1 00:00:00,360 --> 00:00:09,330 Louis gripped his coffee mug. The liquid inside, slowly getting colder in his hands, had been called in early, very early, 2 00:00:09,330 --> 00:00:16,470 and the usual office chatter had been replaced by hushed conversations held rapidly behind closed doors. 3 00:00:16,470 --> 00:00:25,110 Yes, there was something new in the air. The Pasteur Institute's today attention, a sense of unease. 4 00:00:25,110 --> 00:00:32,220 He was picking up more whispers about the cases in Guinea. Of course, everyone had known about those since the start of the year. 5 00:00:32,220 --> 00:00:37,920 But these rumours were different. These rumours were saying that the unknown illness. 6 00:00:37,920 --> 00:00:44,680 Well, it wasn't unknown anymore. Joanna, do you know what's happening? 7 00:00:44,680 --> 00:00:50,430 As his colleague walked past, he caught her eye and murmured his question in a muted, secretive tone. 8 00:00:50,430 --> 00:01:00,820 If confirmed as Louis this morning and say, the Ebola virus, it looks like it's spreading. 9 00:01:00,820 --> 00:01:10,240 Welcome to 2014 and the last episode in our history of ending the outbreak we're focussing on today is one 10 00:01:10,240 --> 00:01:18,280 you're likely to remember both because it happened to the and because the disease has never really gone away. 11 00:01:18,280 --> 00:01:26,650 While the event will cover ended in 2016, this virus has caused an outbreak nearly every year. 12 00:01:26,650 --> 00:01:29,470 You are, of course, talking about Ebola. 13 00:01:29,470 --> 00:01:40,990 And given our discussion at the start of this year about whether this may have been caused, the plague that we have in some ways come full circle. 14 00:01:40,990 --> 00:01:46,120 Our guides today have been working at the forefront of tackling the Ebola virus. 15 00:01:46,120 --> 00:01:53,660 Dr. Kevin de Cock. We've already met Surplused, the team leader at the Centres for Disease Control and Prevention, 16 00:01:53,660 --> 00:02:00,100 for their Ebola response in Liberia, and Dr. Keiji, who is currently a senior immunologist. 17 00:02:00,100 --> 00:02:11,600 Oxford Ebola vaccine. First, though, as we often do, let's cheque in with Dr. Bloche Obuchi about what this disease actually means. 18 00:02:11,600 --> 00:02:15,700 Ebola virus disease is a severe disease caused by the Ebola virus, 19 00:02:15,700 --> 00:02:21,310 which is a member of the fight of virus family, and it occurs in humans and also other primates. 20 00:02:21,310 --> 00:02:28,690 The disease emerged in 1976, almost simultaneous outbreaks in the DRC and Sudan at the time. 21 00:02:28,690 --> 00:02:32,260 The incubation period is around two to 21 days. 22 00:02:32,260 --> 00:02:41,800 And the onset of the illness, you have a non-specific picture fever, headache, muscle pain, suffering, intense weakness. 23 00:02:41,800 --> 00:02:44,830 Sometimes that can be diarrhoea and vomiting present. 24 00:02:44,830 --> 00:02:54,790 Some people develop rash red eyes because they can have derange kidney, liver function and also internal and external bleeding rhinovirus. 25 00:02:54,790 --> 00:03:02,950 Disease is fatal, about 40 to 90 percent of all critically ill cases that this depends on the virus species. 26 00:03:02,950 --> 00:03:07,840 Also how old the person is and those of other factors. 27 00:03:07,840 --> 00:03:17,440 And it was fascinating to hear Bloche. And then Kevin and Kiki talk through what we do and still don't know about where Ebola might have come from. 28 00:03:17,440 --> 00:03:24,700 There are many species of Ebola or several known species of the better, four of which had been meant to cause disease in humans. 29 00:03:24,700 --> 00:03:32,620 It's thought to be, as you know, six. So that's an infectious disease which is caused by a pathogen that is jumped from a non-human animal to a human. 30 00:03:32,620 --> 00:03:37,750 Although the natural reservoir is unknown, despite extensive investigations, 31 00:03:37,750 --> 00:03:42,430 currently non-human primates have been seen as the source of human infection. 32 00:03:42,430 --> 00:03:46,390 However, they're not thought to be the reservoir because when they develop Ebola, 33 00:03:46,390 --> 00:03:52,490 they also get fatal illnesses and they die essentially one house and the animal reservoir, 34 00:03:52,490 --> 00:03:57,280 they are called a reservoir because they tolerate the pathogen really well. 35 00:03:57,280 --> 00:04:06,070 And that means and that they they is longer and therefore able to then act as a source of infection for other species. 36 00:04:06,070 --> 00:04:10,420 So no one knows exactly what the reservoir is, the virus. 37 00:04:10,420 --> 00:04:14,350 We don't know the natural reservoir. It's probably a bat. It's probably a fruit. 38 00:04:14,350 --> 00:04:22,750 But it's a very similar virus to Marburg. Virus in the reservoir is more definite from Marburg, but it's probably a fruit bat. 39 00:04:22,750 --> 00:04:27,130 And it's it's an infection that's, you know, natural in the forest. 40 00:04:27,130 --> 00:04:34,780 And there is a reservoir there. We must expect that there will be further outbreaks and we have to be able to contain them. 41 00:04:34,780 --> 00:04:38,590 I don't know if it's but me. It's definitely been confirmed. 42 00:04:38,590 --> 00:04:46,390 I must admit, at the time, the anecdote was that it was a kid playing in a tree. 43 00:04:46,390 --> 00:04:55,610 Webb bats feasted and there was lots of faeces around and that it might have been picked up and contaminated faeces that way. 44 00:04:55,610 --> 00:05:02,980 The professor in the case of any Ebola outbreak is usually for in contact with blood or secretions or organs or opposition. 45 00:05:02,980 --> 00:05:12,010 It's from an infected animal. She's in the first case and I think the first case in West Africa was likely to be via exposure to bats. 46 00:05:12,010 --> 00:05:20,800 Then the virus becomes transmitted from person to person, from Armitt contact with blood secretions, organs and bodily fluids. 47 00:05:20,800 --> 00:05:29,590 And people can also become infected if they come into contact with objects, soiled clothing, things have been contaminated, most infected secretions. 48 00:05:29,590 --> 00:05:36,760 That's why health care workers tend to be the most affected subgroup of people during epidemics. 49 00:05:36,760 --> 00:05:42,190 Then you also have some cultural practises which play a role in transmission. I think it's been mentioned before. 50 00:05:42,190 --> 00:05:48,880 So you have traditional burial practises. So mourners come and they have direct contact with the bodies. 51 00:05:48,880 --> 00:05:57,040 They wash the deceased. And the bodies of those that have died of Ebola still are highly infectious with Ebola. 52 00:05:57,040 --> 00:06:04,410 I think in the West African outbreak. This this. Practise did cause the propagation of the of the outbreak. 53 00:06:04,410 --> 00:06:13,700 Wilson, talk about the 2014 outbreak, but first I wanted to ask Kevin when we first discovered how deadly a threat Ebola posed. 54 00:06:13,700 --> 00:06:22,650 I mean, the first recognised epidemic, which really began as sort of gone down as a legend almost in global health history, 55 00:06:22,650 --> 00:06:35,000 was in 1976 in the quarter province of western DRC, northwestern DRC, in a small settlement called Yambuku. 56 00:06:35,000 --> 00:06:39,990 It was a Belgian missionary station with a hospital and a school. 57 00:06:39,990 --> 00:06:45,900 And about 18 missionary staff, nuns and priests. 58 00:06:45,900 --> 00:06:51,210 An outbreak of an unknown disease occurred late in the year, in the autumn. 