Okay. Can you start by saying your name and what your current title is?
Hello, I'm David Eyre and I'm professor of Infectious Diseases.
Okay, that's great. At can you give you a department?
And so I'm, I'm based at the Big Data Institute, which is within the Department of Population Health.
Okay, that's great. And without going into enormous detail with your whole life story, can you just tell me,
starting from when you first got interested in medicine, the main milestones on your way to your current position?
So when you get to the end of 2019, because we're going to talk a little bit about the area of work generally before we get into COVID.
So I originally went to medicine in Cambridge in 2000,
and then I came over to Oxford to do the clinical part of my degree in 2003 and then since then have worked in an era in around Oxford.
So I, I started off doing my initial medical training split between the John Ratcliffe and
the Horton Hospital and then spent some time in other hospitals in the region as well,
and and became interested in becoming an infectious disease specialist because
it offered a really nice combination of being able to look after patients with
a range of problems and problems that often we could diagnose and offer treatment
for and also some really exciting opportunities to be involved in research.
So before starting my specialist training, I did a PhD and basically that was around the area of pathogen sequencing and particularly
looking at an important problem in hospitals called Clostridium difficile or C2,
and thinking about whether we could use information from sequencing of the pathogens DNA to then I'm sorry,
you're getting the background noise through. No, I'm not hearing anything.
I'm sorry about that. I've got I'm just going to stick to the do not disturb thing.
So hopefully we get no no pinging in the audio.
So if I just go back to it, say so starting off with thinking about sequencing it, see if this pathogen seeded for sale,
which is an important problem in hospitals,
thinking about whether we could work out how infection was spreading and what could we could be done to stop it.
And what was really interesting there was that we we found that actually much less of it was acquired from other patients than we previously thought.
And and that's really changed how we how we think about this infection and how to prevent it.
And then following on from that, I did my specialist training alongside doing some further academic work,
thinking about what we could learn about sequencing other pathogens and was involved in work,
thinking about very antibiotic resistant gonorrhoea or super gonorrhoea in the in the media.
And we had some involvement in cases where we had infections that were resistant to nearly all
antibiotics that have been produced and worked on trying to understand how they'd occurred,
but also sort of some of the messaging around how to stop spreading.
And then also involved in an outbreak of a new emerging super fungus, something called Candida Auris here in Oxford,
where we successfully ended a big outbreak and contributed to guidelines to stopping that.
So and then in in around 2018,
I finished my specialist training and became a consultant in infection and
around the same time also took up a fellowship of the big data institute here.
And so going into 2019 and the start of 2020, I'd got all sorts of plans for what I was going to do.
But that has ended up changing with the with the pandemic. But we'll get to that.
But I'd like to get go into a little bit more detail into how you use genomic sequencing to deal with the problem of infection prevention and control.
So, I mean, it seems to me that there's there's two things you can do with a sequence.
You can use it as a kind of barcode to label to, to finally identify a particular bug, or you can use it to try and find out how that works.
Is that is that correct? Is that the reason? So I think that's right.
So we can do a number of things with sequencing information.
And one thing that we can do is to use it as a way of trying to see whether transmission is likely or whether we can rule it out.
So as an infection spreads, if infection is spread from one person to another person or from one place to another place,
then that infection looks really quite similar and actually in some cases completely identical when we sequence it.
And so we can use that as a way of identifying when transmission might have occurred.
And of course, if two things look very different and that's quite a good rule out to saying transmission hasn't
occurred and actually we need to look somewhere else for the source of the second infection.
So that's, that's one piece of work and and that can be used in a number of ways.
So we can use that to study outbreaks where we've got an unusually unusual cluster of infections.
We can also use it to monitor an infection that we're interested in over time.
And we can look to see whether we can pick up clusters of infection that way.
And that turns out to be quite a sensitive way of doing surveillance that you wouldn't necessarily you would have to
you would have to expend quite a lot more effort if you were just monitoring the number of cases you had because.
It's harder to spot sort of rises in a specific type of case if you don't have that sort of more detailed information that we get from sequencing.
So that's sort of one area. And then that another area where there's interest in sort of looking at specific traits of the of the pathogen.
So it might be, for example, can we predict whether an antibiotic is going to work to treat an infection using sequencing data?
And I'm actually the big success story there has been with TB where now actually the treatment of TB in the UK is
based on where if we find a pathogen to be completely sensitive to an oral antibiotics or based on sequencing,
then we actually use the sequencing and don't do any further diagnostic work.
We rely on the sequencing data to sort of make decisions about treatment.
It's it's not quite so advanced in other areas and it's still a sort of research technique,
but largely but but TB is certainly one one success story there,
and that can be particularly helpful where something takes a long time to grow in the lab inside a traditional sort of lab workflow is slow.
And then we might sort of with TB previously, it may take several weeks to get an answer and now we can get an answer within a week or two.
And there are also times where we can't grow a pathogen.
So some things that simply it's just very difficult to grow in the lab and we can sort of make a diagnosis using sequencing.
And then increasingly it is interesting, can we just detect things faster using sequencing?
