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Okay. So could you just begin by saying your name and what your current title is?

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And my name is Joe Sevilla. I am Professor Perinatal Medicine and the Naval Department, Obstetrics and Gynaecology, Women of Reproductive Health.

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This call now, and there's the General Electric Hospital, the University for Women and Reproductive Health.

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But yes, that's in. So first of all, can you just tell me a little bit about yourself?

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So starting from your earliest interest in your subjects, just give me the the main stopping points on your career so far.

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Well, I'm an obstetrician gynaecologist by training and being around in different places and conducting always

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research on maternal factors and foetal factors affecting perinatal outcomes and long term development.

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And then I they work in in rural areas in Central America.

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I went back to clinical practice ob gyn,

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Johns Hopkins for ten years in the U.S. and then went back to sort of a public health

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largescale research as a coordinator of maternal but maternal medicine at W.H.O. in Geneva.

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Then I was there was a program.

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This is an interesting background for the for the second part.

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The third time was a program called Human to Human Reproduction, A Human Reproduction Program.

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That was this is 1980 in the middle of 1980s.

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It was mostly development and testing and and evaluating, say, think of of contraceptives, different contraceptive methods.

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And then at one point, they decided that was too narrow and that women really because it was why they're then then contraception.

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Then they eventually went up to the maternal and being the component.

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There was there was another component infertility just to why they why there the concept.

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No, only on only contraception. Then I went there in 1989 and they built a large scale multinational multicenter training.

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We should receive training and research component on different factors related you to pregnancy, maternal health and prenatal health.

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And so just so sorry to interrupt, but just to give a little bit of background.

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How much of a public health issue was the kind of additional risks that women faced during pregnancy and childbirth?

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What was the question again?

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So what's what was the kind of scale of the of the public health concern around women at the time of pregnancy and childbirth?

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Well, this is a there was basic error.

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It is the role of the radio. You're supposed to be there.

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Although Joe Biden said this because there is the risk of maternal health changes to relatively high maternal death,

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for example, relatively high as in rural areas of Africa or Southeast Asia,

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or to very low in in developed countries or different diseases have different rates and or some diseases are similar range of complications.

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Then the idea was to understand the risk factors.

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The issue is the mandate of this program was to understand the risk factors and to understand the environmental conditions and environmental factors.

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And try to introduce a. Interventions to ameliorate the risk.

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And then there's the question,

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because that ranges from sort of a specific risk factors on preterm birth or or foetal malnutrition or being undernourished at birth,

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where they have obviously large differences in by vision with other programs that were provided provision of care,

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they get the care that women get during pregnancy or the extra care that they get with.

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There's increased rate of caesarean sections. Now, now there is an epidemic of caesarean section, everybody.

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There is a higher rate of caesarean section than needed for the risk.

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But in many places, the risk profile of the women then that was then.

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Then within that is directly leads to the commitment of our our reaction to react to the

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reaction to the global pandemic was that we learnt in large scale multi-country studies.

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That was my responsibility during 17 years in Geneva.

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And then one of them, for example, it was the issue of socialisation.

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What is the risk of is maternal risk associated with having a male surgery vis a vis the the benefit of saving, saving foetal life?

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Then obviously there is a balance between and now we are in the balance of saving fewer foetuses with a 30, 40% of caesarean section.

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And then this got this guide of a type of a balance.

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Then we did we did a similar large scale study in the whole in the whole world.

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No we didn't, we sort of a randomised we, we select randomly selected countries, hospitals and cities in the whole world.

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And then this was a is, it is a landmark study on the effect of maternal maternal factor.

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But interestingly enough there was, there was a, there was a very good contribution of this research.

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And so these contractions,

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there was a thing where we were in the it wasn't in the headlines or the newspapers in the UK actually saying that women were to push the push.

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I remember I was sort of in a tree with a Jemmy, which was not the case, but I think was it a good, good sense going around with these things?

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But I promote the papers as such. That was basically that the the they issue.

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No. And in 2008 and 2006, I moved to a firm with M&A to try to, you know, remain the main.

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There are there are several there are many maternal conditions affecting pregnancy.

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Fortunately, most in most countries where adequate care is provided and environmental factors are acceptable and or other group, these risk are low.

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But they still they are there and they need the risk.

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I mean, the risk during the labour and delivery, if conditions are adequate, they are very low.

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But there are still there are there are risk involved in pregnancy and feeding growth and so on.

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Maternal diseases, anxiety, postpartum depression.

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There are many other factors. Then they they they mandate.

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I got a good job for inches I think I was to conduct specific research large scale is to try to understand

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in a relatively short period of time with a large number of big big what is called now a big data a.

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What are the risk factors? Possible interventions and targeting subgroup subgroups to reduce the negative pregnancy outcomes.

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That being in general terms, the most central of these was preterm birth babies born earlier than than it should.

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And why is that? Why is that a bad thing for the the outcomes for those children who were born preterm?

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There's a risk of morbidity and mortality, long term development that that increases every week or every day that you get younger or earlier.

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Then that's basically the mandate. Then the problem.

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Obviously, this is a reason, of course, that then it has a has its extraordinary capability to provide care to southern England, if you will.

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But it still was traditionally in the age of the issue of pregnancy.

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It was sort of a regional hospital then we but the university is a is why it has a wider scope and it has a long tradition of international work.

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Then the task was to expand the gynaecological activities to a larger scale,

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according to the tradition of the university that has been a training for many tropical diseases or other things globally,

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then that's where we started doing it. But the bottleneck was not there wasn't a patient, it was not the university, although,

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as you know, huge, slowly, but there wasn't it was not the the University of the Negev.

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These large skills and a project was that the the the the clinical and scientific status of pregnancy,

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pregnancy care and pregnancy research was rather uncontrollably and not standardised.

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Then it was, was basically very difficult to conduct multicenter studies with, with people more or less doing whatever they feel better.

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By the obvious, you can imagine the feeling better.

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It changes dramatically with it, which was this person of each institution.

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Then the they were task. And then we spent about the 40 or five years until early just ten or 11 a standardisation.

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Care occurs globally across those people.

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I want you to do it. Obviously, you don't want to do it, but there are those people that were willing to do it.

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Standardised care according to the best practices.

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So you have participating hospitals in different countries around the world who were agreeing to fund the right thing.

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Yes. Then that was that was one issue.

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But the other issue was that. And in many areas, the standard of care was unknown.

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And in other areas it's done. That care was risky.

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And that's you know, I don't know if you're expecting this but the amazing is harder to modify and and non effective treatment is harder than

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what you find an effective treatment than effective treatment then there are no effective practices or risk there has been.

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No, no, I mean historically amazing just being inside the product.