59 00:06:51,210 --> 00:06:54,960 I think it was a schoolteacher who I imagine it may need to be corrected on that. 60 00:06:54,960 --> 00:07:04,440 But an individual came into the hospital and died. Then other hospital staff and other patients became ill and died. 61 00:07:04,440 --> 00:07:08,880 And it was apparent within a few weeks a very severe epidemic was occurring. 62 00:07:08,880 --> 00:07:14,010 The Ministry of Health in Kinshasa was alerted and sent to a team. 63 00:07:14,010 --> 00:07:18,630 And long story short, an international investigation was mounted. 64 00:07:18,630 --> 00:07:24,150 The virus was isolated. It was called Ebola after a name of a local river. 65 00:07:24,150 --> 00:07:34,410 And it was a very severe outbreak, widely described and talked about was wrapped up within a few weeks or months. 66 00:07:34,410 --> 00:07:42,540 A lot of field investigations. I think there were there were over 300 cases and something like 280 deaths by the time it was all over. 67 00:07:42,540 --> 00:07:50,850 And that was the first documented outbreak, something like eleven out of 18 or so of the missionary staff actually died. 68 00:07:50,850 --> 00:07:57,060 But since 1976, there've been about 29 or so documented outbreaks. 69 00:07:57,060 --> 00:08:06,540 One very interesting observation that I think merits more attention or discussion is that of those 29 outbreaks since 1976, 70 00:08:06,540 --> 00:08:10,890 they've accounted for close to 35000 cases, cumulative. 71 00:08:10,890 --> 00:08:15,870 Over 90 percent of those cases have actually occurred in the last six years. 72 00:08:15,870 --> 00:08:25,530 The huge outbreak in West Africa and the second largest outbreak was the DRC outbreak in eastern Congo from 2018 to 2020. 73 00:08:25,530 --> 00:08:29,250 So that's striking. It suggests something's changed or something's different. 74 00:08:29,250 --> 00:08:38,280 The West African outbreak resulted in something like between 28 and twenty nine thousand cases and between eleven and twelve thousand deaths. 75 00:08:38,280 --> 00:08:44,040 A huge geographic area affected, including cities and including capital cities. 76 00:08:44,040 --> 00:08:51,850 I mean, Conakry and Guinea, Freetown, Sierra Leone and Monrovia in Liberia all had outbreaks. 77 00:08:51,850 --> 00:09:00,150 You know, all of that was pretty unprecedented. And then in DRC, in 2018 to 2020, again, over 3000 cases, very, 78 00:09:00,150 --> 00:09:09,210 very large geographic area and cities affected because places like Bhutan, Bob and Beneš, which many people wanted heard of. 79 00:09:09,210 --> 00:09:14,990 I was absolutely staggered when I went to Tembo and saw that this is a city of a million people. 80 00:09:14,990 --> 00:09:16,080 So things have changed. 81 00:09:16,080 --> 00:09:24,480 And, you know, the simple way and the classic way of thinking about disease epidemiology is that it's the interaction of the agent. 82 00:09:24,480 --> 00:09:33,990 That's the virus, the host. That's us. I mean, inhuman epidemics and the environment, which includes the social environment. 83 00:09:33,990 --> 00:09:38,760 And, you know, you have to ask, well, why why did why do we have the outbreak in West Africa? 84 00:09:38,760 --> 00:09:43,260 That's that's the farthest west that Ebola has ever been described. 85 00:09:43,260 --> 00:09:51,990 Apart from the big outbreak, the only time had been described in West Africa was a in a Swiss veterinarian in the 1990s. 86 00:09:51,990 --> 00:09:57,990 And she got infected doing an autopsy on a dead chimpanzee who died in the Thai forest. 87 00:09:57,990 --> 00:10:02,400 Chimps get affected by Ebola and their groups can be severely affected. 88 00:10:02,400 --> 00:10:08,190 So what changed to to push it that far west and why these huge geographic areas? 89 00:10:08,190 --> 00:10:18,300 And I think one of the reasons that I think one of the issues for the geographic extension is population mobility, not least because of motorcycles. 90 00:10:18,300 --> 00:10:27,750 You go to you go to the DRC in a place like Goma. It is just staggering the thousands and thousands of motorcycles and the distances they can travel. 91 00:10:27,750 --> 00:10:38,430 So it's rather striking observation. Two striking observations, the geographic extension and the very large outbreaks, I think, merit more notice. 92 00:10:38,430 --> 00:10:44,310 It's fascinating what kinds of things can play a major role in the spread of disease. 93 00:10:44,310 --> 00:10:53,400 Moving onto the focus of today's episode, I asked first Katie and then Katie, what do we know about how the 2014 outbreak began? 94 00:10:53,400 --> 00:10:59,010 Say the first case in this outbreak was thought to be a young child, a toddler, 95 00:10:59,010 --> 00:11:07,410 somewhere in very rural Guinea in December and about, yeah, in December 2013, he became the first case to be identified. 96 00:11:07,410 --> 00:11:15,210 And there was a small number of cases of diarrhoea in that population and it created a small alert in that area. 97 00:11:15,210 --> 00:11:25,260 But nothing, you know, massive. And then it was confirmed after the disease had actually spread to Conakry in in sort of March ships the next year. 98 00:11:25,260 --> 00:11:32,340 And by that time, it was already in a major city and the outbreak was declared shortly after that. 99 00:11:32,340 --> 00:11:35,430 But those first few cases were kind of identified retrospectively, if you like. 100 00:11:35,430 --> 00:11:40,680 They were identified as an unidentified disease, but not necessarily thought to be Ebola. 101 00:11:40,680 --> 00:11:50,880 Well, retrospectively, the first case probably occurred just before Christmas in twenty thirteen in Guinea, 102 00:11:50,880 --> 00:11:55,680 in the forest area of Guinea, in a little village called Melley Undo. 103 00:11:55,680 --> 00:12:08,700 And now that forest area is close to where the three countries, the boundaries of the three countries come together with Sierra Leone and Liberia, 104 00:12:08,700 --> 00:12:13,980 loafer county in Liberia within a few weeks of that initial case. 105 00:12:13,980 --> 00:12:21,540 And this is retrospective analysis by Dr. WHL investigator trying to trace what happened. 106 00:12:21,540 --> 00:12:26,700 Within a few weeks, there had been two or three further generations of cases. 107 00:12:26,700 --> 00:12:34,710 Infection had reached the town of Grecco Do. In Guinea and very quickly had reached Conakry, the capital. 108 00:12:34,710 --> 00:12:46,050 All of that was in the early months of 2014. In the latter half of March, some cases were reported from Liberia, from love for county up in the north. 109 00:12:46,050 --> 00:12:51,750 And there was actually an investigation by an international group. 110 00:12:51,750 --> 00:12:56,160 A colleague of mine, Joel Montgomery, who was working in Kenya. 111 00:12:56,160 --> 00:13:00,480 I was the country director, so I was his immediate boss locally. 112 00:13:00,480 --> 00:13:08,500 He was asked to go to Liberia and went for a couple of weeks and it seemed that the outbreak was was dying out. 113 00:13:08,500 --> 00:13:14,970 You know, there was no major. They did not appear to be a major emergency. But in the following months, things changed. 114 00:13:14,970 --> 00:13:19,950 And clearly, you know, the world did not pay enough attention. 115 00:13:19,950 --> 00:13:26,310 It began to fester in Sierra Leone and cases were increasing in Liberia. 116 00:13:26,310 --> 00:13:35,880 I remember actually in late June reading a CDC report, there's a known internal daily update of epidemics going on around the world. 117 00:13:35,880 --> 00:13:44,220 I remember reading about, you know, ongoing transmission, apparently in Guinea and Liberia and thinking, you know, really we ought to be doing. 