> 00:36:40.680 but it's the kind of behaviors 00:36:40.704 --> 00:36:43.147 that would drive infections into those groups. NOTE Paragraph 00:36:44.448 --> 00:36:47.264 CA: Does that mean that people should think twice 00:36:47.288 --> 00:36:50.464 before, I don't know, visiting a loved one 00:36:50.488 --> 00:36:55.454 in an old people's home or in a residential facility? 00:36:55.478 --> 00:36:59.281 Like that, we should just pay super special attention to that, 00:36:59.305 --> 00:37:02.155 should all these facilities be taking great care 00:37:02.179 --> 00:37:03.630 about who they admit, 00:37:03.654 --> 00:37:06.910 taking temperature and checking for symptoms or something like that? NOTE Paragraph 00:37:06.934 --> 00:37:09.832 AK: I think those measures definitely need to be considered. 00:37:09.856 --> 00:37:11.387 In the UK, we're getting plans 00:37:11.411 --> 00:37:13.863 for potentially what's known as a cocooning strategy 00:37:13.887 --> 00:37:15.172 for these older groups 00:37:15.196 --> 00:37:17.810 that we can really try and seal off interactions 00:37:17.834 --> 00:37:19.212 as much as possible 00:37:19.236 --> 00:37:21.847 from people who might be bringing infection in. 00:37:22.202 --> 00:37:24.879 And ultimately, because as you said, 00:37:24.903 --> 00:37:27.371 we can't target these other aspects of transmission, 00:37:27.395 --> 00:37:30.331 it is just reducing the risk of exposure in these groups, 00:37:30.355 --> 00:37:34.099 and so I think anything at the individual level you can do 00:37:34.123 --> 00:37:36.321 to get people reducing their risk, 00:37:36.345 --> 00:37:39.385 if either they're elderly or in other risk groups, 00:37:39.409 --> 00:37:40.561 I think is crucial. 00:37:40.585 --> 00:37:43.020 And I think more at the general level 00:37:43.044 --> 00:37:47.077 those kind of more large-scale measures can help reduce interactions overall, 00:37:47.101 --> 00:37:49.696 but I think if those reductions are happening 00:37:49.720 --> 00:37:50.955 and not reducing the risk 00:37:50.979 --> 00:37:53.244 for people who are going to get severe disease, 00:37:53.268 --> 00:37:56.912 then you're still going to get this really remarkably severe burden. NOTE Paragraph 00:37:58.107 --> 00:38:03.361 CA: I mean, do people have to almost apply this double lens 00:38:03.385 --> 00:38:04.901 as they think about this stuff? 00:38:04.925 --> 00:38:07.292 There's the risk to you as you go about your life, 00:38:07.316 --> 00:38:09.348 of you catching this bug. 00:38:09.657 --> 00:38:12.839 But there's also the risk of you being, unintentionally, a carrier 00:38:12.863 --> 00:38:15.897 to someone who would suffer much more than you might. 00:38:15.921 --> 00:38:19.569 And that both those things have to be top of mind right now. NOTE Paragraph 00:38:19.593 --> 00:38:22.204 AK: Yeah, and it's not just whose hand you shake, 00:38:22.228 --> 00:38:24.434 it's whose hand that person goes on to shake. 00:38:24.458 --> 00:38:27.323 And I think we need to think about these second-degree steps, 00:38:27.347 --> 00:38:29.529 that you might think you have low risk 00:38:29.553 --> 00:38:31.331 and you're in a younger group, 00:38:31.355 --> 00:38:34.450 but you're often going to be a very short step away 00:38:34.474 --> 00:38:37.077 from someone who is going to get hit very hard by this. 00:38:37.101 --> 00:38:39.744 And I think we really need to be socially minded 00:38:39.768 --> 00:38:43.082 and think this could be quite dramatic in terms of change of behavior, 00:38:43.106 --> 00:38:44.765 but it needs to be 00:38:44.789 --> 00:38:47.238 to reduce the impact that we're potentially facing. NOTE Paragraph 00:38:48.556 --> 00:38:51.135 CA: So the opportunity number, we bring down 00:38:51.159 --> 00:38:53.805 by just reducing the number of physical contacts we have 00:38:53.829 --> 00:38:55.532 with other people. 00:38:55.556 --> 00:38:58.810 And I guess the transmission probability number, 00:38:58.834 --> 00:39:01.334 how do we bring that down? 00:39:01.358 --> 00:39:03.188 That impacts how we interact. 00:39:03.212 --> 00:39:04.558 You mentioned hand-shaking, 00:39:04.582 --> 00:39:06.876 I'm guessing you're going to say no handshaking. NOTE Paragraph 00:39:06.900 --> 00:39:08.910 AK: Yeah, so changes like that. 00:39:08.934 --> 00:39:10.341 I mean, another one, I think, 00:39:10.365 --> 00:39:12.026 handwashing operates in a way 00:39:12.050 --> 00:39:16.363 that we might be still be doing activities that we've previously done, 00:39:16.387 --> 00:39:20.601 but handwashing reduces the chance that from one interaction to another, 00:39:20.625 --> 00:39:22.172 we might be spreading infection, 00:39:22.196 --> 00:39:23.633 so it's all of these measures 00:39:23.657 --> 00:39:26.338 that mean that even if we're having these exposures, 00:39:26.362 --> 00:39:29.655 we're taking additional steps to avoid any transmission happening. NOTE Paragraph 00:39:30.346 --> 00:39:32.822 CA: I still think most people don't fully understand 00:39:32.846 --> 00:39:34.886 or don't have a clear model of the pathway 00:39:34.910 --> 00:39:38.886 by which this thing spreads. 00:39:38.910 --> 00:39:40.879 So you think definitely people understand 00:39:40.903 --> 00:39:42.664 that you don't breathe in 00:39:42.688 --> 00:39:46.941 the water droplets of someone who has just coughed or sneezed. 00:39:46.965 --> 00:39:49.117 So how does it spread? 00:39:49.141 --> 00:39:51.403 It gets onto surfaces. How? 00:39:51.427 --> 00:39:54.586 Do people just breathe out and it goes on from people who are sick, 00:39:54.610 --> 00:39:56.784 they touch their mouth or something like that, 00:39:56.808 --> 00:39:59.110 and then touch a surface and it gets on that way? 00:39:59.134 --> 00:40:01.022 How does it actually get onto surfaces? NOTE Paragraph 00:40:01.046 --> 00:40:03.864 AK: I think a lot of it would be that you cough in your hand 00:40:03.888 --> 00:40:05.497 and it ends up on a surface. 00:40:05.871 --> 00:40:09.565 But I think the challenge, obviously, is untangling these questions 00:40:09.589 --> 00:40:10.947 of how transmission happens. 