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They're amazing. They're very very difficult to take it over. And then the.

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And this was one of the main challenges.

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Fortunately, all four had these been involved in these efforts,

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a change of settling practices and collecting data based on best best practices

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and more effective effective which was eventually became evidence based medicine.

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And a colleague and friend and gentleman, it was the director of the National Perinatal Epidemiology Unit.

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And then he introduced promoted the concept of evidence based medicine in obstetrics.

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Then with me on background and the university background, we identified which things would be standardised right away.

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And but there were other, many other practices that were not ready to be standardised and even there were people having a conflict, the thinking.

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Then we spent all this time, particularly in pregnancy and preterm birth and FEDOROV Then we spent all this time and by.

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By 2014 or 18.

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Can we just get some names so that one of the projects that you set up was called into growth?

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Is that correct? You went back and.

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Yeah, and then the main the main project, because that was part of the mandate.

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The main project was called in the that will be a project to study the potential of foetal growth as a as a the early as a component of human growth,

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if you will, a that is known to affect early and long term medical conditions, development and so on.

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Then the the the issue the issue was to study a larger scale and the many different conditions,

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the consequences of different growth, foetal growth patterns and as a result of the project is gone that it was calling the road.

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The problem is, I don't know if you want to go on this.

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The only the only problem was that one of the bottlenecks on the standardisation and implementation of

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of large scale research or medical intervention was that it was entrenches and it still no in many,

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many areas the concept that the foetal growth.

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Is not a universal process and is more more related to a.

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Environmental, religious rights, a skin colour and so on.

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So the idea that people in but babies in some countries are naturally smaller than babies in other countries.

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Exactly. Then obviously, obviously like in other is if you are if you consider a feeding growth, this is abnormal foetal growth.

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And this is all bread and butter and this is your backbone earlier.

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And that that pathology is associated.

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With environmental factors, disease conditions, socioeconomic location, immigration, all the things.

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No, but it may. As you said, the main issue is that the.

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Following that concept. It is entrenched in many places still that that is is is is my is environmental is this is it.

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But at the end of the day, foetuses grow differently depending on the race, skin colour, ethnicity or even even more.

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Certainly not a country of origin of the mother or a all.

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And there is a sort of it genetic conditions associate with ethnicity.

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Where what did the integral study find.

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Well, obviously, obviously this concept where in some area in some in some of its manifestations were rather bizarre.

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Oh, I'm sure. And particularly people living in living in the in the in the previous century in in Europe or in in many developing countries

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where the borders were changed as there'd be women even now even no women arriving in the UK it you and get pregnant.

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Maybe they were living in one country when they left and they know the country has changed.

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Regions got changed. You know this is this is going suddenly well.

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But we we then confront a much larger scale resistance to this.

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Now, obviously in the road they originally conceived of, the road that was already there.

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Even more extraordinary thing was that they paediatricians in early 2000 decided for the

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attack the same concept because the concept was also extended to the to the children,

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that the children were genetically a smaller they were Indians from the subcontinent.

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They were smaller than or Chinese. The Chinese were smaller then, obviously by the changed by 200.

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Obviously, people start realising that Chinese were not any longer sure that they got it all.

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And in the subcontinent, there are many millions of people that are totally innocent.

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Then it's just to do with the mother being better nutrition environment nourished and the children being baptised and development development.

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Then there all these.

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Then they be regions immediately and before, which is, I think by the end the gist of it jump to Judaism and starting confronting these issues.

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Then us basically what we did is we made the approach to go to different regions,

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extreme regions like extreme related to the Mississippi and geographic areas,

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but no by the European adequate regions as we select the populations in which there were different ethnicity,

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religious skin, colours and noses and all the things different, but they were living, living under adequate conditions.

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Then there was the study saying that girls, girls, the world in which there were Chinese.

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Sort of just to make the argument simpler middle classes or high or middle middle classes in China?

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Me the middle classes in Nairobi. Blah, blah, blah.

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No different in Brazil. You know, places where in the US and England and in Europe.

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In continental Europe. Then there was. And then that's what they say.

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So. And the. And the hypothesis was. And then people started claiming, you know, the negative reaction was start blaming.

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No, we don't. We are not all identical.

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This is absurd. We're not identical. We never said that people would be identical.

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But the answer to that question, it was the variability.

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The answer is that they. Among humans.

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In in in the growth of the foetus, the growth of the brain of the foetus, the growth of any brain structures, oh,

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the foetuses and the development postnatal development of these multiple,

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multiple geographic areas where they studied a standardised and very rigorously.

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And when the background were similar in terms of carbon duration care, socioeconomic status,

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environmental fibre, the big, the foetal growth and up to two years in terms of any anything you name where.

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Unbelievable. Closer. Even age.

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Age of language, acquisitions, you know, even even all the things or things that were less and less tangible,

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like obviously tie or length is something you can measure.

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But then there are many other developmental issues in the one year or two years that they are not a obviously easily measured well,

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but then all the things were remarkably similar. More than expected.

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More than expected. And even yesterday.

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Yesterday I have we have a a colleague that is a workshop on artificial machine learning artificial intelligence in the in the in Oxford in the it.

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And then she was showing me yesterday that they have it they have a special way to

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take in three 3D volumes with ultrasound of the foetuses with our our foetuses,

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if you will. And then she got a fantastic technique in where they changed that sort of a very complicated

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are the individual intelligent things they in their measuring their the the the

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volume of the brain and the and different different structures within the brain as she

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was showing me yesterday that they they they they grow of children they are identical.

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But one if you if you're wrong in a growth language of the brain volumes.

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Of the foetuses of the original foetuses.

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We're using these most sophisticated things to measure, to quantify and describe the grey matter of the brain of the foetus.

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They are absolutely identical, but one line on top of the other.

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It's a thrilling because he's obviously, as you can imagine, that there is variability.

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They are not all identical, but the distribution, the distribution is the same.

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Well, yes, but their variability is a very small.

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But there is very religious. Your imagination can be both.

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You know, we cannot control these. These are free living individuals.

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But by the way, the more you get to things that are very specific to human nature,

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like the size of the brain, you know, the size of the brain or the or the structures of the brain.

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These are things that you can't know much about because, you know, people were saying they were completely even these things.

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I think they you can grow more grosser than all the other things.

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Mm hmm. In order to answer your question overall, we can say that the anything you want to measure we got, if the conditions were adequate,

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thereby the ability between sides is always in any measure that you make, there's always less than 10%.

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There is the variability. There is a 90% variability, which in humans is either or environmental or errors in they measure.

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But between the among sites, the comparison among ethnic geographic areas in the world today,

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there is never about 10% eight and for, as I said, sort of things that are basic to humanity, like size of the brain or a.