118 00:13:44,220 --> 00:13:51,450 Sounds like more ought to be being done about this. I actually wrote this to some of my senior colleagues back in Atlanta. 119 00:13:51,450 --> 00:13:58,110 Anyway, we around the same time, we actually got a request from the Ministry of Health through the U.S. embassy in Monrovia, 120 00:13:58,110 --> 00:14:06,630 a request to CDC for assistance. I happened to be back in Atlanta in early July and I was asked, well, can you go to Liberia? 121 00:14:06,630 --> 00:14:13,260 And I said, well, OK. I actually arrived there. I remember exactly that just happened to be my sister's birthday. 122 00:14:13,260 --> 00:14:18,060 I arrived on the 16th of July. I flew from Kenya, arrived on the 16th. 123 00:14:18,060 --> 00:14:24,000 And within a couple of days, a few other people arrived, four or five A.I.S officers. 124 00:14:24,000 --> 00:14:28,560 These guys or women doing their two year initial training programme. 125 00:14:28,560 --> 00:14:36,600 And we took it from there. So where did you start? You know, you arrive in a place and you sort of you have to figure it out for yourself. 126 00:14:36,600 --> 00:14:43,170 I mean, there is a there is a standard way, a logical way of investigating in an epidemic. 127 00:14:43,170 --> 00:14:48,090 And it's the best analogy for it is it's not as a as a medical student. 128 00:14:48,090 --> 00:14:54,210 You're taught how to examine a patient in clinical medicine. And there's a there's a you know, how to take a history and how to examine a patient. 129 00:14:54,210 --> 00:14:58,450 And there's a very systematic way of doing it. And the same is actually true for an outbreak. 130 00:14:58,450 --> 00:15:01,750 There's some very logical series of steps. 131 00:15:01,750 --> 00:15:07,290 You know, the first question is, is there an epidemic like they're asking, is this patient really sick or not? 132 00:15:07,290 --> 00:15:10,740 Sometimes you get asked to investigate or to go somewhere. 133 00:15:10,740 --> 00:15:14,580 And actually there isn't an epidemic. It's just that reporting practise has changed. 134 00:15:14,580 --> 00:15:20,580 Or you have a new Kiene public health person who actually does his job or something like that. 135 00:15:20,580 --> 00:15:24,990 Is there an epidemic? Is it due to what you think it's. Is it is it due to what you've been told. 136 00:15:24,990 --> 00:15:31,350 It's stupid. Is there a case definition? And can you organise the data in time, place and person? 137 00:15:31,350 --> 00:15:38,150 When did it start? What's new in time? The classic thing to do is to draw an epidemic curve place. 138 00:15:38,150 --> 00:15:42,850 Where is it person who's affected age, sex and other. 139 00:15:42,850 --> 00:15:47,050 Demographic characteristics. So, you know, you try and organise yourself that way. 140 00:15:47,050 --> 00:15:55,270 But that's easier said than done and it certainly was much easier said than done in Liberia initially and in fact, in the whole epidemic. 141 00:15:55,270 --> 00:16:00,390 Because you look at an epidemic curve of the outbreak, the whole West African outbreak. 142 00:16:00,390 --> 00:16:04,390 And, you know, we've we've published one. There are published versions of it. 143 00:16:04,390 --> 00:16:11,290 And you sort of look at it, you think, well, how close to reality is it is really because of underreporting under recognition, 144 00:16:11,290 --> 00:16:14,260 inadequate laboratory capacity, et cetera, et cetera. 145 00:16:14,260 --> 00:16:22,270 So the figure of the overall figure I gave of, you know, twenty eight thousand six hundred and forty six cases, how accurate is that? 146 00:16:22,270 --> 00:16:27,970 I'm not really sure. I suspect it's an underestimate. But by how much is impossible to say. 147 00:16:27,970 --> 00:16:33,940 I was keen to hear more about Kevin's personal experience during those early days of the outbreak. 148 00:16:33,940 --> 00:16:41,470 The early situation in Monrovia was truly extraordinary. As I've said, firstly, the country is so very, very weak. 149 00:16:41,470 --> 00:16:47,380 It had gone through two civil wars and infrastructure was very weak, 150 00:16:47,380 --> 00:16:52,750 very poor physical infrastructure, still a lot of damage from the fighting and so on. 151 00:16:52,750 --> 00:16:55,510 Very few highly trained individuals. 152 00:16:55,510 --> 00:17:04,540 You know, again, one of the one of the 10 weakest countries on Earth in relation to development, human development and capacity. 153 00:17:04,540 --> 00:17:14,290 And literally every day those first 10 days I was there were remarkable because every day something a stunning thing would happen. 154 00:17:14,290 --> 00:17:20,590 For example, I had been there less than a week, a colleague and I worked particularly closely with I mean, 155 00:17:20,590 --> 00:17:24,790 we had the ISI officers had to assign them tasks and so on. 156 00:17:24,790 --> 00:17:31,390 And I worked at the most senior of this group of folks who was with me was a colleague called Satish Pinay. 157 00:17:31,390 --> 00:17:36,280 And Satish was really this sort of he was he was a linchpin in our work. 158 00:17:36,280 --> 00:17:39,880 He and I would go to the task force meeting at the Ministry of Health, 159 00:17:39,880 --> 00:17:45,130 and they had formed a task force and we'd go every day and it was rather disorganised. 160 00:17:45,130 --> 00:17:48,970 Anybody could come. It might be as many as 80 people in the room. 161 00:17:48,970 --> 00:17:55,210 Sometimes the president showed up and the minister was there and somebody ran the meeting and there was an agenda. 162 00:17:55,210 --> 00:18:01,630 But the next day there wouldn't really be any follow up and it would sort of be a repeat of the day before. 163 00:18:01,630 --> 00:18:06,670 And I said to my colleague Satish, after a few days, I said, look, this isn't gonna work. 164 00:18:06,670 --> 00:18:11,080 What we really need is an incident management system. 165 00:18:11,080 --> 00:18:16,780 Now, an incident management system is a very structured way of dealing with emergencies. 166 00:18:16,780 --> 00:18:23,730 And it's it's how CDC does it when we we have an up an emergency operations centre in Atlanta. 167 00:18:23,730 --> 00:18:28,720 And when there's a severe health event that says that centre gets activated, 168 00:18:28,720 --> 00:18:33,430 it's sort of the nerve centre of the response, if you will, information centre. 169 00:18:33,430 --> 00:18:43,110 There is one person in charge, the incident manager, with a very structured organisational structure underneath him or her to deal with logistics. 170 00:18:43,110 --> 00:18:49,000 In this case, with epidemiology, with laboratory, with communications, et cetera, et cetera. 171 00:18:49,000 --> 00:18:55,590 And the incident manager reports afterwards to the minister, the president, the CDC director, whoever, whoever. 172 00:18:55,590 --> 00:18:59,620 But it was a very structured system. And I said to him, look, this isn't gonna work. 173 00:18:59,620 --> 00:19:06,460 We have to go and see the minister and advise him to to change the structure and have an incident management system. 174 00:19:06,460 --> 00:19:10,630 I remember very clearly, I think I was on a Wednesday, it's about a week after it arrived, 175 00:19:10,630 --> 00:19:13,480 went to his office on the third floor of the Ministry of Health, 176 00:19:13,480 --> 00:19:19,720 sat down, literally opened my mouth when the secretary came in and said, we have to evacuate the building. 177 00:19:19,720 --> 00:19:27,820 The buildings on fire. The minister goes, who is this was, I think, a seventy six or seven seven year old surgeon. 