00:40:10.971 --> 00:40:12.789 You have transmission in a household, 00:40:12.813 --> 00:40:15.403 and is it that someone coughed and it got on a surface, 00:40:15.427 --> 00:40:17.332 is it direct contact, is it a handshake, 00:40:17.356 --> 00:40:18.779 and even for things like flu, 00:40:18.803 --> 00:40:22.014 that's something that we work quite hard to try and unpick, 00:40:22.038 --> 00:40:25.250 how does social behavior correspond to infection risk. 00:40:25.274 --> 00:40:28.537 Because it's clearly important, but pinning it down is really tough. NOTE Paragraph 00:40:29.228 --> 00:40:32.442 CA: It's almost like embracing the fact 00:40:32.466 --> 00:40:34.990 that for a lot of these things, we actually don't know 00:40:35.014 --> 00:40:38.855 and that we're all in this game of probabilities. 00:40:39.156 --> 00:40:42.117 Which, in a way, is why I think the math is so important here. 00:40:42.141 --> 00:40:48.148 That you have to think of this as these multiple numbers 00:40:48.172 --> 00:40:49.887 working together on each other, 00:40:49.911 --> 00:40:51.545 they all have their part to play. 00:40:51.569 --> 00:40:56.562 And any of them that you can take down by a percentage 00:40:56.586 --> 00:40:58.062 is likely contributing, 00:40:58.086 --> 00:41:00.807 not just to you but to everyone. 00:41:00.831 --> 00:41:04.609 And people don't actually know in detail how the numbers go together, 00:41:04.633 --> 00:41:06.728 but they know that they probably all matter. 00:41:06.752 --> 00:41:11.664 We almost need people to, somehow, you know, embrace that uncertainty 00:41:11.688 --> 00:41:16.799 and then try to get some satisfaction by acting on every single part of it. NOTE Paragraph 00:41:16.823 --> 00:41:18.085 AK: I think it's this idea 00:41:18.109 --> 00:41:21.797 that if on average, you're infecting, say, three people, 00:41:21.821 --> 00:41:24.695 what's driving that and how can you chip away at that value? 00:41:24.719 --> 00:41:26.123 If you're washing your hands, 00:41:26.147 --> 00:41:29.403 how much might that chip away in terms of the handshakes, 00:41:29.427 --> 00:41:32.006 you know, you may have had virus and you no longer do, 00:41:32.030 --> 00:41:35.744 or if you are changing your social behavior in a certain way, 00:41:35.768 --> 00:41:37.903 is that taking away a couple of interactions, 00:41:37.927 --> 00:41:39.131 is that taking away half? 00:41:39.155 --> 00:41:42.584 How can you really chip into that number as much as you possibly can? NOTE Paragraph 00:41:43.698 --> 00:41:47.203 CA: Is there anything else to say about how we could reduce 00:41:47.227 --> 00:41:51.693 that transmission probability in our interactions? 00:41:51.717 --> 00:41:54.525 Like, what is the physical distance 00:41:54.549 --> 00:42:00.140 that it's wise to stay away from other people if we can? NOTE Paragraph 00:42:00.665 --> 00:42:02.680 AK: I think it's hard to pin down exactly, 00:42:02.704 --> 00:42:06.216 but I think one thing to bear in mind is that there's not so much evidence 00:42:06.240 --> 00:42:08.871 that this is a kind of aerosol and it goes really far -- 00:42:08.895 --> 00:42:10.428 it's reasonably short distances. 00:42:10.452 --> 00:42:11.759 I don't think it's the case 00:42:11.783 --> 00:42:14.846 that you're sitting a few meters away from someone 00:42:14.870 --> 00:42:17.028 and the virus is somehow going to get across. 00:42:17.735 --> 00:42:19.085 It's in closer interactions, 00:42:19.109 --> 00:42:22.096 and it's why we're seeing so many transmission events 00:42:22.120 --> 00:42:25.906 occur in things like meals and really tight-knit groups. 00:42:25.930 --> 00:42:27.271 Because if you imagine 00:42:27.295 --> 00:42:30.310 that's where you can get a virus out and onto surfaces 00:42:30.334 --> 00:42:31.882 and onto hands and onto faces, 00:42:31.906 --> 00:42:36.031 and it's really situations like that we've got to think more about. NOTE Paragraph 00:42:37.818 --> 00:42:39.024 CA: So in a way, 00:42:39.048 --> 00:42:41.993 some of the fears that people have may actually be overstated, 00:42:42.017 --> 00:42:44.720 like, if you're in the middle of an airplane 00:42:44.744 --> 00:42:47.268 and someone at the front sneezes, 00:42:47.292 --> 00:42:49.077 I mean, that's annoying, 00:42:49.101 --> 00:42:53.458 but it's actually not the thing you should be most freaked out about. 00:42:53.482 --> 00:42:57.220 There are much smarter ways to pay attention to your well-being. NOTE Paragraph 00:42:57.244 --> 00:43:00.697 AK: Yeah, if it was measles and the plane was susceptible people, 00:43:00.721 --> 00:43:02.847 you would see a lot of infections after that. 00:43:02.871 --> 00:43:05.395 I think it is, bear in mind, that this is, on average, 00:43:05.419 --> 00:43:07.184 people infecting two or three others, 00:43:07.208 --> 00:43:11.029 so it's not the case of your maybe 50 interactions over a week, 00:43:11.053 --> 00:43:12.982 all of those people are at risk. 00:43:13.006 --> 00:43:14.633 But it's going to be some of them, 00:43:14.657 --> 00:43:16.625 particularly those close contacts, 00:43:16.649 --> 00:43:19.331 that are going to be where transmission's occurring. NOTE Paragraph 00:43:19.355 --> 00:43:21.498 CA: So talk about, 00:43:21.522 --> 00:43:25.632 from a sort of national strategy point of view. 00:43:25.656 --> 00:43:29.863 There's a lot of talk about the need to "flatten the curve." 00:43:29.887 --> 00:43:31.212 What does that mean? NOTE Paragraph 00:43:31.236 --> 00:43:35.946 AK: I think it refers to this idea that for your health systems, 00:43:35.970 --> 00:43:38.641 you don't want all your cases to appear at the same time. 00:43:38.665 --> 00:43:40.712 So if we sat back and did nothing 00:43:40.736 --> 00:43:42.260 and just let the epidemic grow, 00:43:42.284 --> 00:43:44.625 and you had this growth rate that, at the moment, 00:43:44.649 --> 00:43:46.380 in some places is looking like maybe 00:43:46.404 --> 00:43:48.550 three to four days, you're getting doubling. 00:43:48.574 --> 00:43:51.098 So every three or four days, the epidemic is doubling. 00:43:51.122 --> 00:43:52.804 It will skyrocket and you'll end up 00:43:52.828 --> 00:43:55.982 with a whole bunch of really severely ill people 00:43:56.006 --> 00:43:58.042 needing hospital care all at the same time, 00:43:58.066 --> 00:44:00.029 and you just won't have capacity for it. 00:44:00.053 --> 00:44:03.204 So the idea of flattening the curve is if we can slow transmission, 00:44:03.228 --> 00:44:05.276 if we can get that reproduction number down, 00:44:05.300 --> 00:44:07.164 then there may still be an outbreak, 00:44:07.188 --> 00:44:08.545 but it will be much flatter, 00:44:08.569 --> 00:44:09.736 it will be longer 00:44:09.760 --> 00:44:12.054 and there will be fewer severe cases showing up, 00:44:12.078 --> 00:44:14.759 which means that they can get the health care they need. NOTE Paragraph 00:44:16.220 --> 00:44:23.220 CA: Does it imply that there will be fewer cases overall, or -- 00:44:24.323 --> 00:44:26.776 When you look at the actual images of people showing 00:44:26.800 --> 00:44:28.577 what flattening the curve looks like, 00:44:28.601 --> 00:44:31.879 it almost looks as if you've got the same area still under the graph, 00:44:31.903 --> 00:44:34.855 i.e. that the same number of people, ultimately, are infected 00:44:34.879 --> 00:44:37.672 but over a longer period. 