1 00:00:04,110 --> 00:00:19,620 And welcome, everyone. Wherever you are to today's conversation, which is titled 21st Century Technologies for Tackling 21st Century Pandemics. 2 00:00:19,620 --> 00:00:26,940 Thanks for joining us. This event is part of a series of talks organised by the Oxford Martin School called 3 00:00:26,940 --> 00:00:34,590 Building Back Better Lessons and Opportunities from the Cave at 19 Pandemic. 4 00:00:34,590 --> 00:00:42,810 My name is Oliver Pipers. I'm Professor of Evolution and Infectious Diseases at the Department of Zoology at Oxford University, 5 00:00:42,810 --> 00:00:50,440 and I'm also a co-director of the Oxford Martin School Programme on Pandemic Genomics. 6 00:00:50,440 --> 00:00:57,330 I am absolutely delighted to be joined in conversation today by Professor Christophe Fraser. 7 00:00:57,330 --> 00:01:02,940 Cristoff is professor of infectious disease dynamics at the Nuffield Department of Medicine, 8 00:01:02,940 --> 00:01:11,460 and he's a senior group leader in Pathogen Dynamics at Oxford University's Big Data Institute. 9 00:01:11,460 --> 00:01:21,210 Christophe is a world leading expert in infectious disease epidemiology in the mathematical modelling of epidemics and in pathogen genomics. 10 00:01:21,210 --> 00:01:27,240 He originally trained in physics before turning to mathematical biology after his PHC. 11 00:01:27,240 --> 00:01:37,740 And before joining the Big Data Institute at Oxford in 2016, he was a professor of epidemiology at Imperial College London. 12 00:01:37,740 --> 00:01:41,700 Now, Christopher's applied his expertise to numerous epidemics, 13 00:01:41,700 --> 00:01:54,540 including the H1N1 pandemic influenza in 2009 and the West Africa Ebola virus epidemic in 2014, 2016 and more recent years. 14 00:01:54,540 --> 00:02:00,160 His team is particularly focussed on HIV in Africa and Europe. 15 00:02:00,160 --> 00:02:05,020 This year, Cristoff and his team published the first paper that suggested an important role 16 00:02:05,020 --> 00:02:11,500 for contact tracing smartphone apps and controlling the Kofod 19 pandemic. 17 00:02:11,500 --> 00:02:21,220 And he has provided scientific advice to the NHS and Google to support their development of smart phone contact tracing apps. 18 00:02:21,220 --> 00:02:28,600 So before I begin our conversation proper. I have two administrative announcements to make. 19 00:02:28,600 --> 00:02:37,840 For all watchers and listeners. Firstly, there'll be a question and answer session after our conversation. 20 00:02:37,840 --> 00:02:46,030 And if you'd like to ask a question, you need to be watching via crowd cast. 21 00:02:46,030 --> 00:02:53,530 If you click on the ask a question button and that's towards the bottom right hand side of your screen. 22 00:02:53,530 --> 00:03:02,080 You'll be able to add a question there. If you're watching on YouTube, I don't believe there's any way that you're able to feed in a question, 23 00:03:02,080 --> 00:03:05,830 but I hope you enjoy the conversation nonetheless. 24 00:03:05,830 --> 00:03:16,550 And secondly, if you do ask a question, please be aware that this event is being recorded and live streamed. 25 00:03:16,550 --> 00:03:22,160 OK, with the introductions out of the way. Let's begin that conversation. 26 00:03:22,160 --> 00:03:31,130 And, of course, that the pandemic needs no introduction. It's become a defining event of the 20th 21st century. 27 00:03:31,130 --> 00:03:35,420 We've been in a race with a marathon, now with the virus. 28 00:03:35,420 --> 00:03:40,940 So we're trying to trace and prevent transmission faster than they occur. 29 00:03:40,940 --> 00:03:49,620 Some countries and regions have managed to get ahead of the virus, whilst others have struggled to keep up. 30 00:03:49,620 --> 00:03:57,350 And today we'll be discussing whether new modern technologies can provide alternate ways to 31 00:03:57,350 --> 00:04:05,000 understand virus transmission and to get ahead of the virus and control the epidemic spread. 32 00:04:05,000 --> 00:04:14,270 So what are the opportunities and challenges in applying new technologies such as smartphone apps or pandemic at a pathogen genome sequencing? 33 00:04:14,270 --> 00:04:21,950 And can we deploy these tools fast enough to make a real difference to public health? 34 00:04:21,950 --> 00:04:32,120 So to set the scene to begin with, I think it be good to talk about the history of the study of transmission as a scientific pursuit. 35 00:04:32,120 --> 00:04:35,450 So before the current pandemic, 36 00:04:35,450 --> 00:04:45,470 how did we go about understanding where transmission occurred and how it occurred and using that information to control spread? 37 00:04:45,470 --> 00:04:49,280 And there's a number of linked terms here that I think might be useful to introduce, 38 00:04:49,280 --> 00:04:54,830 such as the difference between contact tracing and outbreak investigation. 39 00:04:54,830 --> 00:05:01,250 So what do you think that defining events were in the history of the study of transmission, Christof? 40 00:05:01,250 --> 00:05:01,940 Well, sir, 41 00:05:01,940 --> 00:05:15,250 the most famous outbreak investigation that everybody studies in and introductions to to do epidemiology is is is John Snow in London and Soho, 42 00:05:15,250 --> 00:05:22,730 who is investigating a cholera epidemic, know arranging cholera epidemic. 43 00:05:22,730 --> 00:05:36,310 And he collects data himself around to find out the source where people were were were getting sick from. 44 00:05:36,310 --> 00:05:43,380 And what he found by mapping them out and sort of produced this very beautiful map of of time and space 45 00:05:43,380 --> 00:05:52,150 is showing the cases of the cases where we're very clustered around a single drinking water pump, 46 00:05:52,150 --> 00:05:56,270 the Broad Street pump. And he also found that there was a few unlinked cases. 47 00:05:56,270 --> 00:06:03,590 But when he went to interview people, he found, you know, that the that that the cases that were far away, 48 00:06:03,590 --> 00:06:10,260 people were coming to Broad Street pump because because that's where they they liked the water from. 49 00:06:10,260 --> 00:06:18,490 So so that was a classic outbreak investigation. Well, you you ask a number of people who are suffering from heart disease, you know, 50 00:06:18,490 --> 00:06:25,400 a questionnaire and you look for a common denominator and that common denominator points to it being a source. 51 00:06:25,400 --> 00:06:31,670 So so that's kind of an outbreak investigation, which identifies a common source, which is, you know, 52 00:06:31,670 --> 00:06:39,550 a closed space and time where people have been exposed to infection and acquired infection and went out. 53 00:06:39,550 --> 00:06:46,140 And first, there's sort of one of the later founders of of the study of epidemiology and 54 00:06:46,140 --> 00:06:51,260 who was the head of the U.S. Public Health Service in the 1918 pandemic of, 55 00:06:51,260 --> 00:06:57,570 you know, the famous Spanish flu pandemic. He had systematised John Snow's approach. 56 00:06:57,570 --> 00:07:04,700 So so he would travel around the U.S. sort of investigating what water borne diseases 57 00:07:04,700 --> 00:07:10,550 and he would produce these maps and he would invariably find find their source. 58 00:07:10,550 --> 00:07:21,080 Now, contact tracing is is a little bit different. It's sort of, you know, in the early days of this, what it was done a lot for, for tuberculosis. 59 00:07:21,080 --> 00:07:25,170 And it was done, you know, for for for for cholera in households. 60 00:07:25,170 --> 00:07:29,730 And that was done at actually went home come first, did it in the 1918 flu. 61 00:07:29,730 --> 00:07:36,860 You know, you go around and you look at the cases, you typically see clustering of cases in and households. 62 00:07:36,860 --> 00:07:43,640 And basically the point of that is that if it's people who are in close contact for a period of time, 63 00:07:43,640 --> 00:07:48,140 you might not be able to attribute it to a particular place. 64 00:07:48,140 --> 00:07:50,250 And it may only be a small number of cases. 65 00:07:50,250 --> 00:07:59,330 A contact tracing is about mapping out the contact events that link ball and to break the transmission chains, 66 00:07:59,330 --> 00:08:03,570 typically by by quarantining, quarantining people at home. 67 00:08:03,570 --> 00:08:10,220 But they're kind of linked together because if you imagine, you know, and we saw this a lot in Ebola, 68 00:08:10,220 --> 00:08:14,450 we saw this in this large epidemic, if you imagine a superstar Supersport. 69 00:08:14,450 --> 00:08:19,370 And let's get this president is kind of where contact tracing meets outbreak analysis. 70 00:08:19,370 --> 00:08:23,660 That's a single person, not a single place. You know, it can be in a food market. 