Personalized Public Health in Africa: Balancing Disease, Privacy and Ancestry

January 09, 2024

Information

December 13, 2023

Steven Schiff, MD, PhD, FACS

Vice Chair for Global Health in Neurosurgery

Yale University School of Medicine

ID11161

To CiteDCA Citation Guide

00:04OK. We're going to go ahead
00:05and get started tonight.
00:06Thank you so much for coming for joining us.
00:09And for those who are dialed in on Zoom,
00:12just a couple of quick housekeeping issues.
00:14We have a terrific schedule for 2024,
00:18which is available on the website.
00:20Just if you just go biomedical ethics
00:22at Yale, you'll find yourself,
00:23you'll find pretty easily to get to
00:26the program for Biomedical Ethics and
00:27you'll see the schedule for the spring,
00:29which looks very exciting.
00:30But we wanted to finish off
00:322023 on a high note.
00:34And so I want to tell you a bit
00:36about our speaker for this evening.
00:37I just not too long ago met Steve
00:40Schiff and was so excited to be
00:42able to kind of bring him into our
00:44bioethics community because, you know,
00:46it's Yale's a pretty big place and there's
00:47people around here that if you don't know.
00:49And I see that, I see some student
00:52bioethics leaders among us as well.
00:54So when you're sometimes looking for members
00:55of the faculty to address to students,
00:57it's good to get to know these guys too.
01:00Steve Schiff is a professor and
01:01vice chair for Global Health in the
01:03Department of Neurosurgery here at Yale.
01:05But I should say he is professor,
01:06but as of relatively recently,
01:09he's also in fact the Harvey and Kate
01:11Cushing Professor of Neurosurgery,
01:13which is which is as they say, not nothing.
01:16So this is a very important
01:18endowed professorship.
01:18So congratulations for that,
01:21Steve.
01:21He's a pediatric neurosurgeon with
01:23interest in neural engineering,
01:25Sustainable health engineering
01:26and global health.
01:27He received his NIH Directors
01:29Pioneer and Transformative Awards
01:31in 2015 and 2018 respectively.
01:34The support enabled him to lead the
01:37recent discovery and characterization
01:39of neonatal panabesiliosis,
01:41a new disease syndrome that is an
01:44important 'cause of infant sepsis
01:47and hydrocephalus in East Africa.
01:49And that's a conversation you
01:50and I need to have afterwards,
01:52maybe at dinner because I need
01:53to learn more about that.
01:54I don't know nothing about that.
01:55He's taught neuro ethics at the
01:57undergraduate and graduate levels
01:58and is deeply involved in the
02:00ethics of ancestral genomics in
02:02predictive personalized public health,
02:04which is what we're going to
02:05hear about tonight,
02:05specifically those efforts in Africa.
02:09Steve is largely a product
02:11of Duke University.
02:12He received his MD,
02:13did his surgery residency there,
02:15his neurosurgery residency there,
02:17also received a PhD in Physiology
02:19and then went to CHOP to train
02:22in pediatric neurosurgery.
02:23So Professor Steve Schiff,
02:25we're so pleased you're here
02:26and please join me in welcoming
02:33most of you guys kind of know the drill.
02:34So just to remind you and
02:35those who are on the call,
02:36there'll be a talk of about 45 minutes,
02:38maybe a little bit longer,
02:39a little bit less depending
02:41on how our speakers feeling.
02:42And then I'll moderate AQ and A.
02:43So you'll have a chance after the talk.
02:45And those who are on Zoom,
02:47put your questions in through
02:48the Q&amp;A function on Zoom,
02:49if you would, and then we'll have
02:51a conversation that'll take us.
02:53And but at at 6:30 at the latest,
02:56I will close it up.
02:57So you don't have to wonder how
02:59long you're going to be or even
03:00if the questions are really good
03:01and the conversation's great.
03:02We will stop.
03:03So we'll be done at 6:30 to set you
03:05free to go and and read, you know,
03:07some neurosurgery texts all night or
03:09whatever it is that you're inclined to do.
03:11And for now,
03:12I turn it over to Steve.
03:13Thank you,
03:14Sir.
03:14Thanks
03:14very much, Martin. And thanks to everyone
03:17for the invitation. Here, let me.
03:25Yeah.
03:42So
03:44let me tell you a bit of a story
03:48about some of the work that
03:51we've been doing and is
03:56people is this the microphone? I need?
04:00No. Do I this thing?
04:23That's right.
04:37All right,
04:41that should work.
04:43So I put an outline together of of
04:46what I'll talk to you about tonight
04:48and let's start off with the global
04:53code of conduct for research in
04:57Research resource Poor Settings.
05:01And this is a a consensus document
05:05that's been worked on for several
05:08years and it really highlights
05:11some of the differences that ought
05:14to be considered in working in
05:18countries in the developing world.
05:21This year they changed the title
05:23of this to say the Trust Code.
05:26I think that's an effort to
05:29hide what it's about.
05:32Perhaps the European Parliament has
05:35adopted this as its ethics for how
05:39European countries ought to conduct
05:42research in the developing world.
05:45And there are two overarching principles.
05:50The 1st is that you need to develop
05:54local community partnerships.
05:57There's been a long history of what
06:01has been termed colonial science.
06:06We sit in institutions like this,
06:08dream of wonderful research projects
06:11and go out and find a place where
06:14we can carry those projects out,
06:16publish papers and there's
06:18very little benefit locally.
06:20So that's the second major principle is
06:24that there should be local social value.
06:28So and that's a key difference to what we
06:33typically do in an institution like Yale.
06:36We have people here with very
06:39successful academic careers.
06:41We value the creation of knowledge,
06:45but we have with all due respect we
06:48have people here who work on number
06:50theory that if you did that in rural
06:54Africa it might be very interesting,
06:57but it doesn't improve the lives or the
07:00health of the people that you've worked with.
07:03And so curiosity based research
07:06is something that these global
07:10codes advocate that we don't
07:12do in vulnerable populations.
07:14So you add general and local value to to
07:21how we value science and interesting delay.
07:25So I am a pediatric neurosurgeon
07:29and the most common indication for
07:31operating on the brain of children
07:34is that they have hydrocephalus,
07:36they build up fluid and we do a
07:39variety of different kinds of surgery
07:42to relieve pressure on the brain.
07:45The vast,
07:47vast majority of children with hydrocephalus
07:51are in the the developing world.
07:54The largest concentration of cases is in
07:58sub-Saharan Africa and the most common
08:01cause is infection earlier in life.
08:05This is very different from what we see
08:07in the US or in Europe or Australia,
08:09where hydrocephalus following infections
08:11is not at all of that common anymore.
08:21I have had the privilege for the last
08:2416 years of collaborating with this
08:27small hospital in eastern Uganda.
08:30It's the Cure Children's Hospital.
08:33It specializes in neurological
08:36surgery of children.
