1 00:00:00,210 --> 00:00:07,290 My name is Crystal Donnally. I'm the deputy head of department at the Oxford Department of Statistics, 2 00:00:07,290 --> 00:00:14,280 and I'm delighted to welcome you today for our Florence Nightingale Bicentenary lecture. 3 00:00:14,280 --> 00:00:18,270 This was an event that was originally scheduled for the 18th of March, 4 00:00:18,270 --> 00:00:26,040 but it was not able to go ahead because of code and control measures and required social distancing to keep us all safe. 5 00:00:26,040 --> 00:00:30,600 But we're really pleased to be able to welcome you still within twenty 20. 6 00:00:30,600 --> 00:00:35,880 So we're still respecting the bicentenary nature of this lecture. 7 00:00:35,880 --> 00:00:41,910 The planning for this event began over five years ago, and we're extremely grateful to David Greene, 8 00:00:41,910 --> 00:00:46,680 who's the director of the Florence Nightingale Museum for bringing people together, 9 00:00:46,680 --> 00:00:53,130 setting up a Florence Nightingale 2020 planning committee and bringing together a wide range of professions. 10 00:00:53,130 --> 00:00:56,580 And that was from both the UK and beyond. 11 00:00:56,580 --> 00:01:02,790 So we could really leave a legacy of this and help people understand Florence Nightingale and what she stood for. 12 00:01:02,790 --> 00:01:09,570 Please do take the opportunity to visit the virtual exhibition that we've compiled that includes you 13 00:01:09,570 --> 00:01:15,330 being able to view some original correspondence between Florence Nightingale and Benjamin Jowett, 14 00:01:15,330 --> 00:01:18,990 who is at the time warden of Balliol College. 15 00:01:18,990 --> 00:01:26,140 You can find out about some modern nightingales and also learn more about the Florence Nightingale Museum and its work. 16 00:01:26,140 --> 00:01:33,090 The link will be published on a slide during the break, which, as you can see on the schedule here, is between four and four fifteen. 17 00:01:33,090 --> 00:01:40,410 I'd like to thank them individually, but the ICM s more generally for hosting this event and more widely for supporting 18 00:01:40,410 --> 00:01:45,540 mathematical sciences through what has been a very difficult time for all of us. 19 00:01:45,540 --> 00:01:56,730 We also thank X X markets who generously have sponsored this event and more generally this annual lecture series. 20 00:01:56,730 --> 00:02:03,150 So they've been supportive over a long time period and specifically gave us additional funding to support 21 00:02:03,150 --> 00:02:09,790 the creation of this bicentenary commemorative programme that hopefully many of you have received. 22 00:02:09,790 --> 00:02:17,800 Finally, we'd like to give thanks to the RSS, the Royal Statistical Society, for their help and support in planning this event. 23 00:02:17,800 --> 00:02:23,230 Now, hundreds of you are joining us today from around the world. 24 00:02:23,230 --> 00:02:28,720 And those come from a range of disciplines, including medical research and nursing. 25 00:02:28,720 --> 00:02:32,470 But in areas as well as government and education. 26 00:02:32,470 --> 00:02:39,250 And just a general interest in Florence Nightingale and the history of science, 27 00:02:39,250 --> 00:02:45,820 it is my great pleasure to welcome our speaker and my colleague, Professor Deborah Ashby. 28 00:02:45,820 --> 00:02:54,100 She is director of the School of Public Health at Imperial College London, where she holds the chair in medical statistics and clinical trials. 29 00:02:54,100 --> 00:02:58,960 She was a founding co-director of the Imperial College Trials Unit. 30 00:02:58,960 --> 00:03:05,950 She is a chartered statistician and her interests are in clinical trials at risk benefit 31 00:03:05,950 --> 00:03:11,620 decision making for medicines and the utility of Bayesian approaches in these areas. 32 00:03:11,620 --> 00:03:19,540 She has that on the UK Commission on Human Medicines and she acts as an adviser to the European Medicines Agency. 33 00:03:19,540 --> 00:03:24,880 She was awarded an OBE for services to medicine in 2009. 34 00:03:24,880 --> 00:03:36,640 She was appointed as an FDA H.R. senior investigator in 2010 and was elected as a fellow of the Academy of Medical Sciences in 2012. 35 00:03:36,640 --> 00:03:44,500 She is currently the president of the Royal Statistical Society and the supposedly be one of her last events in that capacity. 36 00:03:44,500 --> 00:03:53,830 So we're very honoured to hear from her. Thank you very much. Thank you, Crystal. 37 00:03:53,830 --> 00:04:04,580 So I just need to share my screen. She's. 38 00:04:04,580 --> 00:04:09,510 Right. Is that shaving properly? Yes, read it. 39 00:04:09,510 --> 00:04:16,740 So thank you so much for the invitation. It was one of the most advanced invitations I got. 40 00:04:16,740 --> 00:04:21,480 I think it was more than a year, a year and a half in advance of when this was originally meant to be. 41 00:04:21,480 --> 00:04:29,620 And thank you so much for reconvening. It influences bicentenary year. 42 00:04:29,620 --> 00:04:36,280 So we got to talk about Florence Nightingale. She was born in. 43 00:04:36,280 --> 00:04:43,000 If you're good at Sum's, you'll realise she was born in 1920. And she was born in the city of Florence. 44 00:04:43,000 --> 00:04:48,790 This is her registration of her birth, which was done after her parents came back to this country. 45 00:04:48,790 --> 00:04:55,560 But they'd named her after Florence. And this is slightly more legible. 46 00:04:55,560 --> 00:05:01,920 It's got her family history and you can see that she and her sister path. 47 00:05:01,920 --> 00:05:08,730 Nope. Are down on the left. They are the daughter of William and Frances. 48 00:05:08,730 --> 00:05:15,900 If you look Hopwood's, you'll see that she should have been by rights or by convention anyway, named Florence Shaw. 49 00:05:15,900 --> 00:05:21,320 But. The Nightingale name. Further up, the family of died out. 50 00:05:21,320 --> 00:05:31,490 And so Aunt Evans, Elizabeth in her well, had basically left money to Florence's father so long as he changed his name to Nightingale. 