71 00:08:23,660 --> 00:08:31,420 It can be in a church. It can be in a concert somewhere where people aggregate and where where essentially. 72 00:08:31,420 --> 00:08:37,130 And a lot of people came into contact with a single person causing causing an outbreak. 73 00:08:37,130 --> 00:08:38,540 So in all cases, 74 00:08:38,540 --> 00:08:48,660 it's about finding the source case and using that to to contain the infection while disrupting as few people as possible in the process. 75 00:08:48,660 --> 00:08:53,180 So in the case of the famous cholera outbreak that John Snow investigated, 76 00:08:53,180 --> 00:09:02,180 there was a fairly direct public health intervention that came from his his identifying the outbreak, which. 77 00:09:02,180 --> 00:09:08,970 Yeah. He removed the Broad Street pump so that people can drink water and people still look at the time series. 78 00:09:08,970 --> 00:09:15,820 And, you know, just as just as we see now, people argue whether it was actually already going down before before he asked the pump. 79 00:09:15,820 --> 00:09:20,420 Yeah. You you hit. That was an ongoing exposure in a place. 80 00:09:20,420 --> 00:09:23,910 And you you you close the Broad Street pump. 81 00:09:23,910 --> 00:09:32,150 And that direct analogue of that was if you look back at the start of this year, the exposure in the food market, 82 00:09:32,150 --> 00:09:36,700 seafood market, and we're hattan, which was the first time that we heard about it. 83 00:09:36,700 --> 00:09:40,670 And it's not where we think Kevin starts. And we think probably. 84 00:09:40,670 --> 00:09:46,710 I mean, you know, you can comment more on on on on the origins from your from your own work. 85 00:09:46,710 --> 00:09:56,140 But we think it started a few weeks before. But in the seafood market, it was a very similar situation to John Broad. 86 00:09:56,140 --> 00:10:00,130 Broadstreet pump is, you know, people were coming to the market. 87 00:10:00,130 --> 00:10:05,420 It had these had these strange symptoms that were showing up in hospital. 88 00:10:05,420 --> 00:10:08,750 And similarly, people went through the question as and what did they have in common? 89 00:10:08,750 --> 00:10:15,380 They all went shopping. And this at the supermarket and the first intervention with closing the seafood market. 90 00:10:15,380 --> 00:10:16,910 And then, of course, now, you know, 91 00:10:16,910 --> 00:10:25,520 we have lots of molecular tools which we're able to say this was a this was a new virus and people were being exposed by contaminated surfaces. 92 00:10:25,520 --> 00:10:30,950 And that's safe at markets. So theoretically, it's exactly the same approach that John Snow took. 93 00:10:30,950 --> 00:10:40,110 So it sounds from what you're saying, there's this sort of continuum and it's contact tracing, an outbreak investigation layer on this continuum. 94 00:10:40,110 --> 00:10:50,270 And for some pathogens, are they better controlled with outbreak investigation or other pathogens better controlled through contact 95 00:10:50,270 --> 00:10:59,450 tracing and other characteristics of pathogens that make them better controlled by either of those two options? 96 00:10:59,450 --> 00:11:08,390 Yes. So I think there are two two really important characteristics which determine, you know, whether you want to focus the contact tracing. 97 00:11:08,390 --> 00:11:15,590 You're really looking at the person and the outbreak investigation. You're looking at the source, which might be a person at that point in time. 98 00:11:15,590 --> 00:11:23,120 But it really depends on the route of transmission and the extent to which you have super spreading. 99 00:11:23,120 --> 00:11:32,630 So if you imagine if you look at it to some extent, all pathogens have surface spreading, but some more so than others. 100 00:11:32,630 --> 00:11:44,120 So. So if you look at flu transmission, the some people, in fact, are more likely to infect others. 101 00:11:44,120 --> 00:11:49,190 Some people are more infectious than others, but it's it's not massively heterogeneous. 102 00:11:49,190 --> 00:11:56,770 I mean, we characterise this in an earlier works, even going back to us on that date of 1999. 103 00:11:56,770 --> 00:12:05,150 We see a very consistent message that it's sort of it's it's close proximity contacts 104 00:12:05,150 --> 00:12:12,680 predominantly through through droplets and aerosols and predominantly three, 105 00:12:12,680 --> 00:12:17,780 three, three children at schools and then children when they come home. 106 00:12:17,780 --> 00:12:28,030 But the that you don't see these really large outbreaks now, you see at the other end of the spectrum, Sovs is somewhere in between. 107 00:12:28,030 --> 00:12:34,430 If you if you look back to 2000, 2003, it kind of causes really big outbreaks. 108 00:12:34,430 --> 00:12:37,120 There was a big outbreak in a hotel in Hong Kong. 109 00:12:37,120 --> 00:12:45,890 Know a couple of hospitals had outbreaks involving 200 people that were, you know, at a single point in time. 110 00:12:45,890 --> 00:12:48,660 There was a block of flats. So it contaminated. 111 00:12:48,660 --> 00:12:56,240 And so that's that's sort of, you know, where you want to be doing both contact tracing and outbreak investigation. 112 00:12:56,240 --> 00:13:00,290 And then you look at sort of the environmental sources of cholera. 113 00:13:00,290 --> 00:13:06,350 So, for example, there was a really big outbreak of cholera in Haiti recently after the earthquake. 114 00:13:06,350 --> 00:13:13,390 And there it was really linking it back to a contamination to get to a source of contamination. 115 00:13:13,390 --> 00:13:22,950 So. You know, something like flu or maybe HIV, you're not going to look for four for places and sources, 116 00:13:22,950 --> 00:13:27,700 you're going to focus on the people cowritten source somewhere in the middle. 117 00:13:27,700 --> 00:13:35,400 And and and Connor probably is it's really focussed on environmental sources safe. 118 00:13:35,400 --> 00:13:48,300 I think both of these are what we might call traditional shoe leather epidemiological methods or shoe leather and clipboard approaches. 119 00:13:48,300 --> 00:13:55,530 But as as I alluded to at the beginning, this idea of a race between between tracking transmission and the virus, 120 00:13:55,530 --> 00:14:03,690 creating new infections that approach a contact tracing doesn't scale particularly 121 00:14:03,690 --> 00:14:10,590 well once we get to tens or hundreds of thousands of new infections every week. 122 00:14:10,590 --> 00:14:18,290 Which brings us to our main theme, which is that can technology help us in this race? 123 00:14:18,290 --> 00:14:26,240 And the two technologies I think we're going to mainly talk about today are using smart 124 00:14:26,240 --> 00:14:36,180 phones to help notify people of that of the risk of infection and using genomics to 125 00:14:36,180 --> 00:14:42,540 look at the genomes of viruses and pathogens to understand how they have been spreading 126 00:14:42,540 --> 00:14:49,770 in the past and say let's let's first have a talk about these two new technologies. 127 00:14:49,770 --> 00:14:53,640 They might not be familiar to everyone listening and explain briefly how they work. 128 00:14:53,640 --> 00:15:04,780 They should start with with a smartphone apps. Okay, so where there is nowadays, we have we have smartphone apps for or for everything, 129 00:15:04,780 --> 00:15:17,940 but these smartphone contact tracing apps where they rely on is is the technology low energy Bluetooth to measure the proximity between phones. 130 00:15:17,940 --> 00:15:28,050 So if you if you have two people who are carrying smartphones, spend a certain amount of time together, 131 00:15:28,050 --> 00:15:33,240 there's an there's an exchange of Bluetooth signals, which is basically just a handshake. 132 00:15:33,240 --> 00:15:37,920 And this is this is a technology that's been there for a while. It's for example, you know, 133 00:15:37,920 --> 00:15:43,380 when you use a find my phone function and that's that's how your that's how 134 00:15:43,380 --> 00:15:47,940 your phone is is funnelled through this sort of very energy efficient states. 135 00:15:47,940 --> 00:15:56,450 And so what happens is, is, you know, if if we were meeting in person rather than virtually our phones, 136 00:15:56,450 --> 00:16:07,080 would we'd exchange these handshakes and based on the signal strength and so on and some other characteristics, we can work out that distance. 137 00:16:07,080 --> 00:16:13,700 You can work out actually first signals being scrambled, you know, like in a bus, for example. 138 00:16:13,700 --> 00:16:21,480 So you can get a pretty good idea of of whether the risks the event is something that could give rise to transmission. 