00:44:37.696 --> 00:44:40.264 Is that typically what happens, 00:44:40.288 --> 00:44:45.247 and even if you adopt all these strategies of social distancing 00:44:45.271 --> 00:44:49.006 and washing hands and etc. 00:44:49.030 --> 00:44:52.149 that the best you can hope for is that you slow the thing down, 00:44:52.173 --> 00:44:54.910 you actually will get as many people infected in the end? NOTE Paragraph 00:44:54.934 --> 00:44:57.792 AK: Not necessarily -- it depends on the measures that go in. 00:44:57.816 --> 00:45:00.212 There are some measures like, shutting down travel, 00:45:00.236 --> 00:45:03.418 which typically delay the spread rather than reduce it. 00:45:03.442 --> 00:45:05.719 So you're still going to get the same outbreaks, 00:45:05.743 --> 00:45:07.845 but you're stretching out the outbreaks. 00:45:08.338 --> 00:45:09.783 But there are other measures. 00:45:09.807 --> 00:45:11.675 If we talk about reducing interactions, 00:45:11.699 --> 00:45:13.568 if your reproduction number's lower, 00:45:13.592 --> 00:45:15.849 you would expect fewer cases overall. 00:45:16.384 --> 00:45:18.183 And eventually, in your population, 00:45:18.207 --> 00:45:20.111 you will get some buildup of immunity, 00:45:20.135 --> 00:45:22.964 which would help you out if you think about the components, 00:45:22.988 --> 00:45:24.243 reducing susceptibility, 00:45:24.267 --> 00:45:26.553 alongside what's going on elsewhere. 00:45:26.577 --> 00:45:29.164 So the hope is that the two things will work together. NOTE Paragraph 00:45:29.848 --> 00:45:33.727 CA: So help me understand what the endgame is here. 00:45:34.904 --> 00:45:37.117 So, take China, for example. 00:45:38.967 --> 00:45:42.570 Whatever you make of the early suppression of data 00:45:42.594 --> 00:45:43.759 and so forth 00:45:43.783 --> 00:45:47.713 that seems pretty troubling there. 00:45:47.737 --> 00:45:53.426 The intensity of the response come January time or whatever, 00:45:53.450 --> 00:45:57.449 with the shutdown of this huge area of the country, 00:45:57.473 --> 00:45:59.356 seems to have actually been effective. 00:45:59.380 --> 00:46:04.879 The number of cases there are falling at a shockingly high rate in some ways. 00:46:04.903 --> 00:46:06.791 Falling to almost nothing. 00:46:06.815 --> 00:46:09.966 And I can't understand that. 00:46:09.990 --> 00:46:14.115 You are talking about a country of, whatever, 1.4 billion people. 00:46:14.139 --> 00:46:16.242 There have been a huge number of cases there, 00:46:16.266 --> 00:46:19.718 but it was a tiny fraction of the population have actually got sick. 00:46:19.742 --> 00:46:24.613 And yet, they've got the number way down. 00:46:24.637 --> 00:46:29.458 It's not like every other person in China has somehow developed immunity. 00:46:29.482 --> 00:46:33.396 Is it that they have been absolutely disciplined 00:46:33.420 --> 00:46:37.507 about shutting down travel from the infected regions 00:46:37.531 --> 00:46:43.335 and somehow really dialed up, massively dialed up 00:46:43.359 --> 00:46:46.363 testing at any sign of any problem, 00:46:46.387 --> 00:46:50.065 so that literally, they are back in containment mode 00:46:50.089 --> 00:46:52.272 in most parts of China? 00:46:52.296 --> 00:46:55.623 I can't get my head around it, help me understand it. NOTE Paragraph 00:46:55.647 --> 00:46:58.197 AK: So we estimated, in the last two weeks of January, 00:46:58.221 --> 00:46:59.585 when these measures went in, 00:46:59.609 --> 00:47:02.014 the reproduction number went from about 2.4 to 1.1. 00:47:02.038 --> 00:47:04.403 So about 60 percent decline in transmission 00:47:04.427 --> 00:47:06.418 in the space of a week or two. 00:47:06.442 --> 00:47:08.919 Which is remarkable and really, 00:47:08.943 --> 00:47:13.490 a lot of it is likely to be driven by just fundamental change 00:47:13.514 --> 00:47:14.801 in social behavior, 00:47:14.825 --> 00:47:16.262 huge social distancing, 00:47:16.286 --> 00:47:19.055 really intensive follow-up, intensive testing. 00:47:20.166 --> 00:47:21.540 And it got to the point 00:47:21.564 --> 00:47:23.825 where it took enough off the reproduction number 00:47:23.849 --> 00:47:25.053 to cause the decline, 00:47:25.077 --> 00:47:28.166 and now, of course, we're seeing, in many areas, 00:47:28.190 --> 00:47:30.863 a transition back to more of this kind of containment, 00:47:30.887 --> 00:47:33.257 because there's few cases, it's more manageable. 00:47:34.320 --> 00:47:36.493 But we're also seeing them face a challenge, 00:47:36.517 --> 00:47:40.312 because a lot of these cities have basically been locked down 00:47:40.336 --> 00:47:41.507 for six weeks 00:47:41.531 --> 00:47:43.974 and there's a limit to how long you can do that for. 00:47:43.998 --> 00:47:47.164 And so some of these measures are gradually starting to be lifted, 00:47:47.188 --> 00:47:48.806 which of course creates the risk 00:47:48.830 --> 00:47:51.570 that cases that are appearing from other countries 00:47:51.594 --> 00:47:54.708 may subsequently go in and reintroduce transmission. NOTE Paragraph 00:47:57.610 --> 00:48:00.847 CA: But given how infectious the bug is, 00:48:00.871 --> 00:48:05.371 and how many theoretical pathways and connection points there are 00:48:05.395 --> 00:48:09.053 between people in Wuhan, even in shutdown, 00:48:09.077 --> 00:48:10.371 or relatively shut down, 00:48:10.395 --> 00:48:13.323 or the other places where there's been some infection 00:48:13.347 --> 00:48:14.736 and the rest of the country, 00:48:14.760 --> 00:48:21.009 does it surprise you how quickly that curve has gone down to nearly zero? NOTE Paragraph 00:48:21.865 --> 00:48:23.016 AK: Yes. 00:48:23.040 --> 00:48:26.863 Early on when we saw that flattening off in cases 00:48:26.887 --> 00:48:28.696 in those first few days, 00:48:28.720 --> 00:48:32.268 we did wonder whether it was just they hit a limit in testing capacity 00:48:32.292 --> 00:48:34.053 and they were reporting 1,000 a day, 00:48:34.077 --> 00:48:36.109 because that's all the kits they had. 00:48:36.133 --> 00:48:38.371 But it continued, thankfully, 00:48:38.395 --> 00:48:41.490 and it shows that it is possible to turn this over 00:48:41.514 --> 00:48:43.276 with that level of intervention. 