51 00:05:31,490 --> 00:05:39,020 And he wasn't a tough man. He did exactly that. And that provided some of the wealth that's enabled Florence to do what she did. 52 00:05:39,020 --> 00:05:47,270 The other reason for sharing this very sensitive. The other is sharing this is that you will notice that Francis, her mother, 53 00:05:47,270 --> 00:05:51,860 was the daughter of William Smith, who was named pay of many years standing. 54 00:05:51,860 --> 00:05:57,730 And that, we will see, plays into Florence's life a bit later. 55 00:05:57,730 --> 00:06:07,330 She died some 90 years later. And just a couple of things that I'll highlight on this one is that the death certificate is of a different format, 56 00:06:07,330 --> 00:06:12,790 much more like the modern justifications that we use now. And we'll talk about that a little bit. 57 00:06:12,790 --> 00:06:21,910 And the other I noticed when I put this up is that if you can see the person signing off the death, it's a garret, Anderson. 58 00:06:21,910 --> 00:06:27,790 I can only imagine that's Elizabeth Garrett Anderson, who was the first female surgeon and physician. 59 00:06:27,790 --> 00:06:36,350 So I think that's a really nice touch. I didn't realise that they'd had contact. 60 00:06:36,350 --> 00:06:38,420 The beginning and end of her life isn't much fun. 61 00:06:38,420 --> 00:06:49,640 So we're going to go right back to her early education and her father was enlightened not just in taking money and changing his name, but. 62 00:06:49,640 --> 00:06:54,710 Unusually, he wants to educate his daughters. And he did that himself. 63 00:06:54,710 --> 00:07:03,000 He'd been educated at Cambridge. And although we think Florence is perhaps someone who specialised in maths, actually, 64 00:07:03,000 --> 00:07:09,150 she had started Latin, Greek history, philosophy, modern languages, music as well. 65 00:07:09,150 --> 00:07:19,620 And. She her sister, very much fed sketching, this is a picture from the National Portrait Gallery in 1936 of Florence, 66 00:07:19,620 --> 00:07:26,140 the in the Pink was about 16 and her sister is holding her own sketchbook, whereas Florence is Greek. 67 00:07:26,140 --> 00:07:30,810 It's good enough that later on she helped Benjamin Jowett in his translation of Plato's dialogue. 68 00:07:30,810 --> 00:07:42,670 So she was clearly a very able young woman. And judging by that picture, destined for a fine life, probably as the wife of a rather rich man. 69 00:07:42,670 --> 00:07:55,810 But Florence didn't want to do that. And at 16, she had a mystical experience, her calling that she wasn't destined for a conventional life. 70 00:07:55,810 --> 00:07:58,510 She was deeply religious, which we often brush over. 71 00:07:58,510 --> 00:08:04,440 But I wanted to show this window, which has been commissioned for her two hundredth anniversary in Romsey Abbey. 72 00:08:04,440 --> 00:08:10,810 Stephen Evans drew it to my attention. And I contacted Sophie Hacker, who did it to ask permission to show it. 73 00:08:10,810 --> 00:08:18,700 Show me a High-Quality image and made me promise that I would also say that she's about to have a book come out, which is about the imagery on it. 74 00:08:18,700 --> 00:08:25,340 So although you probably can't see it here in the background, places like Scutari that were very important to her. 75 00:08:25,340 --> 00:08:31,020 There's an owl up there, that baby owl she saved in Athens, apparently very, very keen on birds and source of vomitus. 76 00:08:31,020 --> 00:08:35,260 Franciscan. And that's a quotation from my. 77 00:08:35,260 --> 00:08:40,540 It is I. And she answered. Here I am, Lord. Send me now whatever you make of that. 78 00:08:40,540 --> 00:08:47,550 She went on to do good things, but that state is one of the cause of her life. 79 00:08:47,550 --> 00:08:52,020 So as a young adult, she'd not get marriage. She felt called by God. 80 00:08:52,020 --> 00:08:58,020 She was obviously searching for what she did want today. And by the age of 25, 81 00:08:58,020 --> 00:09:01,620 she'd got into my head that she wants to be a nurse and she wanted to go to 82 00:09:01,620 --> 00:09:06,570 Solsbury Infirmary and she said it was as if I wanted to be a kitchen maid. 83 00:09:06,570 --> 00:09:14,980 And she drew the conclusion, not unreasonably, that only widowhood or poverty would give an educated woman a reason to work. 84 00:09:14,980 --> 00:09:22,660 By 1848, having not been allowed to go into nursing. She actually went tenanted some teaching at the ragged school in Westminster and 85 00:09:22,660 --> 00:09:27,640 I don't know whether it was this one that support threats by Bellette Blakely, 86 00:09:27,640 --> 00:09:32,620 but I suspect it if it wasn't that one, it was very similar and not open to rise to poverty. 87 00:09:32,620 --> 00:09:41,060 This was not the life she'd been accustomed to. But but her family did not like her doing it, but did not want her near those people. 88 00:09:41,060 --> 00:09:48,020 So what was she going to do? Well, a quick whistle stop tour. Her family thought that she needed to travel. 89 00:09:48,020 --> 00:09:53,120 So she went to Egypt and Greece. Was she taken by the classical antiquities? 90 00:09:53,120 --> 00:09:58,830 Not at all. While she was in Germany, she went to a school in Cosworth near Dussel Dorf. 91 00:09:58,830 --> 00:10:05,850 It was a hospital, an orphanage and a school, and it was staffed by Deaconesses, which were trained by the pastor and his wife. 92 00:10:05,850 --> 00:10:13,950 And she really got drawn towards that. And essentially a year later, she went back to Kaisa Worth, again, strong from family opposition. 93 00:10:13,950 --> 00:10:20,280 But by now, she was 30 by this point. She wasn't taking no for an answer. 94 00:10:20,280 --> 00:10:24,690 But when she got back to Britain, she couldn't find an outlet for a training. 95 00:10:24,690 --> 00:10:29,250 So she'd visited hospitals throughout the UK and Europe. She collected information. 