1
00:00:00,060 --> 00:00:05,010
The testing you're getting. So this is I'm talking to John Bell for the second time.

2
00:00:05,010 --> 00:00:11,250
And we're picking up from having got to the point where we had agreement between AstraZeneca and the university and the government.

3
00:00:11,430 --> 00:00:23,909
Yeah. So so I have to go back to go forward because the what became very clear during the month of February as the disease took off in Lombardy,

4
00:00:23,910 --> 00:00:29,160
in Italy, that the that we were likely to have a really bad pandemic.

5
00:00:29,280 --> 00:00:34,170
So this is February 2020. Exactly. That's it. Yeah. And that.

6
00:00:35,170 --> 00:00:39,489
You can. It was interesting because I spent a lot of time looking at the curves and the numbers of cases,

7
00:00:39,490 --> 00:00:42,910
and you can see the curve in Lombardy, which went like that.

8
00:00:42,910 --> 00:00:48,520
And if you just went back about six weeks, we were just here and we were following the curve.

9
00:00:48,520 --> 00:00:55,330
Exactly. So you knew it was going to happen and the the health service hadn't yet sprung into action?

10
00:00:56,200 --> 00:01:03,280
Not that it ever would, I don't think. But anyway, the the health system was largely unprepared for trouble.

11
00:01:04,330 --> 00:01:08,440
And there were a set of things that were of real concern.

12
00:01:08,470 --> 00:01:17,650
One was PPE, where despite the fact, knowing something was coming from early in January, they made no effort to fix the PPE problem.

13
00:01:17,650 --> 00:01:22,750
That was going to be a catastrophic problem which had turned on me and I didn't have anything to do with that.

14
00:01:22,750 --> 00:01:27,430
I stayed completely away from that nonsense. I actually wasn't entirely true.

15
00:01:27,430 --> 00:01:34,320
I did take a big shipment of PPE from. Friends in Hong Kong rang me up and said, We are in trouble.

16
00:01:34,850 --> 00:01:39,089
My life. You want a container for PBS? Yes, please. But that.

17
00:01:39,090 --> 00:01:42,300
That society. That's the second one with ventilators.

18
00:01:43,380 --> 00:01:46,430
And everybody knew you're going to need a lot of ventilators.

19
00:01:46,440 --> 00:01:50,800
And the Italians had started to run out of ventilators, so thinking it's good.

20
00:01:51,510 --> 00:01:55,320
So the government decided to launch a competition for ventilators.

21
00:01:56,350 --> 00:01:59,680
In the hope that they would be able to find a design for a ventilator that would

22
00:01:59,800 --> 00:02:03,220
work and that we could make here because they didn't have enough ventilators, basically.

23
00:02:04,030 --> 00:02:12,610
And I, I was not directly involved in competition, but I was very directly involved in thinking about the ventilator solution.

24
00:02:14,740 --> 00:02:20,950
And indeed, in the middle of March, at the end of March, I called the Chennai Zoo,

25
00:02:20,950 --> 00:02:24,519
who used to be the minister of health in China, who's an old colleague.

26
00:02:24,520 --> 00:02:28,570
And I called him up until we need a ventilator. So he said, no, I will get your ventilators.

27
00:02:28,600 --> 00:02:33,520
And they lined up a big shipment of ventilators from the UK and then I passed that

28
00:02:33,520 --> 00:02:36,759
through to number ten and they actually number ten were on the call with me,

29
00:02:36,760 --> 00:02:41,440
I think. And that and, and meanwhile they were running this competition.

30
00:02:41,770 --> 00:02:47,110
But the competition in the end got to a completion.

31
00:02:47,290 --> 00:02:50,529
But they never they never activated because they turned off.

32
00:02:50,530 --> 00:02:57,790
They had nothing later. So I was in, but there was a very good ventilator done by the engineers here, which I thought was one of the best in play.

33
00:02:58,240 --> 00:03:03,370
And I helped them to get it in the right place. But in the end they never got their ventilators deployed.

34
00:03:03,370 --> 00:03:06,160
But it was another problem. And then the third thing was testing.

35
00:03:07,300 --> 00:03:16,390
And I was involved in a meeting, I guess that second or third week of March with the team from number ten and that small group of people from.