178 00:19:27,820 --> 00:19:33,370 He was a very good man, actually. Very good man. He sort of starts shuffling around his computer and so on. 179 00:19:33,370 --> 00:19:35,090 I say to Satish, we got to get out of here. 180 00:19:35,090 --> 00:19:41,950 As I started hearing people shouting and more commotion and I saw people streaming out of the building through the window. 181 00:19:41,950 --> 00:19:46,920 So we go down the stairs and by now there's smoke in the hallway, in the stairwell. 182 00:19:46,920 --> 00:19:54,220 And it actually made it made us cough, got out of the building and hundreds of people in the car park and get our folks together, 183 00:19:54,220 --> 00:19:59,440 find all our CDC folks and head out pretty smartly in two or three vehicles we had. 184 00:19:59,440 --> 00:20:07,750 And it later turned out that somebody had actually piled all the plastic chairs together in the conference room where we had been meeting, 185 00:20:07,750 --> 00:20:14,080 poured kerosene over them and set the building on fire. I never quite found out what the reason was, 186 00:20:14,080 --> 00:20:19,690 although rumour was that it was a disgruntled or affected member of the public who 187 00:20:19,690 --> 00:20:25,060 had lost a relative to Ebola and was just very angry about the whole situation. 188 00:20:25,060 --> 00:20:31,480 But it sort of set the tone of the whole environment and that the the element of fear that was in the air, 189 00:20:31,480 --> 00:20:35,830 I mean, the tension that you could literally feel wherever you went, it was remarkable. 190 00:20:35,830 --> 00:20:41,680 And it's I it was something I, despite many years of experience, is something I'd never experienced to that degree. 191 00:20:41,680 --> 00:20:46,090 So but every day. Something else would happen that you think, I just can't believe this is happening. 192 00:20:46,090 --> 00:20:54,040 It was around that time that very famous episode of the rather senior well-connected Liberian individual who flew to Lagos, 193 00:20:54,040 --> 00:20:59,040 visibly ill, flew to Lagos, collapsed in the airport, was taken to a hospital. 194 00:20:59,040 --> 00:21:09,760 A correct diagnosis was made by the consultant physician in Lagos, but a secondary cluster of infections of Ebola was established in Lagos. 195 00:21:09,760 --> 00:21:15,040 And I think the total number of cases where I counted was 18 or 20, something like that. 196 00:21:15,040 --> 00:21:23,320 Fortunately, only two or three generations of cases. Nigeria responded very, very well to that outbreak, contained it. 197 00:21:23,320 --> 00:21:28,900 The consultant physician who correctly made the diagnosis died from Ebola. 198 00:21:28,900 --> 00:21:35,770 And the fact that they got on top of it so quickly was unquestionably the field epidemiologist training programme. 199 00:21:35,770 --> 00:21:40,690 The capacity that had been built and the resources of the polio eradication initiative in 200 00:21:40,690 --> 00:21:47,380 Nigeria all contributed in a major way to contain that epidemic very without outbreak. 201 00:21:47,380 --> 00:21:52,720 Very quickly, I mean, the thoughts of Ebola spreading in Nigeria, as Lassa has done, 202 00:21:52,720 --> 00:21:58,360 for example, this sort of Ebola spreading, it would be, you know, truly frightening. 203 00:21:58,360 --> 00:22:05,560 And very quickly, Kevin got used to cooperating with other organisations to try to get the outbreak under control. 204 00:22:05,560 --> 00:22:10,940 One of the first things you do when you arrive, obviously, is gonna introduce yourself and look around, 205 00:22:10,940 --> 00:22:15,600 you know, is this really Ebola and how do we know where is it being tested, et cetera? 206 00:22:15,600 --> 00:22:21,100 So, you know, we've done a bit of all of that and had visited a couple of the local hospitals, 207 00:22:21,100 --> 00:22:27,250 including a facility called Elwha, which stands for Eternal Love Africa. 208 00:22:27,250 --> 00:22:39,370 It was a faith based organisation that ran the hospital and they had seen some Ebola cases and had set up a very rudimentary Ebola treatment unit. 209 00:22:39,370 --> 00:22:49,470 Now, the folks, the folks who have really experienced in dealing with Ebola treatment and looking after patients, which is not what CDC does, 210 00:22:49,470 --> 00:23:01,780 a group that really is well recognised for this is MSF medicine support yet and MSF were heroic in West Africa, but by this time very, very stretched. 211 00:23:01,780 --> 00:23:08,500 They had been active in loafer county and across the border in in Guinea in could do. 212 00:23:08,500 --> 00:23:17,710 But they were absolutely stretched. And what they did, rather, and this actually illustrates the the uniqueness of this outbreak of this epidemic. 213 00:23:17,710 --> 00:23:22,900 They had worked with another organisation called Samaritan's Purse, 214 00:23:22,900 --> 00:23:29,110 which is an American faith based organisation, not politically and philosophically. 215 00:23:29,110 --> 00:23:33,970 MSF and Samaritan's Purse are about as different as chalk and cheese. 216 00:23:33,970 --> 00:23:38,890 Samaritan's Purse was actually set up by the evangelist Billy Graham's son. 217 00:23:38,890 --> 00:23:48,790 It's a very evangelical organisation. They are very connected, very well connected politically to the religious right in Washington. 218 00:23:48,790 --> 00:23:53,050 They've done some very, very good work in many different places. 219 00:23:53,050 --> 00:23:59,920 They had worked with MSF to get their staff who had been in Liberia for a very long time and knew the country well. 220 00:23:59,920 --> 00:24:09,320 They had worked with MSF to get trained up in Ebola and be able to set up any T.U., an Ebola treatment unit and care for patients. 221 00:24:09,320 --> 00:24:13,240 Anyway, a few days after the ministry episode I described, 222 00:24:13,240 --> 00:24:20,260 I was asked to chase up a lab result by Samaritan's Purse colleagues because we were helping. 223 00:24:20,260 --> 00:24:26,950 We were coordinating lab work, not actually doing it, but had managed to sort of persuade people to work together and stuff. 224 00:24:26,950 --> 00:24:31,610 So I chase up this resolved and get it to two to then eventually learn. 225 00:24:31,610 --> 00:24:38,050 It actually was a false name and that the actual specimen came from the lead doctor 226 00:24:38,050 --> 00:24:45,730 in the Samaritan's Purse group who had woken up on a Tuesday or so with fever, 227 00:24:45,730 --> 00:24:49,960 had isolated himself and eventually got tested for Ebola. 228 00:24:49,960 --> 00:24:52,930 And yes, lo and behold, was infected. 229 00:24:52,930 --> 00:25:03,130 Now, this was the first time that a expatriate health worker other than, you know, those initial nuns and priests who died in Yambuku. 230 00:25:03,130 --> 00:25:10,000 To my knowledge, this was the first time an expatriate, certainly in modern time, not an expatriate health worker, had gotten infected. 231 00:25:10,000 --> 00:25:18,190 And we then had to figure out what to do. I mean, it wasn't my decision, obviously, but we frankly, 232 00:25:18,190 --> 00:25:25,330 we did not have in place a system for dealing with the now increasing number of health care workers from outside. 233 00:25:25,330 --> 00:25:35,590 What to do with them if they got sick? Long story short, Samaritan's Purse were able to evacuate the Dr. Kent Brantly to Atlanta, to Emory University, 234 00:25:35,590 --> 00:25:42,280 which is right next to CDC, to the hospital in Atlanta, where they had set up a unit that could. 235 00:25:42,280 --> 00:25:46,300 For Ebola patients. And he was evacuated. There was a second. 