So there's a whole area of research called better genomic sequencing where we try and without using the sort of
traditional culture based methods that we've been using in microbiology for the last last hundred years or so,
we actually just try and go straight from the original sample and see what's in it using sequencing.
And you mentioned that you're now based in the Big Data Institute. So where does where does big data come into all this web?
Where does computer analysis extend what you do?
So a typical typical virus is has a sort of genome sequence that's maybe a few thousand acres jus inches long,
whereas a bacteria, it might be a few million.
And so and when we do sequencing, typically we can't get that entire sequence all in one, get it, we get it in fragments.
And so actually what we need to do is to to reconstruct the the sequence data that was there in the original pathogen from lots of small pieces.
And so this is sort of rather like putting together a jigsaw puzzle.
And you can do this through a number of ways, some of which involve sort of knowing what it looks like,
sort of analogous to having the picture on of what the jigsaw supposed to look like.
And then the other way is really just looking at overlap of bits of the sequencing data
and trying to piece it together just from sort of what looks similar around the edges.
But doing that involves a degree of computational computational processing and then trying to make inferences from the sequencing data that we get.
So trying to piece together how related the different sequences are or to look for specific
pieces of sequence within the overall sequence also requires a degree of computation.
The the other thing that and one of the big reasons that I'm based at the BDA is actually we're not just looking at sequencing data in isolation.
Often we're looking at it in conjunction with other health care data.
So we're thinking about maybe how patients move around the hospital.
So piecing together data from electronic patient records on when patients are admitted, which wards they go to,
who they share time and space with while they're in hospital and and sort of coming out of that.
I've also become increasingly interested in how we can use electronic health care data actually as a tool in itself.
So not necessarily just with sequencing data,
but can we use it to better understand infection in terms of the epidemiology of infection and the transmission of infection,
but also thinking about diagnosis, prognosis and treatment?
So can we use information on what happens in routine care within hospitals to then try and make
try and give advice on how to better manage manage patients and and also not just patients,
but sort of thinking about hospitals as systems as a whole.
And can we can we control infection, spread of infection in hospitals better, but can we also just manage hospitals better?
Can we cope with peaks of seasonal infection and be able to sort of help help patients journeys through hospitals be more efficient?
And and so that so that is really not just sequencing,
but that sort of come out as a sort of increasing, increasing interest in the practice of works of.
Are a bit before COVID, but certainly the afterwards as well.
So let's just one final question, because not everybody necessarily knows.
Can you tell me a bit about the genome sequencing technology that's available to you now?
Because I think people may have heard the story of how the human genome sequence was originally
deciphered and it cost $3 billion and took is clearly we're not still in that in that world.
Yes. And so when when I first started thinking about what I was going to do for my Ph.D. and sort of towards the end of 2008,
2009, sequencing was really an emerging technology.
And we thought if we're lucky, we might just be able to sequence a few bacteria and that would be a big, big success.
And what really happened is over over the few years following from that,
there was really a kind of explosion in the availability of sequencing data such that actually we could see we could go from thinking we'd only built
sequence a handful of things to actually sequencing thousands of bacterial genomes and probably doing so for around about the sort of £50 genome,
which was really unthinkable previously. And what drove a lot of that was this sort of expansion in what we call short read sequencing technology,
where we could sequence up to several hundred base pairs of several hundred
genes and tease of the bacterial genome in one go and generate many thousands or
millions of these these bacterial reads that would then put together what's what's
happened more recently is there've been different different approaches taken,
including approaches where you can generate much longer.
So rather than just fragments of sequencing of a few hundred long getting up to several thousand long
and this has the property because it makes it it much easier to reconstruct these bacterial genomes.
And and also we've seen changes in the way that technology is deployed from being something where you'd
have to generate big batches of sequences to where you can actually it's not quite random access,
but that sequence sort of a relatively small number of things together,
which has meant that we're able to to offer sequencing and sort of more real time,
real time service when we're thinking about how we want to think about wanting to deployed.
Mm hmm. So, I mean, do hospitals already have sequencing available?
It's something it's done relatively routinely. Yes.
So the it's largely been a research tool or something that reference laboratories have used.
One of the things that has happened, and we may come on to talk to is about is that because of everything that's happened in Cambridge,
the capacity of routine laboratories in hospitals to.
Undertake the sorts of molecular microbiology work that are involved in sequencing has gone up substantially.
And so with that, there's been a clear focus on sequencing COVID as well.
And that's and that's meant that both the sequencing machines,
but also the kind of familiarity and competence of a stopwatch in hospitals is massively increased.
And so, for example, in our own hospital, we would now have been able to routinely sequence COVID.
And I'd also thinking about routinely sequencing a number of a number of other things,
But there's still challenges around maybe demonstrating that the sequences cost effective and that it may be a nice to have things.
But does it actually does it actually improve outcomes for patients or outcomes hospitals?
And I think this is probably still a bit more work to be done there. Right.
Well, I think we've arrived at coded. So can you remember when you first heard that there was an outbreak happening in China and how soon it was
before you realised that this was something that was going to have a major effect on you and your colleagues.
So I think we still would remember the exact dates, but we certainly became increasingly aware as reports came out of China,
that there was this unexplained respiratory problem and, and then actually had.