08:39Forty of their hydrocephalus cases,
08:41which are their most common need for surgery,
08:4540% are post infectious,
08:4830% are children born with spina bifida,
08:52an open spine.
08:53They're also called neural tube defects,
08:56so we have to surgically close their back.
08:59Once their back is closed,
09:012/3 or more of those children will
09:04need to be treated for hydrocephalus.
09:08And this delay here,
09:12malnutrition is a pervasive
09:15comorbidity for all of these patients.
09:18And I'll get back to that a
09:21little later on in the talk.
09:27Most infectious hydrocephalus,
09:29as I'm describing here,
09:32if you were to look inside the brain,
09:35you'd see with a scope,
09:38very small pustules lining what
09:41is called the appendimal surface
09:44of the ventricles in the brain.
09:47These are small postules
09:48with space in between them.
09:50They don't tend to become confluent.
09:53There's a variety of things that that
09:56we could discuss regarding that,
09:58but we see this throughout
10:01sub-Saharan Africa.
10:02The sites that are able to
10:04operate on these children.
10:06The first thing I saw walking
10:08into an operating room in Vietnam,
10:10it's exactly the same phenomenon.
10:13We're not in Haiti right now,
10:15but my colleagues who've operated
10:18in Haiti have seen again the
10:20same type of syndrome.
10:22It's completely uncharacterized.
10:24And so much of the work that
10:29I'll show you today is an effort
10:32to learn more about this.
10:35So I visit this site in 2007 and
10:42in discussing with their physicians,
10:45I I was very impressed with just how hard
10:48it is to do technical neurosurgery in a
10:52setting where the resources are not ample.
10:55And I actually asked the medical director,
11:00all right, what's the most
11:03important problem you can't solve?
11:07And he answered nicely.
11:08It was Ben Wharf,
11:09who's now on faculty at Harvard.
11:12And And Ben said, well, why don't you
11:15figure out what makes these kids sick?
11:16And I thought, how hard can that be?
11:222023 was really the year that
11:24we finished up with the first
11:26set of answers to that question.
11:29So it's been a long journey
11:31here and we finally needed the
11:36resources of some major NIH support.
11:40It's interesting to me,
11:42it was a struggle to get NIH to
11:45support this because it was felt
11:47to have no feedback and impact on
11:50the health of the United States.
11:53Excuse me, Steve.
11:56Yeah, definitely the weak link of the crowd.
11:57So forgive you that I would move that and
12:00I have to phone up.
12:02Yeah, I can also just talk into this thing.
12:06I just hate standing.
12:09Is that any better? It is.
12:12All right, So we got enough resources
12:15from NIH to put together the kind
12:18of study you'd want to do here.
12:20Get very high quality samples,
12:22put together a cryogenic
12:25infrastructure that didn't exist.
12:27Get thousands of samples safely shipped,
12:30frozen to the US And in recent
12:36years I'll describe what we found.
12:38But in the last several years
12:41there've been multiple cases that
12:43are identical seen in the US.
12:49What do you do when you
12:51can't grow an Organism?
12:53This is a brutally difficult set of strains
12:57to get to grow in culture it turned out.
13:02And so if you don't know what causes
13:05infection, you can do several things.
13:07All bacteria have genes that
13:09are only present in bacteria,
13:11so you can amplify them and sequence them.
13:14And we have large databases so you
13:17can tell what at least the genus is,
13:19if not the species of of
13:23an uncultured bacteria.
13:24We confirm this with things
13:28like RNA seq or PCR targeted to
13:31what we think we've found.
13:34RNAC is also critical.
13:35There's no one gene in viruses,
13:38so if you want to look for an
13:41unbiased survey for what viruses
13:43might be infecting someone or
13:45what parasites might be present,
13:47then you're dealing with RNAC.
13:55By 2020, we'd teamed up with people
14:00both from Penn State and from Columbia
14:04University and found that there was only one
14:07Organism that dominated these infections.
14:10It's an unusual one.
14:11It was a painy bacillus, which is
14:14Greek or Latin for almost a bacillus.
14:19It formed a highly neurotropic and
14:22destructive infection of the brain.
14:24You can see one of the images of one of the
14:27infant brains here with calcified abscesses.
14:31We did manage to get some
14:34of these strains to grow,
14:37figuring out when these children got
14:41sick and how this apparent infection
14:44might have related to previous disease.
14:49We just finally put together and reported
14:543 simultaneous linked case control trials.
14:58This is 1400 patients,
15:01thousands of samples,
15:03over 2500 qPCR reactions to confirm what we
15:10had found and this involved a maternal trial.
15:15Many infants catch infections during
15:18the process of birth or there
15:22are also congenital infections.
15:24In the US we screened all mothers
15:28before at the time of delivery for
15:31one Organism which used to cause the
15:34most trouble in the United States.
15:36We found no evidence of this Organism
15:39in any of the maternal specimens.
15:42Vaginal, placental,
15:45maternal blood or cord blood.
15:48Not likely it's coming from the mothers.
15:51We looked at 800 neonatal sepsis
15:55cases in several sites in the country
15:58and 400 cases of hydrocephalus,
16:01half of whom had a history of infection.
16:06Almost half of the infants under three
16:09months of age that came to us were still
16:13PCR positive to this one Organism,
16:17and 6% of the neonates with sepsis.
16:21And we actually were able to capture
16:24some true linkage cases where we
16:26could capture the Organism within a
16:30week of birth with clinical sepsis,
16:33treat the sepsis,
16:35appear to clear it from the periphery
16:39of the infant.
16:40Child's not febrile feeding well,
16:42no longer lethargic, goes home,
16:45but comes back a month or two later with
16:49continued infection in the brain and
16:51with the head enlarging from hydrocephalus.
16:55So what did we just do over 20 years ago,
17:00Frederickson Relman talked about
17:03the possibility of doing a sequence
17:07based identification of pathogens and
17:11proof that these molecules showed
17:14that an Organism caused an infection.
17:18Robert Koch,
17:20about 150 years ago had postulates
17:24that said to prove an infection you've
17:27also got the culture and Organism you
17:29have to be able to infect an animal with it.
17:33We've just violated all of those
17:39those strictures. Now here,
17:40if I'm standing in front of you,
17:44you all will think that's
17:46cutting edge and clever.
17:48But I didn't quite see covenants
17:50that in other settings.
17:52I just violated all the fundamental
17:55principles that good physicians were
17:58taught by their highly respected mentors.
18:01Working in other societies and in
18:05other settings is often challenging
18:07in ways that I can never predict.
18:11Well, now the So what question.
18:14I just spent millions of dollars
18:16of our tax good taxpayers money.
18:18It took years to finish all of this analysis.
18:22We're still working on some pieces
18:25of it and microbial genomic testing
18:29is very expensive and it's slow and
18:35none of the scales very readily.
18:39And these are medical emergencies.