00:48:43.300 --> 00:48:46.529 I think the key thing now is seeing how it works in other settings. 00:48:46.553 --> 00:48:51.221 Italy now are putting in really dramatic interventions. 00:48:51.245 --> 00:48:53.293 But of course, because of this delay effect, 00:48:53.317 --> 00:48:54.896 if you put them in today, 00:48:54.920 --> 00:48:57.094 you won't necessarily see the effects on cases 00:48:57.118 --> 00:48:58.277 for another week or two. 00:48:58.301 --> 00:49:00.418 So I think working out what impact that's had 00:49:00.442 --> 00:49:02.649 is going to be key for helping other countries 00:49:02.673 --> 00:49:04.140 work on how to contain this. NOTE Paragraph 00:49:04.711 --> 00:49:06.045 CA: To have a picture, Adam, 00:49:06.069 --> 00:49:09.990 of how this is likely to play out over the next month or two, 00:49:10.014 --> 00:49:13.585 give us a couple of scenarios that are in your head. NOTE Paragraph 00:49:14.560 --> 00:49:17.315 AK: I think the optimistic scenario 00:49:17.339 --> 00:49:20.465 is that we're going to learn a lot from places like Italy 00:49:20.489 --> 00:49:22.532 that have unfortunately been hit very hard. 00:49:22.556 --> 00:49:25.176 And that countries are going to take this very seriously 00:49:25.200 --> 00:49:27.688 and that we're not going to get this continued growth 00:49:27.712 --> 00:49:29.337 that's going to overwhelm totally, 00:49:29.361 --> 00:49:33.138 that we're going to be able to sufficiently slow it down, 00:49:33.162 --> 00:49:35.409 that we are going to get large numbers of cases, 00:49:35.433 --> 00:49:38.210 we're probably going to get a lot of severe cases, 00:49:38.234 --> 00:49:40.035 but that will be more manageable, 00:49:40.059 --> 00:49:41.951 that's the kind of optimistic scenario. 00:49:41.975 --> 00:49:43.260 I think if we have a point 00:49:43.284 --> 00:49:45.674 where countries either don't take this seriously 00:49:45.698 --> 00:49:49.721 or populations don't respond well to control measures 00:49:49.745 --> 00:49:51.389 or it's not detected, 00:49:51.413 --> 00:49:52.696 we could get situations -- 00:49:52.720 --> 00:49:55.387 I think Iran is probably the closest one at the moment -- 00:49:55.411 --> 00:49:58.495 where there's been extensive widespread transmission, 00:49:58.519 --> 00:50:01.480 and by the time it's being responded to, 00:50:01.504 --> 00:50:03.536 those infections are already in the system 00:50:03.560 --> 00:50:06.313 and they are going to turn up as cases and severe illness. 00:50:06.337 --> 00:50:08.202 So I'm hoping we're not at that point, 00:50:08.226 --> 00:50:10.209 but we've certainly got, at the moment, 00:50:10.233 --> 00:50:13.547 potentially about 10 countries on that trajectory 00:50:13.571 --> 00:50:15.799 to have the same outlook as Italy. 00:50:15.823 --> 00:50:18.918 So it's really crucial what happens in the next couple of weeks. NOTE Paragraph 00:50:19.811 --> 00:50:22.302 CA: Is there a real chance that quite a few countries 00:50:22.326 --> 00:50:25.087 end up having, this year, 00:50:25.111 --> 00:50:30.774 substantially more deaths from this virus than from seasonal flu? NOTE Paragraph 00:50:31.942 --> 00:50:34.609 AK: I think for some countries that is likely, yeah. 00:50:34.633 --> 00:50:36.817 I think if control is not possible, 00:50:36.841 --> 00:50:38.759 and we've seen it happen in China, 00:50:38.783 --> 00:50:43.116 but that was really just an unprecedented level of intervention. 00:50:43.140 --> 00:50:45.632 It was really just changing the social fabric. 00:50:45.656 --> 00:50:51.767 I think people, many of us, don't really appreciate, at a glance, 00:50:51.791 --> 00:50:53.022 just what that means, 00:50:53.046 --> 00:50:55.780 to reduce your interactions to that extent. 00:50:55.804 --> 00:50:58.968 I think many countries just simply won't be able to manage that. NOTE Paragraph 00:51:00.769 --> 00:51:03.410 CA: It's almost a challenge to democracies, isn't it -- 00:51:03.434 --> 00:51:07.936 "OK, show us what you can do without that kind of draconian control. 00:51:07.960 --> 00:51:10.065 If you don't like the thought of that, 00:51:10.089 --> 00:51:12.862 come on, citizens, step up, show us what you're capable of, 00:51:12.886 --> 00:51:14.859 show that you can be wise about this 00:51:14.883 --> 00:51:17.450 and smart and self-disciplined, 00:51:17.474 --> 00:51:19.863 and get ahead of the damn bug." NOTE Paragraph 00:51:19.887 --> 00:51:21.291 AK: Yeah. NOTE Paragraph 00:51:21.315 --> 00:51:25.117 CA: I mean, I'm not personally superoptimistic about that, 00:51:25.141 --> 00:51:29.805 because there's such conflicting messaging coming out in so many different places, 00:51:29.829 --> 00:51:35.753 and people don't like to short-term sacrifice. 00:51:35.777 --> 00:51:38.177 I mean, is there almost a case that -- 00:51:38.673 --> 00:51:40.580 I mean, what's your view 00:51:40.604 --> 00:51:43.568 on whether the media has played a helpful role here 00:51:43.592 --> 00:51:44.763 or an unhelpful role? 00:51:44.787 --> 00:51:46.575 Is it actually, in some ways, helpful 00:51:46.599 --> 00:51:50.529 to, if anything, overstate the concern, the fear, 00:51:50.553 --> 00:51:53.212 and actually make people panic a little bit? NOTE Paragraph 00:51:53.236 --> 00:51:55.617 AK: I think it's a really tough balance to strike, 00:51:55.641 --> 00:51:58.133 because of course, early on, if you don't have cases, 00:51:58.157 --> 00:52:01.464 if you don't have any evidence of potential pressure, 00:52:01.488 --> 00:52:05.029 it's very hard to get that message and convince people to take it seriously 00:52:05.053 --> 00:52:06.260 if you're overhyping it. 00:52:06.284 --> 00:52:08.728 But equally, if you're waiting too long, 00:52:08.752 --> 00:52:11.783 and saying it's not a concern yet, we're OK for the moment, 00:52:11.807 --> 00:52:14.207 a lot of people think it's just flu. 00:52:14.553 --> 00:52:17.711 By the time it hits hard, as I've said, 00:52:17.735 --> 00:52:20.855 you're going to have weeks of an overburdened health system, 00:52:20.879 --> 00:52:23.671 because even if you take interventions, 00:52:23.695 --> 00:52:26.531 it's too late to control the infections that have happened. 