96 00:10:29,250 --> 00:10:38,430 She analysed and reflected on hospital reports and government publications and public health, really putting her previous training to really good use. 97 00:10:38,430 --> 00:10:45,240 And then eventually, and I can only imagine her family must have been relieved. She got a job with a good name. 98 00:10:45,240 --> 00:10:50,280 The lady, superintendent of an institution for sick woman number one, upper Harley Street, 99 00:10:50,280 --> 00:10:57,090 which is still where the sort of posher type of medicine takes place. 100 00:10:57,090 --> 00:11:02,700 But the trauma of war came along, and like so many women when the war came along. 101 00:11:02,700 --> 00:11:11,540 She got going. And she went out to the Crimea, which is where she earned the super K, the lady of the lamp. 102 00:11:11,540 --> 00:11:13,640 Now, she did some nursing. 103 00:11:13,640 --> 00:11:22,700 But again, as she'd already been doing, she started thinking and analysing and these graphs are well known amongst statisticians, 104 00:11:22,700 --> 00:11:32,390 but maybe not some of the other of the audience. And they looked at causes of mortality amongst the soldiers from 1854 to 1855. 105 00:11:32,390 --> 00:11:36,860 And then the following year for the same cycle. And the wedges are months. 106 00:11:36,860 --> 00:11:45,410 And what she's got here is a wonderful graphical representation showing that although some of the soldiers were dying from battle, 107 00:11:45,410 --> 00:11:51,500 actually a lot more were dying from infectious diseases, which are much more preventable. 108 00:11:51,500 --> 00:11:57,470 And only a few were dying from other things. And after some interventions, the reason the left hand one is so much on the right hand. 109 00:11:57,470 --> 00:12:02,180 One is that she got those deaths right down. 110 00:12:02,180 --> 00:12:10,730 And if when lockdown reopens, you come to London, the originals of those are in the science museum in the Winton gallery, 111 00:12:10,730 --> 00:12:17,220 and they're well worth seeing because they're just lovely to look at. 112 00:12:17,220 --> 00:12:25,680 And on the strength of that, she was elected a fellow of the Roar's disconcert of what was then the Siskel site of London, 113 00:12:25,680 --> 00:12:30,450 which was the forerunner of the raw Siskel society. You had to be nominated. 114 00:12:30,450 --> 00:12:34,770 She had nominees who included William Farr and William Guy. 115 00:12:34,770 --> 00:12:37,620 William Farr set up the General Register Office. 116 00:12:37,620 --> 00:12:47,460 And it was he who was responsible for taking the essentially way of registering births and deaths through the parishes into a national system, 117 00:12:47,460 --> 00:12:55,080 which is why she her birth was done just sort of on what happened to be there on the church it was registered in. 118 00:12:55,080 --> 00:13:05,030 Whereas by the end, it's a national certificate, you say, and William Guy is went on to be president of the Ross Society. 119 00:13:05,030 --> 00:13:11,070 You founded the guy Medal's which on that panellists were joining me later, have got a goodly collection of between them. 120 00:13:11,070 --> 00:13:22,950 So these were she was supported by some eminent people and a lot of people called William around at that stage, I notice, in passing. 121 00:13:22,950 --> 00:13:27,510 So what else she did she do? And she said she wrote a lot. 122 00:13:27,510 --> 00:13:33,300 Which means that we know a lot about what she thought. I would call her a feminist. 123 00:13:33,300 --> 00:13:37,870 She wouldn't have used that word. It wasn't in currency at that time. 124 00:13:37,870 --> 00:13:45,730 But she was scathing about the education available to women and the limited expectations society had of their role. 125 00:13:45,730 --> 00:13:53,080 She was fuming. The time has come when women must do something more than domestic half, which means nursing the infants, 126 00:13:53,080 --> 00:13:57,580 keeping a pretty house, having a good dinner and an entertaining party. 127 00:13:57,580 --> 00:14:04,020 Well, I must say, right at the moment, the idea of being allowed to meet people for a good dinner, having an entertaining party is rather nice. 128 00:14:04,020 --> 00:14:06,940 But for me, that would be the icing on the cake. 129 00:14:06,940 --> 00:14:12,550 The expectations of woman of her time was that would be her entire life of ageing, that kind of thing. 130 00:14:12,550 --> 00:14:20,620 She said, why have women, passion, intellect, moral activity, these three and a place in society, what not one of these three can be exercised? 131 00:14:20,620 --> 00:14:27,620 So she really saw it and articulated what was unfair about it. 132 00:14:27,620 --> 00:14:34,850 So I'm just coming forward to memorialise the present day briefly and then we'll go back to carry on with Florence. 133 00:14:34,850 --> 00:14:42,260 How are we doing now? What do these people have in common? 134 00:14:42,260 --> 00:14:49,550 I mean, clearly, they are white men of a certain age, with the exception of this one down here. 135 00:14:49,550 --> 00:14:57,630 And the reason I've got the heroin in there is that. There was some call David Hare I wanted to include, but I couldn't find a picture of, 136 00:14:57,630 --> 00:15:03,970 so the heron from my locked down walks in St James's Park is proudly standing surrogate. 137 00:15:03,970 --> 00:15:11,070 Well, if you don't recognise all of them, the clues, racist society of Presidents board. 138 00:15:11,070 --> 00:15:16,710 They are all previous presidents of the Royal Society and what they have in common. 139 00:15:16,710 --> 00:15:22,260 And you might guess if you know, even two or three of them is that they are all called David and wonderful presidents. 140 00:15:22,260 --> 00:15:31,280 They've been. But if I might, my my three year old grandson likes building towers. 141 00:15:31,280 --> 00:15:39,690 He loves building the historic Hamada's Lego. So if I put these chaps into a tower. 