36
00:03:20,440 --> 00:03:30,490
And DHC and because it was pretty clear and the W.H.O. had even said it, if you don't testing, you're done because you don't know who's got it.

37
00:03:30,820 --> 00:03:35,200
At that stage, we didn't know that at least half the people were going to be asymptomatic.

38
00:03:35,230 --> 00:03:42,540
That's a little hamstring. So we didn't know that. But if if it was true and we know from flu that a large number of people are often Asian man.

39
00:03:42,550 --> 00:03:46,570
So if it was like flu, we were going to be in big trouble if we had no testing.

40
00:03:47,440 --> 00:03:54,970
So I was at a meeting where we were trying to work out a testing strategy and we ascertained that the whole of the NHS,

41
00:03:56,290 --> 00:04:00,670
the whole of the NHS were managing about 4000 tests a day.

42
00:04:02,060 --> 00:04:05,170
Actually, I think we did this. Okay. All right. Okay. We've done this. Okay.

43
00:04:05,190 --> 00:04:09,470
That's how we do. We do the Lighthouse Labs. Yes, we do. All right. Okay, so roll that.

44
00:04:09,650 --> 00:04:13,010
That's all good. That's fine. That's okay. Yeah. So then.

45
00:04:13,010 --> 00:04:16,310
Then lots of action stuff done to deal with Pasco.

46
00:04:16,460 --> 00:04:24,890
Ready to go? Pasco then launched off to try and find global manufacturers for the vaccine, which she did unbelievably well,

47
00:04:25,160 --> 00:04:28,640
signed a deal with Serum Institute within about a week of signing the deal with us.

48
00:04:29,090 --> 00:04:33,530
Serum Institute is the big global player in vaccine production, so that was really exciting.

49
00:04:34,820 --> 00:04:44,629
In India. It's in India. Yeah, that's right. And and actually at its peak, Sherman said it was producing 250 million doses a month of our vaccine,

50
00:04:44,630 --> 00:04:47,690
which is, if you think about it, is eyewatering amounts of vaccine.

51
00:04:47,690 --> 00:04:50,810
So so these they really did do what they said they were.

52
00:04:51,110 --> 00:05:01,670
So that was good. And and and of course, I was tracking down they phase two trial, which Andy had done is phase one now moving into phase two.

53
00:05:03,590 --> 00:05:08,690
And of course, during the course of that spring there was quite a lot of disease in the UK.

54
00:05:08,690 --> 00:05:10,760
So we were quite optimistic we were going to get a signal.

55
00:05:11,240 --> 00:05:18,190
We thought there would be a signal by September based on that prevalence of cases, but everybody was pretty wary about that.

56
00:05:18,800 --> 00:05:22,640
It's a it's a pandemic goes away, then you don't get an answer, if ever.

57
00:05:22,970 --> 00:05:28,040
And that's what happened. So you'll remember that for summer, the disease largely went away in the summer.

58
00:05:28,050 --> 00:05:34,310
Yes. And and as a result, they were now in Brazil, where they were having a wave in July, August, September.

59
00:05:34,790 --> 00:05:41,840
But the whole thing was a bit awkward, actually. And and then there were multiple events over that period that were complicated.

60
00:05:42,620 --> 00:05:45,740
They had a lady in the trial who.

61
00:05:46,700 --> 00:05:52,280
Developed transverse myelitis and inflammation. And and Andy quite rightly stopped the trial.

62
00:05:55,130 --> 00:06:02,390
And the MHRA looked at it. Single case transverse myelitis happens in young women.

63
00:06:03,260 --> 00:06:07,810
What to do? The vaccine? Who knows? They thought about it was fine.

64
00:06:07,820 --> 00:06:10,970
She was getting better. But on steroids all time back in action.

65
00:06:11,000 --> 00:06:17,780
So that was all complicated. But the problem with that was that the Americans who hated this vaccine because it wasn't

66
00:06:17,780 --> 00:06:22,909
an American vaccine decided that they would put a full hold on the AstraZeneca trial,

67
00:06:22,910 --> 00:06:30,680
which AstraZeneca had now started and which was going to be one of our key pivotal trials for approval in America.