236 00:25:46,300 --> 00:25:53,430 Actually, there were two other Samaritan's Purse infections. One was a Liberian hygienist who died. 237 00:25:53,430 --> 00:26:00,540 And one was a an American nurse, Nancy Writable, who also got evacuated and also survived. 238 00:26:00,540 --> 00:26:04,290 So this was all in about the first two weeks of 10 days, two weeks of being. 239 00:26:04,290 --> 00:26:09,660 There is a pretty dramatic situation. It certainly sounds dramatic. 240 00:26:09,660 --> 00:26:16,620 Meanwhile, back in Oxford, the work quickly began on researching this disease and what might be done about it. 241 00:26:16,620 --> 00:26:23,280 As Keiki reports, yes, that this stamp was from that first outbreak made their way to institute Pasteur. 242 00:26:23,280 --> 00:26:25,560 Is there a kind of visual reference centre? 243 00:26:25,560 --> 00:26:32,190 So anything that's called the viral haemorrhagic fever will go to a reference centre for presumptive identification. 244 00:26:32,190 --> 00:26:37,320 And then as soon as a case of a disease like Ebola is identified, then, you know, 245 00:26:37,320 --> 00:26:43,050 you're going to let the W.H, you know, that's the standard, a standard procedure at that time. 246 00:26:43,050 --> 00:26:49,530 It was then already spreading widely through West Africa to the two neighbouring countries of Liberian Sierra Leone. 247 00:26:49,530 --> 00:26:55,500 It was rapidly established in the capitals, which was one of the things that kind of sets us apart from other outbreaks that we've seen. 248 00:26:55,500 --> 00:27:03,780 And really by July, it was beginning to become apparent that this was going to be a bit more than a usual handful of cases in a remote region. 249 00:27:03,780 --> 00:27:13,480 I went to a holiday to France on the 1st of August, at which time the word Ebola was not widely mentioned in this institute. 250 00:27:13,480 --> 00:27:18,390 And I was away for two weeks. And by the time we came back, they were well on our way to, you know, 251 00:27:18,390 --> 00:27:24,300 undertaking some work to participate in evaluating some vaccines that were available before vaccines. 252 00:27:24,300 --> 00:27:30,270 And later, the teams on the ground were working on more standard public intervention. 253 00:27:30,270 --> 00:27:39,000 Historically, these outbreaks have always been brought under control through community engagement and basic public health measures. 254 00:27:39,000 --> 00:27:46,860 There are no silver bullets for these types of diseases, even with vaccines, because they are hard to access places with poor infrastructure. 255 00:27:46,860 --> 00:27:51,930 Which means even if you've got a vaccine available, as we often talk about with with vaccine deployment, 256 00:27:51,930 --> 00:27:56,180 it's that last mile, five miles, 10 miles, delivering the vaccine. 257 00:27:56,180 --> 00:28:05,340 That's always the most difficult. And there's problems persist. So in terms of interventions and control measures prior to vaccines, I mean, 258 00:28:05,340 --> 00:28:08,460 if you look at most of the outbreaks that have happened in Central Africa, 259 00:28:08,460 --> 00:28:18,870 they've been brought under control through usual processes of contact tracing, safe burials, implementation, better sanitation and all those. 260 00:28:18,870 --> 00:28:22,730 There's real basic tenets of public health. An epidemiologist, really. 261 00:28:22,730 --> 00:28:28,230 And let me just start by quickly saying, how do we actually control Ebola with, you know, with what we know today? 262 00:28:28,230 --> 00:28:31,830 The basics are the same. Isolate the sick safely. 263 00:28:31,830 --> 00:28:38,190 Bury the dead. Follow the contacts and isolate them immediately if they get sick, 264 00:28:38,190 --> 00:28:48,900 that it is the isolation of the sick that drops the basic reproductive rate below one and extinguishes will extinguish transmission. 265 00:28:48,900 --> 00:28:51,930 And you probably from the modelling that's been done at CDC, 266 00:28:51,930 --> 00:28:59,260 you probably need to achieve 70 percent or so rapid isolation within three days of symptom onset to, 267 00:28:59,260 --> 00:29:04,710 you know, to get there a lot more difficult than it sounds, especially in these difficult areas. 268 00:29:04,710 --> 00:29:06,540 In addition to those three things, 269 00:29:06,540 --> 00:29:13,680 we have to strengthen infection control in health care settings because in some situations there's a lot of transmission in health care settings, 270 00:29:13,680 --> 00:29:21,780 probably in West Africa, between 10 and 15 percent, probably 10 percent or so of people with Ebola and deaths. 271 00:29:21,780 --> 00:29:23,040 We're actually in health care workers. 272 00:29:23,040 --> 00:29:30,870 So strengthen infection control, provide treatment for the people with Ebola that we now have better therapeutics, 273 00:29:30,870 --> 00:29:35,340 particularly the monoclonal antibody preparations. And finally, we have a vaccine. 274 00:29:35,340 --> 00:29:40,260 So vaccinate the contacts of cases and vaccinate health care workers. 275 00:29:40,260 --> 00:29:47,220 And increasingly today recognised vaccinate the contacts of survivors because survivors can harbour 276 00:29:47,220 --> 00:29:53,910 the virus and sometimes transmitted sexually or actually also rarely suffer recrudescence. 277 00:29:53,910 --> 00:30:02,880 So those are the basics of control. However, as Professor Brian Angas outlines, these basics of control are often easier to implement. 278 00:30:02,880 --> 00:30:09,280 In theory, the Maillol during the practical reality of the pandemic, because what I mean, again, 279 00:30:09,280 --> 00:30:16,920 what tends to happen often in West Africa was people would run away, you know, and it an Ebola outbreak. 280 00:30:16,920 --> 00:30:20,970 We would want to get as far away as possible, you know, carefully understandable. 281 00:30:20,970 --> 00:30:25,770 But as far as transmission of the disease was concerned, that was one of the worst things you could do. 282 00:30:25,770 --> 00:30:31,770 But again, asking people to stay, stay and potentially stay and die because there's no treatment is is very difficult. 283 00:30:31,770 --> 00:30:38,550 And again, you have to think what you would do in that situation as well. How would you react to being to do that? 284 00:30:38,550 --> 00:30:42,170 And similarly, how would you react to being told to do something? 285 00:30:42,170 --> 00:30:49,970 Against your culture, against religious beliefs, for example, to avoid a disease that no one has actually explained to you. 286 00:30:49,970 --> 00:30:57,450 I'm so grateful to see particularly I think it's difficult when it relates to things like sexual health, but also relates to funeral rites as well. 287 00:30:57,450 --> 00:31:05,240 And a lot of a lot of things have been hurt, seem to be related to culturally how societies deal with dead bodies, 288 00:31:05,240 --> 00:31:15,470 particularly in transmission of these things. And also, it's interesting that that something should evolve to take advantage of that weakness to HIV. 289 00:31:15,470 --> 00:31:20,930 We found that niche in sexual promiscuity, Ebola seem to find a niche. 290 00:31:20,930 --> 00:31:28,140 Funeral practises. And it always seems to be that infectious diseases particularly find a weak spot. 291 00:31:28,140 --> 00:31:32,540 That we've got and and multiply within that within that weeks. 292 00:31:32,540 --> 00:31:37,040 That isn't the only challenged tackling the rapid spread of the disease. 293 00:31:37,040 --> 00:31:46,460 Weak medical infrastructure within a country alongside the concurrent return of other diseases can make this an incredibly difficult situation. 