A number of visitors to Oxfordshire from hand in the in the run up to it.
And I was involved as the infectious diseases consultant on COOL and we had a number of queries about sort of what.
What should be you know, what should be happening and what would happen if people became unwell.
And then we gradually got more and more calls about what to do with people who come
back from various parts of the world where there was concern about about COVID.
And we had some quite initially sent quite some quite clear but sort of restricted guidelines about who
needed testing and then gradually became sort of more and more aware that this was a sort of growing,
growing issue.
And and I think from a from a clinical point of view, this initially was something that sort of the infectious diseases team dealt with,
but it became increasingly apparent that this was really going to be something that impacted the whole the whole hospital.
And it's I think although although we hoped it wouldn't become a big problem, it's quite interesting, actually,
even looking back at a sort of WhatsApp message sent between me, my wife and her colleagues at the time,
sort of in February, in February, saying, you know, this could be a really big problem,
it could have a substantial economic impact and really being aware that it could be a big problem.
But then. I interestingly myself reflecting that I then sort of took minimal personal action to sort of,
you know, I still run out of food along with everyone else when we ran out of food or or, you know,
sort of failed to sort of fail to sort of take all sorts of actions that you maybe could have done with this prior knowledge,
because maybe deep down sort of hoping that it just wouldn't become such an issue.
And. That said, I was lucky.
I managed to go to my cousin's wedding on the 29th of February, and in 2020, a big, big wedding with over 250 people in London.
And so, so obviously wasn't so worried that I because I was still prepared to go to that.
And and then and then actually subsequent to that personally became unwell and developed a fever and
cough and was subsequently antibody positive where I thought at the wedding or from somewhere else,
I don't know, but spent much of that sort of first the sort of middle of March actually feeling ill
and being off work and sort of not feeling necessarily a part of what was going on.
But then sort of towards the end of March and coming back into the hospital and and really in that first part of the pandemic,
actually just being a part of a medical team looking after after patients in the hospital.
Yes. I was going to ask you about that, because obviously you clearly had a need to deal with patients and work on your clinical side.
But that was also, I mean, across the university, a very quick realisation that this was a massive research opportunity.
Indeed, research is going to be necessary in order to tackle the pandemic,
and it had to be done while there were cases you had to do it while you had the pandemic going on.
So how soon did you know? Let's do the clinical side first.
So what what how were you deployed? And as patients began to come into the hospital with COVID,
So we we had several wards which were sort of given over to looking after patients with COVID.
And I was involved in being the consultant running one of those, and you sort of organised the wards into the level of support that people needed.
So there were some wards where people needed to go to the intensive care unit,
other units where people still needed oxygen, but maybe less, less support with the with their breathing.
And so they were on the the ward that I was helping run.
And. I have to say, initially it was really quite a frustrating experience because as I said at the beginning,
I think in infectious disease, often we we can we there's both often a bit of a challenge about working out what's wrong with people.
And then secondly, we then usually able to treat things, whereas here it was fairly obvious what was wrong with people,
but we were not able really to offer much meaningful treatment.
And so, so both those things really quite, quite different and difficult to what we were used to.
And, and I think really a very challenging time in that actually, you know, lots, lots of people have pushed me to either nothing I,
I certainly remember times where you'd come into the hospital and actually I just
really vividly remember coming in one Saturday morning and there was all this backed
up possessions that had been left from people who died the night before or the day
before that were just waiting on the ward and electronic bed ward of patients.
And the hospital was both full of patients who had been there and patients who'd been admitted.
And there was just no one necessarily available to update the system.
And so it sort of this sort of rather rather chaotic, but everyone trying their best to try and help people as best they could.
So I think I think that was a very difficult time and I think people were also quite.
Quite worried and lots of uncertainty and we've not really experienced anything like this before.
And in infectious diseases we have a relatively good amount of training around using personal protective equipment.
But actually even having had the people stuck in it, people still feeling personally worried about about their own health and safety as well.
And certainly that colleagues around you not had so much training.
So, yeah, I think a really challenging time.
And I think you mentioned research and I think there was this sort of tension where I was off feeling unwell and then I was working in the
hospital and sort of being aware peripherally that there were a number of people then with various bits of research work starting up and.
I think I had quite mixed feelings about that because from a personal perspective that,
you know, that actually there opportunity to contribute that I was potentially missing out on,
but also recognising that there was an important,
important role to do in the hospital to say this is a bit of a sort of conflict in terms of how I felt about so.
So that was really the the sort of first first few weeks of the pandemic.
But then I then ended up getting involved in a number of different things,
mostly around the area of diagnostics and also around a programme testing healthcare workers in Oxfordshire.
And then following that, actually quite a lot of work to do with antibody testing and using antibodies as well,
tracking response to to vaccination, infection, sex. Yeah, happy to sort of pick up, pick up on each of those.
Yes. Yeah. That's all of that. So, so one of the first things I ended up doing was there was a hope that.
The sort of lateral flow tests that we become very used to using for detecting whether people would have infection initially,
that you would be able to use these for detecting antibodies and seeing who had been infected.
And then maybe if you knew who'd been infected, then you might be able to relax restrictions for those people.