68
00:06:31,850 --> 00:06:35,249
And the Americans said, no, no, you had a case of transverse myelitis.

69
00:06:35,250 --> 00:06:41,000
You got to stop the trial. And instead of doing what the imagery did, which was, hey, look, you know, let's keep going.

70
00:06:41,600 --> 00:06:44,930
And to be clear, there were no other cases transverse myelitis throughout all the trials.

71
00:06:46,910 --> 00:06:55,970
They paused the AstraZeneca trial for six weeks, which actually is pretty identical, actually, a trial which is in fact is very, very bad behaviour.

72
00:06:56,750 --> 00:07:01,280
And AstraZeneca was then in a series of scraps with the American.

73
00:07:03,470 --> 00:07:10,640
Hierarchy. Operation Warp Speed, which has been set up by Trump to accelerate the development of vaccines,

74
00:07:11,210 --> 00:07:15,530
was accelerating the development of the American vaccines and holding up AstraZeneca at

75
00:07:15,530 --> 00:07:21,280
every turn with a whole load of ridiculous inputs that just didn't make any sense at all.

76
00:07:21,410 --> 00:07:23,360
Run by coming months have Slaoui,

77
00:07:23,360 --> 00:07:32,130
who had run vaccines GSK and I'd often wondered whether he had a grudge about AstraZeneca being in the lead rather than GSK.

78
00:07:32,150 --> 00:07:33,709
Anyway, that's a separate issue.

79
00:07:33,710 --> 00:07:46,320
But the anyway he was that was that was very bad behaviour and and the American press were being pretty negative about it and saying, well it's bad.

80
00:07:46,430 --> 00:07:50,900
And by the way they hated the fact that it was a not for profit. Yes, they really hated it.

81
00:07:51,350 --> 00:07:52,430
And they said, well, you know,

82
00:07:52,910 --> 00:07:58,550
the only successful vaccines are going to be ones where people make a lot of money because the money driving innovation turned out not to be true.

83
00:07:59,000 --> 00:08:03,260
So anyway, so that was so that was pretty bumpy all the way through the summer.

84
00:08:05,310 --> 00:08:10,380
And that. Obviously that caused a lot of.

85
00:08:11,430 --> 00:08:17,579
Questions and challenges, and we had to work quite closely with AstraZeneca to manage all that stuff.

86
00:08:17,580 --> 00:08:25,260
And I was meeting with them weekly with many and Pascal and Andy Pollard and I were on the phone saying, What do we do about this?

87
00:08:25,260 --> 00:08:31,140
What to do about that? And then there was lots of tricky got.

88
00:08:32,090 --> 00:08:35,960
Communications issues, as you might imagine, because everybody want to know about the vaccine,

89
00:08:36,030 --> 00:08:39,640
but they also wanted to know if there were any problems with the vaccine.

90
00:08:39,650 --> 00:08:47,840
So it was it was the usual press melee. And then as we got through the end of the summer or then there was excitement was

91
00:08:47,840 --> 00:08:52,480
growing because we thought we might get a readout of the vaccine fairly soon.

92
00:08:52,490 --> 00:08:59,809
And the way that works is you have a safety monitoring committee that sees the cases as

93
00:08:59,810 --> 00:09:03,050
they come in and they're either in the placebo group or they're in the treated group.

94
00:09:03,410 --> 00:09:08,000
And once you get to a certain number of cases, you can then look to see if it's 5050,

95
00:09:08,000 --> 00:09:13,790
in which case it hasn't worked or whether it's 73, in which case it has worked or whether it's 9010 and all that stuff.

96
00:09:14,450 --> 00:09:21,080
And so we we had expected a result late September, but of course, we didn't know.

97
00:09:21,090 --> 00:09:22,520
And Andy didn't know. Nobody knew.

98
00:09:22,520 --> 00:09:27,890
On our end it was all data was going in and out, but we did know it was going to be slower because of the lack of UK cases.

99
00:09:29,480 --> 00:09:39,799
And then that ground on a bit through the autumn until I guess late October when the news of the Pfizer vaccine,

100
00:09:39,800 --> 00:09:46,300
which was either late October, early November, but it was about that time their result came through because they had had a much bigger trial.