139 00:16:21,480 --> 00:16:28,890 And then the nice thing is that if or the useful thing is that if two days later one of us test positive for Turbit, 140 00:16:28,890 --> 00:16:30,800 then the other one gets a notification. 141 00:16:30,800 --> 00:16:39,630 And that can be an entirely anonymous notification that you've spent a set amount of time in an in close proximity with somebody. 142 00:16:39,630 --> 00:16:48,630 Now turns out. So this is sort of a window in the past. Now turns out to be infected and you get instant notification. 143 00:16:48,630 --> 00:16:57,180 And in that gain, speed is is absolutely critical because the issue which we saw we've covered really early on, 144 00:16:57,180 --> 00:17:08,100 which is which is still really problematic, is, is that a lot of transmission occurs in people before they get characteristic Turbit symptoms. 145 00:17:08,100 --> 00:17:13,890 So by the time you're looking for contacts to break chains of transmission, you know, 146 00:17:13,890 --> 00:17:20,910 the you're really in a race against time where on average you've got about two days between, 147 00:17:20,910 --> 00:17:28,620 you know, developing symptoms and the contact being notified. And then, you know, that's an average of quite white distribution. 148 00:17:28,620 --> 00:17:34,270 So, yeah. So the key benefits over shoe leather epidemiology, 149 00:17:34,270 --> 00:17:47,250 one speed of notification and to the fact that this system will continue to work perfectly well depending on where there's 10 infections or 10000, 150 00:17:47,250 --> 00:17:56,310 and it takes just as long, I seem to notify a thousand people that they might be at risk as it does to just notify one person. 151 00:17:56,310 --> 00:18:04,170 Absolutely. Yeah. So it's it's it's instantaneous. I mean, there's there's it's not quite instantaneous. 152 00:18:04,170 --> 00:18:14,220 So, for example, there are some filters that are built in to make sure that the system stays to cure, you know, that that it can't be gamed. 153 00:18:14,220 --> 00:18:25,130 En masse and so on, which is really important, I think, with with digital technologies, but basic needs is it's very scalable. 154 00:18:25,130 --> 00:18:34,260 And if you start to imagine that coupled with these rapid point of care test, which can now be manufactured antigen tests and in the future, 155 00:18:34,260 --> 00:18:42,270 you know, we can mount Manufaktura antigen test, vote for Enea and your antigens for future pathogens. 156 00:18:42,270 --> 00:18:50,790 You could imagine getting tested, you know, getting a result within half an hour and then notifying contacts, being notified later. 157 00:18:50,790 --> 00:18:54,840 But at this point in time, it sort of speeds the contact tracing process. 158 00:18:54,840 --> 00:19:09,100 It's also it's also the other benefit is that it helps when, you know, you don't necessarily you don't necessarily take down the name of everybody. 159 00:19:09,100 --> 00:19:17,150 You know, if you spend some time at the or the from the person who was sitting behind you closely in the in the adjacent table. 160 00:19:17,150 --> 00:19:22,590 Now, you know, we've seen through it through the pandemic that restaurants are supposed to take people's names. 161 00:19:22,590 --> 00:19:27,090 And in fact, you know, they then sell out some of them so that they could make money. 162 00:19:27,090 --> 00:19:37,680 And so. So this is a much more privacy preserving. And, you know, it doesn't care whether you know, the person you have contact with or not. 163 00:19:37,680 --> 00:19:42,570 Is there a key threshold in terms of the number of people that need to be using it for it to be effective? 164 00:19:42,570 --> 00:19:47,490 Or is there still benefit from it, irrespective of the take take-up? 165 00:19:47,490 --> 00:19:55,980 So there's benefit from it. You know, as soon as you have one group of friends or a group of colleagues or a group, 166 00:19:55,980 --> 00:20:04,320 a big group of co-workers who meet, there's there's a protective effect for for that sort of bubble of people. 167 00:20:04,320 --> 00:20:05,640 There's two ways of thinking about it. 168 00:20:05,640 --> 00:20:13,200 You can either think about it, you know, from the perspective of the the the chief scientific adviser or the minister of health, 169 00:20:13,200 --> 00:20:17,800 you think, what do I need to to protect, you know, the whole population? 170 00:20:17,800 --> 00:20:25,650 And there is a protective effect that probably once you get past about 15 percent of the population who are users in the UK, 171 00:20:25,650 --> 00:20:32,790 we're sort of over 30 percent, something like 40 percent of adults, and we're well above that threshold. 172 00:20:32,790 --> 00:20:40,560 But if you think about it as an individual user, the threshold is, you know, other people you come into contact with also using that. 173 00:20:40,560 --> 00:20:49,570 So it really only depends on what's happening in your in your neighbourhood in terms of that direct sort of benefit. 174 00:20:49,570 --> 00:20:54,990 Okay. Let's let's briefly introduce listeners to Pathogen Genomics. 175 00:20:54,990 --> 00:21:06,660 And here, of course, we're talking about virus genomics. And this is a topic that both you and I have spent a lot of time researching. 176 00:21:06,660 --> 00:21:17,700 So some but not all of our listeners might know that infectious microorganisms such as bacteria and viruses, undergo quite high rates of evolution. 177 00:21:17,700 --> 00:21:29,760 And that means that the genome or the instruction set for that virus or bacteria is often slightly different in each infected individual. 178 00:21:29,760 --> 00:21:38,250 And if you use genomic technologies to read that genome, you can observe these differences. 179 00:21:38,250 --> 00:21:46,800 And the interesting thing is that they their differences accumulate during the chain of transmission so that the pattern is shared. 180 00:21:46,800 --> 00:21:52,730 Differences amongst different infections reveals the history of transmission events. 181 00:21:52,730 --> 00:22:02,690 Is that pathogen that's been spreading? Now, that's seems a little bit remote, I guess, from the process of transmission. 182 00:22:02,690 --> 00:22:12,240 But but does it contain information about transmission that the other sources of information that we've been talking about, don't you? 183 00:22:12,240 --> 00:22:23,280 Absolutely. So certainly imagine, you know, maybe some person who's infected, who you've sampled, being able to work out. 184 00:22:23,280 --> 00:22:26,830 So if you're investigating a cluster, for example, 185 00:22:26,830 --> 00:22:34,670 you've got a cluster of cases in a hospital or a cluster of cases around a school or a cluster of cases as appeared, 186 00:22:34,670 --> 00:22:40,860 you know, around a car, then being able to being able to say, oh, these infections actually linked. 187 00:22:40,860 --> 00:22:43,350 You know, is there a surface spread even as happened here? 188 00:22:43,350 --> 00:22:51,150 Is there something for me to understand or authorise you being able to reject transmission dredges? 189 00:22:51,150 --> 00:22:57,030 Well, you know, yes, there are a few cases here, but they don't seem related to each other. 190 00:22:57,030 --> 00:23:03,990 They just happened to be in the same place at the same time. You know, it is critical to your understanding. 191 00:23:03,990 --> 00:23:10,400 And if you're going to if you're going to do something like close a school or close a workplace, 192 00:23:10,400 --> 00:23:14,070 you know, and you want to do it quite early on the basis. 193 00:23:14,070 --> 00:23:17,930 The because as you're saying, because this is always about speed. 194 00:23:17,930 --> 00:23:27,140 So, you know, the metaphorical Broadstreet pump, you want to save prevent infections by removing it as quickly as possible. 195 00:23:27,140 --> 00:23:37,020 So so the quicker you get information about whether you're really seeing your outbreak can be, the more effective your action is going to be. 196 00:23:37,020 --> 00:23:47,040 I mean, likewise, I don't know if you want to get this letter as a study looking instead of school level or country level, 197 00:23:47,040 --> 00:23:51,660 you know, the number of introductions and into the into the UK. 198 00:23:51,660 --> 00:23:56,250 You know how that worked out. Tell us about. 199 00:23:56,250 --> 00:24:00,900 Yeah, I think you're right that one of the key benefits of this data is the ability to determine 200 00:24:00,900 --> 00:24:06,000 the number of different chains of transmission that are in a particular location. 201 00:24:06,000 --> 00:24:14,880 And this year, during the covered pandemic in the UK, genome sequencing has been widely used across lots of settings and in hospitals. 202 00:24:14,880 --> 00:24:21,000 Very important if there is an outbreak occurring to determine where this is just one outbreak or multiple. 