And there were a number of tests that were procured from various suppliers, which we were then involved in evaluating in Oxford.
And so. Quite a few people were involved in going around taking blood from people who had been infected.
In fact, some of the earliest cases of people who'd been infected sort of driving around the countries that are going and seeing those people and
asking if we take blood from them so that we we had samples from people where we knew we sort of had that what happened to their antibodies.
And then we had a number of blood samples that were, say, from before the pandemic,
which we could use to work out sort of whether whether we got negative results when we expected to get negative results.
And we tested a number of these different devices, and it turned out that none of them really worked very well.
And. This is sort of frustrating on a number of levels.
It would have been obviously really helpful to have had that information.
But it also meant that a number of the tests that had been had been bought then then could be couldn't be used.
And it was sort of quite, quite an interesting initial experience at the sort of interface between
research and then subsequent policy and that sort of quite a bit of discussion
at the time about what we could and couldn't publish in the publication that we eventually released didn't actually name the the device manufacturers,
but there was sort of quite, quite clear contractual reasons why that had to be the case,
but quite different to how we might normally normally do science.
But I think that the main message that came out of that was that we knew that these tested didn't work.
So what? Well, you tell what were you testing them against? What was your gold standard?
The gold standard was people we knew who had an infection.
So people who tested positive on a PCR test for infection and these were some of them were were health care workers,
some of them were people who were sort of early,
early case early cases from from yeah, from around the country and had blood samples taken at different time intervals after they'd become infected.
And then the sort of negative controls with the blood samples which we had stored from from before the pandemic.
So going back. Oh, I see. Did you not have any method at that stage that could detect antibodies?
So So we were yes. So we were relying on the fact that we were essentially saying, well, how many times in people have been infected?
Do they did these devices test positive?
And then if people who we knew hadn't been infected because of the time window, how many times did they test negative?
And what we found was simply that we got some of the positive when they shouldn't do.
And then we also got quite a few that didn't test positive when we expected them to test positive.
And as you say, we didn't have a good antibody test, sort of a lab antibody test at the time to to compare performance against.
And so that really comes on quite nicely to to sort of second second area of work that I was involved in,
which was actually around developing an antibody, a better antibody test.
So we'd seen these devices didn't work very well. So it was quite clear we needed something that worked better and colleagues here in the university
were involved in sort of rapidly trying to trying to try to develop synthetic antibodies,
monoclonal antibodies that could mimic the kinds of antibodies that were produced.
And then also the the coating of the SARS-CoV-2 virus, the spike protein,
also creating synthetic versions of that so that you could use the synthetic version of that to capture antibodies,
which you could then could then measure.
And what I was involved in was taking some of the initial synthetic antigen, a synthetic viral spike protein and synthetic antibodies,
and turning that into a sort of more high throughput antibody testing platform.
And probably to summarise what was a lot of work quite quickly, I mean, it ended up being successful,
but it was clear that in order to have an impact, it would need to be delivered at really quite, quite a quite wide scale.
And so we initially went to colleagues at the the Target Discovery Institute here in Oxford who worked on screening a large number
of drug compounds and other compounds very rapidly using robotics and said could they help running antibody tests at scale?
And so we initially got something set up there and a subject this was this was Daniel Hepner and Stephanie Hatch, was it?
Yes, that's yes, right. Yeah. I got something set up with Donald Leiber and Stephanie Hatch and and then subsequently.
Actually, then we're able to port that to an even higher throughput robotic robotic platform.
That and that and that sense has delivered over a over sort of to 2 million antibody
tests that supported the National Office for National Statistics COVID Infection survey.
So that's really been given us an enormous understanding of what happens to people after they get infected,
what happens to their antibodies, how they rise and then fall, also how antibodies respond to vaccination.
And then putting that together, thinking about sort of what levels of antibodies are associated with protection against infection.
And we've been able to sort of forward then project as to how long immunity from
vaccination might last or how long immunity from previous infection levels as well.
So we might we might just do the those conclusions. Well, while we're here, Ross isn't going to do it.
So what what were your main discoveries? I mean, yeah, over the next 18 months or so, probably.
So I think we what was so what, what came out was that.
Antibodies were when you got infected. We did see in most people antibodies increase and rise.
And actually it depended a little bit on how new or how you detected the infection,
but probably in at least three quarters and possibly more people who were exposed and tested positive at some time for the virus that causes COVID.
SARS-CoV-2 They then developed an antibody response and those antibodies rose
and then and then lasted for for at least several for at least several months,
possibly even possibly even sort of several years after that after people were infected.
And we initially thought that this might offer quite a long standing protection against reinfection.
But what happened was, is that the virus changed, and each time that the virus changed and evolved,
then actually you tended to need more and on higher levels of antibodies to try and offer the same level of protection.
And and so we also found that the vast majority of people, when they were given the vaccines,
responded in probably as many as 95% or more people responded to an initial course of two
vaccines and produced antibody levels that were as high or even higher than we possibly saw.
So when in fact after infection and but those antibodies were possibly less,
less longer lived, they lasted a few months rather than sort of a couple of years.
And they were predicted to last a few months rather than a couple of years at levels that often offered protection.