18:41These children come in and they
18:44are at serious risk of dying and
18:46we need to make decisions quickly.
18:49So I'll walk you through what
18:51I like to call predictive,
18:54personalized public health.
18:57So what does that mean?
19:00We've done a lot of observation.
19:02We've done a lot of surveillance
19:06of these infections.
19:08And I'd like to be able to ask
19:10a mother two questions which
19:12they always know the answer to.
19:14Where are you from?
19:16And when did the infant get sick?
19:19I'd like to use our prior knowledge
19:23and experience then to say,
19:26well,
19:26what are the most likely organisms
19:29and most important point of care
19:32of the available antibiotics,
19:34what are the best ones to pick?
19:37Now if we're looking at post
19:39infectious hydrocephalus,
19:40which is how I backed into this,
19:43that's not the problem.
19:44If you want to cut this off,
19:46you have to address the much
19:49broader issue of neonatal sepsis.
19:52And neonatal sepsis is probably
19:56still responsible worldwide for well
19:59over half a million deaths a year.
20:03It's probably closer to 3/4
20:05of a million deaths.
20:07That's triple, I think,
20:09the number of deaths of any age for malaria.
20:14It's comparable to the number of global
20:17deaths from tuberculosis of any age.
20:20And I actually had the privilege
20:24of testifying to Congress on this.
20:27And the congressmen and women on that
20:31committee are really rather surprised
20:33because they haven't heard about this.
20:35And in my testimony,
20:37I suggested to them that the reason is
20:41that newborn infants dying in developing
20:44countries have had no political voice.
20:48If you look at the most
20:49recent studies I listed,
20:51a Cambodian study,
20:52and Nisa is a huge South Asian study.
20:56These are beautifully done studies
20:59on neonatal sepsis and they're
21:01able to recover an apparent
21:05pathogen in 2% of their cases,
21:082% why test at some point it's the
21:15traditional way we have gone about.
21:18Identifying pathogens is an abysmal
21:21failure in newborn infants for reasons
21:25that I'm also happy to discuss.
21:28But the loss of life here really demands
21:31that we do something very different
21:33from what we've done for many years.
21:38So to try to conceptualize of
21:42what would be an improvement,
21:47we've put all 60,000 villages in Uganda and
21:53fuse them onto the satellite climate grids.
21:57That's useful for a number of
21:58reasons that I'll get into,
22:00but it's also especially useful if we
22:04want to look at environmental effects.
22:07This particular disease
22:08has a huge rainfall effect.
22:11In terms of when these infants get sick,
22:14the neonatal warts fill up as the rains
22:17come in and empty out during the dry season.
22:20Here are 4000 mapped cases.
22:23Now, I don't have microbiology
22:25on 20 years of cases,
22:27but these are 4000 mapped cases.
22:30See my mouse?
22:32Yeah, of these infections
22:34and look at the clustering.
22:37So here's Lake Victoria and
22:40there are huge enormous swamps,
22:43papyrus swamps along the northern bank.
22:46The Nile starts here in the middle of
22:49this cluster and goes N to Lake Choga.
22:53Again, large swampy,
22:54wet areas on the southern and
22:57northern banks of Choga and here in
22:59this North Central region of Uganda.
23:11Let's see if it's unhappy with me.
23:14I'm very unhappy with me.
23:26Well,
23:29yeah, it's happy again.
23:33What about genomics?
23:34So do I need to know something
23:37about the hosts as I'm mapping the
23:40location and timing of disease?
23:45In case you missed it,
23:46the answer has to be yes.
23:48Every infectious disease that we
23:52contract as humans is actually a
23:55product of both the genomics of the
23:57Organism that give the Organism its
24:01characteristics and your genetic
24:03differences that both determine
24:06whether you contract an infection
24:09and how you do from an infection.
24:11Just think of COVID,
24:13there were many people who appeared
24:16to be asymptomatic or perhaps never
24:18got sick and I have two friends of
24:22mine who died within two days or so
24:25of contracting the viral infection.
24:27So the the current thinking is
24:31that we need to dual sequence
24:35the the genetics of bacteria or
24:39viruses as well as host to try to
24:43get a comprehensive picture of how
24:46to deal with infectious disease.
24:53So what to do? I I show up with all of our
24:56colleagues that we work with in Ambala,
24:59Uganda, and I propose this.
25:02And there is an awful lot of pushback.
25:05What are the concerns? First, privacy.
25:07How are we going to do genomic sequencing
25:12of hosts and protect the individuals?
25:16Second, Yeah, I get this one a lot.
25:19What about paternity testing?
25:23We could, if we wished, of course,
25:26determine who the parents are,
25:28if we had three samples.
25:30And lastly, in a society that's
25:33dealt with authoritarian regimes
25:35in the past like Idi Amin,
25:38there's concern for safety if the
25:40government has access or the public
25:43has access to genetic information.
25:46So we wrote a very comprehensive document.
25:49It's eight single space pages
25:51of text going through all of the
25:55issues we thought were important
25:57and how we might approach them.
26:00We would obviously not publish
26:03any names of patients.
26:05We'd use the birth dates
26:06but not publish them.
26:08We would use the village precise
26:11locations but not publish that.
26:13And I'll show you how we will
26:16go about Geo masking and the
26:18care that we offered that.
26:19So you can't re identify by
26:22knowing where someone came from.
26:25The genomes would not be individually
26:29sequenced and deposited.
26:30And then I thought,
26:34I'm an amateur at this,
26:36I need to run this by a pro.
26:39So I had come to meet Judy Illis,
26:41a very well known ethicist.
26:43She is in Canada.
26:45She has an extensive experience working
26:48with the Canadian First Peoples,
26:50the native population in Northern Canada.
26:53So I forwarded this to Judy.
26:55She was great.
26:56She went through every paragraph
26:58and she comes back and says you
27:00may be working with populations,
27:02but you have to figure out
27:04a way to return results.
27:06All right.
27:07So I approached colleagues in the
27:09government and we worked out that if
27:12we had findings that were important
27:14for various peoples within the country,
27:18that we'd work with government agencies
27:21to return those results properly.
27:25And then of course,
27:26we went to all the institutions
27:29to get their approval.
27:30The local IRB ethics boards,
27:33the US Ethics board,
27:35the government oversight board
27:37in Uganda for human research.
27:40And I floated it by NIH as well to
27:42make sure that all of the stakeholders
27:45on the compliance side had a chance
27:48to give us feedback and prove this.
27:51And if you look at those little grid squares,
27:56I looked for the ones that
27:58didn't have much population in
28:00the country of Uganda,
28:06country of Uganda,
28:07you see these sparsely populated areas.
28:10So some of these are game parks.
28:13More elephants and lions live there
28:16than humans for obvious reasons.
28:19There's also a large arid region in
28:23the northeast that has a a sparsely
28:26populated nomadic population,
28:28and we're going to come
28:29back to that in a bit.