142 00:15:39,690 --> 00:15:45,150 There are six of them. And if I then build another tower with all the female presidents, 143 00:15:45,150 --> 00:15:50,100 even if I include the president elect, Sylvia Richardson will be taking over in January. 144 00:15:50,100 --> 00:15:55,380 There are more presidents called David than there are female presidents. 145 00:15:55,380 --> 00:15:57,120 One hundred and eighty five years. 146 00:15:57,120 --> 00:16:02,250 And I think if I could have found all the pictures of this chap called William, it would have been an even bigger tower. 147 00:16:02,250 --> 00:16:09,450 So my younger grandson is at the stage where if you build a tower, he rolls over the carpet until he manages to knock it down. 148 00:16:09,450 --> 00:16:15,790 I don't want to knock that tower down, but I would like to kind of see a few more women beating this lot. 149 00:16:15,790 --> 00:16:22,900 And if Florence were here with us now and she said, well, OK, that's largely the 20th century, 150 00:16:22,900 --> 00:16:28,780 some of that is taking place in 21st century, what does 21st century statistics look like? 151 00:16:28,780 --> 00:16:39,460 I'd give you this. We've got Crystal Donelli, who you've already met, Jen Rogers, who you're about to meet in the upper left hand corner. 152 00:16:39,460 --> 00:16:47,560 We've got a meeting held last year by several of our sections, including the young substation section, celebrating women in statistics. 153 00:16:47,560 --> 00:16:53,890 I was lucky enough to be asked to speak at it as a fairly new president. Men under the bottom right hand corner. 154 00:16:53,890 --> 00:16:58,960 Just the most wonderful photograph of my friend and colleague Jane Hutton, 155 00:16:58,960 --> 00:17:03,790 who heavily involved in the Ames, which is the African Institute Mathematical Cystectomy. 156 00:17:03,790 --> 00:17:10,130 It's not only women, but that is just such a joyful picture. I just wanted to show it to try to rebalance. 157 00:17:10,130 --> 00:17:16,360 And if anyone in this audience dares to look at these photos and say, oh, I feel a bit uncomfortable in that environment, 158 00:17:16,360 --> 00:17:23,860 just put yourself in the shoes of Florence and some of the women who followed in her footsteps walking into a metal environment. 159 00:17:23,860 --> 00:17:36,810 So things are changing. But what Florence does have in common with I think every woman on that picture is that she was passionate about statistics. 160 00:17:36,810 --> 00:17:41,820 She said statistics is the most important science in the whole world for upon. 161 00:17:41,820 --> 00:17:50,430 It depends. The practical application of every other science and of every art, the one science essential to all political and social ministration, 162 00:17:50,430 --> 00:17:57,090 all education, all organisation based on experience for only gives us the results of our experience. 163 00:17:57,090 --> 00:18:09,190 She really did care about autistics. But there was another facet of Florence that I've got to know as I've been reading more about her. 164 00:18:09,190 --> 00:18:14,130 Those she cared, passionate about education, and we'll look at a bit more of that in a minute. 165 00:18:14,130 --> 00:18:21,570 She also cared about action. She said during the middle portion of her life, college education acquirement of knowledge she longed for. 166 00:18:21,570 --> 00:18:26,910 But that was temporary. Whereas I depart from her slightly, I still think that knowledge for knowledge is sake. 167 00:18:26,910 --> 00:18:32,160 If I could do pure mathematics, at least some of the time, I would just for its own sake. 168 00:18:32,160 --> 00:18:41,860 But Florence really had no time for that. She wanted to set up an institute for training of nurses and hospital attenders, 169 00:18:41,860 --> 00:18:46,660 and she spots supporters to set up the Nightingale Fund for former civil hospitals. 170 00:18:46,660 --> 00:18:53,710 She then kept well clear of it. She didn't get involved as many women of her class would have done in the fundraising itself. 171 00:18:53,710 --> 00:18:57,760 She left others to do that while she got on with campaigning for a full commission 172 00:18:57,760 --> 00:19:04,090 of enquiry into Crimea and Deaths 16000 from disease versus only 4000 from battle. 173 00:19:04,090 --> 00:19:10,590 And she was angry about that. And she wanted things done about its. 174 00:19:10,590 --> 00:19:16,020 So just picking up some of the other things about education. 175 00:19:16,020 --> 00:19:21,750 She had a keen interest in the village elementary school near a family home in Derbyshire. 176 00:19:21,750 --> 00:19:28,440 She wrote about education in schools in British colonies. She was passionate about education, what counties of the poor. 177 00:19:28,440 --> 00:19:34,380 And you can see by her experience in Westminster stood him in good stead for that. 178 00:19:34,380 --> 00:19:43,760 And all the time these themes come through, it should be practical, it should be hands on education, manual skills are prioritised. 179 00:19:43,760 --> 00:19:48,830 And whenever she wasn't happy about anything. Education was part of the answer. 180 00:19:48,830 --> 00:19:55,670 She. As we've seen, was very concerned about British soldiers and she championed their education. 181 00:19:55,670 --> 00:20:03,090 She was a bit scathing about the Army doctors. And again, she thought past that solution was education. 182 00:20:03,090 --> 00:20:08,450 She'd got her followers raising money for the Nightingale School of Nursing. 183 00:20:08,450 --> 00:20:12,410 And when it was set up, she then became much more engaged again. 184 00:20:12,410 --> 00:20:18,230 And she gave detailed instructions that should be taught by practitioners, not by people who were hands off. 185 00:20:18,230 --> 00:20:24,530 And there were things in there that each nurse should have her own room so that she could study it quietly. 186 00:20:24,530 --> 00:20:29,210 And what that meant was her influence spread as graduates took senior roles and went worldwide. 