And so this really fed into some of the some of the booster campaigns which came along to both reflecting the fact
that we saw waning of protection when we could follow sort of whether people were infected and after vaccination.
But also we could see this sort of waning antibody levels at the same time.
And and then as people were boosted,
we then saw even more people respond and get response and get responses to vaccination in terms of the antibody levels that we saw.
But again, trailing off after they were they were boosted and then as each new successive variant came out.
So then the Delta and Omega from that, the the amount of antibody that you needed against the original spike protein and the original virus
needed to be sort of progressively higher in order to get similar levels of protection and and.
And then. This sort of most recently,
we've been thinking about the difference between the protection that you get when you have a have a reinfection or get
infected after you've been vaccinated versus the sort of ongoing protection that you get from various booster campaigns.
Because what we've what we've seen is that although we've continued to try and get regular
boosters to those who are most vulnerable to to sort of poor outcomes from infection,
there are a number of people now who aren't being routinely offered vaccination.
So we wanted to understand what was what might happen to them.
And it it turns out that in people who have been vaccinated and then go on to get infected,
that they they then tend to generate relatively sustained antibody responses suggesting that they may be protected from infection,
getting infected again for some time. Whereas the people we need to distinguish, don't we, between getting really ill and getting infected.
So yes, and I think that's been the. The other success story really with vaccination has been that although maybe people
haven't been protected from reinfection as much as we might have hoped initially,
actually, the degree of severe illness has gone down and and possibly also that's been that's
been a consequence of changes that have happened in the SARS-CoV-2 virus as well.
But as time has gone on, the infection that's been caused has been less severe as well, particularly for the combination.
So that's the antibody side of things. And.
Which we are back to. I've got a note here that says Web based application to support trust staff and collect data.
Yes. So. So we. The other thing that sort of working in the hospital motivated us to think about was, well,
what what's happening to stop, you know, our staff more more at risk if they don't know or not.
And if they are, well, why and what can we do to to protect them?
And what we did back in April 2020 was we were fortunate to sort of make it make a bid directly to the Department Health and Social Care to say,
could we set up large scale testing of health care workers in Oxford as a way of trying to understand risk to health care workers?
And some of our really key questions about COVID at the time, You know, did people get reinfected?
How often did that happen?
And so what we what we did was to start by offering staff regular antibody testing and also regular testing for infection with PCR testing and.
In order to do that, we had there was an enormous amount of logistics involved in that, actually.
The hospital employs over 13 and a half thousand staff.
And so being able to offer them regular PCR testing, all of which was performed by by a team we put together and antibody testing,
which was done through blood tests that were also done by the same team, was a really big undertaking.
And part of that was it became quite clear that we needed a system for for people to be able to book into appointments.
We needed a system for people to be able to receive their results because we felt that feeding back to people what the test results were,
was sort of a really important way of getting them engaged and getting them to participate.
People particularly wanted to know what their antibodies were, you know, had they been infected in the past.
And also we wanted a system that was safe because part of the reason for doing this was that we wanted to know when people were healthcare workers
were infected so that we could then get them home to isolate them and protect other patients in hospital and also other staff from getting infected.
And so I said I set up what I thought initially was just going to be a sort of short term fix.
Was it which was a sort of web based application that enables people to to register their interest and to and to look into slots.
And I think when we first made it live,
we had thousands of appointments made within the first few minutes of it being available and it performed and it worked,
didn't fall over, which is certainly sort of a nice, nice feeling.
And then we then got people regularly coming, coming to complete the testing and,
and that was possible because we had an amazing group of research nurses who switched from doing all sorts of things,
including some of the sort of hepatology research nurses supported by lots and lots of medical students,
other people from around the hospital who were redeployed, helping us both with sort of supporting the as supporting the actual testing of people,
swabbing people, and then also some of the sort of additional cooling outs of results, the sort of follow up of people who tested positive.
And and then from that, we we collected the sort of first thing we did was to work out who'd had COVID, and we showed that.
More health care workers have had COVID than in the general population.
So I think we showed our sort of initial result was towards the end of April, early May,
that around ten or 11% of our health care workers had had COVID compared to estimates from antibody tests.
And another test in the community of around 5%,
And we also showed that staff looking after patients with COVID were even greater risk and
actually that was sort of up around the 20% mark or so in areas of the hospital where people,
particularly patients with COVID. We also showed that actually different staff groups were differentially at risk.
So different medical specialities have different degrees of risk.
People particularly working in acute medicine, looking after unwell patients coming first, coming into hospital.
Then also different different sort of staff groups within the hospital.
So nurses and health care assistants, porters and other support staff at greater risk.
And then also staff of Asian and black ethnicity also were at greater, greater risk,
even even an adjusted analysis, adjusting for other factors that we could measure.
Six Coming out of that, we it really became clear that we needed to do more to protect staff.
And we also had, unfortunately, several staff who died of COVID as well and those in the early months of the pandemic.
And so there is a sort of multi, multi sort of action,
sort of multi-point action plan that went to the trust board and was largely
implemented in full as a result of some of the findings that we had from that.
And following on from that, actually, we had some of the lower rates of hospital associated COVID compared to other other hospitals in the country.
And people were sort of coming to us as a sort of source of best practice for how to help try and prevent transmission in hospitals.