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Or even then they had the self-confidence of the head bones, bones that you obviously,

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once you get the bone, the length of your femur, you have it there, you can get the shoulder.

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Well, all the things there are never, ever more than more than five, 10% of the total body ability.

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Well, then this is the answer to this is a long answer to this question.

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Then let's park for a moment. I mean, that was a fantastic result.

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But what was also fantastic was that you had, over a period of years,

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set up a research network of committed individuals in hospitals all over the world

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who were prepared to adopt common standards in order to pursue answers to questions.

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So now I think you can come to say I just I've been asking everybody this question.

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Can you remember when you first heard about the pandemic?

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Yes. There was something going on in China. And that that that that might be something that your research network could become involved with.

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And. Yes. Well, actually I but precisely everything because a.

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And in during the summer.

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Well, during the the winter of 2020.

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In the winter junket agenda because you mean January, January two.

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You mean right at the beginning, January 24? Yes.

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And one of this is sort of one of the one of the one of the few advantages of getting old is is that I have more flexibility than the summer.

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You say that you keep working electronically rather than spend three, three months in the in the beach in South America.

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Well, in South America, basically. And in the beach, because this summer it was a summer there.

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Then I was there. I was preparing to go back. You were prepared.

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You go back to your junior jog for in my area at the end of March, early February, early March.

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And then we have these cases in June. But obviously, I follow that.

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But then at one point, because one of our Winter Warrior Centres,

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one of the main developed country operation is in northern Italy, in Torino and in Milan,

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and particularly in the city of Torino, AC Milan, as I said,

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the well-organised is we restudy all the liberties in the city of Torino during basic training for the growth project.

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No. Then when they beat me because I'm basically ignorant about infectious diseases.

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But when they when they realised that it was it was an infection epidemic or infectious disease, it was a recipe for respiratory transmission.

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And I started thinking in February just is other than trending,

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that is if this kid in northern Italy because northern Italy is in the winter in general.

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But most of the cities in northern Italy, they're well developed by.

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But housing is sometimes they are very, very nice to look at.

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But the they are all there are all all buildings and also because they obviously lot in

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culture there is many in the family leave the mother and father the children there.

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You know it sort of it it very clear that instead of thinking that if this is a respiratory disease, we hit our area.

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I mean, Turin or Lombardia, then I think there were these are the easily disseminate around.

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And particularly because, as you know, the fertility rate is very low among Europeans,

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but is relatively high or maybe about above replacement among immigrants and the immigrants living

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in the benefiting area of the European cities they live in rather than a chronic condition.

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Then I started thinking that maybe where I would bring up population instead of experience is this this epidemic like it happened with the flu?

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And if you had been me before, was it was a disaster then.

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Then in March, I went back the last day before they closed.

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We when we went back to Europe and then immediately in March,

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I contacted my geographic clinicians and colleagues in, you know, for the remainder remain active with us.

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And I said, what we should do, we should do it. We should ask you, as you were thinking, who who is a network to the names of those colleagues?

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We should. Stephen Kennedy. Then he was the head of the department.

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I think is papageorgiou. That is our main clinical active clinician in charge of all the clinical component of the study.

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And I remember I had a. A phone conversation within one Sunday in March.

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And I said, where we should we should go now immediately and do two things.

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One, activate all our centres to look at this.

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And you go to these people, you know,

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before and in the pharmaceutical industry without any contact and tell them that

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we should immediately incorporate a pregnant women to do the vaccine trials.

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Because if we don't, because in the end we don't incorporate the breakdown, we make a.

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Immediately in these vaccine trials. In a year from now, we will be in the same situation.

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And now, without knowing with the effect of pregnant women and and it is obvious that these diseases will affect pregnant women.

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Then I said, then Stephen Guinea, that has no more people in it for our own.

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And then we send a message to John Bell, the visual professor of medicine, that always John helps us support us in many in any way that he can.

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Is there where we should get involved with bringing on women immediately and obviously getting back women in the vaccine trust was almost impossible.

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They didn't do it. But the idea of component there was to activate our network and and and start immediately

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we started we were capable of doing start recruiting basically because in the centres were

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already standardised and we know that we make only a small modification to our they outright

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were a medical record because in the world has a system of electronic medical records.

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Then all of these centres participating they have the medical records electronic the same basically.

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They obviously these hospitals have their own specific things, but the core of the data collection is standardised.

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Then we only had you made modifications on the.

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On the specific issues related to the respiratory condition.

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At that time, nobody knew much about the disease but about the gore or the outbreak,

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and children were already there electronically, and then we basically started activating it.

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Obviously, there was a problem of testing. There were not there was no testing at the time, universal testing.

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And there were there were no vaccines then.

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But in any case, we in April and May, we started we started collecting collecting data.

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And I went to see what was the design of the study that use it and reason I was it

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was a prospective design because all are all this is another beauty of having that

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the system already in place there all these women and all of them but the most most

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of the women in these regions were China through the local medical institutions,

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but also were channelled through the world. I mean, they wrote a recruitment all women, you know, Netflix video thing.

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But then we did we did a detailed follow up in a smaller sample because these are some of these are big.

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And we all all these were geographic areas. There's no regions, cities or regions.

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So there should be then there was a this is a large volume of pregnancy.

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You can imagine we manage about 50,000 deliveries a year.

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This is something completely out of any easy, easy, any possibility to do it.

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If you don't have a good commitment from local authorities and colleagues worldwide,

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that then basically then then there was a prospect that to say, we know that these women will enter.

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And then through the channels of these institutions that we have standardised and we know that we are

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going to collect the data that we want to collect because they are already in online or electronically.

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Then they we even usually we didn't even we didn't physically contact us.

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A woman in the first trimester. The hospitals did contact these women early in pregnancy because they were part of the system and part of the system.

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Then we sort of answer your question. We reconstructed a cohort of women who started in April to South and during the

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day that were either part of the study because they arrived or were recruited,

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by the way, or by our by institutions collaborating with for two or three months earlier.

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Then we reconstruct the image created a huge cohort of pregnant women.

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The problem was there were not enough testing at that time.

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They were not know all old places. Most of the places, even even in developing countries, they have testing.

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But no, they didn't have enough test and they were expensive at this and they really didn't have enough test to test all these women then.

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Did they actually go for that? We follow.

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It was with this was smaller than the the the or the in the growth cohort because obviously these were the interviews with older women,

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but we didn't we didn't have enough testing for that.

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And then we use testing on symptoms at that time because no, they were the women that have already had these symptoms, blah, blah blah.

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But they didn't cause it this. Then.

295
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But these were the limitations in April, May and June of 2020.