00:52:26.555 --> 00:52:28.087 So I think it's a fine line, 00:52:28.111 --> 00:52:30.516 and my hope is there is this ramp-up in messaging, 00:52:30.540 --> 00:52:33.015 now people have these tangible examples like Italy, 00:52:33.039 --> 00:52:36.555 where they can see what's going to happen if they don't take it seriously. 00:52:37.038 --> 00:52:39.799 But certainly, of all the diseases I've seen, 00:52:39.823 --> 00:52:42.465 I think many of my colleagues who are much older than me 00:52:42.489 --> 00:52:44.276 and have memories of other outbreaks, 00:52:44.300 --> 00:52:47.752 it's the scariest thing we've seen in terms of the impact it could have, 00:52:47.776 --> 00:52:49.656 and I think we need to respond to that. NOTE Paragraph 00:52:49.680 --> 00:52:52.311 CA: It's the scariest disease you've seen. 00:52:53.042 --> 00:52:54.192 Wow. 00:52:54.216 --> 00:52:58.732 I've got some questions for you from my friends on Twitter. 00:52:58.756 --> 00:53:04.973 Everyone is obviously super exercised about this topic. 00:53:04.997 --> 00:53:06.536 Hypothetically, 00:53:06.560 --> 00:53:09.052 if everyone stayed home for three weeks, 00:53:09.076 --> 00:53:11.791 would that effectively wipe this out? 00:53:11.815 --> 00:53:14.661 Is there a way to socially distance ourselves out of this? NOTE Paragraph 00:53:15.352 --> 00:53:20.296 AK: Yeah, I think in certain countries with reasonably small household sizes, 00:53:20.320 --> 00:53:22.863 I think average in the UK, US is about two and a half, 00:53:22.887 --> 00:53:26.331 so even if you had a round of infection within the household, 00:53:26.355 --> 00:53:28.019 that would probably stamp it out. 00:53:28.043 --> 00:53:29.270 As a secondary benefit, 00:53:29.294 --> 00:53:31.677 you may well stamp out a few other infections, too. 00:53:31.677 --> 00:53:33.358 Measles only circulates in humans, 00:53:33.372 --> 00:53:35.149 so you may have some knock-on effect, 00:53:35.173 --> 00:53:37.529 if, of course, that were ever to be possible. NOTE Paragraph 00:53:37.553 --> 00:53:41.743 CA: I mean, obviously that would be a huge dent to the economy, 00:53:41.767 --> 00:53:46.043 and this is in a way almost, like, one of the underlying challenges here 00:53:46.067 --> 00:53:49.561 is that you can't optimize public policy 00:53:49.585 --> 00:53:54.946 for both economic health and fighting a virus. 00:53:54.970 --> 00:53:57.628 Like, those two things are, to some extent, in conflict, 00:53:57.652 --> 00:54:01.565 or at least, short-term economic health and fighting a virus. 00:54:01.589 --> 00:54:03.565 Those two things are in conflict, right? 00:54:03.589 --> 00:54:06.503 And societies need to pick one. NOTE Paragraph 00:54:06.988 --> 00:54:10.686 AK: It is tough to convince people of that balance, 00:54:10.710 --> 00:54:12.910 the thing we always say of pandemic planning 00:54:12.934 --> 00:54:15.193 is it's cheap to put this stuff in place now -- 00:54:15.217 --> 00:54:17.218 otherwise, you've got to pay for it later. 00:54:18.207 --> 00:54:20.287 But unfortunately, as we've seen with this, 00:54:20.311 --> 00:54:22.849 that a lot of early money for response wasn't there. 00:54:23.341 --> 00:54:26.746 And it's only when it has an impact and when it's going to get expensive 00:54:26.770 --> 00:54:30.725 that people are happy to take that cost on board, it seems. NOTE Paragraph 00:54:31.612 --> 00:54:33.652 CA: OK, some more Twitter questions. 00:54:33.676 --> 00:54:36.438 Will the rising temperature in coming weeks and months 00:54:36.462 --> 00:54:39.215 slow down the COVID-19 spread? NOTE Paragraph 00:54:39.784 --> 00:54:42.109 AK: I haven't seen any convincing evidence 00:54:42.133 --> 00:54:44.490 that there's that strong pattern with temperature, 00:54:44.514 --> 00:54:48.768 and we've seen it for other infections that there is this seasonal pattern, 00:54:48.792 --> 00:54:51.403 but I think the fact we're getting widespread outbreaks 00:54:51.427 --> 00:54:53.895 makes it hard to identify, and of course, 00:54:53.919 --> 00:54:55.355 there's other things going on. 00:54:55.379 --> 00:54:58.506 So even if one country doesn't have as big an outbreak as another, 00:54:58.530 --> 00:55:00.887 that's going to be influenced by control measures, 00:55:00.911 --> 00:55:04.100 by social behavior, by opportunities and these things as well. 00:55:04.124 --> 00:55:07.045 So it would be really reassuring if this was the case, 00:55:07.069 --> 00:55:09.323 but I don't think we can say that just yet. NOTE Paragraph 00:55:10.038 --> 00:55:11.760 CA: Continuing from Twitter, 00:55:11.784 --> 00:55:15.366 I mean, is there a standardized global recommendation 00:55:15.390 --> 00:55:16.571 for all countries 00:55:16.595 --> 00:55:18.365 on how to do this? 00:55:18.389 --> 00:55:19.723 And if not, why not? NOTE Paragraph 00:55:20.628 --> 00:55:23.454 AK: I think that's what people are trying to piece together, 00:55:23.478 --> 00:55:25.039 first in terms of what works. 00:55:25.345 --> 00:55:28.490 It's only really in the last sort of few weeks 00:55:28.514 --> 00:55:31.330 we've got a sense that this thing can be controllable 00:55:31.354 --> 00:55:32.981 with this extent of interventions, 00:55:33.005 --> 00:55:35.864 but of course, not all countries can do what China have done, 00:55:35.888 --> 00:55:37.314 some of these measures 00:55:37.338 --> 00:55:41.077 incur a huge social, economic, psychological burden 00:55:41.101 --> 00:55:42.547 on populations. 00:55:42.925 --> 00:55:44.734 And of course, there's the time limit. 00:55:44.738 --> 00:55:46.734 In China they've had them in for six weeks 00:55:46.744 --> 00:55:48.078 it's tough to maintain that, 00:55:48.122 --> 00:55:49.942 so we need to think of these tradeoffs 00:55:49.966 --> 00:55:52.799 of all the things we can ask people to do, 00:55:52.823 --> 00:55:56.696 what's going to have the most impact on actually reducing the burden. NOTE Paragraph 00:55:57.807 --> 00:55:59.006 CA: Another question: 00:55:59.030 --> 00:56:02.008 How did this happen and is it likely to happen again? NOTE Paragraph 00:56:03.295 --> 00:56:07.544 AK: So it's likely that this originated with the virus that was circling in bats 00:56:07.568 --> 00:56:10.807 and then probably made its way through another species 00:56:10.831 --> 00:56:12.045 into humans somehow, 00:56:12.069 --> 00:56:14.934 there's a lot of bits of evidence around this, 00:56:14.958 --> 00:56:16.910 there's not kind of single, clear story, 00:56:16.934 --> 00:56:18.925 but even for SARS, it took several years 00:56:18.949 --> 00:56:22.253 for genomics to piece together the exact route that it happened. 