294 00:31:46,460 --> 00:31:54,560 The proportion of doctors to people in in these kind of countries is is ridiculous. 295 00:31:54,560 --> 00:32:01,370 I think it's something like thousand patients per doctor in Sierra Leone compared with something like 400 patients. 296 00:32:01,370 --> 00:32:02,420 But doctors in the US. 297 00:32:02,420 --> 00:32:10,610 So just the capacity and the general infrastructure to treat our share information and escalate up to somebody in the National Ministry of Health, 298 00:32:10,610 --> 00:32:17,900 for example, is going to do anything about it. It is really minimal. As soon as you then have an outbreak of something like Ebola, 299 00:32:17,900 --> 00:32:23,570 the first thing that happens is the very minimal existing public health work it is going on. 300 00:32:23,570 --> 00:32:30,680 So things like, you know, childhood vaccinations, malaria prevention, all of those things just stop. 301 00:32:30,680 --> 00:32:36,500 So in addition to things like Ebola, you have resurgence of diseases like malaria, measles outbreaks, 302 00:32:36,500 --> 00:32:42,920 all those things then starts to break down along side to make a pretty dire situation a lot worse. 303 00:32:42,920 --> 00:32:49,280 And it takes time for things like vaccination campaigns to catch up even once the outbreak is contained. 304 00:32:49,280 --> 00:32:53,930 The first thing to say is the continent is extremely heterogeneous. 305 00:32:53,930 --> 00:33:00,930 I mean, we tend to sort of, you know, in global parlance, we sort of tend to treat Africa as just one big village where, 306 00:33:00,930 --> 00:33:05,180 you know, everybody lives at the same level of subsistence and it's pretty poor. 307 00:33:05,180 --> 00:33:08,030 And that's just such a misrepresentation. 308 00:33:08,030 --> 00:33:16,170 It is such a heterogeneous continent in many, many different ways and culture, economies, peoples and disease. 309 00:33:16,170 --> 00:33:25,670 So, I mean, to go back to Ebola, when I arrived in Liberia in mid-July, in 2014, I was truly shocked. 310 00:33:25,670 --> 00:33:29,730 That's a word I very rarely use in in medicine. 311 00:33:29,730 --> 00:33:35,060 I you know, I, I always tell people, you know, when I read manuscripts, for example, 312 00:33:35,060 --> 00:33:40,610 and see someone use the word dramatic, I, I always strike it out and say, look, we do medicine, we don't do drama. 313 00:33:40,610 --> 00:33:44,750 You go to drama school. I was truly shocked in Liberia by two things. 314 00:33:44,750 --> 00:33:48,380 One, the severity of the Ebola epidemic coming up. 315 00:33:48,380 --> 00:33:53,300 It was just extraordinary. But secondly, that there was nothing there. 316 00:33:53,300 --> 00:33:59,870 The infrastructure and the capacity of the country was so, so weak. 317 00:33:59,870 --> 00:34:07,370 It was I was truly surprised. And, you know, decades before I'd worked in Cote d'Ivoire, which is not only bordering Liberia. 318 00:34:07,370 --> 00:34:11,350 And that was to a couple of you know, that was several decades ago. And it was just completely different. 319 00:34:11,350 --> 00:34:15,690 You know, Liberia, Sierra Leone and Guinea, they've all had conflict. 320 00:34:15,690 --> 00:34:22,100 They've had was they've had civil strife. But they're really they have really been neglected and kind of forgotten. 321 00:34:22,100 --> 00:34:28,490 And they're at the bottom of the any scale that you see of human development, health, et cetera. 322 00:34:28,490 --> 00:34:32,690 That's very different from East Africa and certainly Kenya, which, you know, 323 00:34:32,690 --> 00:34:39,070 which has made seen extraordinary changes over the last couple of decades in terms of, 324 00:34:39,070 --> 00:34:48,060 well, firstly dealing with the AIDS epidemic, but extraordinary progress in child survival, life expectancy and a change in the pattern of disease. 325 00:34:48,060 --> 00:34:54,650 And they still have a dual pattern with a lot of infectious disease and also a 326 00:34:54,650 --> 00:34:59,090 rapidly emerging problem of non-communicable diseases cardiovascular disease, 327 00:34:59,090 --> 00:35:05,030 hypertension, diabetes, obesity, cancers, chronic respiratory disease. 328 00:35:05,030 --> 00:35:13,460 So a very mixed picture. Its development economists who are best placed to ask why are some countries developed and others not? 329 00:35:13,460 --> 00:35:17,840 But a characteristic of these Low-Income countries is weakness of systems, 330 00:35:17,840 --> 00:35:24,710 weakness of health systems, of the educational sector, under-investment in these poor management. 331 00:35:24,710 --> 00:35:30,890 And of course, if you have governance issues of corruption, if you have weakness in one sector, I mean, if you find that, you know, 332 00:35:30,890 --> 00:35:37,310 the public transport sector or the educational sector is weak, well, it's not gonna be any different in any other sector. 333 00:35:37,310 --> 00:35:41,710 So that is pervasive. Intrinsic problems of. 334 00:35:41,710 --> 00:35:49,150 System's capacity training and so on with that underlying structural problem. 335 00:35:49,150 --> 00:35:58,600 I was curious as to where the CDC and organisations like it concentrate their resources in preparing for a pandemic like Ebola. 336 00:35:58,600 --> 00:36:09,130 There are four areas where we've focussed, particularly disease surveillance and health information systems, the strengthening of laboratory systems, 337 00:36:09,130 --> 00:36:16,420 the development of the workforce, particularly in epidemiologic capacity to investigate outbreaks and things like that. 338 00:36:16,420 --> 00:36:22,570 And then fourthly, in the use of data data for making decisions, investment and implementation, 339 00:36:22,570 --> 00:36:28,720 science, if you will, operational research more broadly referred to as implementation science. 340 00:36:28,720 --> 00:36:34,420 So those are some of the areas we focussed on. And I must say, in Kenya, the country I know best. 341 00:36:34,420 --> 00:36:39,580 We've seen remarkable. The country has changed remarkably over the last couple of decades. 342 00:36:39,580 --> 00:36:51,100 Moving now towards the end of the 2014 16 Ebola outbreak, I asked Kerry how they finally started to get this disease under control in Liberia. 343 00:36:51,100 --> 00:36:58,450 Control was pretty rapidly achieved. Then there are clusters that happen and further small outbreaks. 344 00:36:58,450 --> 00:37:04,120 But by isolating the cases and getting enough Ebola treatment unit beds, the outbreak was contained. 345 00:37:04,120 --> 00:37:08,410 And then there were clusters here and there that had to be dealt with in the same way. 346 00:37:08,410 --> 00:37:14,240 And there were some secondary transmissions from Ebola survivors, including sexual transmission. 347 00:37:14,240 --> 00:37:18,130 Where is all this going? Well, the DRC has it well. 348 00:37:18,130 --> 00:37:25,450 West Africa was eventually declared Ebola free in 2016 and there were no more cases. 349 00:37:25,450 --> 00:37:30,340 The DRC has had three outbreaks since 2018. 350 00:37:30,340 --> 00:37:35,680 There was a smaller one in the Aquata province, followed by the very big one that went on for two years. 351 00:37:35,680 --> 00:37:39,820 And we're not coming to the end of the third outbreak in the last couple of years. 352 00:37:39,820 --> 00:37:44,320 That's the 11th DRC outbreak overall in a quarter. That's just coming to an end. 353 00:37:44,320 --> 00:37:51,220 Now, throughout this time, Haiti and her colleagues at Oxford have been working away on vaccine development. 354 00:37:51,220 --> 00:37:58,460 The vaccine that we were involved in, hireling was developed by the US government at the NIH and I. 355 00:37:58,460 --> 00:38:08,150 D It was commissioned under George Bush's administration as a potential defence against bioterrorism. 