101
00:09:46,310 --> 00:09:51,530
Their trial was 40 or 50,000 people in America where the disease was rife.

102
00:09:51,770 --> 00:09:54,770
So they got lots of cases and they had a great result.

103
00:09:56,790 --> 00:10:00,210
With very high levels of efficacy, 90 some percent efficacy.

104
00:10:01,050 --> 00:10:04,410
And so everybody said, wow, we, you know, there will be a vaccine.

105
00:10:04,440 --> 00:10:08,340
Now, the problem with that vaccine, of course, is it had to be handled at -80 degrees.

106
00:10:08,670 --> 00:10:13,440
You could never get it to the developing world. And they were charging a ton of money for it.

107
00:10:13,450 --> 00:10:19,950
So it kind of didn't meet any of our criteria for what we wanted to achieve, but it was a good vaccine.

108
00:10:19,950 --> 00:10:23,820
And so we knew at that point that things were going to be okay, probably.

109
00:10:24,600 --> 00:10:34,770
And and and I was famously asked by Sarah Montague on the back of that whether I thought things would be okay by the spring.

110
00:10:35,640 --> 00:10:44,129
And I did say that they would be. And this was I think I made a note because you had to comment to the Select Committee on Science and Technology.

111
00:10:44,130 --> 00:10:47,880
This whole epidemic has relied too heavily on assumptions that have turned out not to be true.

112
00:10:47,910 --> 00:10:53,720
My strong advice is to be prepared for the worst. So I think that was the most downbeat I ever heard you be.

113
00:10:53,730 --> 00:10:57,920
And after that, you started being more on the optimistic and chirpy trophy.

114
00:10:57,990 --> 00:11:03,570
That's exactly right. And I and actually what's interesting is I she said by the spring, we're going to be getting back to normal.

115
00:11:04,410 --> 00:11:07,740
And I said I said, yes, yes, yes, we will.

116
00:11:07,860 --> 00:11:12,150
And that got broadcast everywhere, keeping broadcast even to this day.

117
00:11:12,510 --> 00:11:22,290
And it turns out that actually I was probably right and the only thing and because that that corresponds to exactly their on my behalf.

118
00:11:22,710 --> 00:11:25,140
Had we paid attention to the date of the message.

119
00:11:25,140 --> 00:11:30,410
Sorry, I'm just saying that on the graph this is a massive falloff in the number of jobs deaths, I guess.

120
00:11:30,420 --> 00:11:34,920
And so what did I think? And to be clear, I didn't know this when I said that.

121
00:11:35,370 --> 00:11:40,200
But what is now become apparent is that it had this massive impact on the most severe form of the disease,

122
00:11:40,560 --> 00:11:47,130
which is that terrible, inflammatory pneumonia that put lots of old people face down in a hospital on a ventilator.

123
00:11:48,630 --> 00:11:53,850
And that was almost completely eliminated by two doses of any of the three big vaccines.

124
00:11:54,000 --> 00:11:59,220
So so that was marvellous, actually. So I thought, okay, here we go, this is going to be great.

125
00:12:00,360 --> 00:12:07,589
Let's wait and see. Modiano reported about two weeks later, same sort of data and then about two weeks later.

126
00:12:07,590 --> 00:12:11,550
And he called me up in a weekend and said, You better get together because the data is now in.

127
00:12:11,940 --> 00:12:15,989
And I knew if you called me that we had a result because they wouldn't have that.

128
00:12:15,990 --> 00:12:22,230
We wouldn't have had a result. Okay, well, that's fine. So we had a long chat on Sunday night and the data was pretty good,

129
00:12:22,480 --> 00:12:30,840
but not easy to interpret in the sense that there were several groups of patients that were different because of the way the vaccine had been given.

130
00:12:31,350 --> 00:12:34,560
In one group there had been a low dose in a normal dose.

131
00:12:34,890 --> 00:12:39,810
And you know, that sounds about right. Yeah. And annual explained to you what it actually happened.

132
00:12:40,260 --> 00:12:47,970
And you know, the good news is at its best it was 90% and at at at its worst it was 60%.

133
00:12:48,180 --> 00:12:56,040
And that's still a fantastic result, a message that we we we were hoping for 60%, I have to say that's I kept saying if we got 60%, be amazing.