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Those that's what you were looking to do was very simply to compare women who but whether it was by testing or by looking at their symptoms,

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you were pretty certain had COVID. I did not.

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And look at the outcomes. Yes. And this is exactly the way we did it, because we didn't call women with COVID.

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These were women diagnosed. Of having COVID because they were diagnosed, whatever, whatever method they have, they were they were they not.

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Somebody at the end of the day said, this woman hasn't gone and we recreate it prospectively.

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And the other thing that was unique was we compare these women with pregnant women that they know are going.

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And this is interesting because you you know, people always say, oh, that's obvious.

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We're building a enabling. It isn't.

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And there was no because there were there were many, many publications of ten, five, nine, nine in cases.

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Of course, within this place, another place and so on.

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Compare with Norway man with no comparison or compare with a known pregnant women.

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And then we said, this is not possible. This is this is a this is a this is a wrong comparison.

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And then at that time, the issue was, don't worry, this is a flu.

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And pregnant women are not at different risk of a flu than non-pregnant.

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That's was what it was known. Therefore, this is an old flu.

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Women, pregnant women should be taken. This is not a problem.

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And so on. But then, then, then our study and we were lucky also that, as I said, following the teaching,

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the young children, we had a system already in place also doing continuous, systematic reviews.

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We continuously review the literature in in collaboration with a group being bringing in that we continue to collect the data

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any paper published in 2002 and the own respiratory diseases where were collected and read and classify and and summarise.

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Then we were saying, listen, we are here saying that this is a new flu.

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No problem. There is you are a pregnancy is not a problem.

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And. And but but they don't have control groups.

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Even if they do, they have their own control because it's a no brainer.

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Women are different from their women for many, many working condition reasons, whatever.

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Then there should be a concomitant control group of pregnant women with some symbol.

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But then there was the difficult to convince people was difficult to convince a donors.

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But immediately.

324
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But interesting that neither one of centre we have Junes in February and in April 2002 ended with like a 5050 hospitals around the world as it were,

325
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willing to participate on this. And it wasn't really anything.

326
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It was that many of them did not exist because, you know, the pyramid was moved from China to northern Italy,

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then in Europe and then eventually disseminated many other places.

328
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But they were just because we don't have any place, any for any guys.

329
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We don't get guys who want to be part of the study, but we all have cases and we said,

330
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Don't worry, you will get away with it because you will get these cases is moving it.

331
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And then fortunately, which is the reality is always rather complicated.

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You have this diverse diversity in the U.S. We we really have immediately because we have had an integral jump from the U.S. and other.

333
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And then, of course, with us in Boston that they're participating in gigabit.

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But we're always satellites, friend friendly to us.

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They jump in immediately.

336
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Then we have a very nice, very nice representation with a concomitant contrast, I think that makes it make the whole difference.

337
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And then by October 2020, the study was over.

338
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We finished we have the largest study with controls and.

339
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They only want one thing before I tell you.

340
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They find that it was the funding issue.

341
00:42:51,840 --> 00:42:59,520
Yeah. And the we there was a completely these violence.

342
00:43:01,070 --> 00:43:08,719
Logical, logical. These balance between the investment made on many other things,

343
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including vaccines and the investment made in systematically analysing and documenting the risk associated with with COVID, with pregnant women.

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We we we did it before. The other thing for which we were already prepared is because we did it the same the same process with a sick epidemic,

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the virus infection in north in Brazil, we have we were participated and documented, I think, for the first time.

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And this this is another benefit of the decision.

347
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We documented for the first time the magnitude of the effect of Zika on brain development of the foetuses because that that's

348
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where they made their main problem was and because we were standardised already with the same way to measure the head.

349
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Oh, they feed us and then you work. We were able to document the exact magnitude of the effect.

350
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Then with all these background and then the funding was appropriate,

351
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we have in the reserves have been always grateful and lucky to have very good donors.

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And then with with good donors, we in general was blessed, which we conducted otherwise would have been impossible.

353
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And who are the who are the donors? Well, then the use of usual suspects by the church.

354
00:44:41,270 --> 00:44:54,410
By the. By the. If the pandemic was moving in a different direction, obviously, logically on on or on vaccine vaccine development.

355
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But. If we were not, we were not lucky.

356
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We were limited to lucky funding.

357
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Then we operated in a in a rather a rather not a or a budget for the question that we thought that was the obvious question.

358
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Then what is the concept? Pregnant women, particularly many in Europe and many, many.

359
00:45:24,870 --> 00:45:35,100
There were all the time working. They were working in conditions that were conditions that they were at high risk.

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Nurses and doctors and and a services restaurants support care and general care of the elderly.

361
00:45:49,370 --> 00:45:57,509
They were always were working on a risky front line of risk and many of young women what

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was there would be a large number of them pregnant eventually one woman and one boy.

363
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And then just to me, still, I mean, this is this is why there was a high risk population, a pregnant woman in direct contact with a basis.

364
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And then we still I don't understand why there were not a support or B or jump being donors to.

365
00:46:31,290 --> 00:46:38,239
And you you of these and the sort of money that you needed would have been very

366
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small compared with the money needed for a big amount of the money that we

367
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needed was very small compared with the growth and compare with the gigantic

368
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amount of money that was invested that logically I'm not complaining wasn't the.

369
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But then then the interesting thing is we didn't get from the university and we are grateful to the universities

370
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where we some yeah we get support just a minimum to operate but they we did get it and we gave for that.

371
00:47:12,620 --> 00:47:17,600
But the interesting thing is that most of the other the rest of the countries.

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The funding was only for coordination and standardisation as a priority because we knew that there were no standardised credibility will not be it.

373
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We would have concerns about it.

374
00:47:35,930 --> 00:47:47,780
The standardisation and data management and local issues were ignored by the rest of the institutions that participated.

375
00:47:47,990 --> 00:47:53,420
We didn't provide any cash to them, but they immediately jumped in, saying,

376
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this is the opportunity to do good research in a dramatic situation and finish it.

377
00:47:59,810 --> 00:48:05,690
Then, by by October, November 2020, we finished.

378
00:48:06,320 --> 00:48:16,610
There was a five month, five months, six months study from the first the first day from April to October.

379
00:48:16,610 --> 00:48:24,499
November. We we kept we kept a month more in the way we were writing the paper because we

380
00:48:24,500 --> 00:48:29,570
wanted to have more complete cases and cover more cases in other places and so on.

381
00:48:29,880 --> 00:48:38,150
Then that was a no. That was perhaps the easiest part.

382
00:48:38,360 --> 00:48:43,790
Then the results were clear. This was a very bad thing for women, for pregnant women,

383
00:48:44,000 --> 00:48:51,979
compared with women that the pregnant women that did not have COVID then completely a throw

384
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away the issue that what this was is just a fluke and they didn't have to worry and that the.