187 00:20:29,210 --> 00:20:34,790 I gave a talk, which I did about Florence in Australia and found that she'd sent she'd never been out there, 188 00:20:34,790 --> 00:20:40,370 but some of her proteges had been out there and set up the way that they were doing things there. 189 00:20:40,370 --> 00:20:43,220 So her influence was phenomenal. 190 00:20:43,220 --> 00:20:50,600 And I think those involved in education know the often the most important thing we do is the future generations that we train. 191 00:20:50,600 --> 00:20:59,170 And Alex Outwell has written a lot about her education, so I'm grateful for that. 192 00:20:59,170 --> 00:21:06,230 And as I said. She was passionate that education is to teach men not to know, but to do. 193 00:21:06,230 --> 00:21:13,670 It's about observation, reflection, training. And she said every five or 10 years really requires a second training nowadays. 194 00:21:13,670 --> 00:21:20,130 Well, nothing could be true. Now, I think the pace we're going at, we could all do the second training. 195 00:21:20,130 --> 00:21:29,390 So who else did she think needed educating? And this is where her relationship with her grandfather comes in because. 196 00:21:29,390 --> 00:21:34,010 Those as a woman, she would not have gone anywhere near Parliament through her grandfather. 197 00:21:34,010 --> 00:21:38,690 I think if I've got it right. Was an MP for best part of four decades. 198 00:21:38,690 --> 00:21:42,890 She knew that politicians didn't always get it right. 199 00:21:42,890 --> 00:21:48,380 And she had a correspondence going with Benjamin Jowett, who was, I think, just three years old on her. 200 00:21:48,380 --> 00:21:56,780 And this wonderful quote, which you've got to imagine it, those of you know, Sheila Byrd need this read in her tone of voice. 201 00:21:56,780 --> 00:22:03,020 Our chief point was that the enormous amount of statistics this moment available at their disposal or in their pigeonholes, 202 00:22:03,020 --> 00:22:07,310 which means not at their disposal, is almost absolutely useless. Why? 203 00:22:07,310 --> 00:22:12,350 Because cabinet ministers, their subordinates, the large majority of whom have received a university education, 204 00:22:12,350 --> 00:22:16,460 have received no education whatsoever on the point upon which all legislation 205 00:22:16,460 --> 00:22:20,870 demonstration must to be progressive and not vibratory ultimately be based. 206 00:22:20,870 --> 00:22:28,960 We do not want a great arithmetical law. We want to know what we are doing and things which must be tested by results. 207 00:22:28,960 --> 00:22:39,610 And I just find that such a powerful image that these highly educated politicians have facts and figures which over venue how to use them, 208 00:22:39,610 --> 00:22:43,480 would help them plan in the running of the country, but they just didn't know how. 209 00:22:43,480 --> 00:22:52,770 And so they're languishing in these pigeonholes. So what was she going to do about that? 210 00:22:52,770 --> 00:22:59,400 The reason she was writing to Benjamin Jamot was that she was well aware that Oxford was the place Stenders, 211 00:22:59,400 --> 00:23:06,330 for that matter, that educates a large number of our politicians. So she thought that Cicek should be introduced into the studies. 212 00:23:06,330 --> 00:23:10,680 University of Oxford. By setting up a professorship of applies to sticks. 213 00:23:10,680 --> 00:23:15,870 And she wanted to address the need for statistics related to education, penology, workhouses and India. 214 00:23:15,870 --> 00:23:20,580 This was not about mathematics and probability theory. This was replication. 215 00:23:20,580 --> 00:23:25,580 At the time, Oxford didn't think it was suitable. They tried to persuade you, I think, to write an essay. 216 00:23:25,580 --> 00:23:29,730 It found an essay prise and strategy, but had nothing to do with it. 217 00:23:29,730 --> 00:23:30,960 And so they missed out. 218 00:23:30,960 --> 00:23:38,100 I have to say that if she came to Imperial saying, what's up, a chair for this kind of purpose, our advance, more people would be leaping at her. 219 00:23:38,100 --> 00:23:39,630 And I'm quite sure in Oxford now, 220 00:23:39,630 --> 00:23:50,270 your development teams would also be quite willing to help anybody who feels minded to fund this because it is still needed. 221 00:23:50,270 --> 00:23:55,400 So what's the equivalent of pigeonholes? Because though we may still have them, they're not. 222 00:23:55,400 --> 00:24:00,950 Now our primary means of communication. And. 223 00:24:00,950 --> 00:24:04,880 Again, when I saw this image, I just it just summed it up for me. 224 00:24:04,880 --> 00:24:14,750 These days we have databases, email accounts full of attachments that we are meant to read, much digest that would help us do our jobs more properly. 225 00:24:14,750 --> 00:24:18,500 But we either don't know how to get in there. Or we don't have the time. 226 00:24:18,500 --> 00:24:24,050 And so that to me is the modern analogue for politicians that it's not necessarily that we're short of data. 227 00:24:24,050 --> 00:24:30,920 Sometimes we're short of good data, but you need the wherewithal to do something useful with it. 228 00:24:30,920 --> 00:24:37,550 And one of the things the Raw Siskel Society has done is to publish its data manifesto. 229 00:24:37,550 --> 00:24:46,280 So whenever there's an election, we send our data manifesto to the candidates and try and get to sign up to it. 230 00:24:46,280 --> 00:24:53,300 It's got 10 recommendations about how to improve data, policymaking, democracy and prosperity of society. 231 00:24:53,300 --> 00:24:57,260 And very often they sign up to say that if they're elected, they'll do some training. 232 00:24:57,260 --> 00:25:04,040 Some of them actually do it. And probably the most potent one that I think Florence would like is that politicians, policy makers, 233 00:25:04,040 --> 00:25:15,050 not professionals working in public services, should be given basic training, data, handling statistics, interpreting evidence. 