134
00:12:56,490 --> 00:12:57,340
So that was a gap.

135
00:12:57,360 --> 00:13:05,190
And and of course, the other thing, which, of course, emerged as we interrogated the data was the dose interval turned out to be crucially important.

136
00:13:05,760 --> 00:13:11,280
And they the 60% was a four week after dose interval, which is the worst interval you can have.

137
00:13:11,280 --> 00:13:17,970
Six is better, eight is better, ten is better, 12 is better. So as we got better, of course, the the results got better and better.

138
00:13:18,570 --> 00:13:24,330
And I did make the point and I think I made this point on Radio four over that period.

139
00:13:24,330 --> 00:13:29,820
I said, look, first of all, it's not a it's not this is not an Olympic 100 metre race.

140
00:13:30,240 --> 00:13:35,790
We're not competing against anybody. We're just trying to get vaccines out and terrific work for everybody because it's great,

141
00:13:36,300 --> 00:13:43,920
but just go a bit carefully trying to compare this vaccine to that vaccine, because the truth is they were different trials.

142
00:13:43,920 --> 00:13:47,280
They were done in different groups of people. The end points are completely different.

143
00:13:47,280 --> 00:13:54,690
And now that turned out to be a very wise observation because the endpoint had been severe pneumonia leading to death.

144
00:13:55,710 --> 00:13:58,020
We would have been equally good as any of the other vaccines.

145
00:13:58,290 --> 00:14:03,480
If it was a head cold and bit of a cough, they might have been a bit better than we were and so on and so forth.

146
00:14:03,870 --> 00:14:10,259
And I also said, look, you know, we still don't know the rules of the road. So and we also don't know how durable vaccines are going to be.

147
00:14:10,260 --> 00:14:13,530
Said, you know, be careful because they only last three months.

148
00:14:13,530 --> 00:14:17,040
It's not much help to you. And of course, all that's played out.

149
00:14:17,160 --> 00:14:20,639
It turns out that none of the vaccines are very durable and none of the vaccines

150
00:14:20,640 --> 00:14:23,850
stop transmissions and none of the vaccines stop you getting the head cold.

151
00:14:24,600 --> 00:14:28,170
And they're very bad against various forms of the variant of the virus,

152
00:14:28,560 --> 00:14:33,180
but they fix that problem, which is to win, because that's actually what we were trying to do.

153
00:14:33,510 --> 00:14:37,110
The problem of the people, severe illness. That's right. Exactly.

154
00:14:37,110 --> 00:14:41,610
So that I mean, that was hugely exciting. And then, of course, over the course of the next three months,

155
00:14:41,970 --> 00:14:46,800
we started to get lots of real world data in from what was really happening in people who've been vaccinated.

156
00:14:47,130 --> 00:14:52,170
And that data showed that our vaccine was within a couple of percentage points, the same as the RNA vaccines.

157
00:14:52,500 --> 00:14:55,580
And you can do all this stuff. So.

158
00:14:56,990 --> 00:15:00,710
So that was that was a very interesting time.

159
00:15:01,120 --> 00:15:05,929
But, you know, it had its all its challenges. So we you know, the Russians took a run at us.

160
00:15:05,930 --> 00:15:11,180
They said if you had the vaccine, you'd turn into a monkey because it was a challenge vector German virus in the times and all that stuff.

161
00:15:11,630 --> 00:15:16,400
And then and then we had then, of course, Pascal, this massive fight with the Europeans,

162
00:15:17,030 --> 00:15:22,550
which was entirely bad behaviour from the Europeans beginning to end, wasn't Pascal's fault at all.

163
00:15:23,090 --> 00:15:28,069
He'd spoken to me earlier in the autumn and said, Oh, JBS, and now I understand why you guys get Brexit.

164
00:15:28,070 --> 00:15:35,420
I'm trying to negotiate the bloody European complete nightmare because they were trying to procure in a classical European procurement mode.

165
00:15:35,810 --> 00:15:40,640
And he was trying to say, If you want some vaccines, get your name on the bloody list because everybody else wants a vaccine.

166
00:15:42,980 --> 00:15:52,219
And then of course, when it when the vaccine actually then was approved and the Europeans said, well, where's our 200 million doses?