203 00:24:21,000 --> 00:24:29,880 And in fact, it might be affecting different wards of different parts of the hospital into the need one outbreak response team or two. 204 00:24:29,880 --> 00:24:33,480 And typically going all the way back to John Snow in the Broad Street pump, 205 00:24:33,480 --> 00:24:39,030 you were saying about how people had come in from outside and being been infected. 206 00:24:39,030 --> 00:24:41,720 So in in traditional epidemiology, 207 00:24:41,720 --> 00:24:49,200 there will be the idea that cases that are near each other in space and time are likely to be linked through transmission. 208 00:24:49,200 --> 00:24:57,870 And that's usually, but not always the case. And if there has been movement of individuals, whether within a country or internationally, 209 00:24:57,870 --> 00:25:01,350 that can produce infections close to each other in space and time, 210 00:25:01,350 --> 00:25:10,180 but they're not actually linked to each other in terms of a close chain of transmission and pathogen genomes have very. 211 00:25:10,180 --> 00:25:14,500 Powerful information about Rissole think that and our work was looking at the 212 00:25:14,500 --> 00:25:21,730 number of times that size Cavey two has been introduced into the UK from abroad, 213 00:25:21,730 --> 00:25:25,900 particularly during the first wave in early summer. 214 00:25:25,900 --> 00:25:31,990 And there was some very interesting dynamics, both a number of introductions, which was at least 13. 215 00:25:31,990 --> 00:25:41,350 Fifteen hundred, and almost certainly many more. But also the rate of of change of introductions changed over a matter of just a few weeks. 216 00:25:41,350 --> 00:25:46,390 And also, the source countries have where introductions were coming from was very dynamic as well. 217 00:25:46,390 --> 00:25:54,340 And that was all information that I think pretty much any pathogen genome sequence data could could resolve. 218 00:25:54,340 --> 00:26:07,860 So I guess we were already starting to sort of explore that the new types of information that these new technologies can give us. 219 00:26:07,860 --> 00:26:13,470 I mean, we're mostly talking about smartphone apps and and pathogen genome sequencing. 220 00:26:13,470 --> 00:26:20,230 I think that's some more that is perhaps even more experimental that that hasn't been fully utilised in this pandemic. 221 00:26:20,230 --> 00:26:29,050 But that could be really important in the future. And those are wastewater surveillance. 222 00:26:29,050 --> 00:26:32,710 This is a genomic technology, but it is slightly different, actually, 223 00:26:32,710 --> 00:26:43,750 being able to detect and quantify the number of cases either in the region or a building 224 00:26:43,750 --> 00:26:51,430 or a district through looking at the presence of the virus in wastewater and sewage. 225 00:26:51,430 --> 00:27:03,400 And secondly, it's very interesting, recent work on on using smart watches and fitness trackers as potential measures of people's physiology. 226 00:27:03,400 --> 00:27:11,920 And in fact, if you can, those detect whether somebody is infected or not, do you think these are potential tools of the future? 227 00:27:11,920 --> 00:27:17,740 Absolutely. Because, I mean, again, you know, in the name of the game is is speed. 228 00:27:17,740 --> 00:27:26,740 And just to sort of comment on your on a really interesting finding about the number of introductions early on in the U.K., 229 00:27:26,740 --> 00:27:31,150 I think we're now in a difficult situation, obviously economic then epidemiologically, 230 00:27:31,150 --> 00:27:38,680 where we're just now obviously want to prevent infections without, you know. 231 00:27:38,680 --> 00:27:42,130 But the economy in its turn to keep on going. But I think well, 232 00:27:42,130 --> 00:27:48,990 what's really clear is that there was an opportunity early on to to take sort of take 233 00:27:48,990 --> 00:27:56,530 the economic shock for a short period of time in terms of of movement restrictions. 234 00:27:56,530 --> 00:27:56,790 Right. 235 00:27:56,790 --> 00:28:09,090 To this start not letting all of these chains of transmissions sort of sort of get pounded around the country and really use more limited capacity. 236 00:28:09,090 --> 00:28:14,510 Was told to contain the first few outbreaks and then to build up that capacity. 237 00:28:14,510 --> 00:28:20,050 I mean, there's been a lot of talk about control measures just delaying the epidemic, but that's kind of the whole point. 238 00:28:20,050 --> 00:28:28,930 If by delaying their pandemic, you know, you have that you have the ability to increase capacity and then actually open up things later on. 239 00:28:28,930 --> 00:28:36,540 I think economically and epidemiologically, you know, that the early action is is Rubini. 240 00:28:36,540 --> 00:28:37,430 And, you know, 241 00:28:37,430 --> 00:28:47,530 it's not a theoretical argument because very clear that that's one of the signatures of the countries that have come out of this relatively well. 242 00:28:47,530 --> 00:28:49,510 And again, the early notification. 243 00:28:49,510 --> 00:29:00,670 I mean, at the moment, you see the pandemic starting with a cluster of cases, essentially by the time you see the first surface bird event. 244 00:29:00,670 --> 00:29:10,060 But you can imagine you could imagine that with sequencing, sequencing as is sort of as very specific and it's it's very agnostic. 245 00:29:10,060 --> 00:29:14,920 So you could see very quickly, you know, people come and Mora's Børge infections. 246 00:29:14,920 --> 00:29:24,850 If this if this looks unfamiliar, sequencing is now getting sort of cheap enough that it can be and it is being worked and 247 00:29:24,850 --> 00:29:31,090 sort of standard diagnostic practises and because it's rich in information is quantitative. 248 00:29:31,090 --> 00:29:33,530 It tells it how much of a pathogen there is. 249 00:29:33,530 --> 00:29:38,920 It gives you something, some indication about what the best way to treat these particular cases and so on. 250 00:29:38,920 --> 00:29:43,690 So I think there's lots of future there. And and Westwater surveillance as well. 251 00:29:43,690 --> 00:29:50,310 You know, again, it's anonymous and that allows it to count how many how many pathogens are circulating. 252 00:29:50,310 --> 00:29:56,170 The wearables, you know, again and gives you that speed. 253 00:29:56,170 --> 00:30:04,600 So you could imagine you can imagine at an indication we probably don't all want to be testing for everything or time. 254 00:30:04,600 --> 00:30:10,010 But you can imagine an indication that would tell you, yes, you should get tested. 255 00:30:10,010 --> 00:30:23,500 You know, and anything that allows allows you at the right time to get tested and then to take appropriate action at a personal level in terms of, 256 00:30:23,500 --> 00:30:27,650 you know, managing your risks, not transmitting to your family members, 257 00:30:27,650 --> 00:30:34,270 not transmitting that to people who are vulnerable and allows contact tracing to happen to people. 258 00:30:34,270 --> 00:30:45,400 You know, contact tracing is all about disseminating information so that people can take appropriate, appropriate action on an infection spread. 259 00:30:45,400 --> 00:30:53,090 So so digital technologies, tremendous way of disseminating that information and organising that information. 260 00:30:53,090 --> 00:31:05,480 And the genetic technologies really allow you to to differentiate between the different pathogens that go on together. 261 00:31:05,480 --> 00:31:16,250 And I mean, it comes back to our analogy of a race that no matter what the infrastructure for tests traced and an isolate is, 262 00:31:16,250 --> 00:31:23,120 it's always going to have a finite capacity. And we've been able to build the capacity of that infrastructure through time. 263 00:31:23,120 --> 00:31:31,430 It was initially too small in the U.K. and it was potentially great in other countries before the pandemic occurred, 264 00:31:31,430 --> 00:31:39,280 which is why they were able to deal with things better. And. 265 00:31:39,280 --> 00:31:46,000 All of these technologies are helping us increase our speed in this race and to try and keep up with the virus. 266 00:31:46,000 --> 00:31:53,290 And do they work synergistically? I mean, I'm looking towards a super optimistic future where actually some of these technologies start to link 267 00:31:53,290 --> 00:32:00,600 in with each other and that that combination would be vastly more efficient than each on its own. 268 00:32:00,600 --> 00:32:13,900 Yes, I think so. I mean, as I think pathogen genomics, you know, will get linked into into emerging diagnostics because I mean, 269 00:32:13,900 --> 00:32:17,370 it probably is just to do the the the pricing. 