So so that was a really, really positive initial outputs of that.
But having tested all these people in the first wave of the pandemic,
then when the second wave of the pandemic came along in the autumn of 2020, we were in a position to ask, well,
given we had a group of people who've been infected before with a protected from getting infected again,
and that allowed us to actually quantify for the first time anywhere in the world what your chances were being infected, infected again.
So towards the end of October into November 2020, it became quite clear that there was actually quite good protection against against reinfection,
that your risk might be only around sort of 10% of what it was if you hadn't been previously infected.
And. And we then we then did some work with our health care workers as well, thinking about sort of response to vaccination.
But that sort of actually that that initial testing program really,
really helped really sort of helped help both establish protection from reinfection and also sort of have a better shot of the staff.
And then we were then when lateral flow testing was rolled out as a routine thing to start,
we were then able to use the same systems to track lateral flow test results and and continue to offer testing to staff first,
first first half of the pandemic. Really using that is in our system.
It's now been retired, which I'm very pleased about because it was a lot of work keeping it going better.
But I think we in the end certainly supported hundreds of thousands of tests, the staff, the staff through it,
and several thousand positive results notified staff and their staff so that that sort of be able to
be able to sort of be able to go home and isolate and prevented from transmitting on in hospital.
Mm hmm. I think you listed three things earlier and I now can't remember what the other one was.
So we. Yes. So so I think and sort of developing the antibody tests,
the and then the sort of using them through the COVID infection survey and start testing other things.
Other things we have have been involved in to.
To some extent was thinking about whether we could use sequencing as a tool for tracking infection in hospital.
And certainly others have done larger scale studies than what we did.
But we did do some work in Oxford and also the experience was that we found that
it was actually quite a bit of the transmission from hospital in hospitals.
That happened happened from a relatively small percentage of the patients and staff who had COVID.
So and it tended to be sort of particularly patients with newly acquired infection in hospital who were most.
It was the sort of most infectious and who sort of posed the greatest sort of risk of onward onward transmission to it to other patients.
And so you almost got this sort of this sort of ever increasing feedback loop where patients that came in from the community with COVID,
they'd been ill for a few days at home and most infectious in that period, and then once they came into hospital were less infectious.
But if that then that then happened to trigger off one additional infection in hospital.
That person was then much more infectious. A number of people then became infected who were also much more infectious.
And so we saw these sort of clusters of cases where you got this progressive amplification of transmission that we could see.
And so that really prompted us to particularly focus on making sure our infection control
was really was really tighter around patients who had been newly diagnosed with COVID.
And it also underlined the importance of making sure that if staff became infected,
that we were aware of as soon as possible, because actually they were likely most infectious at the start of their infection.
And so making sure that that people followed advice and testing and rapidly isolated was also also really important.
And did you continue your regular surveillance of other pathogens in the hospital?
Yeah, and. Know, from a research point of view,
I think people continue to be aware of some of the pathogens that we might routinely monitor for infection control purposes.
And so one of the one of the challenges was with that increased PPE,
personal protective equipment that people were wearing in the intensive care unit,
that actually we had an increase in infections due to a bacteria MRSA, which actually we hadn't had a particular issue with in the hospital.
But but it sort of came back to being more of an issue because actually some of the sort of washing of hands and changing of gloves and
changing and sort of changing equipment became much more difficult where people were having to sort of continuously where we're keeping at.
And also actually,
it is just difficult to be as sort of physically precise about how you might clean things and maintain things when you've got all the barriers,
the extra, extra people as well.
So so that was an example of something we saw rise and then had to then think again about sort of how we how we addressed that.
Did we need to modify the way we use people need needed. We need to change what people we use it to try and control and and set up that.
That was one thing we did see happen. But otherwise actually that we did, as people would imagine, see quite a lot of sort of the routine activity.
The hospitals slow down or stop. And so some of the other things that we would normally monitor or have challenges with actually went went down.
And I think that's what I was thinking, that you had fewer patients from the general community coming in with all kinds of things up their noses.
Yes. Yes. So.
What kind of hours we work. I mean, I've just I've just been trying to tot up your workload.
I mean, one of the things I looked at was your list, the list of publications that have got your name on.
And it seemed to massively increase over the past three years.
I don't know how much actual writing you had to do yourself because they're mostly papers with huge numbers of of authors.
But I mean, that's just kind of the end of the pipeline, isn't it? You've got to work the research work do you've got all the clinical work to do.
How much pressure were you under in terms of the hours you put in?
Yeah, I, I think you clearly can't work the kind of hours that people worked.
And, you know, I think lots of people worked enormous numbers of hours in all sorts of capacities.
So, you know, I don't think it was by any means unique, but you clearly can't sustain that forever.
But what I think what a number of people did was to work enormously hard and much, much longer hours than they would they would do normally.
I sort of came in in several forms, I think previously that no one would have dreamt of having organised meetings at eight
or 8:00 in the morning or 730 in the morning or late on a Friday evening or whatever.
And those things then almost became normalised and people sort of routinely did those things or spoke
to each other at the weekend in a way in which people wouldn't have done necessarily previously.