167
00:15:52,220 --> 00:15:56,030
You two were like, can you be tremendous? And you him 40 million doses, whatever the number was,

168
00:15:57,620 --> 00:16:04,820
which incidentally was as a percentage at least as much as they were going to get from Pfizer and more much more than they were going to get from JNJ.

169
00:16:04,850 --> 00:16:09,560
But despite that, I think again, because of the Brexit UK thing,

170
00:16:10,490 --> 00:16:15,590
they could see that the UK was rolling out this massive vaccine programme largely based on our vaccine,

171
00:16:15,590 --> 00:16:19,100
and they were going, Well, hang on then, what about us? And Pascal said, Sorry, you guys.

172
00:16:19,460 --> 00:16:28,220
They signed the agreement in July. You waited forever to sign it, and we're doing it as fast as we can, so you have to stay calm.

173
00:16:28,610 --> 00:16:37,850
So that was ugly. And then there was a lot of bad social media, mostly driven by the Russians again, which talk the vaccine down.

174
00:16:39,320 --> 00:16:43,190
Macron said it couldn't be used in the over 50 fives.

175
00:16:43,190 --> 00:16:46,280
And then it said, well, it can only be used in the older kid, you guys.

176
00:16:46,280 --> 00:16:50,510
And then he said, I'm not having the nature of my word at it. So, I mean, he was a complete idiot.

177
00:16:51,140 --> 00:16:57,770
Angela merkel and the Paul Eric Institute in Germany were also completely helpless because they had decided,

178
00:16:58,190 --> 00:17:02,979
because they had their own German vaccine, that they didn't want any bother about the anniversary.

179
00:17:02,980 --> 00:17:09,470
So they caused a lot of trouble with misinformation, even a statement that the vaccine had an 8% efficacy level.

180
00:17:09,680 --> 00:17:12,920
And I mean, A&E has never been able to work out where that number came from.

181
00:17:13,190 --> 00:17:16,190
Somebody just dreamt it up. I think we can all in despair.

182
00:17:17,270 --> 00:17:18,530
So that that was tough.

183
00:17:19,790 --> 00:17:27,439
But the good news was MHRA responded immediately and got the approval and in the first week of January they started to run the vaccine.

184
00:17:27,440 --> 00:17:31,300
And then, you know, AstraZeneca was great about providing 5 million doses.

185
00:17:31,310 --> 00:17:39,350
We started out with three fab actually Oxford Biomedica, another star performer, best production on the planet.

186
00:17:40,640 --> 00:17:44,330
Well, actually, volume wise, it was Sherman's stupid speed watch.

187
00:17:44,330 --> 00:17:51,170
It was actually Biomedica. So that was great. The only people who couldn't produce the vaccine were the Americans who were trying

188
00:17:51,170 --> 00:17:54,829
to make it and they couldn't make it and they couldn't make the vaccine either,

189
00:17:54,830 --> 00:18:00,530
which is quite interesting. And and then the plant in Belgium which the European plant, they couldn't make it either.

190
00:18:00,530 --> 00:18:08,359
So so all our raw that you got from America was, you know, specious because the truth is they didn't you know,

191
00:18:08,360 --> 00:18:12,800
they didn't know the first thing about CMC and all that stuff. So they were pretty stupid.

192
00:18:13,070 --> 00:18:16,640
But nevertheless the UK program went terrifically well. They rolled it out.

193
00:18:16,670 --> 00:18:21,530
Nadhim Zahawi Star. I knew him from the last government thing.

194
00:18:21,530 --> 00:18:29,120
He's such a good guy and set the programme up, took it out of the NHS, get it as a separate programme, which is the right thing to do.

195
00:18:29,660 --> 00:18:38,690
And off they went. So that now then about mid-March we got a few reports of surgical vein thrombosis,

196
00:18:39,500 --> 00:18:46,580
a form of stroke, but a venous stroke clustered in northern Europe, mostly Norway.

197
00:18:48,730 --> 00:18:50,620
Denmark and Germany.

198
00:18:52,430 --> 00:19:00,860
And at first we thought, okay, because we'd seen a bit here and it was very difficult to know whether it was above background levels.