00:56:22.277 --> 00:56:25.331 But certainly, I think it's plausible that it could happen again. 00:56:25.355 --> 00:56:27.876 Nature is throwing out these viruses constantly. 00:56:28.419 --> 00:56:31.005 Many of them aren't well-adapted to humans, 00:56:31.029 --> 00:56:32.207 don't pick up, 00:56:32.231 --> 00:56:35.437 you know, there may well have been a virus like this a few years ago 00:56:35.461 --> 00:56:37.207 that just happened to infect someone 00:56:37.231 --> 00:56:40.054 who just didn't have any contacts and didn't go any further. 00:56:40.078 --> 00:56:42.046 I think we are going to face these things 00:56:42.070 --> 00:56:44.474 and we need to think about how can we get in early 00:56:44.498 --> 00:56:47.291 at the stage where we're talking small numbers of cases, 00:56:47.315 --> 00:56:49.363 and even something like this is containable, 00:56:49.387 --> 00:56:51.339 rather than the situation we've got now. NOTE Paragraph 00:56:51.363 --> 00:56:53.379 CA: It seems like this isn't the first time 00:56:53.403 --> 00:56:56.709 that a virus seems to have emerged from, like, a wild meat market. 00:56:57.664 --> 00:57:00.346 That's certainly how it happens in the movies. (Laughs) 00:57:00.370 --> 00:57:03.029 And I think China has already taken some steps this time 00:57:03.053 --> 00:57:05.696 to try to crack down on that. 00:57:05.720 --> 00:57:08.505 I guess that's potentially quite a big deal for the future 00:57:08.529 --> 00:57:11.656 if that can be properly maintained. NOTE Paragraph 00:57:11.680 --> 00:57:13.569 AK: It is, and we saw, for example, 00:57:13.593 --> 00:57:15.633 the H7N9 avian flu, 00:57:15.657 --> 00:57:19.759 over the last few years, in 2013, it was a big emerging concern, 00:57:19.783 --> 00:57:21.803 and China made a very extensive response 00:57:21.827 --> 00:57:24.489 in terms of changing how they operate their markets 00:57:24.513 --> 00:57:26.217 and vaccination of birds 00:57:26.241 --> 00:57:29.791 and that seems to have removed that threat. 00:57:29.815 --> 00:57:33.585 So I think these measures can be effective if they're identified early on. NOTE Paragraph 00:57:34.323 --> 00:57:35.847 CA: So talk about vaccinations. 00:57:35.871 --> 00:57:37.744 That's the key measure, I guess, 00:57:37.768 --> 00:57:41.170 to change that susceptibility factor in your equation. 00:57:44.720 --> 00:57:49.053 There's obviously a race on to get these vaccinations out there, 00:57:49.077 --> 00:57:51.687 there are some candidate vaccinations there. 00:57:51.711 --> 00:57:54.047 How do you see that playing out? NOTE Paragraph 00:57:55.099 --> 00:57:58.647 AK: I think there's certainly some promising development happening, 00:57:58.671 --> 00:58:00.686 but I think the timescales of these things 00:58:00.710 --> 00:58:03.797 are really on the order of maybe a year, 18 months 00:58:03.821 --> 00:58:05.728 before these things be widely available. 00:58:05.752 --> 00:58:08.666 Obviously, a vaccine has to go through these stages of trials, 00:58:08.690 --> 00:58:11.125 that takes time, so even if by the end of the year, 00:58:11.149 --> 00:58:13.491 we have something which is viable and works, 00:58:13.515 --> 00:58:16.831 we're still going to see a delay before everyone can get ahold of it. NOTE Paragraph 00:58:16.855 --> 00:58:18.784 CA: So this really puzzles me, actually, 00:58:18.808 --> 00:58:21.760 and I'd love to ask you as a mathematician about this as well. 00:58:21.784 --> 00:58:23.717 There are already several companies 00:58:23.741 --> 00:58:27.745 believing that they have plausible candidate vaccines. 00:58:28.061 --> 00:58:31.839 As you say, the process of testing takes forever. 00:58:32.909 --> 00:58:37.552 Is there a case that we're not thinking about this right 00:58:37.576 --> 00:58:42.553 when we're looking at the way that testing is done 00:58:42.577 --> 00:58:45.279 and that the safety calculations are made? 00:58:45.303 --> 00:58:47.879 Because it's one thing if you're going to introduce 00:58:47.903 --> 00:58:49.471 a brand new drug or something -- 00:58:49.495 --> 00:58:53.681 yes, you want to test to make sure that there are no side effects, 00:58:53.705 --> 00:58:55.125 and that can take a long time 00:58:55.149 --> 00:58:58.482 by the time you've done all the control trials and all the rest of it. 00:58:58.506 --> 00:59:00.482 If there's a global emergency, 00:59:00.506 --> 00:59:02.994 isn't there a case, 00:59:03.018 --> 00:59:04.903 both mathematically and ethically, 00:59:04.927 --> 00:59:07.276 that there should just be a different calculation, 00:59:07.300 --> 00:59:08.744 the question shouldn't be 00:59:08.768 --> 00:59:13.807 "Is there any possible case where this vaccine can do harm," 00:59:13.831 --> 00:59:15.855 the question surely should be, 00:59:15.879 --> 00:59:18.291 "On the net probabilities, 00:59:18.315 --> 00:59:22.188 isn't there a case to roll this out at scale, 00:59:22.212 --> 00:59:27.250 to have a shot at nipping this thing in the bud?" 00:59:27.274 --> 00:59:30.170 I mean, what am I missing in thinking that way? NOTE Paragraph 00:59:30.654 --> 00:59:32.885 AK: I mean, we do see that in other situations, 00:59:32.909 --> 00:59:36.751 for example, the Ebola vaccine in 2015 00:59:36.775 --> 00:59:39.720 showed, within a few months, very promising evidence 00:59:39.744 --> 00:59:44.601 and interim results of the trial in humans 00:59:44.625 --> 00:59:47.180 showed what seemed very high efficacy. 00:59:47.204 --> 00:59:50.434 And even though it hadn't been licensed fully, 00:59:50.458 --> 00:59:53.141 it was employed for what is known as compassionate use 00:59:53.165 --> 00:59:54.680 in subsequent other outbreaks. 