234 00:25:15,050 --> 00:25:21,380 And she was firmly of the opinion that the main end of system should not be to inform the government as to how many men have died, 235 00:25:21,380 --> 00:25:27,650 but to enable immediate steps to be taken to prevent the extension of disease and mortality. 236 00:25:27,650 --> 00:25:35,820 And. When I use some of this material in my presidential dress last year, that was more or less what I stopped. 237 00:25:35,820 --> 00:25:43,060 In the current climate, I think we can look a bit further. So what are we now doing? 238 00:25:43,060 --> 00:25:50,170 Firstly, modelling. My colleagues Neil Ferguson and a big team includes Crystal got going. 239 00:25:50,170 --> 00:25:54,430 As soon as we identified Kov it and they put out lots of reports. 240 00:25:54,430 --> 00:25:58,840 Report number nine is arguably the most influential, least most talked about, 241 00:25:58,840 --> 00:26:06,970 which was what would happen to cases of hospitalised case of covered if we did nothing. 242 00:26:06,970 --> 00:26:12,970 And this red line here is the surge capacity in hospitals. You can see that it would be wildly exceeded. 243 00:26:12,970 --> 00:26:19,960 And what would it do on to various lockdowns, gestures? And for me, my last day in my office was actually the 16th of March. 244 00:26:19,960 --> 00:26:25,860 On the basis of this report, politicians spoke out. It took them a week later before we probably went into lockdown. 245 00:26:25,860 --> 00:26:30,850 But this is a message that I really don't know what I'm doing coming into work. 246 00:26:30,850 --> 00:26:34,990 And that, of course, was two days before we would use to this lecture on the 18th of March. 247 00:26:34,990 --> 00:26:44,920 It was cancelled, I think, the previous Friday. But I was also delighted when I saw that I wasn't delighted that new hospitals needed building, 248 00:26:44,920 --> 00:26:49,240 but they named them the Nightingale hospitals, and I'm sure that was for the nurses. 249 00:26:49,240 --> 00:26:55,210 But I rather like the idea that it was data modelling that was informing a response. 250 00:26:55,210 --> 00:26:59,020 As it turned out, it wasn't needed. Not me so far as much as we thought it might be. 251 00:26:59,020 --> 00:27:02,500 But I think it was upset, the right call at the time. 252 00:27:02,500 --> 00:27:10,170 And many of us, certainly at Oxford and Imperial, have been collecting data ever since the open air sinks. 253 00:27:10,170 --> 00:27:12,430 Johnson University of Oxford. Collecting lots of data. 254 00:27:12,430 --> 00:27:21,130 But I'm part of the imperial wrapped studies which have collected data now every month since May. 255 00:27:21,130 --> 00:27:26,170 And this you can look at the different regions of the country. 256 00:27:26,170 --> 00:27:31,540 So up in the top left hand corner, we can see in London where the rates weren't too high. 257 00:27:31,540 --> 00:27:38,940 On the up the axis, the top of that is two and a half percent, two percent just underneath it, dirt without flicking this lights on. 258 00:27:38,940 --> 00:27:44,590 So that's 2%. London have never gone anywhere near that, whereas the north west. 259 00:27:44,590 --> 00:27:54,040 Next to it. And I'm Liverpool is my second city. Hit that a while ago, but with severe lockdown and other measures, they've come back down again. 260 00:27:54,040 --> 00:27:59,590 So this kind of data rigorously done on random samples is vital. 261 00:27:59,590 --> 00:28:04,210 As one of the contributing factors to the epidemic, this data was released yesterday. 262 00:28:04,210 --> 00:28:10,370 These data were released yesterday. But the first version was with government last week. 263 00:28:10,370 --> 00:28:13,550 And what's wonderful about this is the team I'm working with, 264 00:28:13,550 --> 00:28:20,150 all sorts of people that I've worked alongside but never worked with properly before, including Crystal. 265 00:28:20,150 --> 00:28:24,040 When we said, who else do we need? Well, we knew we were going to have temporal spatial data. 266 00:28:24,040 --> 00:28:29,210 So let's get Peter take. It was a bit like putting together your fantasy research team. 267 00:28:29,210 --> 00:28:40,250 And what that means is we're doing our mapping properly. This graph shows a month ago the what the rates were doing up to about three percent. 268 00:28:40,250 --> 00:28:46,940 And whereas they've really got the fact there's not so much dark shows that they've gone down between round six, 269 00:28:46,940 --> 00:28:51,470 amount's seven, the on the upper diagonal, kind of the round six isolated to two. 270 00:28:51,470 --> 00:29:00,440 Because there's a lot of activity in the middle of that. And because we've done over a million tests in total, but because of the rates at the moment, 271 00:29:00,440 --> 00:29:05,570 we have enough to do it at local authority level that are three hundred forty six of them. 272 00:29:05,570 --> 00:29:09,920 And that scale, if you can't read on your machine, goes up to four percent. 273 00:29:09,920 --> 00:29:14,810 So there are some little pockets where the rates are heading in that direction, which is really quite worrying. 274 00:29:14,810 --> 00:29:22,470 But it's level of resolution that means that the data could be used to inform actions is the point I'm trying to make. 275 00:29:22,470 --> 00:29:27,350 I'm a tri list. So. You'd expect me to say something about trials. 276 00:29:27,350 --> 00:29:33,640 There've been a lot of trials started, but the three I want to highlight. 277 00:29:33,640 --> 00:29:39,110 Are three what's called platform trials. They're the national priority clinical trials. 278 00:29:39,110 --> 00:29:48,160 The principle trial, which is in high risk patients in primary care, recover in hospital and ring up capping critically ill patient trials. 279 00:29:48,160 --> 00:29:52,430 And the thing to note is that the chief medical officers of England, Scotland, Wales, 280 00:29:52,430 --> 00:29:58,070 Northern Ireland, wrote to say that these are the national priority trials on the 3rd of April. 