But there was this real sense that it was it was really important to get answers quickly,
that actually we need to do everything possible to to to get answers.
And I think that was largely motivated by sort of. Altruistic reasons for public good.
But but there's also this sense of enormous competition as well,
because actually everyone was working very hard and we're all trying to answer similar questions.
And so I think there was also this external pressure that you wanted to be first.
For example, we talked about the health care workers study. Of course, we wanted to report our results before anyone else reported that.
So we we knew we were kind of likely to have enough results to have a paper.
And so we were almost sort of writing the paper and had it ready to go so that once we had enough data,
we could sort of we were sort of slightly second guessing what we'd found so you could top and tail it with the sort of relevant discussion.
And then once you got the results, sort of slop them in and send it off.
And so I think, yeah, there were, there were times where definitely sort of people were working from 730 in the morning through to,
you know, even 1130 at night on things. I think that was every day.
But there were times when it was it was like that.
And I'm interested what you say about competition,
because I've one question I've been asking people is whether they felt that working
with the pandemic led to it an increased level of openness and collaboration.
And most people say, yes, I think you're the first person who's frankly said that they were driven by competition.
But did you also experience that sense of collaborating with a wider group?
I think I think, yes, there was definitely an immense amount of collaborative working both within the university and sort of across institutions.
And yes, so I think it would be it would be wrong to say everyone was sort of motivated by sort of their own their own selfish sort of motivations.
But I do think that there were times where.
We were aware that other people were doing similar studies and and and yes, everyone.
So wanting to. Wanting to share information quickly.
But also I guess the ultimate ultimately that there are rewards for being for being first and I think that kind of.
Even amongst everything else. I think that's still kind of place some some degree of a role in and what people did and.
But but yeah, I mean, I think as I said, as I said, I think the main thing it was that people wanted to get an answer because it really mattered.
And so to give you another example of something I was involved in as the pandemic went on, there was a a a child on a lateral flow testing in schools.
And I'm thinking about whether.
Rather than sending students home to isolate at home for ten days when they've been a contact in the case where they're actually
they could test regularly and then stay in school because it's a real sort of real issue with with people missing out on school.
And I think unavoidably so when they had coded and were infected.
But actually if they were just a contact and then weren't going to go on to be infected, that they really need to go home.
And so that the trial that was done was to take 200 schools and roughly 100 of them
sort of followed the standard where where when people were a contact of the case,
they were at home to self-isolate for ten days.
And then in the other one, they were offered regular lateral flow testing until one they were tested negative.
They were then able to come into school and and they the outcome was that actually we saw that in the
schools using the lateral flow testing strategy that we didn't see evidence of any large increase in cases.
And actually, although people were absent for quite a lot of other reasons other than other than being contacts of cases,
but still potentially that that strategy could get could get children back into back into school,
and also that teachers and other staff in school as well.
But as we came to finish that, there was this sort of the background to this.
Was this sort of the what got caught at the time in the press,
the pandemic where so many people were off work because they'd been contacts that actually
there was sort of there was a lack of a lack of people actually being able to do things.
And and that was a problem for us in health care, but it wasn't a problem for all sorts of other things as well.
And so. Although it wasn't the subject of the trial, we were mostly looking at children.
There was a lot of pressure that actually what we found may be very relevant to the population more widely.
And so we were under quite a lot of pressure.
It was a trial that was sort of joint sponsored by the Department of Health and Social Care and also education.
And there's quite a lot of pressure to get really quite a rapid answer.
And so unlike a sort of normal study where we might spend months going over things from when we
had the final sort of fixed dataset to actually producing the paper was just a number of things.
And again, we knew what the data that we were going to get.
We knew what they looked like. And so we sort of had already coded up all the sort of analysis as much as
we could based off sort of what we thought the data were going to look like.
So that actually once we got it, we could run it really, really quite rapidly.
So we hadn't seen the results unblinded until the end of the study.
But once we saw them, then actually we could generate lots of that in a few days.
And yes, and that was an example of a paper where some students wrote and wrote and wrote and it was on an incredibly hot ticket to the summer.
And I remember sort of the computer sort of whirring with all the analysis,
sort of creating loads and loads of heat in the room and then being really hot and you sort of frantically writing, trying to do the analysis, check.
You got things right, sort of getting in contact with people, making sure that you were doing the right thing and and that.
Yeah, so getting getting that paper and that result out was sort of under enormous time pressure.
But then also also really important because it changed policy overnight.
I mean, you did you mentioned just in passing that obviously people can't can't work that that kind of pitch the whole time.
Did you actively take any steps to support your own well-being?
Did were you able to say, I must give myself some space?
Yeah, I think you have to.
I would, yes. I sort of put our sort of professional portfolio for kind of the medical side of things.
Part of it was sort of reflecting on things.
And actually one of my reflections from that time is I've got a whole load of lovely pictures of butterflies in our garden,
and I don't know why they were so many that year,
but there were just loads and loads and loads and actually just having the kind of opportunity just to kind of decompress,
go and do something completely different was definitely very helpful.
It's also been very interesting talking to people about kind of how you unlearn the very time
pressured sort of way of working and particularly talking to people from other industries.