00:59:54.704 --> 00:59:56.605 So there are these mechanisms 00:59:56.629 --> 00:59:59.469 where vaccines can be fast-tracked in this way. 00:59:59.934 --> 01:00:03.221 But of course, we're currently in a situation where we have no idea 01:00:03.245 --> 01:00:05.172 if these things will do anything at all. 01:00:05.196 --> 01:00:08.021 So I think we need to accrue enough evidence 01:00:08.045 --> 01:00:10.141 that it could have an impact, 01:00:10.165 --> 01:00:12.566 but obviously, fast-track that as much as possible. NOTE Paragraph 01:00:13.780 --> 01:00:16.946 CA: But the skeptic in me still doesn't fully get this. 01:00:17.439 --> 01:00:19.439 I don't understand 01:00:19.463 --> 01:00:24.786 why there isn't more energy behind bolder thinking on this. 01:00:24.810 --> 01:00:28.252 Everyone seems, despite the overall risk, 01:00:28.276 --> 01:00:31.212 incredibly risk-averse about how to build the response to it. NOTE Paragraph 01:00:31.759 --> 01:00:33.164 AK: So with the caveat that, 01:00:33.188 --> 01:00:35.371 yeah, there's a lot of good questions on this, 01:00:35.395 --> 01:00:37.981 and some of them are slightly outside my wheelhouse, 01:00:38.005 --> 01:00:40.822 but I agree that we need to do more to get timescales out. 01:00:40.846 --> 01:00:42.276 The example I always quote 01:00:42.300 --> 01:00:45.047 is it takes us six months to choose a seasonal flu strain 01:00:45.071 --> 01:00:47.039 and get the vaccines out there to people. 01:00:47.063 --> 01:00:51.085 We always have to try and predict ahead which strains are going to be circulating. 01:00:51.109 --> 01:00:53.228 And that's for something we know how to make 01:00:53.252 --> 01:00:55.367 and has been manufactured for a long time. 01:00:56.212 --> 01:00:58.537 So there is definitely more that needs to be done 01:00:58.561 --> 01:01:00.514 to get these timescales shorter. 01:01:00.538 --> 01:01:02.620 But I think we do have to balance that, 01:01:02.644 --> 01:01:05.788 especially if we're exposing large numbers of people to something 01:01:05.812 --> 01:01:08.081 to make sure that we're confident it's safe 01:01:08.105 --> 01:01:10.930 and that it's going to have some benefit, potentially. NOTE Paragraph 01:01:12.546 --> 01:01:14.903 CA: And so, finally, 01:01:14.927 --> 01:01:18.019 Adam, I guess going into this -- 01:01:18.942 --> 01:01:23.172 There's another set of infectious things happening around the world 01:01:23.196 --> 01:01:24.362 at the same time, 01:01:24.386 --> 01:01:28.124 which is ideas and the communication around this thing. 01:01:28.148 --> 01:01:33.800 They really are two very dynamic, interactive systems of infectiousness -- 01:01:33.824 --> 01:01:36.998 there's some very damaging information out there. 01:01:37.022 --> 01:01:41.829 Is it fair to think of this as battle of credible knowledge and measures 01:01:41.853 --> 01:01:44.045 against the bug, 01:01:44.069 --> 01:01:47.735 and just bad information -- 01:01:47.759 --> 01:01:50.149 You know, part of what we have to think about here 01:01:50.173 --> 01:01:55.022 is how to suppress one set of things and boost the other, actually, 01:01:55.046 --> 01:01:56.705 turbocharge the other. 01:01:56.729 --> 01:01:58.109 How should we think of this? NOTE Paragraph 01:01:58.133 --> 01:02:02.074 AK: I think we can definitely think of it almost as competition for our attention, 01:02:02.098 --> 01:02:03.813 and we see similarly, with diseases, 01:02:03.837 --> 01:02:06.416 you have viruses competing to infect susceptible hosts. 01:02:06.440 --> 01:02:08.227 And I think we're now seeing, 01:02:08.251 --> 01:02:11.331 I guess over the last few years with fake news and misinformation 01:02:11.355 --> 01:02:12.904 and the emergence of awareness, 01:02:12.928 --> 01:02:14.101 more of a transition 01:02:14.125 --> 01:02:16.733 to thinking about how do we reduce that susceptibility 01:02:16.757 --> 01:02:19.391 if we have people that can be in these different states, 01:02:19.415 --> 01:02:21.876 how can we try and preempt better with information. 01:02:21.900 --> 01:02:24.292 I think the challenge for an outbreak is obviously, 01:02:24.316 --> 01:02:26.569 early on, we have very little good information, 01:02:26.593 --> 01:02:30.844 and it's very easy for certainty and confidence to fill that vacuum. 01:02:30.868 --> 01:02:32.971 And so I think that is something -- 01:02:33.320 --> 01:02:36.583 I know platforms are working on how can we get people exposed 01:02:36.607 --> 01:02:38.106 to good information earlier, 01:02:38.130 --> 01:02:40.867 so hopefully protect them against other stuff. NOTE Paragraph 01:02:41.830 --> 01:02:44.410 CA: One of the big unknowns to me in the year ahead -- 01:02:44.434 --> 01:02:47.925 let's say that the year ahead includes many, many more weeks, 01:02:47.949 --> 01:02:49.291 for many people, 01:02:49.315 --> 01:02:52.657 of actually self-isolating. 01:02:52.681 --> 01:02:57.728 Those of us who are lucky enough to have jobs where you can do that. 01:02:57.752 --> 01:02:59.434 You know, staying home. 01:02:59.458 --> 01:03:01.807 By the way, the whole injustice of this situation, 01:03:01.831 --> 01:03:06.291 where so many people can't do that and continue to make a living, 01:03:06.315 --> 01:03:10.331 is, I'm sure, going to be a huge deal in the year ahead 01:03:10.355 --> 01:03:16.122 and if it turns out that death rates are much higher in the latter group 01:03:16.146 --> 01:03:17.502 than in the former group, 01:03:17.526 --> 01:03:19.493 and especially in a country like the US, 01:03:19.517 --> 01:03:22.577 where the latter group doesn't even have proper health insurance 01:03:22.601 --> 01:03:24.326 and so forth. 01:03:25.342 --> 01:03:30.610 That feels like right there, that could just become a huge debate, 01:03:30.634 --> 01:03:33.754 hopefully a huge source of change at some level. NOTE Paragraph 01:03:33.778 --> 01:03:36.084 AK: I think that's an incredibly important point, 01:03:36.108 --> 01:03:37.730 because it's very easy -- 01:03:37.754 --> 01:03:41.164 I similarly have a job where remote working is fairly easy, 01:03:41.188 --> 01:03:44.987 and it's very easy to say we should just stop social interactions, 01:03:45.011 --> 01:03:48.276 but of course, that could have an enormous impact on people 01:03:48.300 --> 01:03:51.100 and the choices and the routine that they can have. 01:03:51.124 --> 01:03:53.299 And I think those do need to be accounted for, 01:03:53.323 --> 01:03:55.705 both now and what the effect is going to look like 01:03:55.729 --> 01:03:57.259 a few months down the line. NOTE Paragraph 01:03:57.283 --> 01:03:58.701 CA: When all's said and done, 01:03:58.725 --> 01:04:03.783 is it fair to say that the world has faced, actually, much graver problems 01:04:03.807 --> 01:04:04.958 in the past, 01:04:04.982 --> 01:04:08.069 that on any scenario, 01:04:08.093 --> 01:04:11.762 it's highly likely that at some point in the next 18 months, let's say, 01:04:11.786 --> 01:04:16.095 a vaccine is there and starts to get wide distribution, 01:04:16.119 --> 01:04:22.101 that we will have learned lots of other ways to manage this problem? 