270 00:32:17,370 --> 00:32:27,530 If you look you know, if you look at the cost of running a standard microbiology or infectious disease laboratory in a hospital, 271 00:32:27,530 --> 00:32:33,060 you know that the progress in sequencing just just makes it competitive on price. 272 00:32:33,060 --> 00:32:38,730 And you just you just start stacking up all of the data that you can get from from this. 273 00:32:38,730 --> 00:32:50,050 This this one sample. To me, it kind of seems inevitable that that things will will go in in that direction. 274 00:32:50,050 --> 00:32:56,930 So that's just what smart phones are all the way as a patient, you know. 275 00:32:56,930 --> 00:33:01,430 That way, you get information in a really usable manner. 276 00:33:01,430 --> 00:33:08,120 So if I if I get information on anonymous information, you know that you should test for X or Y. 277 00:33:08,120 --> 00:33:11,490 That's very useful. Of course, you know, not everybody has a smartphone. 278 00:33:11,490 --> 00:33:19,790 It's still we're in the age of apps, but there's still sort of a quarter of the population who don't have a smartphone. 279 00:33:19,790 --> 00:33:26,330 And so, you know, this is the direction of travel. 280 00:33:26,330 --> 00:33:30,320 But we need we need multiple solutions. So if you look in the case of pivot, you know, 281 00:33:30,320 --> 00:33:39,290 smartphone technologies would not have would not have helped with the cab switch account for a or a very significant fraction of the mortality. 282 00:33:39,290 --> 00:33:50,420 So it's said, you know, and. We we still need we still need care and infrastructure and so on. 283 00:33:50,420 --> 00:33:54,880 But an infectious disease control, to some extent, you never lose. 284 00:33:54,880 --> 00:34:00,710 Right. Because if you're if you're staying, if you if you're preventing infections amongst, you know, 285 00:34:00,710 --> 00:34:07,800 people who are happy to use smartphones and apps, you're also preventing infections spreading out into the hospitals and then into the care. 286 00:34:07,800 --> 00:34:13,390 So because. Because we're so connected. 287 00:34:13,390 --> 00:34:21,290 Great. I was thinking of exploring a bit further distinction between the message, you know, Mick, 288 00:34:21,290 --> 00:34:28,960 virus discovery for for new pathogens that we haven't seen before vs. the kind of testing that we have now, 289 00:34:28,960 --> 00:34:34,690 which is very specific testing for a known disease that we're trying to track the spread of. 290 00:34:34,690 --> 00:34:39,190 I'm going to hold that and maybe come back to it later if we if we have a bit more time, 291 00:34:39,190 --> 00:34:46,750 because we've talked about the the best case scenario is that the synergistic effects of these different 292 00:34:46,750 --> 00:34:54,140 technologies really enabling us both for this pandemic in future pandemics to get ahead of transmission. 293 00:34:54,140 --> 00:34:59,800 Now that the use of these technologies isn't without its own challenges, 294 00:34:59,800 --> 00:35:10,090 and many of those challenges do relate to people's concerns over the use of some of the data that they're generating. 295 00:35:10,090 --> 00:35:14,350 So, I mean, can you explain, a have done to a certain extent, 296 00:35:14,350 --> 00:35:21,790 but in a bit more detail how the privacy is maintained during these these these smartphone apps? 297 00:35:21,790 --> 00:35:36,740 How would you make somebody confident who is a little bit worried about using the app that it's that it's it's a private privacy secure thing to do? 298 00:35:36,740 --> 00:35:47,830 Yeah. So the contact tracing apps that have been rolled up through the Google Apple operating system converged on a privacy first design. 299 00:35:47,830 --> 00:35:55,100 And that meant that the you know, the exchange when you have close proximity and then so. 300 00:35:55,100 --> 00:35:58,960 So the two of us sit next to each other and have a chat. 301 00:35:58,960 --> 00:36:04,390 We exchanged anonymous keys and those keys rotating. 302 00:36:04,390 --> 00:36:09,580 So they can never be traced back and they stay on your phone. 303 00:36:09,580 --> 00:36:20,110 And, you know, if I later get diagnosed at the set of keys, you know, get circulated. 304 00:36:20,110 --> 00:36:23,140 But essentially, there's no central server. 305 00:36:23,140 --> 00:36:35,140 So essentially, they get your phone and cheques up on the list of people who've who've been diagnosed and the anonymous keys and says, 306 00:36:35,140 --> 00:36:43,840 oh, you know, I was in contact with this key and it notifies you of that notification and doesn't doesn't go any further. 307 00:36:43,840 --> 00:36:49,840 Similarly, the NHS up has it does both contact tracing and outbreak investigation. 308 00:36:49,840 --> 00:37:01,000 So so does outbreak investigation. But encouraging people to just Carnamah QR code where they go to a location where an outbreak might take place. 309 00:37:01,000 --> 00:37:08,740 So that's sort of a tool to prevent or to respond to a super spreading event associated with particular locations. 310 00:37:08,740 --> 00:37:18,870 But those QR code scans again and not uploaded anywhere, they stay on your phone and, you know, at the moment to preserve privacy. 311 00:37:18,870 --> 00:37:25,660 And you can delete those. But the contact tracing of manual contact trace call when I called her up. 312 00:37:25,660 --> 00:37:33,220 Can I ask you to read off the locations of your QR code and you're in control of that information in future? 313 00:37:33,220 --> 00:37:41,950 That can be simplified. But I think the person it was was meant to turn to do that. 314 00:37:41,950 --> 00:37:50,500 And I think, you know, I mean, the the the there is quite a complex issue because I think we do want to. 315 00:37:50,500 --> 00:37:57,550 We do want to and we can live in a world where we're not being surveyed all of the time for for everything. 316 00:37:57,550 --> 00:38:03,080 And you can easily imagine them. And there are already abuses of data at the moment. 317 00:38:03,080 --> 00:38:11,260 You know, there are there are apps, non-governmental apps or private companies, you know, who who install. 318 00:38:11,260 --> 00:38:21,970 You know who. I'm sorry, pulling data from from from marketing apps and collect that data and collect a lot of that information. 319 00:38:21,970 --> 00:38:27,100 But with you may not be aware about so. So privacy is a really important issue. 320 00:38:27,100 --> 00:38:37,000 And, you know, the in terms of governments, we don't want, you know, a massive manhunt for everything, 321 00:38:37,000 --> 00:38:45,760 but we want good information to be collected selectively for in situations like emergencies, you know. 322 00:38:45,760 --> 00:38:54,010 So it's a smartphone. Mobility apps mobility data has been very useful when there are disasters, earthquakes, that kind of thing. 323 00:38:54,010 --> 00:38:58,000 And you can see you'd be quite happy if somebody was looking at your smartphone trace. 324 00:38:58,000 --> 00:39:04,630 If you're trapped in a building after an earthquake and you know, and similarly, 325 00:39:04,630 --> 00:39:13,310 you could argue that in pandemics or certain types of data, which would be which would be useful, but it was felt that this is. 326 00:39:13,310 --> 00:39:19,960 You know, the precedent here is to have gone for privacy first design, and I think I think, you know, 327 00:39:19,960 --> 00:39:25,880 that that the system that's been developed is very effective in terms of being able to make sure 328 00:39:25,880 --> 00:39:34,190 that that personalised information meant to turn to contacts and outbreak situations gets to you. 329 00:39:34,190 --> 00:39:39,200 But it does mean that so they're being able to find out what type of contacts or 330 00:39:39,200 --> 00:39:43,970 give rise to infection is not really within within the purview of this stuff. 331 00:39:43,970 --> 00:39:50,060 So, know, we've had to the shoe leather epidemiology that this has focussed much on function. 332 00:39:50,060 --> 00:39:54,080 But I think, you know, it's clearly a compromise, right? 333 00:39:54,080 --> 00:40:02,990 Between what? That the technology could potentially do a lot of that potential isn't being met by the current apps. 334 00:40:02,990 --> 00:40:11,550 But that's a necessary compromise in order to ensure that people feel confident 335 00:40:11,550 --> 00:40:19,590 to use it and that we can still get the benefits of a recently high take-up. 336 00:40:19,590 --> 00:40:23,850 That's right. So. Yeah. And I think, you know, that's the way it was designed. 