385
00:49:01,040 --> 00:49:06,499
Then the the concept and that this was the same risk that non-pregnant women

386
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therefore therefore if pregnant women were in the when when the vaccine appeared,

387
00:49:13,940 --> 00:49:19,070
pregnant women were in the in the priority list of a woman.

388
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25 year old or 28 years old.

389
00:49:24,430 --> 00:49:28,270
That means it was very low, very, very low priority.

390
00:49:28,540 --> 00:49:34,290
Then our I think our research a map provided a scientific foundation.

391
00:49:34,300 --> 00:49:41,930
The first solid thing difficult and danger with proper controls that the women pregnant women should be jumping to in the

392
00:49:41,950 --> 00:49:55,270
in the due to a high risk because it was a dramatic increase of maternal mortality and preterm birth on preeclampsia.

393
00:49:55,540 --> 00:50:00,370
Then there was a dramatic effect, all of it on on preterm birth.

394
00:50:02,320 --> 00:50:08,140
Can you just put some some numbers on that? What what was the risk, double or no double?

395
00:50:09,070 --> 00:50:12,670
You can get there. We can get the exact numbers on the papers.

396
00:50:12,670 --> 00:50:16,510
But the basically overall was double the risk.

397
00:50:17,730 --> 00:50:23,879
On any major outcomes, plus a maternal severe maternal mortality.

398
00:50:23,880 --> 00:50:33,030
The mortality was like 15 to 16 times higher than the norm, not known to pregnant women without COVID.

399
00:50:33,600 --> 00:50:41,130
Then there was a massive effect. And perhaps because of that, is that the second?

400
00:50:41,460 --> 00:50:50,490
The second process was that we got problems, even if it is a struggling me.

401
00:50:50,800 --> 00:50:56,310
And it goes back to what I said before about that the medicine is worse,

402
00:50:56,460 --> 00:51:08,260
it's more difficult to change but a habit that good habit and and is a we send it we I think in the growth yes and I think we

403
00:51:08,260 --> 00:51:15,360
we personally also we have a very good track record of publication we publish in the best job and I think that's what it is.

404
00:51:15,600 --> 00:51:23,640
Then we thought here with the first study, the most important study on COVID in pregnancy with concomitant controls,

405
00:51:23,760 --> 00:51:28,200
not a sample, you know, road for the subject.

406
00:51:29,330 --> 00:51:34,700
We go, we go and publish the paper from November, November, 2008.

407
00:51:34,700 --> 00:51:39,110
You, April, Justin and Judy, when we send it to paper this,

408
00:51:39,500 --> 00:51:47,470
this exactly the same to normal journals that we always getting with no problem during a war.

409
00:51:47,780 --> 00:51:51,290
The paper was rejected in the New England Journal of Medicine.

410
00:51:51,290 --> 00:51:54,870
It was rejected without even without even sending to reviewers.

411
00:51:57,300 --> 00:52:01,740
We gave up a five month delay in the publication.

412
00:52:03,970 --> 00:52:13,600
And there was no delay. Five months through the process of publishing and then the literature was still being evaluated because we had as I said,

413
00:52:13,990 --> 00:52:21,910
we got these a whole life systematic review that everything their papers published was updated.

414
00:52:22,100 --> 00:52:29,560
We're still seeing these things that were probably five cases in the rural provinces, whatever.

415
00:52:31,450 --> 00:52:36,400
And then we got there. We have about 3000 women.

416
00:52:36,430 --> 00:52:40,120
These are the women that are monitoring all their like.

417
00:52:40,900 --> 00:52:49,120
And we publish the the most the most bizarre out of all of this, of the peer review,

418
00:52:49,570 --> 00:52:55,540
all the reviewers we got and things that were or things that were obvious.

419
00:52:56,810 --> 00:53:00,410
As I said at the beginning, no women have tested.

420
00:53:01,510 --> 00:53:04,719
But because there were people to tend to be tested.

421
00:53:04,720 --> 00:53:07,960
I mean really long queues and you got two weeks.

422
00:53:08,230 --> 00:53:11,680
I think things are obvious, but they were. That's where they lived it.

423
00:53:11,920 --> 00:53:15,480
And it was. Then a.

424
00:53:17,360 --> 00:53:22,530
We have we spent about five months where it was rejected in the three main.

425
00:53:22,580 --> 00:53:32,230
Maybe you got to make a journalist got to sit lance it in the in the in the unilateral

426
00:53:32,240 --> 00:53:39,680
amazing a and they and and they and they they basically the comments were.

427
00:53:41,810 --> 00:53:49,340
And then finally, like in in April or March, April something changing.

428
00:53:49,340 --> 00:53:55,160
Once JAMA Paediatrics was in the JAMA, we sent it to JAMA and JAMA.

429
00:53:55,770 --> 00:53:59,390
It was rejected in the in the main JAMA.

430
00:54:01,760 --> 00:54:05,440
Just for the benefit of those who don't know. It's the Journal of the American Medical Association.

431
00:54:05,450 --> 00:54:08,990
But the paediatric specialists? No, the journal.

432
00:54:09,230 --> 00:54:12,860
JAMA mother is a Journal of American Medical Association.

433
00:54:12,920 --> 00:54:17,090
My daughters are. Yes, a.

434
00:54:17,390 --> 00:54:24,690
The then a. But at the same time, most of these are published in other papers.

435
00:54:24,780 --> 00:54:31,260
The most bizarre things in one case of a blessing that we find out by year.

436
00:54:32,220 --> 00:54:40,120
I'm not saying they were not relevant, but they definitely the implications for pregnant women at this point there,

437
00:54:40,140 --> 00:54:43,860
where it will happen with you, I want you die and die.

438
00:54:44,040 --> 00:54:48,300
What is your risk? Well, there is a preterm birth. Sure, we get a sensation.

439
00:54:48,570 --> 00:54:53,670
And the other thing is, should we stop breastfeeding? He was the most dramatic thing.

440
00:54:55,040 --> 00:55:03,919
Because there was, I believe, the time that they chose to grow the placenta, which is none of these babies placenta.

441
00:55:03,920 --> 00:55:13,700
But anyway, there was a believer that that will be contaminating the milk and then the foetus in the newborn will get then the the a because.

442
00:55:15,520 --> 00:55:20,350
Every day. People were scared of that. Then women were separated from the newborn.

443
00:55:21,010 --> 00:55:26,980
Then not only they beat the virus, it was bad for the mother, and mother was there with the respiratory condition.

444
00:55:27,160 --> 00:55:29,590
Then the baby was separated. Maybe it was breeding.