199
00:19:01,310 --> 00:19:04,970
And we we because the numbers were so small, we get to know.

200
00:19:05,360 --> 00:19:11,750
But when more cases started to be reported, there was a question whether it's an ascertainment bias or whether it was a real problem.

201
00:19:12,440 --> 00:19:17,059
But as the cases started minor, we could think of probably a real problem.

202
00:19:17,060 --> 00:19:25,700
So we're going to just go have a look. Then we had a whole load of people looking at vaccine registries and then adding

203
00:19:25,700 --> 00:19:29,450
up everything that they could find that had happened to people who had a vaccine,

204
00:19:29,960 --> 00:19:32,660
which was a massive overestimate of what was going on.

205
00:19:33,350 --> 00:19:40,610
But fortunately, sensible people looked and it looked like this had just had a prevalence of about one in 100,000,

206
00:19:41,090 --> 00:19:43,460
and it had a mortality of about one in a million,

207
00:19:44,030 --> 00:19:49,940
which in the context of a national vaccine was perfectly acceptable, particularly when you saw the mortality from that anyway.

208
00:19:50,180 --> 00:19:55,430
That that, of course that developed its own momentum, revved up by the press, caused all kinds of trouble,

209
00:19:55,820 --> 00:19:59,479
created huge amounts of vaccine hesitancy in various parts of the world,

210
00:19:59,480 --> 00:20:04,940
which is not very helpful and turned out to be, you know, an impediment for the vaccine.

211
00:20:04,940 --> 00:20:09,139
But they the decision taken by the government, which I think was a good decision,

212
00:20:09,140 --> 00:20:15,770
was to just give the vaccine to people over the age of 40 and avoid it going in to younger people and women in particular,

213
00:20:16,550 --> 00:20:21,200
because, of course, we had RNA vaccines, which didn't have that either. So and that was a good decision.

214
00:20:21,200 --> 00:20:25,880
And both Andy and I agreed that for the vaccine, it was best possible thing,

215
00:20:26,360 --> 00:20:29,330
because what you really want to do is give the vaccine to people are going to die,

216
00:20:29,840 --> 00:20:35,390
not people who are six years old and going to school, who you don't want to spread the vaccine or on site, which is fine.

217
00:20:35,400 --> 00:20:41,660
You want to put RNA vaccines into those guys. Good luck to you, because we want our vaccine to be used to stop people from dying.

218
00:20:42,050 --> 00:20:47,240
So the majority of our vaccine globally has actually gone into the high risk populations, which is quite interesting.

219
00:20:47,240 --> 00:20:53,360
And that means that the tally of lives saved gets better and better, because once, you know,

220
00:20:53,360 --> 00:20:58,970
the Americans are now in their fifth dose, you'll be saving no lives in people who are on their fifth dose of vaccine.

221
00:20:59,360 --> 00:21:02,690
Pfizer will be making lots of money, but there will be no lives saved.

222
00:21:02,870 --> 00:21:07,100
So so that basically is that, you know, that's sort of part of that.

223
00:21:07,550 --> 00:21:11,750
It was part of the philosophy. Yeah, I thought, yeah, well, we're not making any money, so let's forget that.

224
00:21:12,080 --> 00:21:19,100
How do we get it out? And then we started to run into trouble because India decided they had a big problem.

225
00:21:19,100 --> 00:21:26,810
We'd always worried about India because lots of people with comorbidities, diabetes, hypertension, fairly elderly population.

226
00:21:27,680 --> 00:21:32,540
There was some worry about ethnic liability and that's how patients want to take care of people.

227
00:21:33,020 --> 00:21:39,020
That story is not really held up by data. We were worried about it and so the Indian government said, well, you know,

228
00:21:39,320 --> 00:21:43,760
Serum Institute's great but and we know most of that have that vaccine's intended to go

229
00:21:43,760 --> 00:21:47,360
to Africa but we're not going to let it go we're going to give it to everybody in India.

230
00:21:47,360 --> 00:21:54,589
So they embargoed the plant. And then I knew we had a problem because that meant Africa was going to get tougher because you couldn't use

231
00:21:54,590 --> 00:21:59,790
the RNA vaccines in Africa and JNJ was still months behind in terms of we haven't entered COVAX in all this.