281 00:29:58,070 --> 00:30:00,890 I mean, if you think how long it normally takes to get trials going. 282 00:30:00,890 --> 00:30:06,380 The idea that we could identify a disease sometime in January and have complicated trials up and 283 00:30:06,380 --> 00:30:14,450 running by April and recovery started recruiting really fiercely straight away is quite phenomenal. 284 00:30:14,450 --> 00:30:19,520 The principle of remap kapper both what's called Bayesian adaptive studies. 285 00:30:19,520 --> 00:30:27,560 They're built on previous work. So the point, again, I'm trying to draw out is that preparedness work matters in all sorts of ways. 286 00:30:27,560 --> 00:30:33,480 And the fact that there were protocols ready to ready to go really meant that we get motoring with us. 287 00:30:33,480 --> 00:30:41,660 I'm not declaring it is not conflict of interest, like the data monitoring committee for the principle trial, which didn't recruit very much early on. 288 00:30:41,660 --> 00:30:45,730 But, my goodness, it's it's. Galloping now. 289 00:30:45,730 --> 00:30:53,710 So we're suddenly having to have at least potentially weekly data monitoring committees in the diary because we're recruiting at over 150 a week. 290 00:30:53,710 --> 00:31:02,350 Justices of snippet remap cap, which is led by my colleague Tony Gordon, has had about 3000 patients randomised. 291 00:31:02,350 --> 00:31:05,260 And it's already shown the height, of course, and steroid treatment improved, 292 00:31:05,260 --> 00:31:11,740 recovering critical patients that moppin of a ton of ERBs, ineffective and provided no additional benefit. 293 00:31:11,740 --> 00:31:16,000 And most recently, to zoom up, which can barely pronounce, 294 00:31:16,000 --> 00:31:21,250 which is not rightest drug gives it an odds ratio of one point eight seven for a better outcome. 295 00:31:21,250 --> 00:31:25,420 And there's a ninety nine point seven five, but it's superior to no immune modulation. 296 00:31:25,420 --> 00:31:36,060 So when they're set up properly, we can get fast answers that are feeding back into the pandemic. 297 00:31:36,060 --> 00:31:47,270 Now. Another area where both Imperial and Oxford are leading the pack, along with various other companies, is vaccines. 298 00:31:47,270 --> 00:31:49,940 When people said to me a few months ago, do you think we'll have vaccines? 299 00:31:49,940 --> 00:31:54,620 I said, well, as far as I knew, corona viruses were extraordinary, different to get vaccines for. 300 00:31:54,620 --> 00:32:02,030 And I wasn't holding my breath. I'm no expert on vaccines, so I don't particularly want to get into the vaccine trials. 301 00:32:02,030 --> 00:32:05,210 But I did want to show this that I saw on Twitter, 302 00:32:05,210 --> 00:32:11,000 which is a so-called Cheverton voice who's not a statistician, but he just said proud husband moment. 303 00:32:11,000 --> 00:32:16,490 My wife has been the lead statistician on the Oxford vaccine trial, working 24/7 since March. 304 00:32:16,490 --> 00:32:24,290 The team has done in 10 months what would normally take a decade to do. Not too early for Publius it then, but the follow up to 80. 305 00:32:24,290 --> 00:32:28,910 His wife had an Angel Murphy, not American. No, I don't know her. 306 00:32:28,910 --> 00:32:35,310 But that to me sounds surrogate for. All the statisticians, all the trials I've shown you. 307 00:32:35,310 --> 00:32:44,480 I can only you can only imagine how hard that imperial team were working for the modelling if they had report nine out by mid-March. 308 00:32:44,480 --> 00:32:46,800 We have had two departments meet here at Imperial. 309 00:32:46,800 --> 00:32:53,430 And people started saying, well, you know, when your department's gonna go back to work, I say, my department have not stopped working. 310 00:32:53,430 --> 00:32:57,450 I have never seen so many people work so hard, such long hours. 311 00:32:57,450 --> 00:33:06,340 And it is truly impressive what science and not just assist experts to six is absolutely at the core of that is done. 312 00:33:06,340 --> 00:33:13,500 So back to. Florence, this picture, you might be wondering what it is. 313 00:33:13,500 --> 00:33:21,300 It's in the dark, and that is actually the House of Commons. That's Big Ben, the Elizabeth Tower over there. 314 00:33:21,300 --> 00:33:26,700 And it's taken from the South Bank, which is where St. Thomas is hospitalist. 315 00:33:26,700 --> 00:33:30,240 And it's actually just people walk round there a couple of hours ago. 316 00:33:30,240 --> 00:33:36,480 But because it's there, there my flat. But unfortunate. I didn't realise they were showing this on Florence's birthday. 317 00:33:36,480 --> 00:33:39,120 So I think it was probably beamed from St. Thomas's. 318 00:33:39,120 --> 00:33:46,530 But I just think it's a wonderful image showing modern nursing alongside nurses of Florence's time. 319 00:33:46,530 --> 00:33:50,190 What I love about it isn't the nursing analogy of our culture that's important. 320 00:33:50,190 --> 00:33:59,610 I just love the idea that Florence is kind of all over those politicians looking at them and saying, OK, so are you doing what you meant to be doing? 321 00:33:59,610 --> 00:34:04,790 Brilliant image. So what does the IRS have been doing? 322 00:34:04,790 --> 00:34:08,640 Because we haven't got Florence do it for us now. 323 00:34:08,640 --> 00:34:16,230 To our March council meeting, which was the first one we had fully online, which was rearranged at a few days notice. 324 00:34:16,230 --> 00:34:22,230 Unsurprisingly, we discussed kov it and what we should do. My initial reaction was my colleagues are doing quite enough. 325 00:34:22,230 --> 00:34:27,480 We don't need any kind of task force. But actually, it was very clear that we did need some coordination. 326 00:34:27,480 --> 00:34:34,170 And I are Sylvia Richardson, who's the incoming president of Spiegelhalter, who is my predecessor to chair it. 327 00:34:34,170 --> 00:34:39,060 And they brought together again a stunning group on designing the data collection, diagnostic studies, 328 00:34:39,060 --> 00:34:43,890 modelling, forecasting treatment studies, enhancement of public understanding and other areas. 