445
00:55:29,950 --> 00:55:35,920
And another issue was stopping breastfeeding, which is maybe, you know, for you it's not such a big deal.

446
00:55:36,070 --> 00:55:45,060
But in many rural areas around the world, if you stop breastfeeding, there was there was a death sentence for for these prisoners.

447
00:55:45,400 --> 00:55:50,860
If you are 15, 34 weeks of gestation, no breastfeeding, no water.

448
00:55:51,940 --> 00:55:55,360
It was a disaster. It was a how people and our babies.

449
00:55:55,360 --> 00:56:02,229
Sure, there was no risk of breastfeeding. There was a double risk of preterm delivery.

450
00:56:02,230 --> 00:56:05,889
So preeclampsia, high mortality and we couldn't prep.

451
00:56:05,890 --> 00:56:11,360
I probably. Finally, Gemma, for whatever reason.

452
00:56:12,520 --> 00:56:20,080
Decided that was no good enough for for Mother JAMA, but was good for JAMA Paediatrics.

453
00:56:23,080 --> 00:56:27,440
So it's sort of a where we want to keep these guys going.

454
00:56:27,500 --> 00:56:38,959
We're going to publish. And they and they were extraordinary because they publish they publish elegies over 21 April, May.

455
00:56:38,960 --> 00:56:45,600
I can't remember exactly. And a front from from early May.

456
00:56:45,620 --> 00:56:49,190
Major Jonathan and Judy went to the end in six months.

457
00:56:49,400 --> 00:57:02,900
They have 600 citations. The then top citation of a better unit of time that we can help in any of our papers and obviously the journals.

458
00:57:04,430 --> 00:57:08,830
This is a massive citation for it, for the paediatric or for the obstetric.

459
00:57:09,240 --> 00:57:13,210
And you had quite a lot of press coverage as well, didn't do this service.

460
00:57:13,430 --> 00:57:27,110
And we we published it after that because we were reanalysing more and more details and the effect on different pregnant women that were

461
00:57:27,140 --> 00:57:37,850
overweight and diabetic and preeclampsia and the newborn I on with with a obsession on on reassuring people that never stop breastfeeding.

462
00:57:39,900 --> 00:57:47,280
Because in these videos you have to get at content.

463
00:57:47,550 --> 00:57:55,650
But they all their measures are cleaning the place cleaned enabled it put in the baby and the mother

464
00:57:55,650 --> 00:58:04,620
with it with a cover the face and so on a demonstrate it with all these normal basic measures.

465
00:58:04,950 --> 00:58:08,940
They were not risk. They were no risk.

466
00:58:09,060 --> 00:58:13,700
And if there was any potential risk was minor compared with the stoppage.

467
00:58:13,710 --> 00:58:18,390
But as we know then they were desperate there, frankly.

468
00:58:19,650 --> 00:58:22,890
But I think they got another cover press covered.

469
00:58:23,170 --> 00:58:32,660
The the newspapers I have a very good interview with a journalist that they promoted all over that and.

470
00:58:36,340 --> 00:58:39,820
And they have citations. I think we have them by now.

471
00:58:40,000 --> 00:58:52,930
All the papers together, about 750 citations, them for for a less than a year for their for their specialised topic.

472
00:58:53,260 --> 00:58:57,640
It's a massive thing. And there was a.

473
00:58:59,700 --> 00:59:07,590
There was a whole process. And then exactly at that time when when a vaccine was available.

474
00:59:09,270 --> 00:59:15,690
Then. Then at that point, then the issue was, one, you didn't pay attention to us.

475
00:59:15,780 --> 00:59:20,880
We honestly put the finger and now we had to vaccinate these women and nobody knows the risk.

476
00:59:21,820 --> 00:59:28,540
But we do at least know that the risk of no vaccinated is very high.

477
00:59:29,140 --> 00:59:32,890
Then at least you get just that vaccinated women. And there was.

478
00:59:32,920 --> 00:59:39,670
And I think things to be honest with our papers, there was a clear evidence.

479
00:59:39,940 --> 00:59:43,060
This is this is a bad thing. This is really bad.

480
00:59:43,090 --> 00:59:47,200
If you have an instrument that can prevent this, you should vaccinated.

481
00:59:48,210 --> 00:59:54,250
Obviously, as you can imagine, there were many, many negative reaction about vaccinating pregnant women.

482
00:59:54,490 --> 01:00:01,540
And I know even the anti-vaccine groups, but the general public know that it was going to happen,

483
01:00:01,540 --> 01:00:07,150
this and that and the virus is going to cross the placenta where most of the vaccines don't have virus.

484
01:00:07,510 --> 01:00:09,970
But then that's basically what it is.

485
01:00:11,710 --> 01:00:20,020
And and to what extent did the results that you were finally able to publish affect public policy around the world on on public health?

486
01:00:20,120 --> 01:00:27,850
Large, large effect. Because, as I said, the citation is one measure, but immediately the CDC.

487
01:00:29,490 --> 01:00:33,090
It is interesting because in.

488
01:00:34,450 --> 01:00:43,509
Thus the Centres for Disease Control, the Centre for Disease Control in the in the U.S. have adopted a lot and say that our our

489
01:00:43,510 --> 01:00:48,780
paper because I think the key issue is that they have concomitant controls does age does it.

490
01:00:48,970 --> 01:00:54,820
That was a make a big difference they have a concomitant controls and a standardised condition.

491
01:00:55,400 --> 01:01:00,160
No, don't do that. And then they they start promoting that.

492
01:01:00,370 --> 01:01:11,589
But is throwing anything is that the people you got to believe always and people are not much in the scientific

493
01:01:11,590 --> 01:01:22,240
community is that the is interesting because a the the most of the provision on the incision took longer.

494
01:01:23,130 --> 01:01:28,020
They were dragging their feet to recommend a vaccination of pregnant women.

495
01:01:28,360 --> 01:01:32,070
Bigger. I didn't have any.

496
01:01:32,550 --> 01:01:37,530
We really didn't have any contact with the vaccine. There were no vaccine policies in any way.

497
01:01:37,860 --> 01:01:42,780
But it was clear that these vaccines, they were they didn't have the virus divide us.

498
01:01:42,780 --> 01:01:44,760
And then there was not that much of a risk,

499
01:01:45,030 --> 01:01:53,459
but it was a massive risk you have to have if you are pregnant then we were pretty much by the provision organisation.

500
01:01:53,460 --> 01:02:02,250
Was they the companies, you know, the subcommittee, the subcommittee was going to decide, well, maybe only high risk women that you'll be selected.

501
01:02:02,880 --> 01:02:07,890
You know, this is sort of combining the political background to go in there.