356 00:38:08,150 --> 00:38:11,710 So it wasn't being developed as a kind of public health intervention. 357 00:38:11,710 --> 00:38:18,970 It was on a list of microorganisms that the U.S. government thought could be went against them as a biological agent. 358 00:38:18,970 --> 00:38:24,190 And so for that reason, these vaccines were creeping through clinical development and they were creeping through. 359 00:38:24,190 --> 00:38:28,750 They'd been in development for many years before this outbreak happened. 360 00:38:28,750 --> 00:38:34,420 So all that really happened was we accelerated the process, the clinical evaluation of safety testing here, 361 00:38:34,420 --> 00:38:39,700 because we have the capacity and the expertise of evaluating Nipah back to vaccines. 362 00:38:39,700 --> 00:38:48,850 The timelines involved for this were quite phenomenal in terms of how long it took to submit the ground, get the grant reviewed, get ethical approval. 363 00:38:48,850 --> 00:38:53,050 And, you know, all of that happened in a fraction of the time it would usually take. 364 00:38:53,050 --> 00:38:58,570 And then from the time of, you know, first conceiving of the well through to first vaccination, 365 00:38:58,570 --> 00:39:02,730 last vaccination of publication of data was unprecedented at that time. 366 00:39:02,730 --> 00:39:07,360 And the Oxford team also played a key role in the manufacture of a vaccine. 367 00:39:07,360 --> 00:39:13,300 It wasn't just that we accelerated clinical trials. We accelerated the development of manufacturing as well. 368 00:39:13,300 --> 00:39:17,770 And I think one of the things about pandemics that we launched we value one of the lasting 369 00:39:17,770 --> 00:39:21,370 legacies of it is that everything just happened too slowly and the money wasn't there. 370 00:39:21,370 --> 00:39:29,410 Whereas now there is much more funding available for Outweight putting two vaccines through SEPI or through the usual routes of funding. 371 00:39:29,410 --> 00:39:39,220 But there's much more pressure to do things at a rapid pace now and get these vaccines ready and deployed, you know, in a in a reasonable timeframe. 372 00:39:39,220 --> 00:39:43,750 It sounded like this outbreak had a significant impact on vaccine development. 373 00:39:43,750 --> 00:39:46,750 It had a huge impact on a lot of different aspects of it. 374 00:39:46,750 --> 00:39:52,900 I mean, we've mainly focussed on the sort of vaccine development and evaluation side, but it had an impact in things like, you know, 375 00:39:52,900 --> 00:39:58,570 the ethics of how clinical trials performed in pandemics and how you have a clinical 376 00:39:58,570 --> 00:40:04,600 trial design to evaluate a vaccine when you can't ethically give people a placebo. 377 00:40:04,600 --> 00:40:08,400 If you think there's a possibility that the vaccine training might work. 378 00:40:08,400 --> 00:40:15,000 It's had impacts and things like whether pregnant women should be included in the early stage assessment of vaccines. 379 00:40:15,000 --> 00:40:17,800 Well, you know, this pandemic potential. And similarly, 380 00:40:17,800 --> 00:40:26,590 children to populations that are largely excluded from the early stage development and testing of vaccines for obvious reasons and reasonable reasons. 381 00:40:26,590 --> 00:40:30,040 It's had an impact on academic publishing. For example, 382 00:40:30,040 --> 00:40:36,310 say the Ebola outbreak was really the first time that we saw widespread use of preprint service 383 00:40:36,310 --> 00:40:41,690 for getting data out there and rapid publication of results from clinical trials in journals. 384 00:40:41,690 --> 00:40:46,790 The New England Journal of Medicine, which would traditionally take much longer to publish that kind of data and The Lancet, 385 00:40:46,790 --> 00:40:56,400 and it's it's it's shaken up so much of the normal kind of processes, you know, rapid ethical approval, rapid approval from things like the MHRA. 386 00:40:56,400 --> 00:40:59,300 Well, those kinds of things have been facilitated by the outbreaks. 387 00:40:59,300 --> 00:41:07,200 It has had a huge impact in terms of what the world's going to look like going forward in terms of global pandemics even before this pandemic. 388 00:41:07,200 --> 00:41:15,330 I think it was important in opening up lots of different channels and and speeding up lots of things that have been unnecessarily cumbersome. 389 00:41:15,330 --> 00:41:19,560 So that experience should make us better at dealing with future pandemics. 390 00:41:19,560 --> 00:41:26,130 The overwhelming thing that came out of it scientifically was that there were too many diseases 391 00:41:26,130 --> 00:41:31,200 that we just didn't have vaccines in the pipeline for and that nobody was prepared to fund, 392 00:41:31,200 --> 00:41:35,730 because it's unreasonable to a certain extent to expect commercial organisations 393 00:41:35,730 --> 00:41:40,020 to manufacture vaccines for diseases that there is no commercial market. It's not what they do. 394 00:41:40,020 --> 00:41:45,810 That doesn't mean that the world doesn't need them, which means there has to be some alternative funding for those vaccine programmes. 395 00:41:45,810 --> 00:41:51,570 And that's where SAPI has really stepped in to fill that gap quite effectively with Ebola. 396 00:41:51,570 --> 00:41:58,380 We already had those vaccines in early stage clinical development that turned out to be highly effective against Ebola. 397 00:41:58,380 --> 00:42:00,600 So we already had the tools we needed. 398 00:42:00,600 --> 00:42:06,840 There just wasn't that drive to get them through and get them out and get them licenced and stockpiled and ready. 399 00:42:06,840 --> 00:42:13,640 And I think the more we interact with wildlife, you know, if you look at all of the emerging zoonoses, they will come from wildlife. 400 00:42:13,640 --> 00:42:15,080 There will viruses. 401 00:42:15,080 --> 00:42:22,710 And if it's as easy to make a vaccine against something as devastating as Ebola is, it is for any of those other emerging pathogens. 402 00:42:22,710 --> 00:42:29,550 And really there's no excuse to push ahead and do it. And I think it's really galvanised the scientific community into sort of pushing 403 00:42:29,550 --> 00:42:33,500 ahead with some of those other vaccines against some of these pathogens. 404 00:42:33,500 --> 00:42:41,370 The WHL produced a document called the R&D Blueprint, which has a list of all of the diseases that they think are a priority for vaccine development, 405 00:42:41,370 --> 00:42:45,780 and that also includes Disease X, and it now also includes Saar's cabi, too. 406 00:42:45,780 --> 00:42:52,370 And that really laid down a roadmap for what the WHL would expect from a vaccine that was going to be developed against any of these pathogens. 407 00:42:52,370 --> 00:42:58,350 And it's it's a really helpful focus. The vaccine developers to kind of start approaching some of these questions. 408 00:42:58,350 --> 00:43:05,100 And we have vaccines in development here at the Janner against many of those diseases on the on the blueprint document. 409 00:43:05,100 --> 00:43:11,870 We're going to talk about Disease X in a bonus episode, which we'll have recorded by the time you hear this. 410 00:43:11,870 --> 00:43:17,700 But for now, I want you to stick with the Ebola outbreak and ask what else we might have learnt. 411 00:43:17,700 --> 00:43:21,690 I think two obvious questions are what is population movement doing? 