329 00:34:43,890 --> 00:34:51,450 And if you want to know more about the work I've left link there. And a lot of this is actually sort of slightly unsung. 330 00:34:51,450 --> 00:34:55,620 They get requests when we put the REACT protocol together over the weekend. 331 00:34:55,620 --> 00:34:58,380 I thought, well, you know, this hasn't got the luxury of peer review, 332 00:34:58,380 --> 00:35:02,040 but we sent it to the Kovar task force and they came back with stunning legal comments. 333 00:35:02,040 --> 00:35:06,810 So, yeah, they they got that study has a great deal. 334 00:35:06,810 --> 00:35:12,820 But if they're important, I know that they're giving advice to government. And David, maybe say more about that. 335 00:35:12,820 --> 00:35:18,740 But what we need to be high profile when we need to do what Florence would have is do we do. 336 00:35:18,740 --> 00:35:30,040 And one of the. Surprising things that we hadn't foreseen came with exams, the exams for 16 year olds and 18 year olds got cancelled. 337 00:35:30,040 --> 00:35:35,620 And I then got a phone call or email from Paula Williamson, who longstanding colleague, 338 00:35:35,620 --> 00:35:40,680 my Never Paul Days, who happens to be married to a teacher and had a couple of lads doing A-levels. 339 00:35:40,680 --> 00:35:45,610 Her twins. And she said, I've just seen the request for schools for what they've got to put in. 340 00:35:45,610 --> 00:35:49,330 And I think there's diskless choose here. What is the RSS done about it? 341 00:35:49,330 --> 00:35:53,440 Well, at that point, we hadn't realised there was fiscal issues because it took some middle ground to flag them up. 342 00:35:53,440 --> 00:35:58,930 But essentially we wrote letters and then when it broke in the summer, we wrote rather more firmly. 343 00:35:58,930 --> 00:36:03,070 And colleagues who know more about educational things, Niger have played a blinder. 344 00:36:03,070 --> 00:36:09,640 But if they wanted to fight in the papers because of Croll said some things that we didn't like. 345 00:36:09,640 --> 00:36:13,300 Yeah, we can have the arguments and headlines. 346 00:36:13,300 --> 00:36:22,570 And equally, I can actually understand why there was a a will to put money into mass testing to try sort things out. 347 00:36:22,570 --> 00:36:27,940 But there are well rehearsed fiscal issues underlying what is essentially screening. 348 00:36:27,940 --> 00:36:33,010 And John Deakes and others wrote on that and the Times pitched up in the front page. 349 00:36:33,010 --> 00:36:41,320 So again, Rosta Society Headline News. So when we need to, I hope that Florence would would appreciate what we're doing. 350 00:36:41,320 --> 00:36:47,420 So what about Florence's legacy? Her correspondence with Benjamin Deryk continued. 351 00:36:47,420 --> 00:36:49,430 And he wrote to her, interestingly, 352 00:36:49,430 --> 00:36:57,560 New Year's Eve 1879 saying that was a great deal of romantic feeling about you 23 years ago when he returned home for the Crimea. 353 00:36:57,560 --> 00:37:04,290 And now you're walking in silence. Nobody knows how many lives are saved by nurse and hospital, how many thousand soldiers are now alive. 354 00:37:04,290 --> 00:37:05,430 Your forethought and diligence. 355 00:37:05,430 --> 00:37:12,290 How many Nita's of India in this generation, generations come and been preserved from famine and oppression by the energy of a sick lady. 356 00:37:12,290 --> 00:37:14,600 You can scarcely rise my back because what I. 357 00:37:14,600 --> 00:37:22,640 Some of you will know, but I didn't mention, is that Florence, after coming back from the Crimea, had some health problem numbers quite short. 358 00:37:22,640 --> 00:37:27,410 But essentially, instead of travelling the globe, she basically took to her room. 359 00:37:27,410 --> 00:37:35,040 So there she is, sick lady, and scarcely writes my bad. The world does not know all this or think about it, but I know it and often think about it. 360 00:37:35,040 --> 00:37:38,420 And I think it was well-meant. 361 00:37:38,420 --> 00:37:44,670 And then I did some songs, I thought when he wrote this, she was 59, which was the age I was when I started my presidency. 362 00:37:44,670 --> 00:37:50,520 It's actually just a lot. It could be right as just a little bit patronising. 363 00:37:50,520 --> 00:37:57,140 But anyway. Roll forward. Benjamin Jamoke died in 1893. 364 00:37:57,140 --> 00:38:02,540 Florence was still going strong in 1996. You can see her in her room. 365 00:38:02,540 --> 00:38:11,680 She's got notebooks. She's got her notebooks. And I came across this this year and I thought I was fading. 366 00:38:11,680 --> 00:38:16,580 Yeah, it's the right thing to do to stay at home. But I thought, gosh, I meant to have been travelling. 367 00:38:16,580 --> 00:38:20,780 I was meant to be coming to Oxford, going to Finland, going to the states, you know, 368 00:38:20,780 --> 00:38:27,500 all sorts of nice things being present about how can I be a president when I'm just stuck in the desk in my bedroom. 369 00:38:27,500 --> 00:38:32,540 But actually, when I saw that, I thought, well, Florence did a huge amount from her room. 370 00:38:32,540 --> 00:38:39,740 She did even more effectively. I think it gave me real courage that, you know, there's more than one way of doing what you need to do. 371 00:38:39,740 --> 00:38:44,510 So at that point. I have haven't even asked that permission. 372 00:38:44,510 --> 00:38:49,880 I have coopted. Preston's past. 373 00:38:49,880 --> 00:38:56,110 The current president and president future to wish Florence a very happy birthday. 374 00:38:56,110 --> 00:39:01,520 And to say that the RSS and statistician's everywhere are trying to follow in her footsteps. 375 00:39:01,520 --> 00:39:10,710 So thank you very much. Oh, thank you very much, Deborah. 376 00:39:10,710 --> 00:39:15,461 That's amazing.