28:30And we we in part of our proposal
28:34is that we would not map any points
28:37on any of the maps we're doing from
28:40any place with less than 1000 people
28:44in 120 square kilometer grid space.
28:50In the US, we don't map zip codes
28:55with less than 20,000 people for the
28:58same reason in Uganda we picked 1000,
29:02we picked a larger square mile area and
29:07then we actually jitter the points.
29:11So the points I just showed you on that
29:14map aren't actually the exact location
29:18where those villages are located.
29:21Here's a little picture of a colleague
29:23of mine and and a local resident
29:26hiking on a footpath over hills
29:28trying to find a village cluster
29:31where one of these infants is located.
29:33We think and all the people we've had review
29:38this think that that's adequate protection,
29:41the way we design this,
29:43so that we can publish maps
29:44and show you the clustering.
29:53We know a lot about ancient migrations in
29:57many parts of the world and of of course,
29:59in Africa. This is an old map of
30:02Jared Diamond who wrote Guns,
30:04Germs and Steel in Science 20 years ago.
30:08And Uganda is right sitting wrapped around
30:12the northern part of Lake Victoria.
30:15Here and in that part of Central
30:19Africa there are two main migrations.
30:21The Bantu expansion started
30:24around 5000 years ago, we think,
30:27and these people came up from
30:29the southern parts of Uganda,
30:31of of sub-Saharan Africa,
30:33and also came in from the southwest.
30:37Several thousand years later,
30:38there's a migration of Nilo
30:41Saharan people from the north.
30:43They come down, they literally
30:45seem to meet at the Nile River,
30:48which is a natural barrier.
30:53If you look at the clustering,
30:55the simplest way of clustering genomes,
30:59each of us has millions of differences
31:03at the single base pair level
31:06between our genomes if we sequenced
31:10up all of us sitting in the room.
31:13But if you look at the simplest
31:15way of doing that,
31:16just using a cluster technique,
31:20principal components to look at,
31:22how many groups could you
31:26statistically have in your data.
31:30This data gives you 4.
31:32There's a northern group in blue,
31:35There's a southern and
31:38southwestern group in red.
31:40There's a little bit of complexity
31:43here along the Kenyan border.
31:45We know that there's a Western
31:48migration from the Swahili coast that's
31:50been identified in recent years,
31:53but basically we pull out the
31:56ancient migration patterns trivially
31:59from doing the simplest version.
32:01This isn't even admixture analysis.
32:05The simplest version of clustering
32:08changes between chinos.
32:11So we've done a little more
32:13sophisticated effort at this.
32:15We've fit these points to a smooth model,
32:19but importantly,
32:20we're looking at the proportion
32:23of those groups.
32:24Because none of us are pure mixtures,
32:28we vary in our proportions
32:31between our ancestries,
32:33and what we find is that there are two
32:36groups that are very closely related.
32:38Those are Bantu,
32:41and then there's one Nilo Saharan group.
32:44The Nilo Saharan group is the largest
32:48distance difference distance between
32:50those two Bantu groups present.
32:54This all makes an awful lot of sense.
32:57Jared Diamond was reasonably correct
33:00in his estimates at the time.
33:03Without the genomic information.
33:06I'm also going to briefly introduce
33:09the second group of hydrocephalus.
33:12These are children with spina bifida.
33:15They're born with what looks
33:17like an open spine.
33:19This is a strongly genetically
33:22influenced malformation,
33:23but it's a gene by environment disease.
33:27We know that we can prevent most of
33:30this with adequate folate fortification
33:33of food or preconception vitamins.
33:36The rates in the US and in most countries
33:39that fortify food is quite low,
33:42about one per 2000 live births.
33:45The rate in Uganda is many,
33:47many multiples of that.
33:49I hope within the year we start to
33:52actually nail down the true incidence
33:54'cause we have to know that if
33:57we're going to be more effective
33:59about controlling the disorder.
34:04If we take that ancestral map and we look
34:09at other covariants such as poverty index,
34:12the two covariants that most
34:15associate with our mapping of
34:18spina bifida risk our poverty and,
34:22independently, nilo Saharan ancestry.
34:27As I tell my colleagues,
34:29this may not be true, but it's such
34:32an important finding to perhaps have
34:35stumbled into that if it's not true,
34:38we need to demonstrate that it's not true.
34:41If it is true, you all need to be asking
34:45us what are the specific pathways and,
34:49for instance, the metabolism of
34:52folate or insert another gene products
34:55that actually help tissues close,
34:58like the neural tube,
35:00and how might they be differently varied?
35:03In people who migrated from
35:06northern parts of Africa,
35:09the World Health Organization a
35:11few months ago passed a resolution
35:14that all member states needed to
35:17fortify or supplement folate to
35:20prevent these neural tube defects.
35:22Unfortunately,
35:23they left it up to each member
35:26state to figure out how to do it
35:29because the context is extremely
35:31different between societies.
35:34If I fortify wheat in a country
35:37where people don't eat wheat,
35:39I'm not doing anything that's
35:42that's helpful here.
35:44So how do you do community engagement and
35:49how do you handle the politics involved?
35:52I usually didn't think I needed
35:55to touch politics.
35:57I mean, I know something about medicine.
35:58I'm a pretty good amateur scientist.
36:01I just went to a talk by John and Kangasong.
36:06John was the former head of the
36:09African CDC until we made him AUS
36:13Ambassador at large from the US State
36:16Department to deal with global health
36:19security and diplomacy over health.
36:22And one of the things he emphasized
36:24to us is that if you can't manage
36:27to bring the decision makers and the
36:30political infrastructure to bear,
36:32you can't affect the impact that you
36:36need for any public health problem.
36:39Just look at the disaster that we
36:42created in our own society over
36:44our public health efforts for COVID
36:47vaccination masking. What a mess.
36:52During COVID,
36:53my colleagues and I created a very
36:57detailed model to try to predict
37:01within the continent of Africa
37:04and track COVID cases.
37:07Actually, it worked pretty well.
37:09Yeah,
37:09we could get pretty good estimates one
37:13week and actually two weeks ahead.
37:17And we work with what is the
37:20national planning authority.
37:22These are the folks that do the financial,
37:25agricultural and health planning
37:27for the country of Uganda.
37:30And we trained with one of their
37:34data scientists to do an excellent
37:36job of of of working with this
37:40model and doing predictions,
37:41scenario predictions of how
37:44policy change would affect COVID.
37:47Abraham Mullen.
37:48Guzi is a manager of technology and
37:51innovation for the country at two ministries.
37:54Joseph Muvwala is one of
37:56their lead economists.
37:58And they're actually here,
38:01these are screenshots on national
38:03television as they're explaining
38:05to their society why this is a
38:09way they can manage the pandemic.
38:12At a cabinet meeting their president thought,
38:16yeah that's exactly what we ought
38:19to be doing and they ran with
38:23this model 3 scenarios 1.