232
00:21:59,790 --> 00:22:03,940
So the COVAX with the guys deploying the vaccine. Yes. So, so, so.

233
00:22:04,100 --> 00:22:07,130
And they had relied very heavily on AstraZeneca for all the right reasons.

234
00:22:09,920 --> 00:22:13,610
But, you know, they were stuck as well because they didn't have any vaccine supply from India.

235
00:22:14,510 --> 00:22:19,459
So we shipped them a bit of vaccine back and forth from other places.

236
00:22:19,460 --> 00:22:22,190
But they, you know, on the whole, they didn't have much.

237
00:22:22,910 --> 00:22:29,719
And that was made worse by the fact that the South Africans decided that they didn't like the vaccine either.

238
00:22:29,720 --> 00:22:36,650
And so they shipped back. They had X million doses and they shipped them back to headquarters saying we don't want the vaccine,

239
00:22:37,190 --> 00:22:40,280
which again was a completely stupid decision because they were back to India.

240
00:22:40,760 --> 00:22:44,360
No, they went back to Geneva because that was where Covaxin shut them in.

241
00:22:44,570 --> 00:22:53,360
So and again, that was it was not you know, it's all this was all there was all this stuff going on and so that it caused what's true.

242
00:22:54,050 --> 00:22:59,690
So so that so Africa was basically unvaccinated, so they were completely exposed.

243
00:22:59,870 --> 00:23:07,520
And and in fact, in the end, although they're vaccinating at reasonable rates at the moment, they protected themselves by natural infection,

244
00:23:08,300 --> 00:23:13,580
which caused lots of deaths in South Africa, but not that many deaths in places like Nigeria, which is interesting.

245
00:23:13,580 --> 00:23:17,480
And nobody really understands that. Maybe ascertainment of it, maybe something else.

246
00:23:19,070 --> 00:23:23,570
So all that was going on as well at the same time.

247
00:23:24,770 --> 00:23:32,569
And it was a you know, it was a pretty bumpy journey because we set up a big program in Eswatini.

248
00:23:32,570 --> 00:23:39,080
So as the South African said, we don't want the vaccine. And that's where people said, well, you know, we want the vaccine.

249
00:23:39,080 --> 00:23:42,320
So Annie and I set up a program there to vaccinate the whole population.

250
00:23:42,920 --> 00:23:50,480
And then subsequently we've been working with Zimbabwe, Uganda, Tanzania, Ghana, whole variety of countries.

251
00:23:50,540 --> 00:23:55,200
So the. The vaccine is still being manufactured and still still being distributed.

252
00:23:55,320 --> 00:23:59,640
Yeah, most of it is still being distributed, although there is now a massive surplus of vaccine.

253
00:23:59,850 --> 00:24:06,840
Is it being used in the UK at all? Don't know. The UK stopped when they got to the booster and I don't think it's being used at all in the UK,

254
00:24:07,140 --> 00:24:11,100
which is fine, you know, because remember it's the first two doses that make a difference.

255
00:24:11,100 --> 00:24:14,400
All the rest of this stuff is just. Yes, that's that's what the booster did.

256
00:24:14,730 --> 00:24:21,330
Absolutely nothing. So. So I so I think it's all you know, I'm relaxed, but it's not a big deal.

257
00:24:21,690 --> 00:24:25,710
But we were also then getting Nepal blue, so we had to get them vaccine.

258
00:24:26,130 --> 00:24:30,540
Thailand, fortunately out of sight in Thailand, which I don't set up to manufacture.

259
00:24:30,540 --> 00:24:34,409
So they started going Malaysia blue, Indonesia got into trouble.

260
00:24:34,410 --> 00:24:38,010
And, you know, the AstraZeneca vaccine was used pretty widely in all those places.

261
00:24:38,010 --> 00:24:41,010
So. So it was a pretty it was pretty good run.

262
00:24:41,640 --> 00:24:46,290
And I'm going to have to go. Yeah, sorry. We've got to go because I've got to.

263
00:24:46,290 --> 00:24:49,500
I'm sorry. I've got a lunch. Yeah, yeah. Oh three. Is that all right?

264
00:24:49,740 --> 00:24:50,680
That's fine. That is.