337 00:40:23,850 --> 00:40:27,830 And I think it's a really good design at this point in time. 338 00:40:27,830 --> 00:40:34,920 So it will be interesting to see in the future whether in a into a pandemic period, 339 00:40:34,920 --> 00:40:47,070 whether people's socially as a society and individually people seise on on the value of this data and and the risks to their data change. 340 00:40:47,070 --> 00:40:56,940 I mean, it's true enough to say that that considerably more personal data is used to to put an advert selling you a car 341 00:40:56,940 --> 00:41:05,710 on a Web site than it is then it's being used to give you notifications through the smartphone tracing apps. 342 00:41:05,710 --> 00:41:17,730 Definitely. There isn't a great deal to touch on in terms of pathogen genomics, I think in terms of patient privacy, 343 00:41:17,730 --> 00:41:24,570 because those genomes are generally shared in entirely anonymous way. 344 00:41:24,570 --> 00:41:30,180 And just just to clarify, these are not genomes of the person who has been infected. 345 00:41:30,180 --> 00:41:39,000 It's the genome of just the infectious agent itself, which tends to be quite, quite small and short. 346 00:41:39,000 --> 00:41:46,960 I mean, there have been instances where that kind of pathogen genomic information is used to. 347 00:41:46,960 --> 00:41:53,380 Try to answer whether a particular person has transmitted an infectious disease to another person. 348 00:41:53,380 --> 00:42:03,940 And here I'm thinking about the U.S., its passage in genomic data, say in a criminal trial where somebody has been accused of deliberate infection, 349 00:42:03,940 --> 00:42:12,940 often of HIV, but sometimes other pathogens that's infecting somebody deliberately, which can be a criminal act. 350 00:42:12,940 --> 00:42:17,560 So it's worth noting, and I think there's a lot of work to be done, 351 00:42:17,560 --> 00:42:23,710 both scientifically and ethically to to enable the best use of pathogen genome 352 00:42:23,710 --> 00:42:30,580 data whilst maintaining the same kind of privacy that we've been talking about. 353 00:42:30,580 --> 00:42:35,410 I agree. And I think I mean, that is also true in healthcare acquired infections. 354 00:42:35,410 --> 00:42:41,750 I mean, you can imagine, you know, this is clearly useful. 355 00:42:41,750 --> 00:42:47,800 So you brought up the example of when you have two outbreaks in different parts of the hospital. 356 00:42:47,800 --> 00:42:56,140 You know, it's really important for the hospital infection control team to know whether the same outbreak and there's some 357 00:42:56,140 --> 00:43:02,080 there's some way in which the pathogen is going backwards and forwards between these two locations in the hospital. 358 00:43:02,080 --> 00:43:06,880 Or if that, too. If there are two separate outbreaks, because then again, 359 00:43:06,880 --> 00:43:13,330 you want to investigate and you just want to make sure it doesn't happen again or doesn't spread to a third location. 360 00:43:13,330 --> 00:43:24,270 But in an era of litigation, that's that's you know, that can be that can be quite a fraud investigation. 361 00:43:24,270 --> 00:43:26,590 And but I think the I mean, 362 00:43:26,590 --> 00:43:37,510 the underlying issue is we need to essentially we need to enable if we need to enable the positive uses which are that prevention, 363 00:43:37,510 --> 00:43:39,040 which are getting the information mixed. 364 00:43:39,040 --> 00:43:45,330 On the other hand, you know, the kind of question as an epidemiologist and I'm sure I'm sure you feel the same, people always ask me, 365 00:43:45,330 --> 00:43:50,890 you know, this virus transmitted here is a virus transmitted that, you know, how safe is it to go to the supermarket? 366 00:43:50,890 --> 00:43:55,150 How safe is it to go to the park in our house? And I should disclose. I should disclose. 367 00:43:55,150 --> 00:44:00,250 We closed. You know, what about somebody jogging past Mayo? 368 00:44:00,250 --> 00:44:04,510 You know that there are all kinds of information. And as the saying, you know what, I'm working on HIV. 369 00:44:04,510 --> 00:44:11,230 People always want to know about, you know, is the virus transmitted in this way or that way? 370 00:44:11,230 --> 00:44:20,800 And the way we we answer those questions is by collecting data on transmissions that have happened and limiting for the common pattern. 371 00:44:20,800 --> 00:44:26,800 And we tried to do that. You know, obviously you can well design studies, but those well-designed studies involve, 372 00:44:26,800 --> 00:44:32,710 you know, people undergoing that that that that they life, as it were. 373 00:44:32,710 --> 00:44:41,320 And you have to collect the data so that you don't keep on reproducing the behaviours or the patterns, 374 00:44:41,320 --> 00:44:45,820 you know, and it can be very enabling because it was collecting data about schools, 375 00:44:45,820 --> 00:44:56,590 which allowed us to say that by and large and schools in the case of covered were not going to be the major drivers of the pandemic. 376 00:44:56,590 --> 00:45:01,300 Despite that, you do have cases in schools and it can be distressing. 377 00:45:01,300 --> 00:45:07,990 But you don't get these explosive epidemics, so you might get another sort of simit similar settings. 378 00:45:07,990 --> 00:45:20,120 We've seen much more difficult Tehran University halls and involving older children and about and in workplaces where people are very close together. 379 00:45:20,120 --> 00:45:27,920 So do factory work, especially if if it's sort of within that confined situation. 380 00:45:27,920 --> 00:45:34,700 Yeah, it's interesting. Our transmission is a social, even an intimate act. 381 00:45:34,700 --> 00:45:39,580 It involves people usually being close to each other. 382 00:45:39,580 --> 00:45:46,600 And and scientifically, it's really important to people researching a very cognisant of that. 383 00:45:46,600 --> 00:45:56,260 And I think I think scientists working in infectious disease have a lot to learn from people working in law and sociology and ethics to 384 00:45:56,260 --> 00:46:04,270 understand how we can get the right balance between getting the real utility information about transmission that you've just mentioned, 385 00:46:04,270 --> 00:46:11,210 but also balancing that with with people's real, real and genuine concerns about this. 386 00:46:11,210 --> 00:46:15,070 But as we mentioned, information, people really want wrong information. 387 00:46:15,070 --> 00:46:20,050 And people, you know, if it is information, people always ask you again and again. 388 00:46:20,050 --> 00:46:26,640 And they're surprised that that information, as you know, isn't as precise as they want about the roots of transmission. 389 00:46:26,640 --> 00:46:30,580 Unknown isn't as plentiful as they were. 390 00:46:30,580 --> 00:46:38,560 People want to know very early on, you know, how protective masks to infecting other people and how much the masks and protective. 391 00:46:38,560 --> 00:46:42,220 And again, you have to study pogoing in everyday life. 392 00:46:42,220 --> 00:46:49,710 So there's sort of three ways of thinking. One is. You can have up to an opt out. 393 00:46:49,710 --> 00:46:55,320 So some people opt in to sharing these data to a certain approaching people. 394 00:46:55,320 --> 00:47:00,840 Then you can think like with the contact tracing out, there was a lot of progress made in terms of privacy, 395 00:47:00,840 --> 00:47:06,300 preserving algorithms to wherever it's possible to do what you want. 396 00:47:06,300 --> 00:47:14,880 And to use algorithms. So so, for example, you know, your computation, the the epidemiological question, where is transmission happened? 397 00:47:14,880 --> 00:47:21,510 It might be that I write or somebody else writes a piece of code, but that piece of code gets run on your phone. 398 00:47:21,510 --> 00:47:26,200 So the answer the important answer, you know, never leaves your phone. 399 00:47:26,200 --> 00:47:33,960 The data never leaves your phone. But the computation is a bit that travels around and that gradually builds up a statistical answer. 400 00:47:33,960 --> 00:47:35,850 And then the third aspect is, 401 00:47:35,850 --> 00:47:43,310 is simply that there are some people who are health researchers who are governed by a code of conduct and who don't misuse your data because, 402 00:47:43,310 --> 00:47:47,290 you know, they're not open nature. 403 00:47:47,290 --> 00:47:52,140 This sensitive data, just like clinical records. You know. 404 00:47:52,140 --> 00:47:58,570 I think I mean, it's been an absolutely fascinating conversation, it's been wonderful talking with you, Cristoff. 405 00:47:58,570 --> 00:48:05,340 Oh, we could we could go on. I was going to ask you sort of what three things do we need to do to prevent the next pandemic? 406 00:48:05,340 --> 00:48:10,170 Perhaps we'll leave that for one of the audience to pose as a question. 