502
01:02:07,890 --> 01:02:19,020
But you know interesting is because I went but then in the US where the epidemic hit very hard, then nurses,

503
01:02:19,530 --> 01:02:31,170
midwives and residents, the large proportion of women, nurses and midwife all and then residents are going after the and ecology.

504
01:02:31,910 --> 01:02:35,280
That's what we call them. Junior doctors. Yeah.

505
01:02:35,550 --> 01:02:46,890
Junior doctors. Yes. And in training there is a large proportion and then the these these women.

506
01:02:48,360 --> 01:02:51,180
Many of them would bring them because they're just young women.

507
01:02:52,500 --> 01:02:59,110
And many of them they said, well, I don't care the recommendation of the professor as it is or I'm going to get it,

508
01:02:59,280 --> 01:03:06,820
you know, because I've seen all these people dying here and then the first the first massive baby.

509
01:03:07,480 --> 01:03:15,299
But promoting or contributing the the the the promotion of actually nation

510
01:03:15,300 --> 01:03:19,680
building as it was a paper in the US in which about three I think they started it

511
01:03:19,680 --> 01:03:22,889
with a population account resulting but the public is about 30 something

512
01:03:22,890 --> 01:03:27,750
pregnant women that were health professionals though they were there they said,

513
01:03:27,750 --> 01:03:30,660
well I don't get the recommendation, I get the vaccine immediately.

514
01:03:30,870 --> 01:03:38,700
And then there was the massive cohort that was the first published, about 30,000 and then was expanded to countries.

515
01:03:38,760 --> 01:03:40,409
I think we've been there was virtually zero.

516
01:03:40,410 --> 01:03:48,000
The risk of the foetus imbalance along with the vaccine is no, no risk associated with the vaccine itself.

517
01:03:48,240 --> 01:03:58,230
Then we strongly recommended vaccination, but it was based in a study of women that basically refused to follow the recommendation.

518
01:03:58,680 --> 01:04:03,629
But because they were there, the nurses and they saw well, they saw the people dying,

519
01:04:03,630 --> 01:04:08,100
they said, well, I better get get the get the vaccine for myself then.

520
01:04:08,100 --> 01:04:12,940
That's interesting how people are not generally provided a cohort of them.

521
01:04:14,250 --> 01:04:21,540
Well, that's that's what it is. The last commercial for you is the second study.

522
01:04:22,760 --> 01:04:26,960
Focusing only on Omega. Aye aye.

523
01:04:27,380 --> 01:04:30,800
Aye. Started in January 2002. Did you. I would.

524
01:04:31,820 --> 01:04:40,720
We repeated the next round. Of the original study in the in the in the same network.

525
01:04:42,820 --> 01:04:44,709
Maybe a little bit more expanded,

526
01:04:44,710 --> 01:04:54,570
but the same network repeated a senior study to evaluate the risk of Omicron because a new variant is said that is another flu.

527
01:04:54,600 --> 01:04:59,659
Don't worry, The A.V. Club. Nothing's going to happen that we said we did.

528
01:04:59,660 --> 01:05:04,330
The ones we're going to do again. A What?

529
01:05:04,420 --> 01:05:09,550
What is the risk associated with Omega in pregnant women?

530
01:05:10,030 --> 01:05:14,980
This time we were even worse. We didn't get any any money at all.

531
01:05:15,360 --> 01:05:18,880
They said this topic is over or migraine is nothing, and so on.

532
01:05:19,210 --> 01:05:22,960
And then we study 50 something women.

533
01:05:23,800 --> 01:05:30,280
It started in January 2000 to do, and it started in preparation.

534
01:05:31,140 --> 01:05:38,860
And we we started the study in April and finished in September.

535
01:05:39,100 --> 01:05:54,280
And paper is ready. It has been submitted for publication and got got a favourable response the first time and we are waiting now

536
01:05:54,460 --> 01:06:06,310
for the reviewers to have a set or come back with Gone with our responses to the reviewers in The Lancet.

537
01:06:06,610 --> 01:06:16,450
Therefore, we are willing to move it up after the first round, and I don't know if we're going to be accepted or not, but the first paper.

538
01:06:19,020 --> 01:06:28,559
A to go to Mosul in five months. The whole process, which we did in October and started then in February, was.

539
01:06:28,560 --> 01:06:31,770
March. June. April-June. May.

540
01:06:32,220 --> 01:06:41,800
June. Six month. Therefore Brussels. Then and then they just for you to listen to anything for so long.

541
01:06:43,410 --> 01:06:46,510
And I think it is it is a mercy.

542
01:06:46,510 --> 01:06:49,089
I think I have seen corroborating the it myself.

543
01:06:49,090 --> 01:07:00,160
I gather MAXINE corroborates that a a and that the only current is less aggressive the previous variant.

544
01:07:00,310 --> 01:07:09,250
But still, if you are not vaccinated and you have been not in a risk, you have been not exposed to COVID before.

545
01:07:09,550 --> 01:07:16,630
If your building if you were for COVID, this variant is not as aggressive the previous,

546
01:07:16,780 --> 01:07:29,829
but during pregnancy it does increase the risk of morbidity and mortality and should should be an incentive for a vaccination for pregnant women

547
01:07:29,830 --> 01:07:43,820
actively because still we are with a with a complete said and and the and and the three with three doses is still in in most of the country.

548
01:07:43,840 --> 01:07:58,810
We are not above 50% of vaccination. Then this then is it is a sort of a choo choo times all the same study and I would experience wonderful story.

549
01:07:58,960 --> 01:08:10,000
Well let's just to the for the last few minutes talk about how the pandemic impacted you personally and and how you were able to work.

550
01:08:10,000 --> 01:08:14,310
So you say you move back to the UK just as the first lockdown was beginning.

551
01:08:15,310 --> 01:08:19,630
So what what circumstances where you personally working in during that time.

552
01:08:20,200 --> 01:08:22,209
Well is it the is. Yeah.

553
01:08:22,210 --> 01:08:40,390
Well we move completely we we were affected but not I personally but they were it was not much affected because we were already electronic.

554
01:08:43,030 --> 01:08:46,359
The we already have one.

555
01:08:46,360 --> 01:08:55,180
All the hospitals were connected already electronically. Then our our we're a statistical unit.

556
01:08:55,600 --> 01:08:58,840
We very collaboratively unit in organisation.

557
01:08:59,140 --> 01:09:10,990
Then our in our statistical and data analysis unit is a collaboration that we have with University of California, Berkeley.

558
01:09:11,800 --> 01:09:15,640
Then our unit is in summer in the Bay Area in Berkeley.

559
01:09:17,050 --> 01:09:25,510
Then we, we already we were already electronically then that didn't affect much.