38:25Continued lockdown 1.
38:28Taking all restrictions away and
38:32one the intermediate course.
38:35And I I was there at the time.
38:38And
38:40predictions on the potential effects
38:42of the different interventions
38:44on the likely outcomes.
38:47The model analyzes a number
38:49of factors, including
38:52I don't think I'll ever see a
38:56a head of state explaining our
38:59computational modeling that we do
39:01here in the lab to an entire nation.
39:04But he uses this to justify changing
39:08his mind because partially restrict,
39:11partially coming out of lockdown
39:14appeared to be safe and fortunately
39:17the predictions were pretty good.
39:21So we had a fair amount of
39:24credibility after that with some of
39:26the decision makers in the country.
39:29And we've been talking with them
39:31and they've asked how can we partner
39:34with them to address a very high
39:37and stubbornly resistant rate of
39:39neonatal mortality in the country.
39:44We began weekly meetings by Zoom here
39:47from Yale and then several trips over
39:51to gather the stakeholders together in
39:54person and go over what we could do.
39:57And I wanted to focus on Preventable.
40:01Causes of neonatal death
40:05what we just closed the deal on two weeks
40:09ago is the agreement to do the following.
40:11It'll be led by the
40:14National Planning Authority.
40:15The Ministry of Health is on board.
40:17Their Ministry of Science and
40:19Technology is on board.
40:21The Kingdom of Usoga,
40:23which is shown here,
40:26which may have the highest rates
40:29of both neural tube defects and
40:32neonatal sepsis in the country,
40:34is on board.
40:37We're going to keep the specimens
40:40in the Ugandan biorepository
40:42that NIH had originally built as
40:44part of the H3 Africa program,
40:47and we're going to try to do as
40:49much of the sequencing as possible
40:52using in country scientists.
40:54What's the community here?
41:01It's a question.
41:03It's a complex question.
41:06Here's what the community
41:09partnership probably looks like.
41:12It involves midwives and nurses.
41:16It involves mothers who are advocates
41:19for children with this disease.
41:21Ruth here is a national organizer
41:25for advocacy for spina bifida.
41:29Lydia is on the National Nursing
41:32Council helping direct policy for
41:34nursing and mid midwives in the country.
41:38This man is one of the lead faculty members
41:42at the National University for Public Health.
41:47This individual is in charge of
41:51health policy for their planning.
41:54Abraham I showed you this individual
41:57is both one of their lead economists.
42:00He's also the Prime Minister of Musoga.
42:05I had a delightful couple of hours
42:07with their Minister of Science.
42:11Monica Musonero is a brilliant
42:14microbiologist.
42:15She's fascinated by all the
42:17things that we've been doing.
42:21This is the Minister of Health for
42:24the Kingdom of Busoga and on board
42:27as well is the Commissioner for
42:29Child Health throughout Uganda,
42:32the nation state of Uganda.
42:35Pamela and Babassi is a protege
42:38of Frances Fukuyama and she
42:41is a renowned urban planner.
42:43She is the chairwoman of their national
42:47planning and on February 11th,
42:51the Chaya Bazinga Day,
42:53the King of Busoga will be rolling
42:57out this project for neural tube
43:01defects and neonatal sepsis to
43:04the Kingdom Takes a Village.
43:08Malnutrition effects absolutely
43:12everything I just discussed,
43:15and stunting is the most obvious physical
43:19manifestation of severe malnutrition
43:22and undernutrition in early childhood.
43:25Worldwide,
43:25there are about 1/4 of a billion
43:29children who are malnourished to
43:32the point that they're stunted.
43:34And across Uganda,
43:36the current estimated stunting rate is 30%.
43:41That's not the worst society
43:43in sub-Saharan Africa,
43:44but these are pretty shocking numbers.
43:48And take a look at this.
43:49So this is probably the currently
43:52best stunt study I know of on the
43:57genetics of infant and child growth.
44:01Look where they pull their populations from.
44:05Yeah, it's from Western Europe,
44:07the United States, and Australia.
44:10I show this to my African colleagues,
44:13and they're appalled.
44:15But there's a serious lack of diversity
44:18in our analysis of even fundamental
44:22features of human existence,
44:24like growth from diverse people
44:27around the world.
44:29Here's 6000 children surveyed in Uganda.
44:34They start off around the median for
44:37size at birth, and within 24 months,
44:4030% of them are stunted in height.
44:44Look at the fallacy that this
44:48this brings you.
44:50So I'm going to circle that
44:52NE province in Uganda.
44:54The Karamajung lived there.
44:56These are tall,
44:58melodic people.
44:59They're related closely to the
45:02Maasai across the border in Kenya.
45:05If you look at height,
45:07there's a little area that they look stunted.
45:10But for the most part,
45:12they're stunting free and it's
45:16totally misleading.
45:17If you look at weight for height,
45:19they're starving.
45:22Fallacy is that if you use the
45:25wrong growth curves,
45:27very tall people will look average in
45:31height if they're seriously malnourished.
45:34Now,
45:35the African peoples are the most
45:38diverse genetically on earth,
45:40and if you look at recent studies,
45:43this is a gorgeous set of papers that
45:46Gurdasani has done over the last few years.
45:49Take a look at the following These
45:52are people from West Africa,
45:54Yoruba and Igbo peoples from
45:57Ghana from Nigeria.
45:59Take a look at this simple plot
46:02of admixture based off of the
46:04single nucleotide changes that
46:06we all have between our genomes.
46:09Now look at the East African peoples
46:12and the South African peoples
46:15like the Khosan or the Zulu.
46:18They have nothing at all like
46:20the West African group do.
46:22They They're very different
46:24and they've had many thousands
46:26of years of differentiation.
46:28Now look with how the World
46:31Health Organization provides
46:32the worldwide growth curves.
46:35They took a survey of wealthy
46:38children in the capital of
46:40Ghana in one neighborhood,
46:43measured their heights and weights.
46:46Then they took children from other
46:48continents, Brazil, India, Norway,
46:50Oman, the US and they created the World
46:55Health Organization growth curves,
46:58They don't actually apply
46:59to any child on Earth.
47:02So there's a really amazing malnutrition
47:06unit at the Jinja Children's Hospital.
47:10This is Harriet Nembuya.
47:12I've been to this unit several
47:14times and I haven't found
47:18a better malnutrition unit in my travels.
47:24Which brings us to a brief
47:26discussion of on growth and form.
47:29Now they teach this in that school.
47:32Well, they didn't do my day either,
47:35but if you're bored one night
47:36wandering around the medical library,
47:38you might find this.
47:39It probably hasn't been checked out a lot CRC
47:42Wentworth Thompson wrote this book in 1917.
47:45It's a little hard to read 'cause he
47:47knew of several different languages,
47:49and he sprinkled them in like just
47:53'cause he could, as he wrote it.
47:55But he looked at the growth and form
47:57of many different animal species,
47:59including humans.