407 00:48:10,170 --> 00:48:21,240 So thank you so much for that for that fabulous conversation. And let's take a look at some of the questions that have come in. 408 00:48:21,240 --> 00:48:27,820 So I am just starting to negotiate the. 409 00:48:27,820 --> 00:48:35,710 The question window on this broadcasting system. 410 00:48:35,710 --> 00:48:47,440 OK. So we have a question here with four upvotes from none other than Charles Godfrey, director of the Oxford Martin School. 411 00:48:47,440 --> 00:48:51,130 And that question is which technology will help cope with? 412 00:48:51,130 --> 00:48:56,110 Each of these challenges has been accelerated the most by Caven 19. 413 00:48:56,110 --> 00:49:02,890 And I guess I could add to that which which needs the most acceleration for the next pandemic. 414 00:49:02,890 --> 00:49:05,460 Yeah, well, I guess we can both give an answer to that. 415 00:49:05,460 --> 00:49:13,850 I mean, clearly, one of the things I take away from from looking at the way things are progress is preparing in advance, 416 00:49:13,850 --> 00:49:22,320 you know, is really useful, and that the speed of the of the vaccine development didn't come from nowhere. 417 00:49:22,320 --> 00:49:29,190 The vaccines that were developed were developed. So that was the most impressive story so far. 418 00:49:29,190 --> 00:49:33,710 For sure. But it was built on on 20 years of planning. 419 00:49:33,710 --> 00:49:39,780 You know, the Coalition for Epidemic Preparedness was well, you know, and go and so on. 420 00:49:39,780 --> 00:49:46,770 International organisations that looked and and committed governments to donate large amounts of money. 421 00:49:46,770 --> 00:49:51,120 With great foresight into into generic platforms. 422 00:49:51,120 --> 00:49:56,220 And that the vaccines, the orks of vaccines, the Moderna, the MRN vaccines, 423 00:49:56,220 --> 00:50:04,680 the usual vaccines which had been explicitly designed for for for a pandemic situation. 424 00:50:04,680 --> 00:50:07,500 And they've worked a certain tremendous. 425 00:50:07,500 --> 00:50:16,360 But still, you know, if we could if we could know, experience what we've experienced this past year while waiting for the vaccine, that would be good. 426 00:50:16,360 --> 00:50:22,770 I think digital technology in all its forms, including contact tracing, really has come forward. 427 00:50:22,770 --> 00:50:30,530 And I'm pretty sure that, you know, we're now in a situation where where something could be deployed. 428 00:50:30,530 --> 00:50:34,010 There was really good could be deployed right to the start of an outbreak with 429 00:50:34,010 --> 00:50:38,890 we're very applicable sort of tools that really would make a difference. 430 00:50:38,890 --> 00:50:45,330 And I think rapid point of care testing, you know, involving sequencing. 431 00:50:45,330 --> 00:50:53,910 So, so, so on the technologies side and in my group and and together with with colleagues 432 00:50:53,910 --> 00:50:59,360 with we're sort of working on getting those rapid point of care tests. 433 00:50:59,360 --> 00:51:03,760 So we've been working on this in the context of HIV. But the platforms are very general. 434 00:51:03,760 --> 00:51:13,530 So when you do that rapid test from coma as a saliva sample or a blood sample and a very small, 435 00:51:13,530 --> 00:51:20,510 very small sample, and you get a result of preliminary result there and then you go and confirm it. 436 00:51:20,510 --> 00:51:29,850 But but doing sequencing, so, so rapid point of care testing, immediate dissemination of the information across the risk network, 437 00:51:29,850 --> 00:51:35,530 you know, through it, through outbreak analysis, through outbreak information and contact tracing. 438 00:51:35,530 --> 00:51:41,280 And I imagine that could be done much more quickly in the future. 439 00:51:41,280 --> 00:51:48,510 Yeah, my my pick for my pick for the future would be, I think, the wastewater surveillance. 440 00:51:48,510 --> 00:51:54,830 I mean, it's starting to be used now, but in a in a. 441 00:51:54,830 --> 00:51:57,200 Still a fairly experimental way. 442 00:51:57,200 --> 00:52:08,330 But if we could get the infrastructure and the analytical capability to pretty much be screening wastewater and other types of environmental samples, 443 00:52:08,330 --> 00:52:15,890 perhaps air filtered virus or bacteria from from large venues, 444 00:52:15,890 --> 00:52:23,300 then we have the potential not only to quantify an outbreak better when it's when it's been detected, 445 00:52:23,300 --> 00:52:31,970 but also to detect a new pathogen that emerges in humans right at the very beginning of an outbreak when there perhaps are any 10, 446 00:52:31,970 --> 00:52:37,650 20 or 100 people infected. And as we know, speed of response is everything. 447 00:52:37,650 --> 00:52:42,740 And to nip to nip an epidemic in the bud. Yeah, and I agree. 448 00:52:42,740 --> 00:52:53,540 I mean, that sounds that sounds phenomenal. Huge, huge technical challenges both both in terms of basic science and in terms of operational research. 449 00:52:53,540 --> 00:52:58,250 I mean, everything from the amount of rainfall, the the water flow in the sewers, 450 00:52:58,250 --> 00:53:03,680 Fatburger and everything comes into whether the numbers you get out of reliable or not. 451 00:53:03,680 --> 00:53:15,210 I mean, I guess the other question where we're going to, you know. Figure out over the next four years that sort of predicting out of, you know, 452 00:53:15,210 --> 00:53:22,100 the multitudes of viruses and bacteria, most of which are entirely harmless. 453 00:53:22,100 --> 00:53:28,110 You know what other things to have a pandemic potential? 454 00:53:28,110 --> 00:53:37,240 Because, I mean, I think as far as like Corona virus, didn't, you know, it was reasonably plausible. 455 00:53:37,240 --> 00:53:42,510 A high risk pathogen. I mean, the most corona virus is not that distantly related. 456 00:53:42,510 --> 00:53:48,700 And that's been sort of regarded as possibly the number one threat, you know, globally. 457 00:53:48,700 --> 00:53:55,150 So we can probably make why do you think we can make quite a good job in terms of knowing what we're looking for as well? 458 00:53:55,150 --> 00:53:59,520 And we're looking so so this is really interesting academic debate happening right now 459 00:53:59,520 --> 00:54:06,300 in terms of whether it is valuable to invest large sums of money in attempting to 460 00:54:06,300 --> 00:54:11,670 identify and discover all of the viruses that are out there in other species and environment 461 00:54:11,670 --> 00:54:16,980 and to get some information about them before they potentially jump into humans. 462 00:54:16,980 --> 00:54:21,480 I mean, the other thing I like about your wastewater proposal, I mean, I've done Tchula. 463 00:54:21,480 --> 00:54:24,930 There's always going to be a role for shoe leather epidemiology on target. 464 00:54:24,930 --> 00:54:32,040 I mean, the sort of human investigator, you know, coming relatively agnostic, me wearing that shirt, 465 00:54:32,040 --> 00:54:36,090 wearing out their shoes because they're walking everywhere and writing on their notepad. 466 00:54:36,090 --> 00:54:42,180 But the more information they have coming in and the more they know where to look and the more they get to look early on, 467 00:54:42,180 --> 00:54:46,170 the better job they can do so. So there's kind of tremendous synergies. 468 00:54:46,170 --> 00:54:54,310 I mean, if you imagine, you know, your you've got a new virus and you've got your West, you look at your wastewater nationally and, you know, 469 00:54:54,310 --> 00:55:02,930 you've you've you've been looking at an outbreak in Southampton and suddenly you see the same the same virus in the west, wastewater very. 470 00:55:02,930 --> 00:55:10,110 And then north of the country. You're not in a specific location. Your letter opener mythologist. 471 00:55:10,110 --> 00:55:18,540 Well, we'll be looking in the right place. Now, we have this vision of of Acento with, you know, big, big computer screens on it, flashing up, 472 00:55:18,540 --> 00:55:28,200 sort of warning new virus reported in Enceladus, say, and then but of course, that's just in Hollywood movies. 473 00:55:28,200 --> 00:55:35,190 But you know that that would be the kind of thing that it would be nice to have before the next pandemic. 474 00:55:35,190 --> 00:55:38,550 Let's let's take a look at some these other questions. 475 00:55:38,550 --> 00:55:46,350 This one from Donna Simmo, which read, you mentioned contamination of surfaces in Chinese food market. 476 00:55:46,350 --> 00:55:49,770 Do you think that was the main media transmission or airborne transmission? 