01:04:22.125 --> 01:04:24.257 But at some point, next year probably, 01:04:24.281 --> 01:04:30.412 the world will feel like it's got on top of this 01:04:30.436 --> 01:04:31.839 and can move on. 01:04:31.863 --> 01:04:33.602 Is that likely to be it, 01:04:33.626 --> 01:04:36.990 or is this more likely to be, you know, it escapes, 01:04:37.014 --> 01:04:42.061 it's now an endemic nightmare that every year picks off far more people 01:04:42.085 --> 01:04:44.634 than are picked off by the flu currently. 01:04:44.658 --> 01:04:47.481 What are the likely ways forward, 01:04:47.505 --> 01:04:49.550 just taking a slightly longer-term view? NOTE Paragraph 01:04:49.574 --> 01:04:52.589 AK: I think there's plausible ways you could see all of those 01:04:52.613 --> 01:04:54.204 potentially playing out. 01:04:54.228 --> 01:04:58.838 I think the most plausible is probably that we'll see very rapid growth this year 01:04:58.862 --> 01:05:03.464 and lots of large outbreaks that don't recur, necessarily. 01:05:03.488 --> 01:05:05.638 But there is a potential sequence of events 01:05:05.662 --> 01:05:09.743 that could end up with these kind of multiyear outbreaks in different places 01:05:09.767 --> 01:05:10.925 and reemerging. 01:05:10.949 --> 01:05:12.826 But I think it's likely we'll see 01:05:12.850 --> 01:05:15.701 most transmission concentrated in the next year or so. 01:05:15.725 --> 01:05:18.761 And then, obviously, if there's a vaccine available, 01:05:18.785 --> 01:05:21.338 we can move past this, and hopefully learn from this. 01:05:21.362 --> 01:05:24.554 I think a lot of the countries that responded very strongly to this 01:05:24.578 --> 01:05:26.006 were hit very hard by SARS. 01:05:26.030 --> 01:05:29.156 Singapore, Hong Kong, that really did leave an impact, 01:05:29.180 --> 01:05:31.910 and I think that's something they've drawn on very heavily 01:05:31.934 --> 01:05:33.276 in their response to this. NOTE Paragraph 01:05:33.300 --> 01:05:34.458 CA: Alright. 01:05:34.482 --> 01:05:37.157 So let's wrap up maybe by just encouraging people 01:05:37.181 --> 01:05:39.101 to channel their inner mathematician 01:05:39.125 --> 01:05:44.414 and especially think about the opportunities 01:05:44.438 --> 01:05:48.358 and the transmission probabilities that they can help shift. 01:05:48.382 --> 01:05:52.760 Just remind us of the top three or four or five or six things 01:05:52.784 --> 01:05:54.719 that you would love to see people doing. NOTE Paragraph 01:05:54.743 --> 01:05:57.615 AK: I think at the individual level, just thinking a lot more 01:05:57.639 --> 01:06:00.020 about your interactions and your risk of infection 01:06:00.044 --> 01:06:02.012 and obviously, what gets onto your hands 01:06:02.036 --> 01:06:03.731 and once that gets onto your face, 01:06:03.755 --> 01:06:06.340 and how do you potentially create that risk for others. 01:06:06.364 --> 01:06:09.037 I think also, in terms of interactions, 01:06:09.061 --> 01:06:13.896 with things like handshakes and maybe contacts you don't need to have. 01:06:13.920 --> 01:06:16.697 You know, how can we get those down as much as possible. 01:06:16.721 --> 01:06:19.134 If each person's giving it to two or three others, 01:06:19.158 --> 01:06:22.371 how do we get that number down to one, through our behavior. 01:06:22.395 --> 01:06:26.204 And then it's likely that we'll need some larger-scale interventions 01:06:26.228 --> 01:06:29.169 in terms of gatherings, conferences, 01:06:29.193 --> 01:06:31.827 other things where there's a lot of opportunities 01:06:31.851 --> 01:06:33.220 for transmission. 01:06:33.244 --> 01:06:36.197 And really, I think that combination of that individual level, 01:06:36.221 --> 01:06:39.227 you know, if you're ill or potentially you're going to get ill, 01:06:39.251 --> 01:06:40.519 reducing that risk, 01:06:40.543 --> 01:06:42.146 but then also us working together 01:06:42.170 --> 01:06:44.274 to prevent it getting into those groups who, 01:06:44.298 --> 01:06:46.130 if it continues to be uncontrolled, 01:06:46.154 --> 01:06:48.392 could really hit some people very, very hard. NOTE Paragraph 01:06:49.434 --> 01:06:51.060 CA: Yeah, there's a lot of things 01:06:51.084 --> 01:06:54.299 that we may need to gently let go of for a bit. 01:06:54.323 --> 01:06:58.553 And maybe try to reinvent the best aspects of them. NOTE Paragraph 01:06:59.077 --> 01:07:00.418 Thank you so much. 01:07:00.442 --> 01:07:03.235 If people want to keep up with you, 01:07:03.259 --> 01:07:05.974 first of all, they can follow you on Twitter, for example. 01:07:05.998 --> 01:07:07.347 What's your Twitter handle? NOTE Paragraph 01:07:07.371 --> 01:07:09.990 AK: So @AdamJKucharski, all one word. NOTE Paragraph 01:07:10.014 --> 01:07:12.524 CA: Adam, thank you so much for your time, stay well. NOTE Paragraph 01:07:12.548 --> 01:07:13.928 AK: Thank you. NOTE Paragraph 01:07:13.952 --> 01:07:20.952 (Music) NOTE Paragraph 01:07:29.263 --> 01:07:32.533 CA: Associate professor and TED Fellow Adam Kucharski. 01:07:33.339 --> 01:07:35.934 We'd love to hear what you think of this bonus episode. 01:07:35.958 --> 01:07:38.799 Please tell us by rating and reviewing us in Apple Podcasts 01:07:38.823 --> 01:07:40.757 or your favorite podcast app. 01:07:41.244 --> 01:07:43.217 Those reviews are influential, actually. 01:07:43.241 --> 01:07:44.617 We certainly read every one, 01:07:44.641 --> 01:07:46.791 and truly appreciate your feedback. NOTE Paragraph 01:07:46.815 --> 01:07:48.768 (Music) NOTE Paragraph 01:07:48.792 --> 01:07:52.592 This week's show was produced by Dan O'Donnell at Transmitter Media. 01:07:52.616 --> 01:07:54.647 Our production manager is Roxanne Hai Lash, 01:07:54.671 --> 01:07:56.988 our fact-checker Nicole Bode. 01:07:57.012 --> 01:07:59.290 This episode was mixed by Sam Bair. 01:07:59.314 --> 01:08:01.355 Our theme music is by Allison Layton-Brown. 01:08:01.379 --> 01:08:03.926 Special thanks to my colleague Michelle Quint. NOTE Paragraph 01:08:04.252 --> 01:08:06.473 Thanks for listening to the TED Interview. 01:08:06.497 --> 01:08:07.998 We'll be back later this spring 01:08:08.022 --> 01:08:11.370 with a whole new season's worth of deep dives with great minds. 01:08:11.759 --> 01:08:14.934 I hope you'll enjoy them whether or not life is back to normal. NOTE Paragraph 01:08:15.634 --> 01:08:16.850 I'm Chris Anderson, 01:08:16.874 --> 01:08:18.879 thanks for listening and stay well.