48:00Take a look at what brains do.
48:05Your brains do most of their growth
48:08in the first three years of life,
48:10but your body keeps growing.
48:12So allometry is the study of
48:16these proportional differences
48:18between organ systems,
48:20and it has a really bad history
48:23associated with it in terms of what's
48:27called biological determinism.
48:28I used to think this was
48:30one of my favorite books.
48:32Stephen J Gould,
48:34the Harvard biologist's book
48:36on the Mismeasure of Man,
48:38and I used to it,
48:40used to be required reading in my laboratory.
48:43He looks at what Paul Broca,
48:46the neurologist in 150 years ago who
48:49named the speech area of the brain.
48:53And Broca said that there's a
48:55remarkable relationship between
48:57the development of intelligence
48:59and the volume of the brain.
49:01Broca had some axes to grind,
49:05In addition to wanting to prove
49:06that the French brain is better
49:08than the German brain.
49:12He was pretty hell bent on showing that
49:15male brains were better than female brains.
49:18So he did a fair amount of study,
49:20carefully done. Taking brains out at
49:24autopsy and weighing them carefully,
49:27he finds that male and female brains
49:30differ by about 200 grams. Now,
49:33Gould knew about Thompson's work and Gould.
49:38If my slide will advance,
49:41Gould corrects for height and age and weight,
49:47and he finds that there's he
49:50cuts that difference in half.
49:52When I read this as a grad
49:54student the first time,
49:55I remembered that the figure
49:58was probably close to 0.
50:00When I reread this many years later,
50:02I realized that Gould couldn't accept
50:05either his own or broke his data,
50:08so he just wrote that the
50:11difference wasn't there.
50:12I no longer recommend
50:14the book to my students.
50:16We looked at over 1000 scans of
50:20normal North American children,
50:23and indeed there is a difference in
50:26size between male and female brands
50:29of normal children proportioned by
50:31the demographics of North America.
50:34Indeed, Roca's difference is right there,
50:37and if you correct for height and weight,
50:40you get ghoul's difference.
50:42They were both right.
50:43What they didn't have a chance
50:45to do without imaging is look at
50:48the ratio of brain size to fluid.
50:50So you're all sitting here,
50:51it's about 6:00 and you're you
50:53have a good brain.
50:55So your brains are all at
50:57least 1400 grams or so,
51:00and they're floating in a couple
51:03of 100 CCS of spinal fluid and
51:05suspended in their little yellow sea.
51:08Your brains are weighing about 50 grams.
51:11And that's why you're kind of happy now,
51:13ready to have a meal and go to sleep.
51:16Don't bang your head is another
51:18lesson because it's kind of a
51:21delicate situation up there.
51:22But the universal featured that
51:25they were all perhaps looking for.
51:27Is that this ratio, a brain to fluid,
51:31is very tightly controlled,
51:32doesn't matter whether you're male or female,
51:35and it doesn't matter whether
51:36you're big or small.
51:38We don't understand it yet,
51:40but we then created childhood growth
51:44curves for normal childhood growth and
51:47we use it in our studies in North America,
51:50and we use it in our randomized
51:53clinical trials in Africa.
51:55Does it apply?
51:58So what about the rest of the
52:01world and its various peoples?
52:03Do we need different growth
52:05curves for their children?
52:09And I will wrap up in a few minutes,
52:12but most brains don't have access to imaging
52:15that we'd need to do brain growth curves.
52:18MRI is about the lowest risk and most
52:23expensive technology we've ever created,
52:26and the costs are around
52:29generating big fields.
52:31So they made the mistake of inviting
52:33me to give a plenary talk at the
52:36large worldwide meeting of MRI people
52:39and I just told them my thoughts.
52:42I said well, we haven't developed an
52:45approach to technology with a cost
52:48to benefit guides our image quality.
52:50We failed in major ways in developing
52:54imaging and we oversell to ourselves
52:57beautiful images that have no correlation
53:00with patient outcome and we failed to
53:03show the value of less expensive imagery.
53:06I've actually got a lot of positive
53:08feedback from this talk in the years since,
53:11which I was quite pleased to see
53:15this is an image from the 70s.
53:17My looked like it wasn't actually
53:20the 1st hemorrhage in the brain that
53:22I saw on ACT but it looked like this
53:25and it's a low resolution image.
53:28Here's a modern day high resolution
53:30MRI of the same kind of hemorrhage.
53:33Patient outcome won't be determined by
53:35how beautiful all those features are.
53:38We need to know where the hemorrhage
53:41is and know where to do the surgery
53:43that we do to get it out.
53:46So in in recent years we've during the
53:49pandemic we got one of the first of
53:52these portable low field units into
53:55that same hospital in Eastern Uganda.
53:57We're all wearing masks there that day.
54:00And most recently this year we assembled
54:03an entirely new type of device.
54:06This is an MRI that can give very
54:09high quality.
54:10So you can see in the image here on top,
54:14but it can be fully assembled,
54:16operated,
54:17maintained by the African engineers
54:20pictured here.
54:21The Dean of Engineering at Emberara,
54:23Jonas Abungalach,
54:24got his PhD in my lap and this
54:29assembly was covered by articles
54:32and Science and Nature.
54:34Francis Shen has a very nice article
54:37out on the ethics of this kind of
54:40low field MRI as it gets distributed
54:42around the world and his principles.
54:45Of the ones I started the talk with,
54:48Local Community Partnerships and
54:51Local Society Value,
54:54let me end with one set of thoughts
54:57for discussion.
54:58First,
54:59does Uganda now need a Bantu and
55:02an Elotic growth curve?
55:05My colleagues in the country very
55:07much want to see us do that.
55:10Would monitoring brain growth
55:12during renourishment help optimize
55:15the recovery of these children?
55:18I think that's a good thing to pursue.
55:21But I'm going to leave you all with
55:24a question. What shouldn't we do?
55:27And I'd like to hear your thoughts
55:31on that in discussion.
55:33Nobody does what I just showed
55:35you on their own.
55:37An awful lot of people in an awful
55:39lot of places have really poured their
55:41hearts and souls into this work,
55:44and really what I'm telling you
55:46today is representing all
55:48of their efforts. So thanks,
55:51everybody, and love to discuss.
56:00Would you like a chair? You've
56:01been standing up here for an hour.
56:02You good? I'm good. OK, so I'm gonna.
56:04I think Karen's gonna bring
56:06me up in a in a minute.
56:08Some of the questions from Zoom.
56:09In the meantime, we'll take
56:11questions for Doctor Schiff
56:12from the audience on this talk.
56:15Yes, Sir. Wait one second. Actually.
56:19So let's focus on Zoom. If you hear
56:22you just wait. If you wait until
56:23we get a microphone,
56:29hold it up close,
56:30Thank you for your for the talk.
56:33You spoke earlier in your talk
56:35about sort of the challenges of
56:39getting funding for your research.