560
01:09:25,510 --> 01:09:32,889
And that is that these point that we are analysing a large amount of data and the knowledge is that

561
01:09:32,890 --> 01:09:42,160
these networks and maybe these and this network works very well but require a lot of physical presence.

562
01:09:43,530 --> 01:09:56,910
And you you look at you go and teach physically A and B, if we're truly a full colleague of all the colleagues that people you know,

563
01:09:56,930 --> 01:10:09,870
the expression of vampire research, the research in which people go go take your blood and disappear and go back to joining Sofia's.

564
01:10:09,870 --> 01:10:19,740
You get a lot then that can create a lot of us is that we don't do much of that but in any way by the I think does it I want to say that the

565
01:10:19,980 --> 01:10:28,170
these people that the college in many places that live in a working condition that are not like the one that we work in in Europe in the UK,

566
01:10:28,890 --> 01:10:35,310
then that, then they go in, they are teaching and being there and say, well we, we are here with you.

567
01:10:35,370 --> 01:10:38,690
You know, the, that thing is a fantastic reward,

568
01:10:38,720 --> 01:10:50,220
more than sometimes more than money then the issues that we did a lot of travelling then I was, I was travelling a lot of time then I didn't.

569
01:10:50,220 --> 01:10:59,070
How did you time to say that the pandemic did not affect much our day to day

570
01:10:59,070 --> 01:11:04,960
activities in the air because we are already moving a lot busier than that.

571
01:11:05,880 --> 01:11:19,680
And then. And I benefit because I took the opportunity to write a lot and then the jail remained closed for a while.

572
01:11:19,680 --> 01:11:23,460
And now I still say my career is not closed,

573
01:11:23,640 --> 01:11:32,430
but people people remain working at home and the university got extended a policy then it did not affect much.

574
01:11:32,640 --> 01:11:41,470
They knew they were. But colleagues that because I'm retired like several times, then I don't do any legal work.

575
01:11:41,920 --> 01:11:49,780
But people that were cleaning the front line, they were a scare and they've been tested all the time because, you know,

576
01:11:49,810 --> 01:11:56,050
I was going to ask you whether you personally, I mean, AdSense or if I may put it politely as an older person.

577
01:11:56,890 --> 01:12:03,370
But were you at any time, did you feel personally threatened by the possibility of being infected before the vaccine was available?

578
01:12:04,180 --> 01:12:07,469
Well. Yes.

579
01:12:07,470 --> 01:12:15,900
But you know, the bigger the pandemic and just trendy the A there were still ignorance at least.

580
01:12:15,940 --> 01:12:20,700
And then I spent time in Switzerland, daughter in Switzerland.

581
01:12:21,000 --> 01:12:34,950
Then there was I ended up passing the pandemic personally in Nomad in a small village it was small communities or sort of say my rural areas.

582
01:12:35,610 --> 01:12:40,890
Then it didn't have much of a social activity before.

583
01:12:41,280 --> 01:12:51,390
And there was a I personally about people that live in the main in London, for example, the Irish population, like I say,

584
01:12:51,690 --> 01:13:02,820
including St George, and he was being tested all the time and in the in the country there with patients and cases and so on.

585
01:13:03,180 --> 01:13:09,870
Then that did affect to me personally I think the more.

586
01:13:11,260 --> 01:13:22,060
And this is how I got my oldest son, those intensive care units in the Bay Area in San Francisco, and then in the intensive care unit,

587
01:13:22,330 --> 01:13:31,150
they were very much affected these people, because normally the death rate of intensive care units, Kyra.

588
01:13:31,450 --> 01:13:37,270
But with Kobe, they kind of 70% or minimum of death.

589
01:13:37,780 --> 01:13:42,010
And then they were they were devastated by these.

590
01:13:43,200 --> 01:13:51,030
And thus, I think the more the closer, the closer I get to myself as I really remain.

591
01:13:52,050 --> 01:13:57,000
And I got immediately a vaccine. As soon as I get it, I got I got the vaccine.

592
01:13:57,000 --> 01:14:00,700
And then the. And that's it.

593
01:14:01,540 --> 01:14:09,160
I think that's. But people that were reluctant to vaccinate and they were more exposed and they were really scared.

594
01:14:09,850 --> 01:14:16,890
And I think everybody. But I remain at home and I'm writing.

595
01:14:17,180 --> 01:14:21,840
Then that was it. There was a way to do it.

596
01:14:22,050 --> 01:14:26,140
And I'm publishing all this. All the all the first verse.

597
01:14:26,160 --> 01:14:30,060
The first thing they wrote in the first Kobe started every day.

598
01:14:30,540 --> 01:14:37,020
Then there's a. Well, it was a good opportunity to do that.

599
01:14:37,470 --> 01:14:45,090
Yes, yes, yes. And must have given you a tremendous sense that however difficult living through the pandemic was,

600
01:14:45,090 --> 01:14:48,230
you had done you and your colleagues had done a really good thing.

601
01:14:48,240 --> 01:14:52,920
And that was something you could feel good about. Well, thank you.

602
01:14:54,820 --> 01:15:01,320
So finally, has your experience of the pandemic changed your attitude or your approach to your work?

603
01:15:03,540 --> 01:15:08,520
Um. Well, no, actually, it was reinforces.

604
01:15:09,860 --> 01:15:19,090
In the force that we were we were on the right track and then one, we will remain that, he said.

605
01:15:19,880 --> 01:15:28,280
Is it true that with globalisation is a global activity and there is nothing better to have it,

606
01:15:28,480 --> 01:15:34,430
it's nothing better to have a large sample size in any area in India accommodating,

607
01:15:34,790 --> 01:15:41,910
having a large sample size and is the best thing that can happen because you can do what you're going to explore.

608
01:15:41,930 --> 01:15:47,250
QUESTION The results are solid and you don't need much statisticians.

609
01:15:47,840 --> 01:15:59,120
There is, there is, is. And also importantly, is that immediately a contribution dissemination?

610
01:16:00,120 --> 01:16:07,409
Because immediate reorg for within the rule book for forecasting it has a no limit.

611
01:16:07,410 --> 01:16:14,430
The cost has a network of maybe a hundred institutions that follow immediately.

612
01:16:14,700 --> 01:16:21,150
Where we recommend because they were part of is that they were somehow one way or the other.

613
01:16:21,270 --> 01:16:32,800
There were policies then then is it is a massive army of people, committed people and they disseminated results.

614
01:16:32,980 --> 01:16:38,190
This is it. This is a fantastic experience. And I think we reinforces our effort.

615
01:16:38,790 --> 01:16:41,820
Yes. Thank you very much.

616
01:16:42,600 --> 01:16:43,680
No, my pleasure.