412 00:43:21,690 --> 00:43:29,670 And secondly, is environmental change in terms of logging, the logging of forests and stuff like that. 413 00:43:29,670 --> 00:43:36,840 Is that making a difference and just bringing the natural reservoir closer to human populations? 414 00:43:36,840 --> 00:43:47,400 One other characteristic of the West African outbreak was the enormous political relevance of this outbreak and its its broader impact. 415 00:43:47,400 --> 00:43:53,340 For the first time, military were heavily engaged in the outbreak response. 416 00:43:53,340 --> 00:44:04,110 President Obama in mid-September of 2014 committed 3000 troops to Liberia for several months and the British military in Sierra Leone as well. 417 00:44:04,110 --> 00:44:09,090 Really the rather unique and of course, lots of discussion about the role of WHL, 418 00:44:09,090 --> 00:44:17,490 the strengths and weaknesses of WHL need for reform and better application of the international health regulations and all of that. 419 00:44:17,490 --> 00:44:21,360 I think it's widely agreed and widely acknowledged at WHL was slow off the ground. 420 00:44:21,360 --> 00:44:30,360 They should probably have declared it earlier. And they didn't back a public health emergency of international concern. 421 00:44:30,360 --> 00:44:34,530 The outbreak might have come under control sooner. 422 00:44:34,530 --> 00:44:40,320 If action had been taken earlier, that might be one parallel that you could draw with the current outbreak as well. 423 00:44:40,320 --> 00:44:48,430 And finally, in DRC, very important in the twenty eighteen to 2020 outbreak. 424 00:44:48,430 --> 00:45:00,300 This was in eastern DRC in North Keibel. Wendy Tuori province says this is an area of instability and fighting very, very difficult, an insecure area. 425 00:45:00,300 --> 00:45:10,110 And the ability for the world to intervene in these areas of insecurity needs a lot more thought and attention. 426 00:45:10,110 --> 00:45:17,760 With that in mind, I was curious to know how prepared Havenport, we were now for future outbreaks of this nature. 427 00:45:17,760 --> 00:45:25,110 Well, I worry about the whole concept of preparedness. I mean, the West African epidemic was so awful and so severe. 428 00:45:25,110 --> 00:45:31,350 People shook their heads and said never again. Well, memories are short. 429 00:45:31,350 --> 00:45:37,740 And when I reflect and think, well, who is really prepared? You know, adequately prepared, properly prepared. 430 00:45:37,740 --> 00:45:41,700 Public health is not the only group that really is prepared. Is the military. 431 00:45:41,700 --> 00:45:48,480 They spend their time training, doing nothing but training and preparing for something they hope will never happen. 432 00:45:48,480 --> 00:45:52,980 Now, I don't think the rest of society can say that, yes, we put in resources. 433 00:45:52,980 --> 00:45:59,550 Yes, we work on preparedness, but not to the degree that the military do for their cause death. 434 00:45:59,550 --> 00:46:08,340 And I think that merits some thinking about what do we really mean by preparedness and how much are we really prepared to do for preparedness. 435 00:46:08,340 --> 00:46:18,960 Finally, coming to the end of the episode and our series, I was keen to understand from my guests how they saw Ebola in relation to other pended, 436 00:46:18,960 --> 00:46:26,790 for example, where we've right to include it now, list of ten. I think it deserves to be that just because of the impact it had. 437 00:46:26,790 --> 00:46:35,470 Even though in terms of mortality, it probably isn't the most pressing public health issue in the world at that time. 438 00:46:35,470 --> 00:46:42,560 I mean, we had 11000 over 11000 deaths from Ebola during the West African outbreak. 439 00:46:42,560 --> 00:46:49,020 Five hundred thousand people die every year from malaria. And if you look at the resources that were put into dealing with the Ebola outbreak, 440 00:46:49,020 --> 00:46:54,480 similar resources were pumped into dealing with malaria, potentially save a lot more lives. 441 00:46:54,480 --> 00:47:03,870 So maybe malaria ought to be on your list as well. And Brian Falta comparison between Ebola and coal would provide useful context for my question. 442 00:47:03,870 --> 00:47:08,610 So I get the impression that you have some vulnerability to cause it. 443 00:47:08,610 --> 00:47:13,860 I think there seems to be something that we're not quite sure completely yet what it is. 444 00:47:13,860 --> 00:47:18,450 So I will say, I said junior staff is a bit like genetic reflect if you get it. 445 00:47:18,450 --> 00:47:22,980 There may be something in your genetic code that means you're prone to getting severe disease. 446 00:47:22,980 --> 00:47:29,190 Might be what your E to receptor looks like. And of course, we've never really looked at these two receptors before. 447 00:47:29,190 --> 00:47:37,240 We no reason to look at genetics, these two receptors. But there are quite a couple of polymorphisms things may make you more prone to get severe. 448 00:47:37,240 --> 00:47:41,220 So where is Ebola? Just looks as though it just kills everyone. 449 00:47:41,220 --> 00:47:50,310 If you get it. So from that token, you know, I think if I if I if I contracted corvids, then I would think I'd maybe had a chance. 450 00:47:50,310 --> 00:47:55,050 If I contracted Ebola with no treatment, then I. I think probably not. 451 00:47:55,050 --> 00:48:00,360 But as I say, we've if we've evolved if you look at Ebola outbreak at the beginning, mortality was quoted 80 percent. 452 00:48:00,360 --> 00:48:04,500 By the end of it, it was about 40 percent. And that was purely with good medical care. 453 00:48:04,500 --> 00:48:09,960 And similarly with SA, with a Corvette, with SA School V two, if you look at the beginning, 454 00:48:09,960 --> 00:48:14,490 mortality in our intensive care units in UK was probably about 60 percent. 455 00:48:14,490 --> 00:48:23,690 And in fact, no, we see it's probably about 30 percent. So we've learnt how to do the basic stuff without having any specific treatment. 456 00:48:23,690 --> 00:48:32,220 But just how to manage the illness that the patients have much better. 457 00:48:32,220 --> 00:48:38,140 On that more optimistic note, we'll conclude our series on the history of pandemics. 458 00:48:38,140 --> 00:48:44,460 We didn't set out to provide a comprehensive account of the disease outbreaks that humanity is faced, 459 00:48:44,460 --> 00:48:50,590 but to invite you to discover along with us more about 10 world events that may 460 00:48:50,590 --> 00:48:56,350 have had a significant impact on the way we think about and prepare for pandemics. 461 00:48:56,350 --> 00:49:03,040 We hope you've taken a lot from the series. And the good news is it's not quite over yet. 462 00:49:03,040 --> 00:49:08,560 Coming soon, we'll be releasing a bonus on how organisations around the world, 463 00:49:08,560 --> 00:49:16,930 including many people here at Oxford, are preparing for what the World Health Organisation Pooles Disease acts. 464 00:49:16,930 --> 00:49:28,280 I do hope you can join us then. I'm Peter Milliken and you've been listening to Future Makers. 465 00:49:28,280 --> 00:49:38,210 Future Makers is created in-house at the University of Oxford School for the series, was composed and recorded by Richard once. 466 00:49:38,210 --> 00:49:44,240 Today's voice actor was me, Benjamin Morales. The podcast is presented by me. 467 00:49:44,240 --> 00:49:52,400 Professor Peter Milliken from Hartford. And the episodes are produced and edited by Ben Hogwood and Steve Fritjof, 468 00:49:52,400 --> 00:49:59,570 who've done most of the work and to whom I'm hugely grateful and thank you on behalf of the whole team. 469 00:49:59,570 --> 00:50:12,840 Listening to our history of Pandemic's.