56:41Could you give us a little more insight
56:43into that justifying taking U.S.
56:48tax dollars to fund research in in Africa and
56:53and you know how you justify that and so on.
57:00So there's two parts to that answer.
57:03First, to quote one of my colleagues here,
57:07if you can do something that's really
57:10worthwhile, just be relentless.
57:12I mean, I've had reject many more
57:15grants rejected than I've ever received.
57:19But you know, learning how to
57:22be compelling is important.
57:25Building a track record,
57:27starting with some small pilots,
57:29None of us ever got major funding
57:32without starting off with small steps.
57:37The value of doing work on important
57:41problems is that all of it benefits
57:46healthcare everywhere.
57:47Learning to diagnose an infection
57:50you can't grow in.
57:52Let's say a part of rural Africa is critical
57:56for the infections we can't diagnose here.
57:59Walk on to our neonatal intensive care unit,
58:02make friends with your favorite
58:04neonatologist and in a quiet
58:06moment it might take half a meal.
58:09In a quiet moment, say,
58:11how many septic infants do you
58:13never get a diagnosis on and you'll
58:16be pretty shocked at that number.
58:18It's well over 50%,
58:20and there's some good reasons for that,
58:22but you can apply that to adult sepsis.
58:25You can apply that to many cases of
58:29syndromic disease where it's not
58:31obvious what causes a syndrome.
58:34Sepsis, Meningitis, fever with rash,
58:38flu like illness.
58:40So these techniques are broadly
58:43needed in many, many settings,
58:46including here.
58:48We had to use them overseas,
58:52but you could have developed all of
58:56this with US based problems as well.
58:59It turns out since we published
59:03the Penny Bacillus finding in 2020,
59:06the 1st paper that we did that
59:09there have been six more recent
59:11reports of US cases same highly
59:15destructive Panibacillus infection.
59:17Most of those children have died.
59:20One or two went on to get hydrocephalus.
59:24We have no idea what the total number is,
59:28but I just presented this to NIH
59:31and they were sort of amazed that
59:35as we studied this disease that we
59:38didn't know anything about far away,
59:40that it's also here.
59:41Now that we know about it.
59:43I hope that answers your question.
59:45Was it?
59:46I think it answers a number of questions
59:48because what was, was it here?
59:51Was it identified by by DNA sequencing?
59:54Was it identified by
59:55by actually growth and culture? So
59:57most of the ones here grew out,
01:00:00we don't know the differences in the strains.
01:00:03And there's a number of things that
01:00:06I'd like to implement very quickly.
01:00:09In our in our African work,
01:00:14I think we may be able to get an
01:00:17echo and mute that. There you go.
01:00:21Got some technology going on here.
01:00:23All right. Did I do something wrong?
01:00:26No, it's OK. I was just something wrong.
01:00:29All right, All right. Very good.
01:00:32Next question, please. Yes, Sir.
01:00:40Hi, Dad. So,
01:00:43OK, so I'll let him have it,
01:00:44let him have it, Robert. Got it.
01:00:46So this is a genuine question.
01:00:47I actually haven't asked this before. So
01:00:51you mentioned Stephen Gould and the
01:00:57kind of the issues with results
01:01:01that you don't like and and
01:01:04discounting those do you worry
01:01:07about the potential ramifications
01:01:09of like you mentioned the Nilus
01:01:15Saharan people had a potential
01:01:19vulnerability to to his Penny Bacillus.
01:01:22Do you do you worry about the ramifications
01:01:24of finding out that that is
01:01:26indeed true or if you indeed
01:01:28need to use different growth curves for
01:01:31the not the Sahara and and Ponto people?
01:01:33Like especially in an area where
01:01:35there's it's very ethnically diverse
01:01:38and genetically diverse as you said.
01:01:40Do you worry about those kind
01:01:42of differences especially in a,
01:01:44as you mentioned a colonial science context.
01:01:48Good question.
01:01:50Sometimes you raise these kids.
01:01:52They do. OK,
01:01:55I think that it's important to be
01:01:59able to personalize our public health,
01:02:02But is everyone here recalls
01:02:05recently. How we do that
01:02:09critically determines whether
01:02:10we're effective or we just turned
01:02:14it into a political nightmare.
01:02:16In societies where the level of education
01:02:20is not what you would hope to have,
01:02:25the messaging becomes critical
01:02:27because people with can easily
01:02:31perceive this as something's
01:02:33wrong with them or create stigma.
01:02:37I can't create that messaging
01:02:40as some person from the US,
01:02:42but my colleagues are going to
01:02:47have that burden who live there
01:02:49and understand the culture well.
01:02:51And my physician colleagues really want to
01:02:55improve the medicine that they deliver.
01:02:59But I did offer a teaser to everyone
01:03:02about what we would not want to do.
01:03:07I'm negotiating right now to get a
01:03:10scanner for that malnutrition unit.
01:03:12I think we'll probably show that
01:03:16with renourishment we can get brains
01:03:20of these children to grow better.
01:03:23Do I want to personalize that?
01:03:29There's several questions I don't think
01:03:32I'll ever explore that I could explore.
01:03:35One is, is there a difference in
01:03:38brain size and brain growth between
01:03:41Nilotic versus Bantu peoples?
01:03:47It's a nil hypothesis to say no,
01:03:50every nothing's identical and
01:03:55somebody's going to have bigger
01:03:57brains than the other person. And it
01:04:02whatever medical benefit you might
01:04:05have from that, I think would be
01:04:08far outweighed by the harms that
01:04:10you potentially would create by
01:04:14stigmatizing a society with no,
01:04:17no realistic benefits. So
01:04:22it's a fine line and it's the judgement call.
01:04:26I have kids dying of infection and
01:04:29I could improve that death rate.
01:04:32Then it's worth stepping into the arena,
01:04:35especially if we can figure out, I mean,
01:04:38what gives you a predilection from disease.
01:04:40Go look at Casanova. Love that name.
01:04:42Look at Casanova's papers and his work.
01:04:44He summarizes it in those
01:04:46two papers in PNAS in 2015.
01:04:49What he finds is that you can have very
01:04:52specific predilections to certain infections,
01:04:56like staph aureus,
01:04:57because you have an interleukin
01:05:01or a cytokine protein that helps
01:05:05you defend against infection.
01:05:07And it's not quite right,
01:05:08the same way that sicklers get into
01:05:11trouble from sickle cell disease
01:05:13because they have one base pair
01:05:16different in their hemoglobin molecule.
01:05:19So what that means is we ought
01:05:23to be able to treat it.
01:05:25We replace protein compounds in hemophilias.
01:05:32Would we treat someday a person with
01:05:36an infection from staph aureus with a
01:05:40commonly defective protein by giving them
01:05:43a replacement protein as well as antibiotics?
01:05:48We don't do that today,
01:05:50but we're probably pretty
01:05:52close to being able to do that.