477 00:55:49,770 --> 00:56:00,990 So I guess this is related to some some recent discussion of whether the virus can be transmitted to a region like China, 478 00:56:00,990 --> 00:56:06,810 which is effectively eradicated. It can initiate any chain of transmission, not three infected travellers, 479 00:56:06,810 --> 00:56:15,450 but three but three products, particularly those that that have been frozen or in the cold chain. 480 00:56:15,450 --> 00:56:22,230 So my understanding is that in this particular outbreak, it was environmental services and the virus was recovered, 481 00:56:22,230 --> 00:56:25,710 environmental services in different locations in the market. 482 00:56:25,710 --> 00:56:36,590 But in the epidemic more generally and sort of airborne and direct droplet transmission has been the most prominent form of transmission. 483 00:56:36,590 --> 00:56:42,370 I mean, it's worth noting that we've closed down a lot of the opportunities for those super spreaders. 484 00:56:42,370 --> 00:56:50,070 So there's sort of at the moment that there's a degree of transmission we see. 485 00:56:50,070 --> 00:56:56,010 So it reflects a little bit that the measures in place are in most parts of the world, big gathering's and are not allowed. 486 00:56:56,010 --> 00:56:59,670 And I know APNIC. And and so on. 487 00:56:59,670 --> 00:57:11,760 But at this point in time that the main foremast transmission, this is airborne and direct and again, the importance of social distancing and masks. 488 00:57:11,760 --> 00:57:19,410 And again, I don't see these things as contradictory. I think a lot of well-designed digital data and passenger data would be very 489 00:57:19,410 --> 00:57:26,160 helpful in the context of studies to better understand the effectiveness of masks. 490 00:57:26,160 --> 00:57:31,140 Again, if you're looking at effective muscle mass, being able to ask whether two cases are linked or not, 491 00:57:31,140 --> 00:57:35,580 women study using pathogen genomes would be an essential tool. 492 00:57:35,580 --> 00:57:44,270 We've seen you know, we've seen that in the case of HIV to prove the effectiveness of condoms, to improve the effectiveness of antiretroviral therapy, 493 00:57:44,270 --> 00:57:56,840 pathogen sequencing said these true people definitely didn't know one thing, but transmission makes those studies much more powerful. 494 00:57:56,840 --> 00:58:07,050 That's great. I'm just scrolling through the questions. 495 00:58:07,050 --> 00:58:12,740 You see the questions, are there any that today is one that has got lots of votes about surveillance and privacy? 496 00:58:12,740 --> 00:58:19,440 OK. I haven't had that one you to read it out. How do you navigate people's concerns of surveillance? 497 00:58:19,440 --> 00:58:26,850 Certain countries that have been successful with contact tracing have more explicit surveillance of its peoples. 498 00:58:26,850 --> 00:58:31,740 But in the US and probably much of Europe, individuals are very forthright about privacy. 499 00:58:31,740 --> 00:58:36,150 How should people feel about these technologies and privacy? We kind of discussed that a little bit. 500 00:58:36,150 --> 00:58:48,720 But I think I think there are ways of. That is a challenge for the scientific community to to find ways of of doing and prevention we 501 00:58:48,720 --> 00:58:56,250 want and getting the generalisable in for information we want without invading people's privacies, 502 00:58:56,250 --> 00:59:00,330 because people are also very forthright that they want the data, they want the information. 503 00:59:00,330 --> 00:59:06,270 They want to know is the scale risk, is my skull risky? You know, people say, you know, it's quite interesting. 504 00:59:06,270 --> 00:59:11,370 I find wonder people. On the one hand, one person doesn't need privacy. 505 00:59:11,370 --> 00:59:18,630 And I you know, I'm a great kind of George Orwell. I don't want to live in a in a surveillance, authoritarian society. 506 00:59:18,630 --> 00:59:21,720 That's very important if you're thinking about future to me. 507 00:59:21,720 --> 00:59:28,380 But on the other hand, you know, if there's an outbreak in in a local school, people really want to know the information. 508 00:59:28,380 --> 00:59:32,510 Was my child playing with that, you know, and and so on and so forth. 509 00:59:32,510 --> 00:59:39,930 So and that there's a balance in between those two things. 510 00:59:39,930 --> 00:59:44,220 But one of the really interesting things I think, going forward, as I've seen, is, 511 00:59:44,220 --> 00:59:51,960 is algorithmically search to one way is to sort of explicitly regulate that balance the same way we regulate whenever, 512 00:59:51,960 --> 00:59:57,660 you know, whenever any human rights you have, you know, you always have trade-offs. 513 00:59:57,660 --> 01:00:07,060 So you can explicitly negotiate that trade off. But also, there are great ways of actually and sort of getting your cake and eating it. 514 01:00:07,060 --> 01:00:13,400 Again, I say I'm getting the information. It's worth noting that the acts in different countries are very different. 515 01:00:13,400 --> 01:00:18,030 Yeah. That that some of those apps that have been used, particularly in East Asia, 516 01:00:18,030 --> 01:00:25,890 are storing and retaining very different kinds of data to the ones that are being Eastern Europe. 517 01:00:25,890 --> 01:00:31,110 And it's been any discussion of of sort of data sunsetting. 518 01:00:31,110 --> 01:00:39,540 So the idea that data that is kept or isn't used for the purposes of gaining information during an outbreak would have 519 01:00:39,540 --> 01:00:50,750 algorithmically at the software level some kind of fixed lifespan and would disappear after it's effectively not useful. 520 01:00:50,750 --> 01:00:55,510 And so there is very active discussion about sunsetting. 521 01:00:55,510 --> 01:01:05,130 And I think to some extent, the new resolution with this particular contact tracing apps has been to go towards privacy. 522 01:01:05,130 --> 01:01:14,280 So not collecting the information in the first place. Know as has been even better than sunsetting in terms of privacy. 523 01:01:14,280 --> 01:01:23,820 But I think, again, that's not straightforward because you have to there's some information that, you know, 524 01:01:23,820 --> 01:01:31,880 you want to keep because your you're helping the next group of people that maybe probably will be us or, 525 01:01:31,880 --> 01:01:39,620 you know, involve many of the many of us, because the next pandemic won't be that long into the future, I think. 526 01:01:39,620 --> 01:01:51,170 I don't know what your opinion is, so. That discussion requires requires quite careful thought, 527 01:01:51,170 --> 01:01:57,230 and I think I think the key thing is that people want to know that the process is relatively transparent and, 528 01:01:57,230 --> 01:02:04,060 you know, and properly overseen by by, you know, members of the public, bioethicists and so on. 529 01:02:04,060 --> 01:02:10,180 And I think if we can have a sort of mature discussion around the value of these data and whether they're sensitive 530 01:02:10,180 --> 01:02:17,050 and who they're valuable for and what how they can be misused and what we can do to stop that from happening, 531 01:02:17,050 --> 01:02:24,030 then, you know, a consensus can be reached. 532 01:02:24,030 --> 01:02:30,590 Yeah. I wholeheartedly agree. 533 01:02:30,590 --> 01:02:37,800 And we'll take that as an opportunity to wrap up the proceedings of our conversation. 534 01:02:37,800 --> 01:02:43,110 Let me just thank you again, Cristoff, for an enlightening and fascinating talk. 535 01:02:43,110 --> 01:02:47,790 I'd like to thank all of the audience for for watching and listening. 536 01:02:47,790 --> 01:02:55,320 Thank you for joining us. And special thanks to those of you that provided some questions at the end. 537 01:02:55,320 --> 01:03:00,090 I'm sorry we weren't able to get through all of them today. 538 01:03:00,090 --> 01:03:06,810 I hope you can find some answers to some of those questions in the near future. 539 01:03:06,810 --> 01:03:10,920 And I have one final announcement before we disappear. 540 01:03:10,920 --> 01:03:23,910 And that is to announce the final talk in this series of conversations, which is with Professor Julian Saville Eskew and Dr. Sam Vandersloot. 541 01:03:23,910 --> 01:03:29,250 And they'll be in conversation on Thursday, the 3rd of December at 5:00 pm. 542 01:03:29,250 --> 01:03:37,340 And they will be talking about mandatory 19 vaccination, the arguments for and against. 543 01:03:37,340 --> 01:03:48,600 And if you want to register for that event, please press the green button at the bottom of the screen that says next event in the series. 544 01:03:48,600 --> 01:03:52,770 So, again, all that's left is for me to thank Cristoff. 545 01:03:52,770 --> 01:03:56,850 Thanks, everyone, for listening. And I hope you all have a great evening. 546 01:03:56,850 --> 01:03:58,067 Goodbye from.