So I was fortunate to do a leadership course at the business school sort of towards the end of the pandemic.
We spent two, two weeks getting to know and work with a number of people from all sorts of different sectors and talking to people,
particularly from banking who'd been involved in the financial crisis in the early 2000s,
and how they then had worked in a very pressured environment then,
and then kind of over time had to unlearn that and actually had to be very kind of active and deliberative in saying I was coming to work,
then I'm actually going to make a conscious decision to not do that or I was having a meeting.
Now I'm going to make a conscious decision to actually say I'm not going to have meetings at that time of day so I can possibly avoid it.
And I think, yeah, by being aware of that for yourself, but also for other people.
So the people on the team and being able to say, look, we done an amazing job,
but actually it is okay now to get back to working in a way that's more sensible or more sustainable, maybe.
Do you think that the fact that you knew all the time you were working on something,
it was really important actually, that helped to support your wellbeing or what?
You too stressed that that I think I think it did.
I'm not sure how much or how much perspective know the busyness dominates rather than having that much time to pause and reflect.
But yeah, I how we were, you know, how I was I think there was you know, there were definitely times where you feel exhausted,
you feel really tired and particularly sort of some of the clinical work you've directly confronted with some really challenging things.
And I, I might pick out the sort of kindness of people originally at the beginning of the pandemic as being a real encouragement.
I think there was sort of one particularly miserable weekend where it all felt pretty horrible in the hospital
and someone brought in this massive tray of Danish pastries from their business or whatever and gave them to us.
And it was amazing. And I kind of felt actually they were the people who needed help because their businesses were essentially like sort of,
you know, that their customer disappeared overnight. And yet there were people being really generous,
kind of bringing in all sorts of stuff to us who actually were were busy and
getting very well paid while they work because they're actually struggling. But I think that was a real encouragement, I think.
I certainly found the whole sort of the whole the whole public support for the NHS, also a great deal, a great encouragement.
And so I think that that definitely contributed to to being supportive of that.
And then I think having sort of family at home and people to talk to also also really helped them on.
Yeah. My wife's also a doctor, she's a urologist,
so I actually spent some of her time being redeployed back to doing things that she hadn't been doing for some time.
But having that that shared experience was definitely also also helpful.
So what how do you think the work that you did during the pandemic has changed what you do now?
Has it has it at all? What's your plans now?
It's a really interesting question because I think definitely the the pandemic
there was sort of a real sense that what you were doing really mattered.
And that manifested in a number of ways, you know, whether it was contact with decision making sort of organisations,
whether that's within government or other advisory bodies or directly being in contact and
participating in meetings with people there and and seeing the direct consequences of your work.
Also the opportunity for sort of various media coverage and, you know,
actually being on the television or being on the radio or being in the print media and and previously sort of,
you know, having had some involvement with the media around some of the other work we've done, whether it was sort of, you know,
sort of some of the work around multi-drug resistant gonorrhoea, which, as you can imagine,
got sort of couched in terms of the world's worst super gonorrhoea or some of the work around Candida Auris,
which we found was linked to transmission to these these axillary thermometers which the sun characterised as deadly armpit super fungus,
which is, which is fantastic. So I had, I had had some of that involvement, but, but actually then through COVID,
actually the kind of media coverage and press involvement was sort of significantly greater.
So so you have this sort of sense of urgency in the work,
you have this sort of connection with sort of official sort of impact of what you do and this contact with the
media and sort of indirectly also through social media and people's interest in your work sort of skyrockets.
And then and then suddenly that's all there anymore and you're sort of left reflecting?
Well, actually, you know, I had I had this list of things I maybe wanted to achieve academically in terms of papers.
I'd like to get published in particular places or numbers of publications or,
or collaborations with people or and previously it might have taken you ten years to accrue those.
And then all of a sudden, within two years, you've racked up an enormous number of publications and, and lots of you know that.
And it had the opportunity to publish in lots of journals that you might not
have otherwise done and has your work covered in a way that you might not.
And so it does make you think, well, what do I want to do next?
And maybe the plans that you had in 2019 kind of don't quite feel the same now compared to that and that.
And so, yeah, I'm not sure it completely got to the answer,
but I think there's there's definitely a sense that you have to sort of pull back and saying, well, what am I what am I good at?
How can I continue to sort of use that to to actually still be benefiting other people?
And so I think coming back to that, yes, it may it may not there may not be the same level of reward,
but it may still be important to continue to do those things and to do them well.
That said, it it also makes you think that it would be quite nice to do things a little bit differently,
whether that's working with different groups of people or working in slightly different areas or doing academic work a little bit differently.
And I think I'm still thinking about that, still exploring still, but it does make you think,
okay, I've done quite a lot and quite a lot of work academically and I'd like to,
yeah, like to make sure that I sort of take the opportunities to do as many different things as I can.
So. So yes, I think it definitely changes your perspective.
I'm not sure quite. I've quite got to where I find me realising where I'm going to be.
But I think yeah, I think I think that but that kind of in the meantime, having the encouragement to go back to doing what you're doing, you know,
you can do well and to do it well and to make sure you're answering meaningful questions, I think has been sort of really where I got to so from.
That's great. Thank you very much indeed.