01:05:55So it's judgment call, Robert.
01:05:58And eventually,
01:06:00it all comes down, I think,
01:06:03to benefits and risks.
01:06:05And I do think as we get
01:06:08deeper into a genomic age,
01:06:10that we have to think pretty
01:06:12carefully about that.
01:06:16Could you, Steve, go back a little bit
01:06:18and and talk or mention you when you
01:06:20talked about Gould's comments on Broca?
01:06:22Sort of like, I remember like
01:06:247 things from medical school,
01:06:26but one of them was new problems
01:06:27of Eclomisphere, Ghosh Broca.
01:06:31And I'm fascinated by Google saying,
01:06:33no, I don't accept that.
01:06:34So he just said, no,
01:06:35I don't even accept my own data.
01:06:37This is in in terms of where
01:06:41science and bioethics meet.
01:06:42I've encountered this
01:06:43from time to time as well.
01:06:44And I've I've coined the phrase as we
01:06:46do this when I teach us don't fear the
01:06:48data because I have heard people say,
01:06:50well here is the data,
01:06:51but we're not going to talk about
01:06:52it because it doesn't bring us
01:06:55to the conclusion we want, right.
01:06:57Do you think some of that has gone
01:06:58on in terms of brain size and brain
01:07:00growth and is that could that possibly
01:07:02could the fear of the data direct
01:07:04how we move forward with the science?
01:07:05Of course.
01:07:07Should it?
01:07:09No.
01:07:11But
01:07:12I'm torn with these things like
01:07:14some of your fan clubs going
01:07:16he's got a test to take tonight.
01:07:19But I I I worry a great deal the power of
01:07:25these technologies to uncover facts which
01:07:29we may not be able to handle. I mean,
01:07:36look at the conflicts around the world.
01:07:37It doesn't take much.
01:07:39I think of Rwanda, in particular
01:07:43the Tutsis and the the Hutu.
01:07:47We're not even sure they were
01:07:49actually both ancestral people,
01:07:52but politically they were set up in a
01:07:56way that led to an enormous genocide
01:07:59of a population within about 90 days.
01:08:06I think we need to be very careful
01:08:09because we have tools which can
01:08:12literally weaponize our science.
01:08:14And this wasn't obvious to me when I
01:08:19started looking at things like the
01:08:21genomics of these children in Africa.
01:08:23But gradually I would sit with my colleagues,
01:08:27helps to spend a lot of time
01:08:29with your colleagues overseas.
01:08:30And I sort of looked at them and said
01:08:34we can cause an awful lot
01:08:36of trouble if we do this.
01:08:37And we all sort of looked
01:08:39at each other and said,
01:08:40yeah, let's not do that.
01:08:44I wish there was like the adult in the
01:08:47room who would have said long ago to us,
01:08:49do this, but don't do that.
01:08:51But there isn't. It's us.
01:08:53And I think these are burdens.
01:08:56Gould really disappointed me.
01:09:00I've read so much of his work.
01:09:02It's He's such a brilliant scientist.
01:09:05If you read Edward O Wilson's
01:09:09autobiography called Naturalist,
01:09:10you might worry a little
01:09:13about how difficult Gould,
01:09:16in a professional environment,
01:09:18might have been to the people around him.
01:09:21But many of us are not easy.
01:09:25And yeah, we do good work, I hope.
01:09:28But it's a trap.
01:09:30It's a trap that Ghoul felled into.
01:09:33He was a very politically active person,
01:09:38and he wasn't going to accept
01:09:40that result for anything.
01:09:42When I read it with, I think,
01:09:45a fair amount of care,
01:09:46I didn't appreciate it as a student.
01:09:50You'd appreciate what? I
01:09:50didn't appreciate his bias as a student.
01:09:53It took took losing hair and being
01:09:56in the business for a long time
01:09:59and to look at that and go, Oh no,
01:10:02look what he did and then he
01:10:04wrote it all down. But you know,
01:10:07we read these things for the message.
01:10:10How many of us look at a scientific paper
01:10:13and you know, you read the abstract,
01:10:16the first paragraph, the last paragraph.
01:10:18Is there anything in between that's
01:10:21worth your time before you move
01:10:23on to the next task of the day?
01:10:25But if I leave you any of you with a caution,
01:10:29it's be careful, and be careful
01:10:32what even the experts tell you.
01:10:38Other questions, things I can try to answer,
01:10:43Sir.
01:10:47Thanks, Doctor Schiff. I'm curious, I
01:10:51mean, you work with so many
01:10:55people from Uganda. Do you find like
01:10:57when when you're working
01:10:58with your African colleagues,
01:10:59you you have any like favorite
01:11:03examples of ethical disagreement
01:11:05where you just that are particularly
01:11:07intractable maybe that are grounded
01:11:09in cultural differences or different
01:11:13just, you know, starting from
01:11:15different ethical premises?
01:11:17Does that make sense? Yeah,
01:11:22I
01:11:26I'm a short white guy from the
01:11:28US and I didn't grow up overseas.
01:11:34And over the years I've worked very
01:11:38closely with a lot of both physicians
01:11:44and also with patients, families.
01:11:49And I think the one thing I
01:11:52come away with is there's a
01:11:56real universe have universality
01:12:00between doing medicine anywhere,
01:12:04and I find very much a lack of
01:12:10disagreement between myself
01:12:11and the colleagues I work with.
01:12:17Whereas we all sort of agree that certain
01:12:21science studies are way out of bounds.
01:12:25And the other thing I noticed is that
01:12:30mothers of sick infants are the same
01:12:33everywhere they care deeply for.
01:12:37And
01:12:41I I look at the women who bring their
01:12:44infants in and their willingness to
01:12:46let us try to enroll them in studies
01:12:50of their children's illnesses.
01:12:54And I think most of the cultural differences
01:13:00just melt away over young infants.
01:13:03It's probably why I can show you those
01:13:09examples of like government leadership,
01:13:14nursing leadership, child advocates,
01:13:17all in total agreement
01:13:20over certain things we do.
01:13:23And it's probably why that list
01:13:25of collaborators was so long.
01:13:29Infants or a universal currency.
01:13:33And if I were studying, I don't know,
01:13:37sexually transmitted disease of teenagers,
01:13:42I think it would be a much
01:13:45more difficult path to follow.
01:13:52Thank you. Other questions,
01:13:57they look tired and hungry. Say again,
01:13:59They look tired and hungry. They look
01:14:01tired and hungry. All right.
01:14:02Well, we gave them a little some of
01:14:04that just wet their appetite both for
01:14:06more sandwiches and more knowledge.
01:14:07This was a wonderful presentation.
01:14:09Doctor Schiff, thank you so much.
01:14:11Thank you all for coming. Thanks
01:14:16everybody. What's the
01:14:16talk about? What's the talk about?
01:14:20All right, we'll see you all in January. Have
01:14:23a good holidays.